Transcript
00:00:00 The following is a conversation with Lee Cronin,
00:00:02 a chemist from University of Glasgow,
00:00:05 who’s one of the most fascinating, brilliant,
00:00:07 out of the box thinking scientists I’ve ever spoken to.
00:00:11 This episode was recorded more than two weeks ago,
00:00:14 so the war in Ukraine is not mentioned.
00:00:17 I have been spending a lot of time each day
00:00:19 talking to people in Ukraine and Russia.
00:00:22 I have family, friends, colleagues,
00:00:23 and loved ones in both countries.
00:00:27 I will try to release a solo episode on this war,
00:00:30 but I’ve been failing to find the words
00:00:31 that make sense of it for myself and others,
00:00:36 so I may not.
00:00:37 I ask for your understanding no matter which path I take.
00:00:41 Most of my time is spent trying to help
00:00:44 as much as I can privately.
00:00:47 I’m talking to people who are suffering,
00:00:49 who are angry, afraid.
00:00:52 When I returned to this conversation with Lee,
00:00:55 I couldn’t help but smile.
00:00:57 He’s a beautiful, brilliant, and hilarious human being.
00:01:01 He’s basically a human manifestation
00:01:03 of the mad scientist Rick Sanchez from Rick and Morty.
00:01:07 I thought about quitting this podcast for a time,
00:01:10 but for now at least, I’ll keep going.
00:01:14 I love people too much.
00:01:16 You, the listener.
00:01:17 I meet folks on the street or when I run.
00:01:21 You say a few kind words about the podcast
00:01:23 and we talk about life, the small things,
00:01:26 and the big things.
00:01:28 All of it gives me hope.
00:01:30 People are just amazing.
00:01:32 You are amazing.
00:01:34 I ask for your support, wisdom, and patience
00:01:37 as I keep going with this silly little podcast,
00:01:41 including through some difficult conversations
00:01:45 and hopefully many fascinating and fun ones too.
00:01:49 This is the Lex Friedman podcast.
00:01:51 To support it, please check out our sponsors
00:01:53 in the description.
00:01:54 And now, dear friends, here’s Lee Cronin.
00:01:59 How do you think life originated on Earth
00:02:02 and what insights does that give us about life?
00:02:06 If we go back to the origin of Earth
00:02:08 and you think about maybe 4.7, 4.6, 4.5 billion years ago,
00:02:13 the planet was quite hot.
00:02:14 There was a limited number of minerals.
00:02:16 There was some carbon, some water, and I think
00:02:20 that maybe it’s a really simple set of chemistry
00:02:22 that we really don’t understand.
00:02:25 So that means you’ve got a finite number of elements
00:02:27 that are going to react very simply with one another
00:02:31 and out of that mess comes a cell.
00:02:33 So literally sand turns into cells
00:02:35 and it seems to happen quick.
00:02:38 So what I think I can say with some degree of,
00:02:41 I think not certainty, but curiosity,
00:02:43 genuine curiosity is that life happened fast.
00:02:47 Yeah, so when we say fast,
00:02:50 this is a pretty surprising fact
00:02:53 and maybe you can actually correct me and elaborate,
00:02:55 but it seems like most, like 70 or 80% of the time
00:02:59 that Earth has been around, there’s been life on it,
00:03:01 like some very significant percentage.
00:03:03 So when you say fast, like the slow part
00:03:06 is from single cell or from bacteria
00:03:09 to something more complicated, organisms.
00:03:11 It seems like most of the time that Earth has been around,
00:03:14 it’s been single cell or like very basic organisms,
00:03:18 like a couple billion years.
00:03:20 But yeah, you’re right.
00:03:21 That’s really, I recently kind of revisited our history
00:03:26 and saw this and I was just looking at the timeline.
00:03:30 Wait a minute, like how did life just spring up so quickly?
00:03:33 Like really quickly.
00:03:35 That makes me think that it really wanted to.
00:03:38 Like put another way, it’s very easy for life to spring.
00:03:42 Yeah, I agree, I think it’s much more inevitable
00:03:45 and I think I try to kind of, not provoke,
00:03:49 but try and push chemists to think about,
00:03:51 because chemists are central to this problem, right?
00:03:54 Of understanding the origin of life on Earth, at least,
00:03:57 because we’re made of chemistry.
00:03:59 But I wonder if the origin of life on a planet,
00:04:02 or sorry, the emergence of life on the planet is as,
00:04:05 common as the formation of a star.
00:04:08 And if you start framing it in that way,
00:04:10 it allows you to then look at the universe
00:04:12 slightly differently, because,
00:04:14 and we can get into this, I think, in quite some detail,
00:04:16 but I think, to come back to your question,
00:04:19 I have little idea of how life got started,
00:04:23 but I know it was simple.
00:04:24 And I know that the process of selection
00:04:27 had to occur before the, by the end of the day,
00:04:31 the selection had to occur before the biology
00:04:35 was established, so that selection built the framework
00:04:39 from which life kind of grew in complexity
00:04:43 and capability and functionality and autonomy.
00:04:46 And I think these are all really important words
00:04:48 that we can unpack over the next while.
00:04:51 Can you say all the words again?
00:04:53 So you said selection, so natural selection,
00:04:57 the original A, B testing.
00:04:59 And so, and then complexity,
00:05:01 and then the degree of autonomy and sophistication,
00:05:05 because I think that people misunderstand what life is.
00:05:10 Some people say that life is a cell,
00:05:12 and some people that say that life is a virus
00:05:15 or life is an on off switch.
00:05:19 I don’t think it’s that,
00:05:21 life is the universe developing a memory.
00:05:25 And the laws of physics and the way,
00:05:27 well, there are no laws of physics.
00:05:28 It’s just memory free stuff, right?
00:05:32 So there’s only a finite number of ways
00:05:34 you can arrange the fundamental particles to do things.
00:05:38 Life is the universe developing a memory.
00:05:43 So it’s like sewing a piece of art slowly,
00:05:49 and then you can look back at it.
00:05:50 So, so there’s a stickiness to life.
00:05:56 It’s like universe doing stuff.
00:05:58 And when you say memory, it’s like there’s a stickiness
00:06:01 to a bunch of the stuff that’s building together.
00:06:04 So like you can, in a stable way,
00:06:07 like trace back the complexity
00:06:10 and that tells a coherent story.
00:06:13 Yeah, and I think, yeah.
00:06:14 Okay, that’s, by the way, very poetic and beautiful.
00:06:19 Life is the universe developing a memory.
00:06:24 Okay, and then there’s autonomy,
00:06:25 you said complexity we’ll talk about,
00:06:27 but it’s a really interesting idea
00:06:30 that selection preceded biology.
00:06:33 Yeah, I think.
00:06:35 So first of all, what is chemistry?
00:06:38 Like does sand still count as chemistry?
00:06:41 Sure, I mean, as a chemist, a card carrying chemist,
00:06:43 if I’m allowed a card, I don’t know.
00:06:45 Don’t know what I am most days, actually.
00:06:46 What is a card made of?
00:06:48 That’s what I’m thinking.
00:06:49 What’s the chemical composition of the card?
00:06:52 So what is chemistry?
00:06:53 Well, chemistry is the thing that happens
00:06:55 when you bring electrons together and you form bonds.
00:06:58 So bonds, well, I say to people
00:07:00 when they talk about life elsewhere,
00:07:02 and I just say, well, there’s bonds, there’s hope,
00:07:04 because bonds allow you to get heterogeneity.
00:07:07 They allow you to record those memories,
00:07:09 or at least on Earth.
00:07:11 You could imagine a Stanislav Lemtri world
00:07:15 where you might have life emerging
00:07:17 or intelligence emerging before life.
00:07:19 That may be something like Solaris or something,
00:07:21 but to get to selection,
00:07:25 if you can form, if atoms can combine and form bonds,
00:07:28 those bonds, those atoms can bond to different elements
00:07:32 and those molecules will have different identities
00:07:35 and interact with each other differently,
00:07:37 and then you can start to have some degree of causation
00:07:39 or interaction and then selection and then existence.
00:07:45 And then you go up the kind of the path of complexity.
00:07:49 And so at least on Earth, as we know it,
00:07:52 there is a sufficient pool of available chemicals
00:07:56 to start searching that combinatorial space of bonds.
00:08:01 So, okay, this is a really interesting question.
00:08:03 Let’s lay it out.
00:08:04 So bonds, almost like cards.
00:08:07 We say there’s bonds, there is life,
00:08:11 there’s intelligence, there’s consciousness.
00:08:14 And what you just made me realize is
00:08:18 that those can emerge, let’s put bonds aside,
00:08:24 those can emerge in any order.
00:08:27 That’s really brilliant.
00:08:28 So intelligence can come before life.
00:08:32 It’s like panpsychists believe that consciousness,
00:08:36 I guess, comes before life and before intelligence.
00:08:41 So consciousness permeates all matter,
00:08:43 it’s some kind of fabric of reality.
00:08:46 Okay, so like within this framework,
00:08:47 you can kind of arrange everything,
00:08:49 but you need to have the bonds
00:08:53 that precedes everything else.
00:08:55 Oh, and the other thing is selection.
00:08:57 So like the mechanism of selection, that could proceed.
00:09:02 See, couldn’t that proceed bonds too?
00:09:04 Whatever the hell selection is.
00:09:05 So I would say that there is an elegant order to it.
00:09:09 Bonds allow selection, allows the emergence of life,
00:09:13 allows the emergence of multicellularity
00:09:15 and then more information processing,
00:09:18 building state machines all the way up.
00:09:19 However, you could imagine a situation if you had,
00:09:23 I don’t know, a neutron star or a sun
00:09:25 or what a ferromagnetic loops interacting with one another
00:09:28 and these oscillators building state machines
00:09:31 and these state machines reading something
00:09:32 out in the environment.
00:09:34 Over time, these state machines would be able
00:09:36 to literally record what happened in the past
00:09:39 and sense what’s going on in the present
00:09:41 and imagine the future.
00:09:43 However, I don’t think it’s ever gonna be
00:09:46 within a human comprehension, that type of life.
00:09:49 I wouldn’t count it out because whenever you say,
00:09:53 I know in science, whenever I say something’s impossible,
00:09:55 I then wake up the next day and say,
00:09:56 no, that’s actually wrong.
00:09:57 I mean, there are some limits, of course.
00:10:00 I don’t see myself traveling fast and light anytime soon,
00:10:03 but…
00:10:04 Eric Weinstein says that’s possible,
00:10:05 so he will say you’re wrong.
00:10:06 Sure, but I’m an experimentalist as well,
00:10:08 so one of my, I have two superpowers.
00:10:11 My stupidity, and I don’t mean that as a,
00:10:14 I’m like absolutely completely witless,
00:10:16 but I mean my ability to kind of just start again
00:10:19 and ask the question and then do it with an experiment.
00:10:22 I always wanted to be a theoretician growing up,
00:10:24 but I just didn’t have the intellectual capability,
00:10:27 but I was able to think of experiments in my head
00:10:30 I could then do in my lab or when I was a child outside
00:10:35 and then those experiments in my head
00:10:37 and then outside reinforced one another.
00:10:40 So I think that’s a very good way of kind of
00:10:42 grounding the science, right?
00:10:44 Well, that’s a nice way to think about theoreticians
00:10:46 is they’re just people who run experiments in their head.
00:10:49 I mean, that’s exactly what Einstein did, right?
00:10:51 But you were also capable of doing that in the head,
00:10:54 in your head, inside your head and in the real world
00:10:57 and the connection between the two
00:10:59 is when you first discovered your superpower stupidity.
00:11:02 I like it.
00:11:03 Yes, there you go.
00:11:04 What’s the second superpower?
00:11:05 Your accent or is that?
00:11:08 Well, I don’t know.
00:11:09 I am genuinely curious.
00:11:11 So I have, like everybody, ego problems,
00:11:15 but my curiosity is bigger than my ego.
00:11:16 So as long as that happens, I can cope.
00:11:20 That’s awesome.
00:11:21 That is so powerful.
00:11:22 You’re just dropping some powerful lines.
00:11:23 So curiosity is bigger than ego.
00:11:26 That’s something I have to think about
00:11:28 because you always struggle about the role of ego in life
00:11:30 and that’s so nice to think about,
00:11:36 don’t think about the size of ego,
00:11:37 the absolute size of ego.
00:11:38 Think about the relative size of ego
00:11:40 to the other horses pulling at you.
00:11:44 If the curiosity one is bigger,
00:11:46 then ego will do just fine and make you fun to talk to.
00:11:51 Anyway, so those are the two superpowers.
00:11:53 How do those connect to natural selection
00:11:55 or selection and bonds and, I forgot already,
00:11:58 life and consciousness?
00:11:59 So we’re going back to selection in the universe
00:12:02 and origin of life on Earth.
00:12:03 I mean, selection, I’m convinced that selection
00:12:07 is a force in the universe.
00:12:09 Not a fundamental force, but it is a directing force
00:12:14 because existence, although existence appears
00:12:18 to be the default, the existence of what,
00:12:21 why does, and we can get to this later, I think,
00:12:24 but it’s amazing that discrete things exist
00:12:29 and you see this cup.
00:12:31 It’s not the sexiest cup in the world,
00:12:33 but it’s pretty functional.
00:12:35 This cup, the complexity of this cup
00:12:38 isn’t just in the object.
00:12:39 It is literally the lineage of people making cups
00:12:42 and recognizing that, seeing that in their head,
00:12:44 making an abstraction of a cup,
00:12:45 and then making a different one.
00:12:47 So I wonder how many billions of cups
00:12:50 have come before this one,
00:12:52 and that’s the process of selection and existence,
00:12:55 and the only reason the cup is still used
00:12:56 is quite useful.
00:12:57 I like the handle.
00:12:58 It’s convenient, so I don’t die.
00:12:59 I keep hydration, and so I think we are missing
00:13:03 something fundamental in the universe about selection,
00:13:07 and I think what biology is is a selection amplifier,
00:13:12 and that this is where autonomy comes in,
00:13:14 and actually I think that how humanity is gonna,
00:13:17 humans and autonomous robots,
00:13:20 or whatever we’re gonna call them in the future,
00:13:22 will supercharge that even further.
00:13:24 So selection is happening in the universe,
00:13:26 but if you look in the asteroid belt,
00:13:28 selection, if objects are being kicked in and out
00:13:31 of the asteroid belt, those trajectories are quite complex.
00:13:35 You don’t really look at that as productive selection
00:13:37 because it’s not doing anything to improve its function,
00:13:40 but is it?
00:13:40 The asteroid belt has existed for some time,
00:13:43 so there is some selection going on,
00:13:45 but the functionality is somewhat limited.
00:13:49 On Earth, at the formation of Earth,
00:13:53 interaction of chemicals and molecules in the environment
00:13:56 gave selection, and then things could happen,
00:13:59 because you could think about, in chemistry,
00:14:01 we could have an infinite number of reactions happen,
00:14:04 but all the reactions that are allowed to happen
00:14:06 don’t happen, why?
00:14:07 Because there are energy barriers.
00:14:08 So there must be some things called catalysts out there,
00:14:12 or there are bits of minerals that,
00:14:14 when two molecules get together in that mineral,
00:14:17 it lowers the energy barrier for the reaction,
00:14:19 and so the reaction is promoted.
00:14:21 So suddenly you get one reaction over another
00:14:24 series of possibilities occurring
00:14:26 that makes a particular molecule,
00:14:28 and this keeps happening in steps,
00:14:30 and before you know it,
00:14:31 almost these waves as discrete reactions work together,
00:14:34 and you start to build a machinery
00:14:38 that is run by existence.
00:14:41 So as you go forward in time,
00:14:44 the fact that the molecules, the bonds are getting,
00:14:48 there are more bonds in a molecule,
00:14:49 there’s more function,
00:14:50 there’s more capability for this molecule
00:14:52 to interact with other molecules, to redirect them,
00:14:55 it’s like a series of little,
00:14:57 and I don’t want to use this term too much,
00:14:59 but it’s almost thinking about
00:15:01 the simplest von Neumann constructor,
00:15:04 that’s the simplest molecule
00:15:05 that could build a more complicated molecule
00:15:07 to build a more complicated molecule,
00:15:09 and before you know it,
00:15:09 when that more complicated molecule
00:15:11 can act on the causal chain that’s produced itself
00:15:14 and change it,
00:15:15 suddenly you start to get towards some kind of autonomy,
00:15:18 and that’s where life, I think, emerges in earnest.
00:15:21 Every single word in the past few paragraphs,
00:15:24 let’s break those apart,
00:15:26 but who’s von Neumann, what’s a constructor,
00:15:30 the closing of the loop that you’re talking about,
00:15:35 the molecule that starts becoming,
00:15:37 I think you said like the smallest von Neumann constructor,
00:15:41 the smallest, the minimal,
00:15:43 so what do all those things mean,
00:15:45 and what is, what are we supposed to imagine
00:15:47 when we think about the smallest von Neumann constructor?
00:15:51 So John von Neumann is a real hero,
00:15:54 actually, not just me, but many people, I think,
00:15:56 computer science and physics.
00:15:58 He was an incredible intellect
00:16:01 who probably solved a lot of the problems
00:16:03 that we’re working on today
00:16:04 and just forgot to write them down.
00:16:05 Yeah.
00:16:06 And I’m not sure if it’s John von Neumann or Johnny,
00:16:09 as I think his friends called him,
00:16:10 but I think he was Hungarian, a mathematician,
00:16:14 came to the US,
00:16:16 and basically was involved in the Manhattan Project
00:16:19 in developing computation
00:16:21 and came up with all sorts of ideas,
00:16:24 and I think he was one of the first people
00:16:25 to come up with cellular automata.
00:16:27 And, but he…
00:16:28 Oh, really?
00:16:29 I didn’t know this little fact.
00:16:30 I think so, I think so.
00:16:31 And I think…
00:16:32 Well, anyway, if he didn’t come up with it,
00:16:34 he probably did come up with it and didn’t write it down.
00:16:37 There was a couple of people who did at the same time,
00:16:38 and then Conway obviously took it on,
00:16:40 and then Wolfram loves CAs.
00:16:42 There is his fabric of the universe.
00:16:44 And what I think he imagined was that he wasn’t satisfied,
00:16:48 and this may be incorrect recollection,
00:16:51 but a lot of what I say is gonna be kind of
00:16:55 just way out of my…
00:16:56 You’re, Lee, you’re just part of the universe
00:17:00 creating its memory, designing…
00:17:02 Exactly, yeah, rewriting history.
00:17:04 Rewriting history.
00:17:05 Exactly, imperfectly.
00:17:06 So, but what I mean is I think he liked this idea
00:17:09 of thinking about how could a Turing machine
00:17:14 literally build itself without a Turing machine, right?
00:17:16 It’s like literally how did state machines emerge?
00:17:19 And I think that von Neumann constructors,
00:17:21 he wanted to conceive of a minimal thing,
00:17:24 autonomous, that could build itself.
00:17:28 And what would those rules look like in the world?
00:17:30 And that’s what a von Neumann kind of constructor
00:17:32 looked like, like it’s a minimal hypothetical object
00:17:35 that could build itself, self replicate.
00:17:37 And I’m really fascinated by that
00:17:41 because I think that although it’s probably not
00:17:45 exactly what happened, it’s a nice model
00:17:47 because as chemists, if we could go back
00:17:49 to the origin of life and think about
00:17:51 what is a minimal machine that can get structured randomly?
00:17:55 So like with no prime mover, with no architect,
00:18:01 it assembles through just existence.
00:18:03 So random stuff bumping in together
00:18:06 and you make this first molecule.
00:18:07 So you have molecule A and molecule A interacts
00:18:11 with another random molecule B and they get together
00:18:14 and they realize by working together
00:18:15 they can make more of themselves,
00:18:17 but then they realize they can mutate
00:18:19 so they can make AB prime.
00:18:21 So AB prime is different to AB
00:18:24 and then AB prime can then act back
00:18:27 where A and B are being created
00:18:29 and slightly nudge that causal chain
00:18:32 and make AB prime more evolvable or learn more.
00:18:38 So that’s the closing the loop part.
00:18:40 Closing the loop part, got it.
00:18:42 It feels like the mutation part is not that difficult.
00:18:46 It feels like the difficult part
00:18:48 is just creating a copy of yourself as step one.
00:18:50 That seems like one of the greatest inventions
00:18:56 in the history of the universe is the first molecule
00:19:00 that figured out, holy shit, I can create a copy of myself.
00:19:04 How hard is that?
00:19:06 I think it’s really, really easy.
00:19:09 Okay, I did not expect that.
00:19:11 I think it’s really, really easy.
00:19:12 Well, let’s take a step back.
00:19:15 I think replicating molecules are rare,
00:19:19 but if you say, I think I was saying on,
00:19:22 I probably got into trouble on Twitter the other day,
00:19:23 so I was trying to work this.
00:19:24 There’s about more than 18 mils of water in there.
00:19:27 So one mole of water, 6.022 times 10 to the 23 molecules.
00:19:31 That’s about the number of stars in universe, I think,
00:19:33 of the order.
00:19:34 So there’s three universe worth, but between one and.
00:19:37 Somebody corrected you on Twitter?
00:19:38 Yeah, as if, I’m always being corrected.
00:19:40 It’s a great, but there’s a lot of molecules in the water.
00:19:44 And so there’s a lot of, so although it’s for you and me,
00:19:47 really hard to conceive of,
00:19:49 if existence is not the default for a long period of time,
00:19:55 because what happens is the molecules get degraded.
00:19:57 So much of the possibilities in the universe
00:20:00 are just broken back into atoms.
00:20:01 So you have this kind of destruction of the molecules
00:20:06 for our chemical reactions.
00:20:07 So you only need one or two molecules
00:20:09 to become good at copying themselves
00:20:12 for them suddenly to then take resources in the pool
00:20:15 and start to grow.
00:20:16 And so then replication actually over time,
00:20:18 when you have bonds, I think is much simpler, much easier.
00:20:23 And I even found this in my lab years ago.
00:20:25 I had one of the reasons I started doing inorganic chemistry
00:20:29 and making rust, making a bit of rust based on
00:20:32 a thing called molybdenum, molybdenum oxide
00:20:35 is this molybdenum oxide, very simple.
00:20:38 But when you add acid to it and some electrons,
00:20:40 they make these molecules you just cannot possibly imagine
00:20:44 would be constructed big, gigantic wheels
00:20:46 of 154 molybdenum atoms in a wheel
00:20:50 or I cost a dodecahedron 132 molybdenum atoms
00:20:54 all in the same pot.
00:20:55 And I realized when I,
00:20:56 and I just finished experiments two years ago,
00:20:58 I’ve just published a couple of papers on this,
00:21:00 that they’re actually, there is a random small molecule
00:21:05 with 12 atoms in it that can form randomly,
00:21:07 but it happens to template its own production.
00:21:10 And then by chance, it templates the ring,
00:21:14 just an accident, just like just an absolute accident.
00:21:17 And that ring also helps make the small 12 mer.
00:21:21 And so you have what’s called an autocatalytic set
00:21:25 where A makes B and B helps make A and vice versa.
00:21:32 And you then make this loop.
00:21:34 So it’s a bit like these, they all work in synergy
00:21:39 to make this chain of events that grow.
00:21:43 And it doesn’t take a very sophisticated model
00:21:46 to show that if you have these objects are competing
00:21:50 and then collaborating to help one another build,
00:21:53 they just grow out of the mess.
00:21:55 And although they seem improbable,
00:21:56 they are improbable, in fact, impossible in one step.
00:22:01 There’s multiple steps.
00:22:02 This is when the blind people look
00:22:04 at the blind watchmaker argument
00:22:06 and you talk about how could a watch spontaneously emerge?
00:22:10 Well, it doesn’t.
00:22:11 It’s a lineage of watches and cruder devices
00:22:14 that are bootstrapped onto one another.
00:22:19 Right, so it’s very improbable,
00:22:23 but once you get that little discovery
00:22:25 like with the wheel and fire,
00:22:29 it just explodes because it’s so successful, it explodes.
00:22:34 It explodes, it’s basically selection.
00:22:37 So this templating mechanism that allows you
00:22:40 to have a little like blueprint for yourself,
00:22:43 how you go through different procedures
00:22:45 is to build copies of yourself.
00:22:49 So in chemistry somehow it’s possible to imagine
00:22:52 that that kind of thing is easy to spring up.
00:22:57 In more complex organisms, it feels like a different thing
00:22:59 and much more complicated.
00:23:00 Like we’re having like multiple abstractions
00:23:04 of the birds and the bees conversation here,
00:23:06 but with human, I’m sorry, with complex organisms,
00:23:10 it feels like difficult to have reproduction to,
00:23:15 that’s gonna get clipped out.
00:23:17 I’m gonna make fun of that.
00:23:18 It’s difficult to develop this idea
00:23:23 of making copies of yourself or no.
00:23:26 Because that seems like a magical idea for life to,
00:23:30 but wow, that feels like very necessary
00:23:35 for what selection is, for what evolution is.
00:23:37 But then if selection precedes all of this,
00:23:40 then maybe these are just like echoes
00:23:43 of the selecting mechanism at different scales.
00:23:47 Yeah, that’s exactly it.
00:23:48 So selection is the default in the universe if you want to.
00:23:52 And what happens is that life,
00:23:54 the solution that life has got on earth,
00:23:57 life on earth, biology on earth is unique to earth.
00:24:01 We can talk about that.
00:24:03 And that was really hard fought for,
00:24:05 but that is a solution that works on earth,
00:24:08 the ribosome, the fundamental machine
00:24:10 that is responsible for every cell on earth
00:24:15 of whatever, wherever it is in the kingdom of life.
00:24:18 That is an incredibly complex object,
00:24:21 but it was evolved over time
00:24:22 and it wasn’t involved in a vacuum.
00:24:24 And I think that once we understand that selection
00:24:27 can occur without the ribosome,
00:24:32 but what the ribosome does,
00:24:34 it’s a phase transition in replication.
00:24:37 And I think that that, and also technology
00:24:39 that is probably much easier to get to than we think.
00:24:45 Why do you put the ribosome as a central part
00:24:50 of living organisms on earth?
00:24:52 It basically is a combination
00:24:53 of two different polymer systems, so RNA and peptides.
00:24:57 So the RNA world, if you like,
00:24:59 gets transmitted and builds proteins
00:25:02 and the proteins are responsible for all the catalysis.
00:25:05 The majority of the catalysis goes on in the cell.
00:25:07 No ribosome, no proteins, no decoding, no evolution.
00:25:11 So ribosome is looking at the action.
00:25:14 You don’t put like the RNA itself as the critical thing,
00:25:17 like information, you put action as the most important thing.
00:25:20 I think the actual molecules
00:25:22 that we have in biology right now are entirely contingent
00:25:24 on the history of life on earth.
00:25:27 There are so many possible solutions.
00:25:29 And this is where chemistry got itself into,
00:25:31 origin of life chemistry gets itself into a bit of a trap.
00:25:33 Yeah, let me interrupt you there.
00:25:35 You’ve tweeted, you’re gonna get,
00:25:36 I’m gonna cite your tweets like it’s Shakespeare, okay?
00:25:40 It’s surprising you haven’t gotten canceled on Twitter yet.
00:25:43 Your brilliance once again saves you.
00:25:46 I’m just kidding.
00:25:49 You like to have a little bit of fun on Twitter.
00:25:51 You’ve tweeted that quote,
00:25:52 origin of life research is a scam.
00:25:56 So if this is Shakespeare, can we analyze this word?
00:26:00 Why is the origin of life research a scam?
00:26:02 Aren’t you kind of doing origin of life research?
00:26:06 Okay, it was tongue in cheek, but yeah,
00:26:08 I think, and I meant it as tongue in cheek.
00:26:12 I’m not doing the origin of life research.
00:26:14 I’m trying to make artificial life.
00:26:16 And I also want to bound the likelihood
00:26:19 of the origin of life on earth,
00:26:21 but more importantly to find origin of life elsewhere.
00:26:23 But let me directly address the tweet.
00:26:26 There are many, many good chemists out there
00:26:27 doing origin of life research, but I want to nudge them.
00:26:31 And I think they’re brilliant.
00:26:32 Like there’s no question the chemistry they are doing,
00:26:36 the motivation is great.
00:26:38 So what I meant by that tweet is saying
00:26:40 that maybe they’re making assumptions about saying,
00:26:43 if only I could make this particular type of molecule,
00:26:47 say this RNA molecule or this phosphodiester
00:26:52 or this other molecule,
00:26:54 it’s gonna somehow unlock the origin of life.
00:26:57 And I think that origin of life has been looking at this
00:27:00 for a very long time.
00:27:01 And whilst I think it’s brilliant to work out
00:27:05 how you can get to those molecules,
00:27:08 I think that chemistry and chemists doing origin of life
00:27:11 could be nudged into doing something even more profound.
00:27:15 And so the argument I’m making,
00:27:18 it’s a bit like right now,
00:27:20 let’s say, I don’t know, the first Tesla
00:27:22 that makes its way to, I don’t know,
00:27:25 into a new country in the world.
00:27:27 Let’s say there’s a country X
00:27:29 that has never had a Tesla before
00:27:31 and they get the Tesla.
00:27:32 Russia.
00:27:32 And they take the Tesla,
00:27:34 and what they do is they take the Tesla apart
00:27:35 and say, we want to find the origin of cars in the universe
00:27:38 and say, okay, how did this form and how did this form?
00:27:41 And they just randomly keep making
00:27:42 till they make the door, they make the wheel,
00:27:44 they make the steering column and all this stuff.
00:27:46 And they say, well, that’s the route.
00:27:48 That’s the way cars emerged on earth.
00:27:50 But actually we know that there’s a causal chain of cars
00:27:53 going right back to Henry Ford and the horse and carriage.
00:27:56 And before that, maybe, you know,
00:27:58 where people were using wheels.
00:28:00 And I think that obsession with the identities
00:28:04 that we see in biology right now
00:28:06 are giving us a false sense of security
00:28:09 about what we’re looking for.
00:28:10 And I think that origin of life chemistry is in danger
00:28:17 of not making the progress that it deserves
00:28:20 because the chemists are doing this.
00:28:22 The field is exploding right now.
00:28:24 There’s amazing people out there, young and old doing this.
00:28:27 And there’s deservedly so more money going in.
00:28:30 You know, I used to complain
00:28:31 there’s more money being spent searching for the Higgs boson
00:28:34 that we know exists than the origin of life.
00:28:36 You know, why is that?
00:28:37 The origin, we understand the origin of life.
00:28:39 We’re gonna actually work out what life is.
00:28:42 And we’re gonna be at a bound,
00:28:43 the likelihood of finding life elsewhere in the universe.
00:28:45 And most important for us,
00:28:47 we are gonna know or have a good idea
00:28:49 of what the future of humanity looks like.
00:28:51 You know, we need to understand
00:28:53 that although we’re precious,
00:28:54 we’re not the only life forms in the universe.
00:28:57 Or that’s my very strong impression.
00:28:58 I have no data for that.
00:29:00 It’s just right now a belief.
00:29:02 And I want to turn that belief
00:29:03 into a more than a belief by experimentation.
00:29:07 But coming back to the scam,
00:29:09 the scam is if we just make this RNA,
00:29:11 we’ve got this fluke event, we know how that’s simple.
00:29:17 Let’s make this phosphodiester,
00:29:19 or let’s make ATP or ADP.
00:29:21 We’ve got that part nailed.
00:29:22 Let’s now make this other molecule, another molecule.
00:29:24 And how many molecules are gonna be enough?
00:29:26 And then the reason I say this
00:29:28 is when you go back to Craig Venter,
00:29:30 when he invented his life form, Cyndia,
00:29:35 this micro, this minimal plasmid,
00:29:38 it’s a myoplasma, something, I don’t know the name of it,
00:29:43 but he made this wonderful cell
00:29:45 and said, I’ve invented life.
00:29:48 Not quite.
00:29:49 He facsimileed the genome from this entity
00:29:52 and made it in the lab, all the DNA,
00:29:55 but he didn’t make the cell.
00:29:56 He had to take an existing cell
00:30:00 that has a causal chain going all the way back to Luca.
00:30:02 And he showed when he took out the gene,
00:30:05 the genes and put in his genes, synthesized,
00:30:08 the cell could boot up.
00:30:09 But it’s remarkable that he could not make a cell
00:30:11 from scratch.
00:30:12 And even now today, synthetic biologists
00:30:15 cannot make a cell from scratch
00:30:17 because there’s some contingent information embodied
00:30:20 outside the genome in the cell.
00:30:23 And that is just incredible.
00:30:26 So there’s lots of layers to the scam.
00:30:29 Well, let me then ask the question,
00:30:32 how can we create life in the lab from scratch?
00:30:37 What have been the most promising attempts
00:30:39 at creating life in the lab from scratch?
00:30:41 Has anyone actually been able to do it?
00:30:44 Do you think anyone will be able to do it
00:30:46 in the near future if they haven’t already?
00:30:50 Yeah, I think that nobody has made life
00:30:53 in the lab from scratch.
00:30:54 Lots of people would argue that they have made progress.
00:30:57 So Craig Venter, I think the synthesis
00:30:59 of a synthetic genome milestone in human achievement.
00:31:03 Brilliant.
00:31:04 Yeah, can we just walk back and say,
00:31:06 what would you say from your perspective,
00:31:09 one of the world experts in exactly this area,
00:31:12 what does it mean to create life from scratch
00:31:15 where if you sit back, whether you do it
00:31:17 or somebody else does it, it’s like,
00:31:20 damn, this is, we just created life.
00:31:24 Well, I can tell you what I would expect,
00:31:27 I would like to be able to do,
00:31:30 is to go from sand to cells in my lab and…
00:31:37 Can you explain what sand is?
00:31:39 Yeah, just inorganic stuff, like basically just,
00:31:42 so sand is just silicon oxide with some other ions in it,
00:31:47 maybe some inorganic carbon, some carbonates,
00:31:50 just basically clearly dead stuff
00:31:52 that you could just grind rocks into sand.
00:31:55 And it would be what, in a kind of vacuum
00:31:57 so they could remove anything else
00:31:59 that could possibly be like a shadow of life
00:32:05 that can assist in the chemical.
00:32:06 You could do that, you could insist and say,
00:32:07 look, I’m gonna take, and not just inorganic,
00:32:09 I want some more, I wanna cheat and have some organic,
00:32:12 but I want inorganic organic,
00:32:13 and I’ll explain the play on words in a moment.
00:32:16 So I would like to basically put into a world,
00:32:19 let’s say a completely synthetic world, if you like,
00:32:23 a closed world, put some inorganic materials
00:32:26 and just literally add some energy in some form,
00:32:30 be it lightning or heat, UV light,
00:32:33 and run this thing in cycles over time
00:32:37 and let it solve the search problem.
00:32:38 So I see the origin of life as a search problem
00:32:41 in chemical space.
00:32:42 And then I would wait, literally wait for a life form
00:32:45 to crawl out of the test tube.
00:32:46 That’s a joke I tell my group.
00:32:48 Literally wait for a very, don’t worry,
00:32:51 it’s gonna be very feeble,
00:32:52 it’s not gonna take over the world.
00:32:54 There’s ways of ethically containing it.
00:32:56 Famous last words.
00:32:58 Indeed, indeed, indeed, but I.
00:33:01 You know this is being recorded, right?
00:33:03 It’ll make you, it will not make you look good
00:33:05 once it crawls out of the lab
00:33:07 and destroys all of human civilization, but yes.
00:33:09 But there is very good,
00:33:11 there is a very good things you can do to prevent that.
00:33:13 For instance, if you put stuff in your world,
00:33:15 which isn’t earth abundant,
00:33:17 so let’s say we make life based on molybdenum
00:33:20 and it escapes, it would die immediately
00:33:21 because there’s not enough molybdenum in the environment.
00:33:23 So we can put in, we can do responsible life.
00:33:26 Or as I fantasize with my research group on our away day
00:33:29 that would go in, it’s, you know,
00:33:31 I think it’s actually morally if we don’t find,
00:33:36 until humanity finds life in the universe,
00:33:38 this is going on a tangent,
00:33:39 it’s our moral obligation to make origin of life bombs,
00:33:42 identify dead planets and bomb them
00:33:43 with our origin of life machines and make them alive.
00:33:46 I think it is our moral obligation to do that.
00:33:50 Some people might argue with me about that,
00:33:51 but I think that we need more life in the universe.
00:33:54 And then we kind of forget we did it
00:33:58 and then come back and then.
00:34:00 So where did you come from?
00:34:02 But coming back to the, what I’d expect.
00:34:04 So I just say. Father, are you back?
00:34:06 I think this is once again, a Rick and Morty episode.
00:34:09 It’s definitely all Rick and Morty all the way down.
00:34:11 So we, I imagine we have this pristine experiment
00:34:15 and everything is, you know, sanitized
00:34:18 and we put in inorganic materials
00:34:20 and we have cycles with them,
00:34:22 day, night cycles, up, down, whatever.
00:34:24 And we look for evidence of replication
00:34:27 and evolution over time.
00:34:28 And that’s what the experiment should be.
00:34:30 Now, are there people doing this in the world right now?
00:34:32 There are a couple of,
00:34:33 there’s some really good groups doing this.
00:34:35 There’s some really interesting scientists
00:34:37 doing this around the world.
00:34:38 They’re kind of perhaps too much associated with the scam.
00:34:44 So, and so they’re using molecules
00:34:48 that are already, were already invented by biology.
00:34:50 So there’s a bit of replication built in,
00:34:54 but I still think the work that is doing,
00:34:55 they’re doing is amazing.
00:34:57 But I would like people to be a bit freer and say,
00:35:00 let’s just basically shake a load of sand in a box
00:35:03 and wait for life to come out
00:35:04 because that’s what happened on earth.
00:35:06 And so that we have to understand that.
00:35:08 Now, how would I know I’ve been successful?
00:35:10 Well, because I’m not obsessing
00:35:11 with what molecules are in life now,
00:35:15 I would wager a vast quantity of money.
00:35:19 I’m not very rich, so just be a few dollars,
00:35:21 but for me, the solution space will be different.
00:35:27 So the genetic material will be not RNA.
00:35:31 The proteins will not be what we think.
00:35:33 The solutions will be just completely different.
00:35:36 And it might be, and it will be very feeble
00:35:37 because that’s the other thing we should be able to show
00:35:40 fairly robustly that even if I did make
00:35:43 or someone did make a new life form in the lab,
00:35:46 it would be so poor that it’s not gonna leap out.
00:35:50 It is the fear about making a lethal life form
00:35:56 in the lab from scratch is similar to us imagining
00:36:00 that we’re gonna make the terminator
00:36:02 at Boston Dynamics tomorrow.
00:36:04 Simply not, and the problem is
00:36:07 we don’t communicate that properly.
00:36:08 I know you yourself very, you explain this very well.
00:36:12 There is not the AI catastrophe coming.
00:36:15 We’re very far away from that.
00:36:16 That doesn’t mean we should ignore it.
00:36:18 Same with the origin of life catastrophe.
00:36:19 It’s not coming anytime soon.
00:36:21 We shouldn’t ignore it, but we shouldn’t let that fear
00:36:24 stop us from doing those experiments.
00:36:26 But this is a much, much longer discussion
00:36:28 because there’s a lot of details there.
00:36:29 I would say there is potential for catastrophic events
00:36:33 to happen in much dumber ways.
00:36:36 In AI space, there’s a lot of ways to create,
00:36:40 like social networks are creating a kind
00:36:43 of accelerated set of events
00:36:46 that we might not be able to control.
00:36:48 The social network virality in the digital space
00:36:53 can create mass movements of ideas that can then,
00:36:58 if times are tough, create military conflict
00:37:01 and all those kinds of things.
00:37:02 But that’s not super intelligent AI.
00:37:05 That’s an interesting at scale application of AI.
00:37:09 If you look at viruses, viruses are pretty dumb,
00:37:13 but at scale, their application is pretty detrimental.
00:37:16 And so origin of life, much like all the kind of virology,
00:37:25 the very contentious word of gain of function research
00:37:28 and virology, sort of like research on viruses,
00:37:33 messing with them genetically,
00:37:36 that can create a lot of problems if not done well.
00:37:38 So we have to be very cautious.
00:37:41 So there’s a kind of,
00:37:43 whenever you’re ultra cautious about stuff in AI
00:37:47 or in virology and biology,
00:37:50 it borders on cynicism, I would say,
00:37:53 where it’s like everything we do is going to turn out
00:37:56 to be destructive and terrible.
00:37:58 So I’m just going to sit here and do nothing.
00:38:00 Okay, that’s a possible solution except for the fact
00:38:04 that somebody is going to do it.
00:38:06 It’s science and technology progresses.
00:38:10 So we have to do it in an ethical way, in a good way,
00:38:14 considering in a transparent way, in an open way,
00:38:18 considering all the possible positive trajectories
00:38:23 that could be taken and making sure as much as possible
00:38:26 that we walk those trajectories.
00:38:28 So yeah, I don’t think Terminator is coming,
00:38:31 but a totally unexpected version of Terminator
00:38:35 may be around the corner.
00:38:36 Might be here already.
00:38:37 Yeah, so I agree with that.
00:38:38 And so going back to the origin of life discussion,
00:38:41 I think that in synthetic biology right now,
00:38:44 we have to be very careful about how we edit genomes
00:38:49 and edit synthetic biology to do things.
00:38:51 So that’s kind of, that’s where things might go wrong
00:38:53 in the same way as Twitter turning ourselves
00:38:56 into kind of strange scale effects.
00:38:59 I would love origin of life research
00:39:01 or artificial life research to get to the point
00:39:04 where we have those worries,
00:39:06 because that’s why I think we’re just so far away from that.
00:39:08 We are just, you know, right now,
00:39:10 I think there are two really important angles.
00:39:13 There is the origin of life people,
00:39:15 researchers who are faithfully working on this
00:39:18 and trying to make those molecules,
00:39:20 the scan molecules I talked about.
00:39:22 And then there are people on the creationist side
00:39:24 who are saying, look,
00:39:25 the fact you can’t make these molecules
00:39:26 and you can’t make a cell means that evolution isn’t true
00:39:29 and all this other stuff.
00:39:30 Gotcha.
00:39:31 Yeah, and so, and I find that really frustrating
00:39:34 because actually the origin of life research
00:39:35 is all working in good faith, right?
00:39:37 Yes.
00:39:38 And so what I’m trying to do
00:39:40 is give origin of life research
00:39:41 a little bit more of an open context.
00:39:47 And one of the things I think is important,
00:39:49 I really want to make a new life form in my lifetime.
00:39:52 I really want to prove that life is a general phenomena,
00:39:56 a bit like gravity in the universe,
00:39:58 because I think that’s gonna be really important
00:39:59 for humanity’s global psychological state,
00:40:04 meaning going forward.
00:40:06 That’s beautifully put.
00:40:09 So one, it will help us understand ourselves.
00:40:12 So that’s useful for science,
00:40:14 but two, it gives us a kind of hope,
00:40:17 if not an awe at all the huge amounts
00:40:23 of alien civilizations that are out there.
00:40:26 If you can build life and understand
00:40:29 just how easy it is to build life,
00:40:31 then that’s just as good, if not much better,
00:40:35 than discovering life on another planet.
00:40:38 Yeah.
00:40:39 It’s, I mean, it’s cheaper.
00:40:41 It’s much cheaper and much easier
00:40:44 and probably much more conclusive
00:40:47 because once you’re able to create life,
00:40:50 like you said, it’s a search problem
00:40:52 that there’s probably a lot of different ways to do it.
00:40:55 Once you create the, once you find the first solution,
00:40:58 you probably have all the right methodology
00:41:00 for finding all kinds of other solutions.
00:41:02 Yeah, and wouldn’t it be great
00:41:03 if we could find a solution?
00:41:04 I mean, it’s probably a bit late for,
00:41:07 I mean, I worry about climate change,
00:41:09 but I’m not that worried about climate change,
00:41:10 and I think one day you could think about,
00:41:13 could we engineer a new type of life form
00:41:15 that could basically, and I don’t want to do this,
00:41:17 and I don’t think we should do this necessarily,
00:41:19 but it’s a good thought experiment
00:41:21 that would perhaps take CO2 out of the atmosphere
00:41:23 or an intermediate life form, so it’s not quite alive.
00:41:26 It’s almost like an add on
00:41:28 that we can, with a time dependent add on,
00:41:32 you could give to say cyanobacteria in the ocean
00:41:35 or to maybe to wheat and say, right,
00:41:37 we’re just gonna, we’re gonna fix a bit more CO2,
00:41:40 and we’re gonna work out how much we need to fix
00:41:42 to basically save the climate,
00:41:44 and we’re gonna use evolutionary principles
00:41:47 to basically get there.
00:41:49 What worries me is that biology has had a few billion years
00:41:51 to find a solution for CO2 fixation,
00:41:54 hasn’t really done, it’s not,
00:41:57 the solution isn’t brilliant for our needs,
00:41:58 but biology wasn’t thinking about our needs.
00:42:00 Biology was thinking about biology’s needs,
00:42:03 but I think if we can do, as you say,
00:42:05 make life in the lab, then suddenly we don’t need
00:42:08 to go to everywhere and conclusively prove it.
00:42:10 I think we make life in the lab.
00:42:12 We look at the extent of life in the solar system.
00:42:14 How far did Earth life get?
00:42:16 Probably we’re all Martians.
00:42:17 Probably life got going on Mars.
00:42:19 The chemistry on Mars seeded Earth.
00:42:21 That might have been a legitimate way
00:42:22 to kind of truncate the surface.
00:42:25 But in the outer solar system,
00:42:26 we might have completely different life forms
00:42:28 on Enceladus, on Europa, and Titan.
00:42:32 And that would be a cool thing, because.
00:42:33 Okay, wait a minute, wait a minute, wait a minute.
00:42:36 Did you just say that you think, in terms of likelihood,
00:42:40 life started on Mars, like statistically speaking,
00:42:43 life started on Mars and seeded Earth?
00:42:45 It could be possible, because life was,
00:42:48 so Mars was habitable for the type of life
00:42:50 that we have right now, type of chemistry before Earth.
00:42:53 So it seems to me that Mars got searching,
00:42:57 doing chemistry, like, and.
00:42:59 It started way before.
00:43:00 Yeah, and so they had a few more replicators
00:43:03 and some other stuff.
00:43:04 And if those replicators got ejected from Mars
00:43:06 and landed on Earth, and Earth was like,
00:43:09 I don’t need to start again.
00:43:10 Right.
00:43:11 Thanks for that.
00:43:12 And then it just carried on.
00:43:13 So I’m not going, I think we will find evidence
00:43:16 of life on Mars, either life we put there by mistake,
00:43:20 contamination, or actually life,
00:43:22 the earliest remnants of life.
00:43:24 And that would be really exciting.
00:43:26 It’s a really good reason to go there.
00:43:28 But I think it’s more unlikely,
00:43:29 because the gravitational situation in the solar system,
00:43:31 if we find life in the outer solar system.
00:43:33 Titan and all that, that would be its own thing.
00:43:35 Exactly.
00:43:36 Wow, that would be so cool.
00:43:37 If we go to Mars and we find life that looks
00:43:40 a hell of a lot similar to Earth life,
00:43:43 and then we go to Titan and all those weird moons
00:43:46 with the ices and the volcanoes and all that kind of stuff,
00:43:49 and then we find there something that looks,
00:43:52 I don’t know, way weirder.
00:43:54 Yeah.
00:43:55 Some other, some non RNA type of situation.
00:43:57 But we might find almost life,
00:43:59 like in the prebiotic chemical space.
00:44:01 And I think there are four types of exoplanets
00:44:03 we need to look for, right?
00:44:04 Because when JWST goes up and touch wood,
00:44:07 it goes up and everything’s fine.
00:44:09 When we look at a star, well, we know statistically,
00:44:12 most stars have planets around them.
00:44:13 What type of planet are they?
00:44:14 Are they going to be dead?
00:44:16 Are they going to be just a prebiotic origin of life coming?
00:44:20 So are they going to be technological?
00:44:23 So with intelligence on them, and will they have died?
00:44:27 So, you know, had life on them, but gone.
00:44:30 Those are the four states of the boat.
00:44:32 And suddenly, it’s a bit like I want to classify planets
00:44:34 the way we classify stars.
00:44:36 Yeah.
00:44:37 And I think that, in terms of their,
00:44:39 rather than having this, oh, we’ve found methane,
00:44:42 there’s evidence of life.
00:44:43 We found oxygen, that’s the evidence of life.
00:44:45 We found whatever molecule marker.
00:44:47 And start to then frame things a little bit more.
00:44:51 As those four states.
00:44:52 Yeah.
00:44:53 Which, by the way, you’re just saying four,
00:44:55 but there could be, before the dead,
00:44:58 there could be other states
00:45:00 that we humans can even conceive of.
00:45:01 Yeah, yeah, just prebiotic, almost alive,
00:45:04 got the possibility to come alive.
00:45:06 I think.
00:45:07 But there could be a post technological.
00:45:08 Like, whatever we think of as technology,
00:45:12 that could be a, like, pre conscious,
00:45:17 like, where we all meld into one super intelligent conscious,
00:45:20 or some weird thing that naturally happens over time.
00:45:23 Yeah, yeah.
00:45:24 I mean, I think that all bets are on that.
00:45:26 The metaverse.
00:45:28 Yeah, we are.
00:45:29 We join into a virtual metaverse and start creating,
00:45:33 which is kind of an interesting idea,
00:45:35 almost arbitrary number of copies of each other,
00:45:38 much more quickly, so we can mess with different ideas.
00:45:41 Like, I can create a thousand copies of Lex,
00:45:45 like, every possible version of Lex,
00:45:48 and then just see, like,
00:45:49 and then I just have them, like, argue with each other,
00:45:52 and, like, until, like, in the space of ideas
00:45:54 and see who wins out.
00:45:56 How could that possibly go wrong?
00:45:58 But anyway, there’s, especially in this digital space
00:46:01 where you could start exploring with AIs mixed in,
00:46:04 you could start engineering arbitrary intelligences,
00:46:07 you can start playing in the space of ideas,
00:46:10 which might move us into a world that looks very different
00:46:13 than a biological world.
00:46:15 Like, our current world, the technology,
00:46:17 is still very much tied to our biology.
00:46:20 It’s, we might move past that completely.
00:46:23 Oh, definitely, we definitely will.
00:46:25 We definitely, but that could be another phase then.
00:46:27 Sure.
00:46:28 Because then you, yeah.
00:46:29 But I did say technological, so I think I agree with you.
00:46:30 I think, so you can have, let’s get this right.
00:46:32 So, dead world, no prospect of alive.
00:46:36 Prebiotic world, life emerging.
00:46:38 Living and technological.
00:46:40 And you probably, and the dead one,
00:46:42 you probably won’t be able to tell
00:46:43 between the dead never being alive and the dead one,
00:46:46 maybe you’ve got some artifacts and maybe there’s five.
00:46:48 There’s probably not more than five.
00:46:50 And I think the technological one could allow,
00:46:53 could have life on it still,
00:46:54 but it might just have exceeded.
00:46:56 Because, you know, one way that life might survive on Earth
00:46:58 is if we can work out how to deal with the coming,
00:47:01 the real climate change that comes when the sun expands.
00:47:05 It might be a way to survive that, you know, but yeah.
00:47:10 I think that we need to start thinking statistically
00:47:12 when it comes to looking for life in the universe.
00:47:15 Let me ask you then, sort of statistically,
00:47:20 how many alien civilizations are out there
00:47:23 in those four phases that you’re talking about?
00:47:26 When you look up to the stars
00:47:28 and you’re sipping on some wine
00:47:30 and talking to other people with British accents
00:47:35 about something intelligent and intellectual, I’m sure.
00:47:39 Do you think there’s a lot of alien civilizations
00:47:42 looking back at us and wondering the same?
00:47:45 My romantic view of the universe
00:47:48 is really taking loans from my logical self.
00:47:52 So what I’m saying is I have no doubt, I have no idea.
00:47:55 But having said that, there is no reason to suppose
00:48:01 that life is as hard as we first thought it was.
00:48:04 And so if we just take Earth as a marker,
00:48:08 and if I think that life is a much more general phenomena
00:48:12 than just our biology,
00:48:13 then I think the universe is full of life.
00:48:16 And the reason for the Fermi paradox
00:48:18 is not that they’re not out there,
00:48:22 it’s just that we can’t interact with the other life forms
00:48:24 because they’re so different.
00:48:27 And I’m not saying that they’re necessarily like
00:48:28 hasn’t depicted in Arrival or other, you know,
00:48:31 I’m just saying that perhaps
00:48:36 there are very few universal facts in the universe
00:48:40 and maybe our technologies are quite divergent.
00:48:47 And so I think that it’s very hard to know
00:48:49 how we’re gonna interact with alien life.
00:48:51 You think there’s a lot of kinds of life that’s possible.
00:48:54 I guess that was the intuition you provided
00:48:57 that the way biology itself,
00:49:02 but even this particular kinds of biology
00:49:04 that we have on Earth is something that is just one sample
00:49:11 of nearly infinite number of other possible,
00:49:15 complex, autonomous, self replicating type of things
00:49:19 that could be possible.
00:49:20 And so we’re almost unable to see
00:49:24 the alternative versions of us, huh?
00:49:28 I mean, we’ll still be able to detect them,
00:49:31 we’ll still be able to interact with them,
00:49:33 we’ll still be able to like which,
00:49:36 what’s exactly is lost in translation?
00:49:39 Why can’t we see them?
00:49:41 Why can’t we talk to them?
00:49:42 Because I too have a sense,
00:49:47 you put it way more poetically,
00:49:49 but it seems both statistically
00:49:54 and sort of romantically,
00:49:58 it feels like the universe should be teeming with life,
00:50:02 like super intelligent life.
00:50:04 And I just, I sit there and the Fermi paradox is very,
00:50:10 it’s felt very distinctly by me
00:50:12 when I look up at the stars because it’s like,
00:50:15 it’s the same way I feel when I’m driving
00:50:18 through New Jersey and listening to Bruce Springsteen
00:50:20 and feel quite sad.
00:50:23 It’s like Lucy Kay talks about pulling off
00:50:25 to the side of the road and just weeping a little bit.
00:50:27 I’m almost like wondering like,
00:50:31 hey, why aren’t you talking to us?
00:50:33 It feels lonely, it feels lonely
00:50:35 because it feels like they’re out there.
00:50:38 I think that there are a number of answers to that.
00:50:40 I think the Fermi paradox is perhaps based
00:50:42 on the assumption that if life did emerge in the universe,
00:50:47 it would be similar to our life
00:50:49 and there’s only one solution.
00:50:50 And I think that what we’ve got to start to do
00:50:52 is go out and look for selection detection
00:50:56 rather than an evolution detection,
00:50:58 rather than life detection.
00:51:01 And I think that once we start to do that,
00:51:03 we might start to see really interesting things.
00:51:07 And we haven’t been doing this for very long
00:51:10 and we are living in an expanding universe
00:51:12 and that makes the problem a little bit harder.
00:51:15 Everybody’s always leaving distance wise.
00:51:19 I’m very optimistic that we will,
00:51:22 well, I don’t know, there are two movies that came out
00:51:25 within six months of one another,
00:51:27 Ad Astra and Cosmos.
00:51:30 Ad Astra, the very expensive blockbuster
00:51:32 with Brad Pitt in it and saying there is no life
00:51:35 and it’s all, we’ve got to,
00:51:37 life on Earth has more pressures than Cosmos,
00:51:39 which is a UK production,
00:51:40 which basically aliens came and visited Earth one day
00:51:42 and they were discovered in the UK, right?
00:51:45 It was quite, it’s a fun film.
00:51:48 But I really loved those two films.
00:51:50 And at the same time, those films,
00:51:53 at the time those films were coming out,
00:51:54 I was working on a paper, a life detection paper,
00:51:58 and I found it was so hard to publish this paper
00:52:02 and it was almost as depressed,
00:52:03 I got so depressed trying to get this science out there
00:52:06 that I felt the depression of the film in Ad Astra,
00:52:11 like life, there’s no life elsewhere in the universe.
00:52:14 And, but I’m incredibly optimistic
00:52:17 that I think we will find life in the universe,
00:52:19 firm evidence of life,
00:52:21 and it will have to start on Earth,
00:52:22 making life on Earth and surprising us.
00:52:24 We have to surprise ourselves
00:52:25 and make non biological life on Earth.
00:52:28 And then people say, well, you made this life on Earth,
00:52:31 therefore it’s, you’re part of the causal chain of that.
00:52:34 And that might be true,
00:52:35 but if I can show how I’m able to do it
00:52:38 with very little cheating
00:52:40 or very little information inputs,
00:52:42 just creating like a model planet.
00:52:44 Some description and watching it, watching life emerge,
00:52:48 then I think that we will be even to persuade
00:52:51 even the hardest critic that it’s possible.
00:52:55 Now, with regards to the Fermi paradox,
00:52:57 I think that we might crush that with the JWST.
00:53:01 It’s basically, if I recall correctly,
00:53:03 the mirror is about 10 times the size of the Hubble
00:53:06 that we’re gonna be able to do spectroscopy,
00:53:09 look at colors of exoplanets, I think, not brilliantly,
00:53:12 but we’ll be able to start to classify them.
00:53:15 And we’ll start to get a real feel
00:53:18 for what’s going on in the universe on these exoplanets.
00:53:21 Cause it’s only in the last few decades, I think,
00:53:25 maybe even last decade that we even
00:53:30 came to recognize that exoplanets even are common.
00:53:33 And I think that that gives us a lot of optimism
00:53:36 that life is gonna be out there.
00:53:38 But I think we have to start framing,
00:53:40 we have to start preparing the fact
00:53:44 that biology is only one solution.
00:53:46 I can tell you with confidence that biology on Earth
00:53:50 does not exist anywhere else in the universe.
00:53:52 We are absolutely unique.
00:53:54 Well, okay, I love the confidence,
00:53:56 but where does that confidence come from?
00:54:02 Chemistry, like how many options does chemistry really have?
00:54:07 Many, that’s the point.
00:54:08 And the thing is, this is where the origin of life scam
00:54:11 comes in, is that people don’t quite count,
00:54:15 they don’t count the numbers.
00:54:16 So if biology as you find on Earth is common everywhere,
00:54:19 then there’s something really weird going on
00:54:21 that basically written in the quantum mechanics,
00:54:23 there’s some kind of these bonds must form over these bonds
00:54:26 and this catalyst must form over this catalyst
00:54:28 when they’re all quite equal.
00:54:30 Life is contingent.
00:54:31 The origin of life on Earth was contingent
00:54:34 upon the chemistry available at the origin of life on Earth.
00:54:38 So that means if we want to find other Earth like worlds,
00:54:43 we look for the same kind of rocky world.
00:54:45 We might look in the same zone as Earth
00:54:47 and we might expect reasonably
00:54:50 to find biological like stuff going on.
00:54:53 That would be a reasonable hypothesis,
00:54:55 but it won’t be the same, it can’t be.
00:54:57 It’s like saying, I don’t believe in magic.
00:55:00 That’s why I’m sure.
00:55:02 I just don’t believe in magic.
00:55:03 I believe in statistics and I can do experiments.
00:55:06 And so I won’t get the same, exactly the same sequence
00:55:09 of events, I’ll get something different.
00:55:11 And so there is TikTok elsewhere in the universe,
00:55:14 but it’s not the same as our TikTok, right?
00:55:16 That’s what I mean.
00:55:17 Which aspect of it is not the same?
00:55:20 Well, I just think, so what is TikTok?
00:55:23 TikTok is a social media where people upload videos, right?
00:55:27 Of silly videos.
00:55:28 So I guess there might be.
00:55:29 Well, there’s humor, there’s attention,
00:55:31 there’s the ability to process,
00:55:33 there’s ability for intelligent organisms
00:55:35 to collaborate on ideas and find human ideas
00:55:38 and play with those ideas, make them viral, memes.
00:55:43 Humor seems to be kind of fundamental
00:55:45 to the human experience.
00:55:46 And I think that that’s a really interesting question
00:55:48 we can ask, is humor a fundamental thing in the universe?
00:55:52 I think maybe it will be, right?
00:55:53 In terms of, you think about in a game theoretic sense,
00:55:56 humor, the emergence of humor serves a role
00:56:00 in our game engine.
00:56:01 And so if selection is fundamental in the universe,
00:56:05 so is humor.
00:56:06 Well, I actually don’t know exactly
00:56:10 what role humor serves.
00:56:12 Maybe it’s like, from a chemical perspective,
00:56:15 it’s like a catalyst for,
00:56:20 I guess it’s for several purposes.
00:56:21 One is the catalyst for spreading ideas on the internet.
00:56:23 That’s modern humor.
00:56:25 But humor is also a good way to deal
00:56:28 with the difficulty of life.
00:56:30 It’s a kind of valve, release valve for suffering.
00:56:35 Throughout human history, life has been really hard.
00:56:39 And for the people that I’ve known in my life
00:56:41 who’ve lived through some really difficult things,
00:56:44 humor is part of how they deal with that.
00:56:47 It’s usually dark humor.
00:56:49 But yeah, it’s interesting.
00:56:51 I don’t know exactly what’s the more mathematically
00:56:56 general way to formulate what the hell is humor.
00:56:58 What humor does it serve?
00:57:01 But I still, we’re kind of joking here,
00:57:03 but it’s a counterintuitive idea to me
00:57:09 to think that life elsewhere in the universe
00:57:14 is very different than life on Earth.
00:57:17 And also, like all of each instantiation of life
00:57:23 is likely very different from each other.
00:57:26 Yeah, like maybe there’s a few clusters of similar life,
00:57:30 but it’s much more likely is what you’re saying.
00:57:34 To me, it’s a kind of novel thought.
00:57:36 I’m not sure what to do with it.
00:57:37 But you’re saying that it’s more common
00:57:40 to be a weird outcast in the full spectrum of life
00:57:44 than it is to be in some usual cluster.
00:57:48 So every instantiation of a kind of chemistry
00:57:51 that results in complexity that’s autonomous
00:57:53 and self replicating however the hell you define life,
00:57:56 that is going to be very different every time.
00:57:59 I don’t know.
00:58:01 It feels like a selection is a fundamental
00:58:04 kind of directed force in the universe.
00:58:07 Won’t selection result in a few pockets
00:58:11 of interesting complexities?
00:58:13 I mean, yeah, if we ran Earth over again,
00:58:19 over and over and over,
00:58:20 you’re saying it’s going to come up with,
00:58:23 there’s not going to be elephants every time?
00:58:26 Yeah, I don’t think so.
00:58:27 I think that there will be similarities.
00:58:30 And I think we don’t know enough
00:58:32 about how selection globally works.
00:58:37 But it might be that the emergence of elephants
00:58:42 was wired into the history of Earth in some way,
00:58:44 like the gravitational force, how evolution was going,
00:58:47 Cambrian explosions, blah, blah, blah,
00:58:49 the emergence of mammals.
00:58:50 But I just don’t know enough about the contingency,
00:58:53 the variability.
00:58:54 All I do know is you count the number of bits
00:58:57 of information required to make an elephant
00:59:00 and think about the causal chain
00:59:03 that provide the lineage of elephants
00:59:05 going all the way back to Luca,
00:59:07 there’s a huge scope for divergence.
00:59:10 Yeah, but just like you said, with chemistry and selection,
00:59:15 the things that result in self replicating chemistry
00:59:22 and self replicating organisms,
00:59:26 those are extremely unlikely, as you’re saying.
00:59:30 But once they’re successful, they multiply.
00:59:33 So it might be a tiny subset of all things
00:59:37 that are possible in the universe, chemically speaking,
00:59:40 it might be a very tiny subset
00:59:41 is actually successful at creating elephants.
00:59:44 Or elephant like or slash human like creatures.
00:59:48 Well, there’s two different questions here.
00:59:48 The first one, if we were to reset Earth and to start again.
00:59:52 The different phases, sorry to keep interrupting.
00:59:54 Yeah, no, if we restart Earth and start again,
00:59:56 say we could go back to the beginning
00:59:58 and do the experiment or have a number of Earths,
01:00:00 how similar would biology be?
01:00:02 I would say that there would be broad similarities,
01:00:06 but the emergence of mammals is not a given
01:00:09 unless we’re gonna throw an asteroid at each planet
01:00:11 at each time and try and faithfully reproduce what happened.
01:00:15 Then there’s the other thing about
01:00:17 when you go to another Earth like planet elsewhere,
01:00:20 maybe there’s a different ratio, particular elements,
01:00:22 maybe the bombardment at the beginning of the planet
01:00:27 was quicker or longer than Earth.
01:00:30 And I just don’t have enough information there.
01:00:32 What I do know is that the complexity of the story of life
01:00:37 on Earth gives us lots of scope for variation.
01:00:42 And I just don’t think it’s a reasonable
01:00:44 mathematical assumption to think that life on Earth
01:00:48 that happened again would be same as what we have now.
01:00:51 Okay, but you’ve also extended that to say
01:00:54 that we might, as an explanation for the Fermi paradox,
01:00:58 that that means we’re not able to interact with them.
01:01:02 Or that’s an explanation for why we haven’t at scale
01:01:06 heard from aliens is they’re different than us.
01:01:10 We’ve only been looking for, say, 70, 80 years.
01:01:13 So I think that the reason we have not found aliens yet
01:01:17 is that we haven’t worked out what life is.
01:01:20 No, but the aliens have worked that out, surely.
01:01:25 Statistically speaking, there must be a large number
01:01:29 of aliens that are way ahead of us
01:01:31 on this whole life question.
01:01:33 Unless there’s something about this stage
01:01:37 of intellectual evolution that often quickly results
01:01:40 in nuclear war and destroys itself.
01:01:42 Like there’s something in this process
01:01:48 that eventually, I don’t know, crystallizes the complexity
01:01:52 and it stops, either dies or stops developing.
01:01:55 But most likely, they already figured it out.
01:01:58 And why aren’t they contacting us?
01:01:59 Is it some grad student somewhere?
01:02:03 Wants to study a new green planet?
01:02:06 Maybe they have.
01:02:07 I mean, I don’t have a coherent answer to your question,
01:02:12 other than to say that if there are other aliens out there
01:02:15 and they’re far more advanced,
01:02:17 they might be in contact with each other.
01:02:19 And they might also, we might be at a point
01:02:22 where what I’m saying quite critically
01:02:24 is it takes two to talk, right?
01:02:26 So the aliens might be there.
01:02:28 But if we don’t have the ability to recognize them
01:02:31 and talk to them, then the aliens aren’t going
01:02:33 to want to talk to us.
01:02:36 And I think that’s a critical point
01:02:37 that probably if that’s a filter,
01:02:42 there needs to be an ability for one
01:02:44 to communicate with the other.
01:02:45 And we need to know what life is before we do that.
01:02:48 So we haven’t qualified to even join the club
01:02:50 to have a talk.
01:02:51 Well, I think they still wanna teach us how to talk, right?
01:02:54 But my worry is that, or I think they would wanna teach us
01:02:59 how to talk like you do when you meet it.
01:03:04 Like when you even meet, I was gonna say child,
01:03:07 but that’s a human species.
01:03:09 I mean like ant.
01:03:12 You want to try to communicate with them
01:03:15 through whatever devices you can,
01:03:17 given what an ant is like.
01:03:19 I just, I worry mostly about that humans
01:03:21 are just too close minded or don’t have the right tools.
01:03:25 No, I’m gonna push back on this quite significantly.
01:03:27 I would say, because we don’t understand what life is
01:03:30 and because we don’t understand
01:03:32 how life emerged in the universe,
01:03:34 we don’t understand the physics
01:03:36 that gave rise to life yet.
01:03:38 That means our fundamental description,
01:03:40 I’m way out of my pay grade, even further out.
01:03:43 But I’ll say it anyway,
01:03:44 because I think it’s a fun.
01:03:44 You don’t get paid much anyway, as you said earlier.
01:03:47 So I would say that we,
01:03:50 because we don’t understand the universe yet,
01:03:52 we do not understand how the universe spat out life.
01:03:56 And we don’t know what life is.
01:03:57 And I think that until we understand that,
01:03:59 it is gonna limit our ability to even,
01:04:02 we don’t qualify to talk to the aliens.
01:04:05 So I’m gonna say that they might be there,
01:04:08 but we just, I’m not gonna say that I believe
01:04:10 in interdimensional aliens being present in this room.
01:04:12 Yeah, but I think you’re just being self critical,
01:04:14 like we don’t qualify.
01:04:15 I think the fact that we don’t qualify qualifies us.
01:04:19 We’re interesting in our innocence.
01:04:22 No, I’m saying that because we don’t understand
01:04:25 causal chains and the way that information
01:04:27 is propagated in the universe.
01:04:29 And we don’t understand what replication is yet.
01:04:31 And we don’t understand how life emerged.
01:04:35 I think that we would not recognize aliens.
01:04:38 And if someone doesn’t recognize you,
01:04:43 you wouldn’t go and talk to it.
01:04:44 You don’t go and talk to ants.
01:04:46 You don’t go and talk to birds
01:04:48 or maybe some birds you do, right?
01:04:49 Cause you can, there’s just enough cognition.
01:04:52 So I’m saying because we don’t have enough,
01:04:55 our cognitive abilities are not yet where they need to be.
01:04:58 We probably haven’t been communicating with them.
01:05:00 So you don’t agree with the dating strategy
01:05:02 of playing hard to get?
01:05:04 Cause us humans, that seems to attract us.
01:05:07 Within a species, that’s fine.
01:05:09 But I think we don’t actually have abstraction.
01:05:11 No, actually I think in this talk, in this conversation,
01:05:15 you’ve helped me crystallize something
01:05:16 that I think has been troubling me for a long time
01:05:19 with the thermi paradox.
01:05:20 I’m pretty sure that a reasonable avenue
01:05:23 is to say that you would not go and talk to your cat
01:05:28 about calculus, right?
01:05:31 But I would still pet it.
01:05:32 Sure, but I’m not talking about petting a cat.
01:05:34 The analogy is that the aliens are not going to talk to us
01:05:37 because we, and I’m using calculus as analogy
01:05:40 for abstraction because we lack the layer,
01:05:44 the fundamental layer of understanding what life is
01:05:47 and what the universe is in our reality
01:05:50 that it would be so counterproductive
01:05:52 interacting with intelligent alien species
01:05:55 that it would cause more angst for human race.
01:05:59 They don’t care.
01:06:00 Okay, they gotta be self interested.
01:06:03 So they’ll probably, they more care about
01:06:05 is it interesting for them?
01:06:06 Maybe they, I mean, surely there’s a way
01:06:10 to pet the cat in this analogy
01:06:16 because even if we lack complete understanding,
01:06:20 it must be a very frustrating experience
01:06:23 for other kinds of intelligence to communicate with us.
01:06:26 Still, there must be a way to interact with us.
01:06:29 Well.
01:06:30 Like perturb the system in interesting ways
01:06:34 to see what these creatures do.
01:06:35 We might actually find the answer.
01:06:37 I mean, again, out of my pay grade,
01:06:39 in a simulation of the Earth,
01:06:42 let’s say a simulation where we allow
01:06:44 an intelligent AI to emerge, right?
01:06:47 And that AI, we then give it the objective
01:06:52 is to be curious, interact with other intelligence
01:06:54 in its universe.
01:06:56 And then we might find the parameters required
01:07:00 for that AI to walk with.
01:07:02 And I think you’ll find if the AI will not talk
01:07:05 to other AIs that don’t share the ability
01:07:08 to abstract at the level of the AI
01:07:10 because it’s just a cat and are you gonna travel
01:07:13 20 light years to go and pet a cat?
01:07:15 So not because of the inability to do so,
01:07:19 but because of like boredom.
01:07:20 It’s more interested, it will start talking to,
01:07:23 it will spend most, it will spend a majority
01:07:28 of its time talking to other AI systems
01:07:30 that can at least somewhat understand
01:07:32 and it’s much more fun.
01:07:33 It’s a bit like, do we know that plants are conscious?
01:07:34 Well, plants are unconscious in the way we typically think,
01:07:36 but we don’t talk to them.
01:07:37 They could be, right?
01:07:38 Yeah, but there’s a lot of people on Earth
01:07:40 who like gardening.
01:07:41 There’s always going to be a weird.
01:07:42 They’re not talking, they’re just gardening.
01:07:44 Okay, well, you’re not romantic enough
01:07:46 to see gardening as a way of communication
01:07:48 between humans and plants.
01:07:48 Oh, okay, you’ve got me there.
01:07:50 But there’s ways, there’s always going to be
01:07:53 the people who are curious.
01:07:55 Jane Goodall who lives with the chimps, right?
01:07:58 There’s always going to be curious intelligent species
01:08:00 that visit the weird Earth planet and try to interact.
01:08:06 I mean, it’s a, yeah, I think it’s a super cool idea
01:08:10 that you’re expressing.
01:08:11 I just kind of have a sense.
01:08:13 Maybe it’s a hope that there’s always going to be
01:08:16 a desire to interact even with those
01:08:18 that can’t possibly understand the depth
01:08:21 of what you understand.
01:08:22 So I’m with you, so I want to be as positive as you
01:08:25 that aliens do exist and we will interact with them.
01:08:29 What I’m trying to do is to give you
01:08:30 a reasonable hypothesis why we haven’t yet.
01:08:35 Yeah.
01:08:35 And also something to strive for to be able to do that.
01:08:38 I mean, you know, there is the other view
01:08:41 that the universe is just too big
01:08:43 and life is just too rare.
01:08:46 But I want to come up with an alternative explanation
01:08:49 which I think is reasonable and not being philosophically
01:08:53 and scientifically thought out, which is this,
01:08:55 if you can’t actually communicate with the object,
01:08:59 the thing competently, you don’t even know it’s there,
01:09:03 then there’s no point yet.
01:09:05 See, I disagree with that, but I’m totally aligned
01:09:07 with your hopeful vision, which is like,
01:09:09 we need to understand the origin of life.
01:09:11 It will help us engineer life.
01:09:13 It will help us engineer intelligent life through perhaps
01:09:16 on the computer side through simulation
01:09:18 and explore all the ways that life emerges.
01:09:20 And that will allow us to, I think the fundamental reason
01:09:24 we don’t see overwhelming amounts of life
01:09:27 is I actually believe aliens,
01:09:31 of course, these are all just kind of open minded beliefs.
01:09:35 It’s difficult to know for sure about any of this,
01:09:37 but I think there’s a lot of alien civilizations
01:09:40 which are actively communicating with us and we’re too dumb.
01:09:45 We don’t have the right tools to see it.
01:09:47 That’s what I’m saying.
01:09:48 No, but maybe I misinterpreted you,
01:09:51 but I interpreted you to say they kind of tried a few times
01:09:56 and they’re like, oh God.
01:09:57 No, no, no, what I’m saying is we, so this goes two ways.
01:10:00 Yeah, I agree with you.
01:10:01 There could be information out there,
01:10:03 but just put in such a way
01:10:05 that we just don’t understand it yet.
01:10:06 Right.
01:10:07 So sorry if I didn’t make that clear.
01:10:09 I mean, it’s not just, I don’t think we,
01:10:11 I think we qualify as soon as we can decode their signal.
01:10:15 Right, so when you say qualify, got it, got it.
01:10:17 So you mean, we’re just not smart enough,
01:10:19 the word qualify was throwing me off.
01:10:21 So we’re not smart enough to do,
01:10:22 it’s like we just need to get smarter.
01:10:25 And there’s a lot of people who believe,
01:10:27 let me get your opinion on this, about UFO sightings.
01:10:31 So sightings of weird phenomena
01:10:36 that, you know, what does UFO mean?
01:10:41 It means it’s a flying object
01:10:45 and it’s not identified clearly at the time of sighting.
01:10:50 That’s what UFO means.
01:10:51 So it could be a physics phenomena,
01:10:53 it could be ball lightning,
01:10:54 it could be all kinds of fascinating.
01:10:56 I was always fascinated with ball lightning as a,
01:11:00 like the fact that there could be physical phenomena
01:11:03 in this world that are observable by the human eye.
01:11:06 Of course, all physical phenomena generally are fascinating
01:11:09 that really smart people can’t explain.
01:11:14 I love that.
01:11:15 Cause it’s like, wait a minute,
01:11:16 especially if you can replicate it,
01:11:18 it’s like, wait a minute, how does this happen?
01:11:20 That’s like the precursor to giant discoveries
01:11:23 in chemistry and biology and physics and so on.
01:11:25 But it sucks when those events are super rare, right?
01:11:29 Physically, like ball lightning.
01:11:32 So that’s out there.
01:11:34 And then of course that phenomena
01:11:36 could have other interpretations
01:11:37 that don’t have to do with the physics of chemistry,
01:11:40 the biology of earth.
01:11:42 It could have to do
01:11:43 with more extraterrestrial explanations
01:11:46 that in large part, thanks to Hollywood and movies
01:11:50 and all those kinds of things,
01:11:51 captivates the imaginations of millions of people.
01:11:56 But just because it’s science fiction
01:11:58 that captivates the imagination of people,
01:12:00 it doesn’t mean that some of those sightings,
01:12:03 all it takes is one.
01:12:05 One of those sightings is actually a sign
01:12:09 that it’s extraterrestrial intelligence,
01:12:11 that it’s object that’s not of this particular world.
01:12:17 Do you think there’s a chance that that’s the case?
01:12:18 What do you make, especially the pilot sightings,
01:12:21 what do you make of those?
01:12:23 So I agree with there’s a chance.
01:12:26 There’s always a chance.
01:12:26 Any good scientist would have to,
01:12:29 or observationist would have to,
01:12:31 I want to see if aliens exist come to earth.
01:12:36 What I know about the universe
01:12:37 is I think it’s unlikely right now
01:12:40 that there are aliens visiting us, but not impossible.
01:12:44 I think the releases, the dramatization
01:12:48 that’s been happening politically
01:12:49 saying we’re gonna release all this information,
01:12:51 this classified information.
01:12:54 I was kind of disappointed
01:12:55 because it was just very poor material.
01:13:02 And right now, the ability to capture high resolution video,
01:13:08 everybody is carrying around
01:13:10 with them an incredible video device now.
01:13:12 And we haven’t got more compelling data.
01:13:18 And so that we’ve just seeing grainy pictures,
01:13:22 a lot of hearsay, instrument kind of malfunctions
01:13:26 and whatnot.
01:13:27 And so I think on balance, I think it’s extremely unlikely,
01:13:30 but I think something really interesting is happening.
01:13:34 And then also during the pandemic, right?
01:13:36 We’ve all been locked down.
01:13:37 We all want to have,
01:13:38 we want to, our imaginations are running riot.
01:13:42 And I think that the,
01:13:44 I don’t think that the information out there
01:13:46 has convinced me there are any,
01:13:47 anything interesting on the UFO side.
01:13:49 But what it has made me very interested about
01:13:51 is how humanity is opening up its mind to ponder aliens
01:13:57 and the mystery of our universe.
01:14:00 And so I don’t want to dissuade people
01:14:02 from having those thoughts and say, you’re stupid
01:14:04 and look at that, it’s clearly incorrect.
01:14:06 That’s not right.
01:14:06 That’s not fair.
01:14:07 What I would say is that I lack sufficient data,
01:14:10 replicated observations to make me go,
01:14:14 oh, I’m gonna take this seriously,
01:14:16 but I’m really interested by the fact
01:14:18 that there is this great deal of interest.
01:14:21 And I think that it drives me
01:14:24 to maybe want to make an artificial life form even more
01:14:28 and to help NASA and the Air Force
01:14:31 and whoever go and look for things even more,
01:14:33 because I think humanity wants to know what’s out there.
01:14:36 There’s this yearning, isn’t there?
01:14:38 Yeah, but I see, I almost,
01:14:43 depending on the day, I sometimes agree with you,
01:14:45 but with the thing you just said,
01:14:47 but one of the disappointing things to me
01:14:52 about the sightings, I still hold the belief
01:14:56 that a nonzero number of them
01:15:02 is an indication of something very interesting.
01:15:06 So I don’t side with the people who say
01:15:09 everything can be explained
01:15:10 with sensor artifacts kind of thing.
01:15:13 Yeah, I agree with you.
01:15:14 I didn’t say that either.
01:15:15 I would say I just don’t have enough data.
01:15:17 But the thing I want to push back on is the statement
01:15:20 that everybody has a high definition camera.
01:15:23 One of the disappointing things to me
01:15:24 about the report that the government released,
01:15:27 but in general, just having worked with government,
01:15:29 having worked with people all over
01:15:32 is how incompetent we are.
01:15:36 Like if you look at the response to the pandemic,
01:15:38 how incompetent we are in the face of great challenges
01:15:44 without great leadership.
01:15:46 How incompetent we are in the face
01:15:47 of the great mysteries before us without great leadership.
01:15:51 And I just think it’s actually,
01:15:54 the fact that there’s a lot of high definition cameras
01:15:56 is not enough to capture the full richness of weird,
01:16:01 of the mysterious phenomena out there
01:16:03 of which extraterrestrial intelligence visiting Earth
01:16:07 could be one.
01:16:08 I don’t think we have,
01:16:09 I don’t think everybody having a smartphone
01:16:12 in their pocket is enough.
01:16:14 I think that allows for TikTok videos.
01:16:17 I don’t think it allows for the capture
01:16:19 of even interesting, relatively rare human events.
01:16:23 That’s not that common.
01:16:25 It’s rare to have been the right moment in the right time
01:16:28 to be able to capture the thing.
01:16:30 I agree, I agree.
01:16:31 Let me rephrase what I think on this.
01:16:33 I haven’t seen enough information.
01:16:35 I haven’t really actively sorted out.
01:16:37 I must admit, but I’m with you
01:16:40 and I love the idea of anomaly detection
01:16:42 in chemistry in particular, right?
01:16:44 I want to make anomalies, sorry,
01:16:45 or not necessarily make anomalies.
01:16:47 I want to understand an anomaly.
01:16:50 Let me give you two from chemistry,
01:16:53 which are really quite interesting.
01:16:56 Phlogiston, going way back,
01:16:59 where people said there’s this thing called phlogiston.
01:17:02 And for ages, the alchemists got really this kind of,
01:17:05 that fire is the thing.
01:17:09 That’s one.
01:17:09 And then we determined that phlogiston
01:17:11 wasn’t what we thought it is.
01:17:13 Let’s go to physics, the ether.
01:17:15 The ether’s a hard one
01:17:16 because I think actually the ether might exist.
01:17:18 And I’ll tell you what I think the ether is later.
01:17:24 Can you explain the ether?
01:17:25 So as the vacuum,
01:17:26 so the light traveling through the ether in the vacuum,
01:17:28 there is some thing that we call the ether
01:17:30 that basically mediates the movement of light, say.
01:17:34 And I think that…
01:17:36 And then the other one is cold fusion,
01:17:38 which is more of a…
01:17:39 So a few years ago,
01:17:40 people observed that when they did some electrochemistry,
01:17:44 when they were splitting water into hydrogen and oxygen,
01:17:48 that you got more energy out than you put in.
01:17:50 And people got excited
01:17:51 and they thought that this was a nuclear reaction.
01:17:54 And in the end, it was kind of discredited
01:17:57 because you didn’t detect neutrons and all this stuff.
01:17:59 But I’m pretty sure…
01:18:02 I’m a chemist.
01:18:03 I’m telling you this on your podcast, but why not?
01:18:06 I’m pretty sure there’s interesting
01:18:07 electrochemical phenomena
01:18:08 that’s not completely bottomed out yet,
01:18:09 that there is something there.
01:18:11 However, we lack the technology and the experimental design.
01:18:15 So all I’m saying in your response about aliens
01:18:18 is we lack the experimental design
01:18:20 to really capture these anomalies.
01:18:22 And we are encircling the planet
01:18:25 with many more detection systems.
01:18:27 We’ve got satellites everywhere.
01:18:28 So there is, I do hope
01:18:30 that we are gonna discover more anomalies.
01:18:32 And remember that the solar system
01:18:35 isn’t just static in space,
01:18:37 it’s moving through the universe.
01:18:39 So there’s just more and more chance.
01:18:40 I’m not what with Avi Loeb.
01:18:42 He’s generating all sorts of kind of a cult,
01:18:46 I would say, with this, but I’m not against him.
01:18:50 I think there is a finite chance
01:18:52 if there are aliens in the universe
01:18:53 that we’re gonna happen upon them
01:18:54 because we’re moving through the universe.
01:18:56 What’s the nature of the following that Avi Loeb has?
01:18:59 He’s doubling down more and more and more
01:19:01 and say there are aliens,
01:19:02 interdimensional aliens and everything else, right?
01:19:04 He’s gone from space junk accelerating out of
01:19:06 to interdimensional stuff in a very short space of time.
01:19:11 I see.
01:19:12 He’s obviously bored.
01:19:15 Or he wants to tap into the psyche and understand.
01:19:18 And he’s playfully kind of trying to interact
01:19:21 with society and his peers to say,
01:19:22 stop saying it’s not possible.
01:19:26 Which I agree with, we shouldn’t do that.
01:19:28 But we should frame it statistically
01:19:30 in the same way we should frame everything
01:19:32 as good scientists, statistically.
01:19:34 Yeah, good scientists.
01:19:40 Recently, the idea of good scientists is,
01:19:45 I take quite skeptically.
01:19:47 I’ve been listening to a lot of scientists
01:19:49 tell me about what is good science.
01:19:52 That makes me sad.
01:19:53 Because you’ve been interviewing
01:19:54 what I would consider a lot of really good scientists.
01:19:56 No, that’s true.
01:19:57 A lot of great thinkers.
01:19:58 But that’s exactly right.
01:19:59 And most of the people I talk to
01:20:01 are incredible human beings.
01:20:03 But there’s a humility that’s required.
01:20:05 Science is not, science cannot be dogmatism.
01:20:10 Sure, I agree.
01:20:11 I mean, authority, like a PhD does not give you authority.
01:20:17 A lifelong pursuit of a particular task
01:20:19 does not give you authority.
01:20:21 You’re just as lost in clues as everybody else.
01:20:24 But you’re more curious and more stubborn.
01:20:27 So that’s a nice quality to have.
01:20:29 But overall, just using the word science and statistics
01:20:37 can often, as you know, kind of become a catalyst
01:20:43 for dismissing new ideas, out of the box ideas, wild ideas,
01:20:49 all that kind of stuff.
01:20:50 Well, yes and no.
01:20:52 I think that, so I like to,
01:20:57 some people find me extremely annoying in science
01:20:59 because I’m basically, I’m quite rude and disruptive.
01:21:04 Not in a rude, you know,
01:21:05 some up to people and say they’re ugly or stupid
01:21:07 or anything like that.
01:21:08 I just say, you know, you’re wrong.
01:21:12 Or why do you think this?
01:21:13 And something, a gift I got given by society
01:21:16 when I was very young,
01:21:17 because I was in the learning difficulties class at school
01:21:20 is I was told I was stupid.
01:21:22 And so I know I’m stupid,
01:21:24 but I always wanted to be smart, right?
01:21:26 I remember going to school going,
01:21:29 maybe today they’re going to tell me
01:21:30 I’m not as stupid as I was yesterday.
01:21:32 And I was always disappointed, always.
01:21:34 And so when I went into academia and everyone says,
01:21:36 you’re wrong, I was like, join the queue.
01:21:39 Yeah.
01:21:40 Because it allowed me to walk through the wall.
01:21:43 So I think that people like to always imagine science
01:21:46 as a bit like living in a Japanese house,
01:21:48 the paper walls, and everyone sits in their room.
01:21:52 And I annoy people because I walk straight through the wall.
01:21:54 Not because, why should I be a chemist
01:21:56 and not a mathematician?
01:21:58 Why should I be a mathematician and not a computer scientist?
01:22:00 Because if the problem requires us
01:22:02 to walk through those walls,
01:22:05 but I like walking through the walls.
01:22:08 But as long, then I have to put up,
01:22:11 you know, I have to do good science.
01:22:12 I have to win the people in those rooms
01:22:15 across by good science,
01:22:17 by taking their criticisms and addressing them head on.
01:22:21 And I think we must do that.
01:22:22 And I think that I try and do that in my own way.
01:22:25 And I kind of love walking through the walls.
01:22:29 And it gives me, it’s difficult for me personally.
01:22:33 It’s quite painful,
01:22:35 but it always leads to a deeper understanding
01:22:38 of the people I’m with.
01:22:39 In particular, you know, the arguments I have
01:22:41 with all sorts of interesting minds,
01:22:43 because I want to solve the problem,
01:22:45 or I want to understand more about why I exist.
01:22:49 You know, that’s it really.
01:22:52 And I think we have to not dismiss science
01:22:55 on that basis.
01:22:55 I think we can work with science.
01:22:58 No, science is beautiful,
01:22:59 but humans with egos and all those kinds of things
01:23:03 can sometimes misuse good things,
01:23:08 like social justice,
01:23:10 like all ideas we’re all aspire to misuse
01:23:14 these beautiful ideas to manipulate people,
01:23:18 to all those kinds of things.
01:23:20 Sure.
01:23:20 And that’s, there’s assholes in every space
01:23:24 and walk of life, including science.
01:23:26 Yeah, yeah, yeah, of course.
01:23:27 And those are no good.
01:23:28 But yes, you’re right.
01:23:29 The scientific method has proven to be quite useful.
01:23:34 That said, for difficult questions,
01:23:36 for difficult explanations for rare phenomena,
01:23:42 you have to walk cautiously.
01:23:47 Because the scientific method,
01:23:50 when you totally don’t understand something,
01:23:53 and it’s rare, and you can’t replicate it,
01:23:55 doesn’t quite apply.
01:23:57 Yeah, yeah, yeah, that’s it.
01:23:58 I agree with you.
01:23:59 The challenge is to not dismiss the anomaly
01:24:02 because you can’t replicate it.
01:24:03 I mean, we can talk about this.
01:24:05 This is something I realized
01:24:06 when we were developing assembly theory.
01:24:10 People thinking that the track they’re on
01:24:13 is so dogmatic, but there is this thing that they see,
01:24:18 but they don’t see.
01:24:19 And it takes a bit of time
01:24:20 and you just have to keep reframing it.
01:24:21 And my approach is to say, well, why can’t this be right?
01:24:25 Why must we accept that RNA is the only way into life?
01:24:29 I mean, who said?
01:24:30 Does RNA have a special class of information
01:24:35 that’s encoded in the universe?
01:24:37 No, of course it doesn’t, right?
01:24:38 RNA is not a special molecule
01:24:41 in the space of all the other molecules.
01:24:42 But it’s so elegant and simple
01:24:44 and it works so well for the evolutionary process
01:24:46 that we kind of use that as an intuition
01:24:48 to explain that that must be the only way to have life.
01:24:51 Sure.
01:24:53 But you mentioned assembly theory.
01:24:55 Well, first let me pause, bathroom break, needed?
01:24:57 Yeah, let’s take two minutes.
01:24:59 We took a quick break and offline,
01:25:02 you mentioned to me that you have a lab in your home.
01:25:08 And then I said that you’re basically Rick
01:25:10 from Rick and Morty,
01:25:11 which is something I’ve been thinking
01:25:13 this whole conversation.
01:25:15 And then you say that there’s a glowing pickle
01:25:19 that you used something involving cold plasma, I believe.
01:25:23 I don’t know, but can you explain
01:25:24 the glowing pickle situation?
01:25:31 And is there many, arbitrarily many versions of you
01:25:34 in alternate dimensions that you’re aware of?
01:25:37 I tried to make an electrochemical memory at home
01:25:41 using a pickle and the only way I could get
01:25:45 any traction with it was actually by plugging it
01:25:49 into a very high voltage alternating current
01:25:51 and then putting in a couple of electrodes.
01:25:53 But my kids weren’t impressed.
01:25:54 They’re not impressed with anything I do,
01:25:56 any experiments I do at home.
01:25:57 I think it’s quite funny.
01:25:58 But you connected a pickle to some electrode.
01:26:01 240 volts, yeah, AC.
01:26:03 And then had a couple of electrodes on it.
01:26:04 So what happens is a pickle,
01:26:07 this is a classic thing you do.
01:26:09 I mean, I shouldn’t, pranks you do,
01:26:11 you put a pickle into the mains
01:26:13 and just leave it, run away and leave it.
01:26:15 And what happens is it starts to decompose.
01:26:17 It heats up and then explodes
01:26:19 because the water turns to steam
01:26:20 and it just violently explodes.
01:26:22 But I wondered if I could cause the iron,
01:26:25 sodium, potassium ions in the pickle to migrate.
01:26:27 It’d been in a jar, right?
01:26:28 So it’d been in a brine.
01:26:31 That was, yeah, that was not my best experiment.
01:26:34 So I’ve done far better experiments in my lab at home.
01:26:36 At that time it was a failed experiment,
01:26:38 but you never know, it could,
01:26:41 every experiment is a successful experiment
01:26:44 if you stick with it long enough.
01:26:46 Well, I mean, I get, I got kicked out of my own lab
01:26:48 by my research team many years ago and for good reason.
01:26:50 I mean, my team is brilliant
01:26:51 and I used to go and just break things.
01:26:53 So what I do do at home
01:26:55 is I have a kind of electronics workshop
01:26:58 and I prototype experiments there.
01:27:01 Then I try and then I try and suggest to my team sometimes,
01:27:05 maybe we can try this thing.
01:27:07 And they would just say, oh,
01:27:08 wow, that’s not gonna work because of this.
01:27:10 And I’ll say, aha, but actually I’ve tried
01:27:12 and here’s some code and here’s some hardware.
01:27:14 Can we have a go?
01:27:15 So I’m doing that less and less now
01:27:17 as I get even more busy, but that’s quite fun
01:27:20 because they feel that we’re in the experiment together.
01:27:24 You do, in fact, brilliantly, just like Rick
01:27:28 from Rick and Morty, connect up chemistry with computation.
01:27:38 And when we say chemistry,
01:27:40 we don’t mean the simulation of chemistry,
01:27:45 a modeling of chemistry.
01:27:46 We mean chemistry in the physical space
01:27:49 as well as in the digital space, which is fascinating.
01:27:52 We’ll talk about that.
01:27:54 But first you mentioned assembly theory.
01:27:56 So we’ll stick on theory in these big ideas.
01:28:00 I would say revolutionary ideas,
01:28:03 this intersection between mathematics and philosophy.
01:28:07 What is assembly theory?
01:28:09 And generally speaking, how would we recognize life
01:28:13 if we saw it?
01:28:15 So assembly theory is a theory,
01:28:17 goes back a few years now in my struggle
01:28:19 for maybe almost 10 years
01:28:22 when I was going to origin of life conferences
01:28:24 and artificial life conferences,
01:28:25 where I thought that everybody was dancing
01:28:28 around the problem of what life is and what it does.
01:28:32 But I’ll tell you about what assembly theory is
01:28:34 because I think it’s easier.
01:28:35 So assembly theory literally says if you take an object,
01:28:39 any given object,
01:28:40 and you are able to break the object into parts very gently.
01:28:43 So just maybe let’s say take a piece
01:28:46 of very intricate Chinese porcelain
01:28:48 and you tap it just with a hammer or the nail at some point,
01:28:52 and it will fragment into many parts.
01:28:54 And if that object is able to fragment into many,
01:28:57 and you count those parts, the different parts,
01:29:00 so they’re unsymmetrical,
01:29:02 assembly theory says the larger the number of parts,
01:29:07 unsymmetrical parts that object has,
01:29:10 the more likely it is that object has been created
01:29:12 by an evolutionary or information process,
01:29:15 especially if that object is not one off,
01:29:18 you’ve got an abundance of them.
01:29:22 And that’s really important.
01:29:23 So because what I’m literally saying about the abundance,
01:29:26 if you have a one off object and you break it into parts
01:29:30 and it has lots of parts,
01:29:32 you’d say, well, that could be incredibly intricate
01:29:36 and complex, but it could be just random.
01:29:39 And I was troubled with this for years
01:29:41 because I saw in reality that assembly theory works.
01:29:44 But when I talked to very good
01:29:46 computational complexity computation lists,
01:29:49 algorithmic complexity people,
01:29:51 they said, you haven’t really done this properly.
01:29:53 You haven’t thought about it.
01:29:54 It’s like, this is the random problem.
01:29:57 And so I kept working this up
01:29:59 because I invented an assembly theory in chemistry,
01:30:03 first of all, with molecules.
01:30:05 And so the thought experiment was,
01:30:08 how complex does a molecule need to be when I find it
01:30:11 that it couldn’t possibly have risen by chance,
01:30:13 probabilistically.
01:30:15 And if I found this molecule,
01:30:16 able to detect it enough quantities in the same object,
01:30:18 like a machine, like a mass spectrometer.
01:30:20 So typically in a mass spectrometer,
01:30:22 you weigh the molecules in electric field.
01:30:24 You probably have to have all the order of 10,000
01:30:26 identical molecules to get a signal.
01:30:28 So 10,000 identical molecules that are complex.
01:30:32 What is the chance of them occurring by chance?
01:30:36 Well, we can do the math.
01:30:37 Let’s take a molecule like strychnine
01:30:39 or, yeah, so strychnine is a good molecule actually to take
01:30:44 or Viagra is a good molecule.
01:30:46 I made jokes about Viagra because it’s a complex molecule.
01:30:49 And one of my friends said, yeah,
01:30:50 if we find Viagra on Mars in detectable quantities,
01:30:53 we know something is up.
01:30:54 And yeah, but anyway, it’s a complex molecule.
01:31:00 So what you do is you take this molecule
01:31:01 in the mass spectrometer and you hit it with some electrons
01:31:03 or in electric field and it breaks apart.
01:31:06 And if the larger the number of different parts,
01:31:09 you know when it starts to get refreshed,
01:31:12 my idea was that that molecule could not be created
01:31:15 by chance, probabilistically.
01:31:17 So that was where assembly theory was born
01:31:20 in an experiment, in a mass spec experiment.
01:31:22 And I was thinking about this
01:31:24 because NASA is sending mass spectrometers to Mars,
01:31:26 to Titan, it’s gonna send them to Europa.
01:31:29 There’s gonna be a nuclear powered mass spectrometer
01:31:32 going to Titan.
01:31:33 I mean, this is the coolest experiment ever.
01:31:35 They’re not only sending a drone
01:31:37 that’s gonna fly around Titan,
01:31:38 it’s gonna be powered by a nuclear slug, a nuclear battery,
01:31:43 and it’s gonna have a mass spectrometer on it.
01:31:45 Is this already launched?
01:31:47 No, it’s Dragonfly
01:31:49 and it’s gonna be launched in a few years.
01:31:50 I think it got pushed a year because of the pandemic.
01:31:53 So I think it’s three or four years.
01:31:55 Dragonfly, nuclear Dragonfly is going to fly to Titan
01:32:00 and collect data about the composition
01:32:07 of the various chemicals on Titan.
01:32:09 Yeah, I’m trying to convince NASA.
01:32:11 I don’t know if I’ll be able to convince
01:32:12 the Dragonfly team that they should apply this approach,
01:32:16 but they will get data.
01:32:18 And depending on how good their mass spectrometer is.
01:32:20 But I had this thought experiment anyway,
01:32:22 and I did this thought experiment.
01:32:24 And for me, it seemed to work.
01:32:26 I turned the thought experiment into an algorithm
01:32:29 in assembly theory.
01:32:30 And I basically, assembly theory, if I take,
01:32:32 let’s just make it generic.
01:32:33 And so let’s just take the word abracadabra.
01:32:36 Say, can I, if you find the word,
01:32:38 so if you have a book with lots of words in it
01:32:41 and you find abracadabra one off,
01:32:42 and it’s a rap book that’s been written by,
01:32:45 in a random way, set of monkeys in a room.
01:32:48 And you’re on typewriters.
01:32:50 And you find one off abracadabra,
01:32:51 no big deal.
01:32:52 But if you find lots of recurrences of abracadabra,
01:32:55 well, that means something weird is going on.
01:32:57 But let’s think about the assembly number of abracadabra.
01:33:00 So abracadabra has a number of letters in it.
01:33:04 You can break it down.
01:33:05 So you just cut the letters up.
01:33:07 But when you actually reassemble abracadabra,
01:33:09 the minimum number of ways of organizing those letters.
01:33:12 So you’d have an A, a B, and keep going up.
01:33:18 When you cut abracadabra up into parts,
01:33:21 you can put it together again in seven steps.
01:33:24 So what does that mean?
01:33:24 That means if you basically don’t,
01:33:26 you’re allowed to reuse things
01:33:28 you make in a chain at the beginning.
01:33:30 That’s the memory of the universe,
01:33:32 the process that makes abracadabra.
01:33:35 And because of that causal chain,
01:33:36 you can then get to abracadabra
01:33:38 quicker than the number of letters
01:33:40 for having to specify only in seven.
01:33:43 So if you take that to a molecule
01:33:44 and you cut the molecule up into parts,
01:33:47 and you can, on the causal chain,
01:33:49 and you basically start with the atoms
01:33:51 and then bonds, and then you randomly add on those parts
01:33:54 to make the A, make the B, and keep going all the way up,
01:33:59 I found that literally, assembly theory
01:34:01 allows me to say how compressed a molecule is.
01:34:04 So when there’s some information in there.
01:34:07 And I realized assembly theory
01:34:09 isn’t just confined to molecular space.
01:34:13 It can apply to anything.
01:34:14 But let me finish the molecular argument.
01:34:16 So what I did is I had this theory.
01:34:18 I, with one of my students, we wrote an algorithm.
01:34:22 We basically took the 20 million molecules from a database
01:34:26 and we just calculate their assembly number.
01:34:28 And that’s the index.
01:34:29 Like basically, if I take a molecule
01:34:32 and I cut it up into bonds,
01:34:33 what is the minimum number of steps I need to take
01:34:36 to reform that molecule from atoms?
01:34:39 So reusability of previously formed things
01:34:42 is somehow a fundamental part of what it is.
01:34:43 Exactly, it’s like a memory in the universe, right?
01:34:46 I’m making lots of leaps here.
01:34:47 Like, it’s kind of weird.
01:34:48 I’m saying, right, there’s a process
01:34:50 that can form the A and the B and the C, let’s say.
01:34:53 And then because we’ve formed A and B before,
01:34:56 we can use A and B again with no extra cost except one unit.
01:35:00 So that’s the kind of what the chain of events.
01:35:02 And that’s how you think about memory here
01:35:04 when you say the universe,
01:35:05 when you talk about the universe
01:35:07 or life is the universe creating memory.
01:35:11 Exactly.
01:35:12 So we went through chemical space
01:35:15 and we looked at the assembly numbers.
01:35:16 We were able to classify it.
01:35:18 So, okay, let’s test it.
01:35:20 Let’s go.
01:35:21 So we’re able to take a whole bunch of molecules
01:35:23 and assign an assembly index to them, okay?
01:35:27 And it’s just a function of the number of bonds
01:35:30 in the molecule and how much symmetry.
01:35:32 So literally assembly theory is a measure
01:35:34 of how little symmetry a molecule has.
01:35:37 And so the more asymmetry, the more information,
01:35:40 the more weird it is,
01:35:41 like a Jackson Pollock of some description.
01:35:44 So I then went and did a load of experiments.
01:35:47 And I basically took those molecules,
01:35:49 I cut them up in the mass spec
01:35:51 and measured the number of peaks
01:35:52 without any knowledge of the molecule.
01:35:55 And we found the assembly number,
01:35:57 there was almost not quite a one to one correlation,
01:36:00 but almost because not all bonds are equal.
01:36:02 They have different energies.
01:36:03 I then did this using two other spectroscopic techniques,
01:36:07 NMR, nuclear magnetic resonance,
01:36:08 which uses radio frequency to basically jangle the molecules
01:36:11 and get a signature out.
01:36:13 And I also used infrared.
01:36:15 And infrared and NMR almost gave us a one to one correlation.
01:36:18 So what am I saying?
01:36:19 Saying by taking a molecule
01:36:21 and doing either infrared or NMR or mass spec,
01:36:26 I can work out how many parts there are in that molecule
01:36:30 and then put it on a scale.
01:36:32 And what we did in the next part of the work
01:36:35 is we took molecules randomly from the environment,
01:36:39 from outer space, from all around earth,
01:36:41 from the sea, from Antarctica,
01:36:45 and from fossils and so on.
01:36:47 And even NASA, because they didn’t believe us,
01:36:49 blinded some samples.
01:36:51 And we found that all these samples that came from biology
01:36:57 produced molecules that had a very high assembly number
01:37:00 above a threshold of about 15.
01:37:02 So basically all the stuff that came
01:37:05 from an ebiotic origin was low.
01:37:08 There was no complexity there.
01:37:10 So we suddenly realized that on earth at least,
01:37:12 there is a cutoff that natural phenomena
01:37:16 cannot produce molecules
01:37:17 that need more than 15 steps to make them.
01:37:21 So I realized that this is a way to make a scale of life,
01:37:25 a scale of technology as well.
01:37:27 And literally you could just go sniffing for molecules
01:37:30 off earth, on Titan, on Mars.
01:37:33 And when you find a molecule in the mass spectrometer
01:37:35 that gives you more than 15 parts,
01:37:37 you’ll know pretty much for sure
01:37:40 that it had to be produced by evolution.
01:37:43 And this allowed me to come up with a general definition
01:37:45 of life based on assembly theory,
01:37:47 to say that if I find an object that has a large number
01:37:51 of parts, say an iPhone or Boeing 747,
01:37:54 or any complex object and I can find it in abundance
01:37:58 and cut it up, I can tell you whether that has been produced
01:38:03 by an informational process or not.
01:38:04 And that’s what assembly theory kind of does.
01:38:07 But it goes a bit further.
01:38:09 I then realized that this isn’t just about life,
01:38:12 it’s about causation.
01:38:14 So actually it tells you about
01:38:15 whether it’s a causal structure.
01:38:17 So now I can look at objects in the universe,
01:38:19 say that again, this cup and say, right,
01:38:20 I’m gonna look at how many independent parts it has.
01:38:23 So that’s the assembly number.
01:38:25 I’ll then look at the abundance, how many cups?
01:38:28 There are two on this table,
01:38:28 maybe there’s a few more you got stashed away.
01:38:31 So assembly is a function of the complexity of the object
01:38:37 times the number of copy numbers of that object
01:38:39 or a function of the copy number normalized.
01:38:41 So I realized there’s a new quantity in the universe.
01:38:45 You have energy, entropy, and assembly.
01:38:49 So assembly, the way we should think about that
01:38:51 is how much reusability there is.
01:38:55 Because reusability is like,
01:38:57 can you play devil’s advocate to this?
01:38:59 So could this just be a nice tertiary signal
01:39:08 for living organisms?
01:39:10 Like some kind of distant signal that’s,
01:39:13 yeah, this is a nice property,
01:39:15 but it’s not capturing something fundamental.
01:39:17 Or do you think reusability is something fundamental
01:39:20 to life and complex organisms?
01:39:22 I think reusability is fundamental in the universe,
01:39:25 not just for life and complex organisms.
01:39:27 It’s about causation.
01:39:29 So I think assembly tells you if you find objects,
01:39:32 cause you can do this with trajectories as well.
01:39:35 You think about it,
01:39:36 that the fact there are objects in the universe on earth
01:39:41 is weird.
01:39:43 You think about it,
01:39:44 we should just have a combinatorial explosion of stuff.
01:39:47 The fact that not everything exists is really weird.
01:39:53 Now then.
01:39:54 And then as I’m looking at two mugs and two water bottles
01:39:59 and the things that exist kind of are similar
01:40:04 and multiply in copies of each other.
01:40:08 So I would say that assembly allows you to do something
01:40:10 that statistical mechanics and people looking at entropy
01:40:14 have got stuck with for a while.
01:40:16 So I’m making, it’s pretty bold.
01:40:18 I mean, I’m writing a paper with Sarah Walker
01:40:20 on this at the moment.
01:40:21 And we’re realizing,
01:40:23 we don’t want to get ahead of ourselves
01:40:24 because I think that there’s lots of ways where this is,
01:40:27 you know, it’s a really interesting idea.
01:40:30 It works for molecules and it appears to work
01:40:33 for any objects produced by causation.
01:40:35 Cause you can take a motor car,
01:40:36 you can look at the assembly of the motor car,
01:40:37 look at a book, look at the assembly of the book.
01:40:39 Assembly theory tells you
01:40:41 there’s a way of compressing and reusing.
01:40:43 And so when people, I talk to information theorists,
01:40:46 they say, oh, this is just logical depth.
01:40:48 I say, it is like logical depth,
01:40:51 but it’s experimentally measurable.
01:40:53 They say, oh, it’s a bit like Komogolov complexity.
01:40:55 And so, but it’s computable.
01:40:59 And now, okay, it’s not infinitely computable,
01:41:00 gets MP hard very quickly, right?
01:41:02 It’s very hard problem when you could get,
01:41:04 but it’s a computable enough,
01:41:06 you could tractable enough to be able to tell
01:41:08 the difference between a molecule
01:41:09 that’s been formed by the random background
01:41:11 and by causation.
01:41:13 And I think that that’s really interesting
01:41:16 because until now there’s no way
01:41:19 of measuring complexity objectively.
01:41:21 Complexity has required algorithmic comparisons
01:41:26 and programs and human beings to label things.
01:41:30 Assembly is label free.
01:41:32 Well, not entirely.
01:41:34 We can talk about what that means in a minute.
01:41:37 Okay, my brain has been broken a couple of times here.
01:41:42 I’m sorry I explained it really badly.
01:41:43 No, it was very well explained.
01:41:45 It was just fascinating.
01:41:45 And it’s, my brain is broken into pieces
01:41:50 and I’m trying to assemble it.
01:41:53 So MP hard.
01:41:55 So when you have a molecule,
01:41:58 you’re trying to figure out, okay,
01:42:01 if we were to reuse parts of this molecule,
01:42:03 which parts can we reuse as an optimization problem,
01:42:10 and be hard to figure out the minimum amount
01:42:13 of reused components that will create this molecule.
01:42:18 And it becomes difficult when you start
01:42:19 to look at a huge, huge molecules, arbitrarily large.
01:42:23 Cause I’m also like mapping this.
01:42:25 Can I think about this in complexity generally,
01:42:28 like looking at a cellular automata system
01:42:30 and saying like, what’s the,
01:42:33 can this be used as a measure of complexity
01:42:35 for like a arbitrarily complicated system?
01:42:38 Yeah, I think it can.
01:42:40 It can.
01:42:41 And I think that the question is, and what’s the benefit?
01:42:43 Cause there’s plenty of, I mean,
01:42:46 in computer science and mathematics and in physics,
01:42:48 people have been really seriously studying complexity
01:42:51 for a long time.
01:42:53 And I think there’s a really interesting problems
01:42:55 of where we course grade and we lose information.
01:42:58 And all assembly theory does really,
01:43:00 assembly theory just explains weak emergence.
01:43:03 And so what assembly theory says, look,
01:43:05 going from the atoms that interact,
01:43:08 those first replicators that build one another,
01:43:12 assembly at the minimal level just tells you evidence
01:43:14 that there’s been replication and selection.
01:43:17 And I think the more selected something is,
01:43:20 the higher the assembly.
01:43:22 And so we were able to start to know
01:43:25 how to look for selection in the universe.
01:43:27 If you go to the moon,
01:43:28 there’s nothing a very high assembly on the moon
01:43:30 except the human artifacts we’ve left there.
01:43:32 So again, let’s go back to the sandbox.
01:43:36 In assembly theory says,
01:43:37 if all the sand grains could stick together,
01:43:40 that’s the infinite combinatorial explosion
01:43:42 in the universe, that should be the default.
01:43:44 We don’t have that.
01:43:45 Now let’s assemble sand grains together
01:43:48 and do them in every possible way.
01:43:51 So we have a series of minimal operations
01:43:54 that can move the sand together.
01:43:56 But all that doesn’t exist either.
01:43:57 Now, because we have specific memory where we say,
01:43:59 well, we’re gonna put three sand grains in line
01:44:01 or four and make a cross or a triangle
01:44:03 or something unsymmetrical.
01:44:05 And once we’ve made the triangle
01:44:06 and the unsymmetrical thing, we remember that,
01:44:08 we can use it again, cause on that causal chain.
01:44:10 So what assembly theory allows you to do
01:44:12 is go to the actual object that you exist,
01:44:14 you find in space.
01:44:16 And actually the way you get there is by disassembling.
01:44:18 It’s disassembly theory works by disassembling objects
01:44:23 you have and understanding the steps to create them.
01:44:27 And it works for molecules beautifully
01:44:30 cause you just break bonds.
01:44:31 But like you said, it’s very difficult.
01:44:33 It’s a difficult problem to figure out
01:44:35 how to break them apart.
01:44:36 For molecules, it’s easy.
01:44:37 If you just keep low enough in molecular weight space,
01:44:40 it’s good enough.
01:44:41 So it’s a complete theory.
01:44:43 When we start to think about objects,
01:44:45 we can start to assign,
01:44:46 we can start to think about things at different levels,
01:44:49 different atoms, what you assign as your atom.
01:44:51 So in a molecule, the atom, this is really confusing
01:44:54 cause the word atom, I mean smallest breakable part.
01:44:57 So in a molecule, the atom is the bond
01:44:59 cause you break bonds, not atoms, right?
01:45:02 So in a car, the atom might be, I don’t know,
01:45:06 a small amount of iron or the smallest reusable part,
01:45:09 a rivet, a piece of plastic or something.
01:45:13 So you gotta be really careful.
01:45:14 In a microprocessor, the atoms might be transistors.
01:45:18 And so the amount of assembly that something has
01:45:23 is a function, you have to look at the atom level.
01:45:26 What are your parts?
01:45:28 What are you counting?
01:45:29 That’s one of the things you get to choose.
01:45:30 What is, at what scale is the atom?
01:45:32 What is the minimal thing?
01:45:34 I mean, there’s a huge amounts of trade offs
01:45:36 in when you approach a system and try to analyze.
01:45:39 Like if you approach Earth,
01:45:41 you’re an alien civilization trying to study Earth,
01:45:43 what is the atom for trying to measure
01:45:45 the complexity of life?
01:45:48 Is it, are humans the atoms?
01:45:50 I would say to start with, you just use molecules.
01:45:53 I can say for sure, if there are molecules
01:45:56 of sufficient complexity on Earth,
01:45:58 then I know that life has made them.
01:45:59 And then go further and show technology.
01:46:01 There are molecules that exist on Earth
01:46:03 that are not possible even by biology.
01:46:06 You needed technology
01:46:07 and you needed microprocessors to get there.
01:46:09 So that’s really cool.
01:46:11 And that there’s a correlation between that,
01:46:14 between the coolness of that and assembly number,
01:46:18 whatever the measure.
01:46:19 What’s the, what would you call the measure?
01:46:21 Assembly index.
01:46:22 Yeah, assembly index.
01:46:23 So there are three kind of fundamental
01:46:25 kind of labels we have.
01:46:26 So there’s the quantity of assembly
01:46:28 and the assembly, so if you have a box,
01:46:31 let’s just have a box of molecules.
01:46:32 So I’m gonna have my box.
01:46:34 We count the number of identical molecules
01:46:36 and then we chop each molecule up
01:46:37 in an individual molecule class
01:46:40 and calculate the assembly number.
01:46:42 So basically you then have a function
01:46:45 that sums over all the molecules for each assembly
01:46:49 and then you divide through.
01:46:50 So you make it divide through
01:46:52 by the number of molecules.
01:46:54 So that’s the assembly index for the box?
01:46:56 So that will tell you the amount of assembly in the box.
01:46:58 So basically the assembly equation we come up with
01:47:01 is like basically the sum of e to the power
01:47:04 of the assembly index for molecule i
01:47:07 times the number of copies of the molecule i
01:47:10 and then you normalize.
01:47:11 So you sum them all up and then normalize.
01:47:13 So some boxes are gonna be more assembled than others.
01:47:16 Yeah, that’s what they tell me.
01:47:17 So if you were to look at me as a box,
01:47:19 so say I’m a box, am I assembling my parts?
01:47:23 In terms of like, how do you know,
01:47:25 what’s my assembly index?
01:47:27 So I’ve been gentle.
01:47:28 So let’s just, we’ll talk about the molecules in you.
01:47:30 So let’s just take a pile of sand the same way as you
01:47:34 and I would take you and just cut up all the molecules.
01:47:40 I mean, and look at the number of copies
01:47:42 and assembly number.
01:47:43 So in sand, let’s say there’s probably gonna be
01:47:46 nothing more than assembly number of two or three,
01:47:48 but there might be trillions and trillions of sand grains.
01:47:51 In your body, there might be,
01:47:53 the assembly number is gonna be higher,
01:47:56 but there might not be as quite as many copies
01:47:58 because the molecular weight is higher.
01:48:01 So you do wanna average it out.
01:48:03 You can average, you do average it.
01:48:04 I’m not defined by the most impressive molecules.
01:48:07 No, no, you’re an average in your volume.
01:48:08 Well, I mean, we’re just working this out,
01:48:10 but what’s really cool is you’re gonna have
01:48:13 a really high assembly.
01:48:15 The sand will have a very low assembly.
01:48:16 Your causal power is much higher.
01:48:19 You get to make decisions, you’re alive, you’re aspiring.
01:48:22 Assembly says something about causal power in the universe.
01:48:26 And that’s not supposed to exist
01:48:28 because physicists don’t accept
01:48:30 that causation exists at the bottom.
01:48:33 So I understand at the chemical level
01:48:34 why the assembly causes causation.
01:48:37 Why is it causation?
01:48:38 Because it’s capturing the memory.
01:48:40 Exactly.
01:48:41 Capturing memory, but there’s not an action to it.
01:48:45 So I’m trying to see how it leads to life.
01:48:51 Well, it’s what life does.
01:48:52 So I think it’s, we don’t know.
01:48:55 So. Yeah, that’s a good question.
01:48:57 What is life versus what does life do?
01:49:00 Yeah, so that’s, this is the definition of life.
01:49:02 The only definition we need, right?
01:49:04 The assembly index.
01:49:05 It’s basically that life is able to create objects
01:49:09 in abundance that are so complex,
01:49:14 the assembly number is so high,
01:49:15 they can’t possibly be formed in an environment
01:49:18 where there’s just random interactions.
01:49:20 Yeah.
01:49:21 So suddenly you can put life on a scale.
01:49:24 And then life doesn’t exist actually in that camp.
01:49:27 It’s just how evolved you are.
01:49:30 And you as an object,
01:49:33 because you have incredible causal power,
01:49:35 you could go and, you can go and, you know,
01:49:39 launch rockets or build cars or create drugs,
01:49:43 or, you know, you can do so many things.
01:49:46 You can build stuff, build more artifacts
01:49:49 that show that you have had causal power.
01:49:52 And that causal power was this kind of a lineage.
01:49:55 And I think that over time,
01:49:57 I’ve been realizing that physics as a discipline
01:50:02 has a number of problems associated with it.
01:50:04 Me as a chemist, it’s kind of interesting
01:50:07 that assembly theory, and I’m really, you know,
01:50:10 I want to maintain some credibility in the physicists eyes,
01:50:13 but I have to push them because they,
01:50:15 physics is a really good discipline.
01:50:17 It’s reduced the number,
01:50:20 physics is about reducing the belief system,
01:50:22 but they’re down to some things in their belief system,
01:50:24 which is kind of really makes me kind of grumpy.
01:50:27 Number one is requiring order
01:50:29 at the beginning of the universe magically.
01:50:31 We don’t need that.
01:50:32 The second is the second law.
01:50:34 Well, we don’t actually need that.
01:50:36 And I…
01:50:37 This is blasphemous.
01:50:39 Well, in a minute, I’ll recover my career in a second.
01:50:42 Although I think the good,
01:50:43 the only good thing about being the regis chair
01:50:45 means I think there has to be an act of parliament to fire me.
01:50:47 Yeah.
01:50:48 Yeah.
01:50:49 Yeah.
01:50:50 Yeah.
01:50:51 Yeah.
01:50:52 But you can always go to Lee’s Twitter and protest.
01:50:56 And I think the third thing is that,
01:50:58 so we’ve got, you know,
01:50:59 we’ve got the order at the beginning.
01:51:02 Second law.
01:51:03 The second law and the fact that causation is emergent,
01:51:06 right?
01:51:07 And that time is emergent.
01:51:09 John Carroll just turned off this program.
01:51:12 I think he believes that it’s emergent.
01:51:13 So causation is not…
01:51:15 That’s clearly incorrect
01:51:17 because we wouldn’t exist otherwise.
01:51:19 So physicists have kind of got confused about time.
01:51:23 Time is a real thing.
01:51:25 Well, I mean, so look,
01:51:29 I’m very happy with the current description
01:51:31 of the universe as physics give me,
01:51:32 because I can do a lot of stuff, right?
01:51:33 I can go to the moon with Newtonian physics, I think,
01:51:36 and I can understand the orbit of Mercury with relativity.
01:51:41 And so, and I can build transistors
01:51:42 with quantum mechanics, right?
01:51:43 And I can do all this stuff.
01:51:45 So I’m not saying the physics is wrong.
01:51:47 I’m just saying, if we say that time is fundamental,
01:51:50 i.e. time is nonnegotiable, there’s a global clock,
01:51:52 I don’t need to require
01:51:56 that there’s order been magically made in the past
01:51:59 because that asymmetry is built into the way the universe is.
01:52:05 So if time is fundamental,
01:52:06 I mean, you’ve been referring to this kind of
01:52:11 an interesting formulation of that is memory.
01:52:13 Yeah.
01:52:14 So time is hard to like put a finger on,
01:52:18 like what the hell are we talking about?
01:52:20 Well, it’s just the direction,
01:52:21 but memory is a construction,
01:52:24 especially when you have like,
01:52:26 think about these local pockets of complexity,
01:52:28 these nonzero assembly index entities
01:52:34 that’s being constructed and they remember.
01:52:37 Never forget molecules.
01:52:39 But remember, the thing is I invented assembly theory.
01:52:42 I’ll tell you how I invented it.
01:52:44 When I was a kid, I mean, the thing is,
01:52:46 I keep making fun of myself to my research group.
01:52:48 I’ve only ever had one idea.
01:52:49 I keep exploring that idea over the 40 years or so
01:52:52 since I had the idea.
01:52:53 I used to be a…
01:52:54 Well, aren’t you the idea that the universe had?
01:52:56 So it’s very kind of hierarchical.
01:52:58 Anyway, go ahead.
01:52:59 I’m sorry.
01:53:00 That’s very poetic.
01:53:02 Yeah.
01:53:02 So I think I came up with assembly theory
01:53:04 with the following idea.
01:53:06 When I was a kid, I was obsessed about survival kits.
01:53:09 What is the minimum stuff I would need
01:53:12 to basically replicate my reality?
01:53:14 And I love computers and I love technology
01:53:17 or what technology is gonna become.
01:53:18 So I imagined that I would have
01:53:20 basically this really big truck full of stuff.
01:53:22 And I thought, well, can I delete some of that stuff out?
01:53:25 Can I have a blueprint?
01:53:26 And then in the end, I kept making this smaller.
01:53:29 I got to maybe a half a truck and then to a suitcase.
01:53:32 And then I went, okay, well, screw it.
01:53:33 I wanna carry my entire technology in my pocket.
01:53:37 How do I do it?
01:53:38 And I’m not gonna launch into Steve Jobs and iPlayer.
01:53:43 I came up with a matchbox survival kit.
01:53:45 In that matchbox survival kit,
01:53:47 I would have the minimum stuff
01:53:48 that would allow me to interact the environment,
01:53:50 to build my shelter, to build a fishing rod,
01:53:54 to build a water purification system.
01:53:57 And it’s kind of like, so what did I use in my box
01:53:59 to assemble in the environment,
01:54:01 to assemble, to assemble, to assemble?
01:54:04 And I realized I could make a causal chain
01:54:07 in my survival kit.
01:54:08 So I guess that’s probably why I’ve been obsessed
01:54:10 with assembly theory for so long.
01:54:11 And I was just pre configured to find it somewhere.
01:54:17 And when I saw it in molecules,
01:54:19 I realized that the causal structure that we say emerges
01:54:24 and the physics kind of gets really stuck
01:54:27 because they’re saying that time,
01:54:28 you can go backwards in time.
01:54:29 I mean, how do we let physicists get away
01:54:32 with the notion that we can go back in time
01:54:34 and meet ourselves?
01:54:35 I mean, that’s clearly a very hard thing
01:54:40 to allow, physicists would not let other sciences
01:54:45 get away with that kind of heresy, right?
01:54:49 So why are physicists allowed to get away with it?
01:54:50 Let’s, let’s.
01:54:51 So first of all, to push back, to play devil’s advocate,
01:54:54 you are clearly married to the idea of memory.
01:54:58 You see in this, again, from Rick and Morty way,
01:55:02 you see, you have these deep dreams of the universe
01:55:06 that is writing the story through its memories,
01:55:08 through its chemical compounds
01:55:10 that are just building at top of each other.
01:55:12 And then they find useful components they can reuse.
01:55:16 And then the reused components create systems
01:55:19 that themselves are then reused
01:55:21 and all in this way, construct things.
01:55:24 But when you think of that as memory,
01:55:27 it seems like quite sad that you can walk that back.
01:55:31 But at the same time, it feels like that memory,
01:55:34 you can walk in both directions on that memory
01:55:37 in terms of time.
01:55:38 You could walk in both directions,
01:55:39 but I don’t think that that makes any sense
01:55:42 because the problem that I have with time being reversible
01:55:50 is that, I mean, I’m just a, you know,
01:55:53 I’m a dumb experimental chemist, right?
01:55:55 So I love burning stuff, burning stuff and building stuff.
01:55:58 But when I think of reversible phenomena,
01:56:01 I imagine in my head,
01:56:02 I have to actually manufacture some time.
01:56:05 I have to borrow time from the universe to do that.
01:56:08 I can’t, when anyone says,
01:56:10 let’s imagine that we can go back in time or reversibility,
01:56:13 you can’t do that.
01:56:14 You can’t step out of time.
01:56:15 Time is nonnegotiable, it’s happening.
01:56:17 No, but see, you’re assuming that time is fundamental,
01:56:20 which most of us do when we go day to day,
01:56:23 but it takes a leap of wild imagination
01:56:27 to think that time is emergent.
01:56:29 No, time is not emergent.
01:56:30 Yeah, I mean, this is an argument we can have,
01:56:32 but I believe I can come up with an experiment.
01:56:35 An experiment that proves
01:56:37 that time cannot possibly be emergent.
01:56:38 An experiment that shows how assembly theory
01:56:43 kind of is the way that the universe produces selection
01:56:48 and that selection gives rise to life.
01:56:50 And also to say, well, hang on,
01:56:53 we could allow ourselves to have a theory
01:56:55 that requires us to have these statements to be possible.
01:56:59 Like we need to have order in the past,
01:57:03 or we can use the past hypothesis,
01:57:06 which is order in the past, but as well, okay.
01:57:10 And we have to have an arrow of time.
01:57:12 We have to require that entropy increases.
01:57:16 And we have to say, and then we can say, look,
01:57:17 the universe is completely closed and there’s no novelty
01:57:21 or that novelty is predetermined.
01:57:23 What I’m saying is very, very important
01:57:26 that time is fundamental, which means,
01:57:28 if you think about it,
01:57:30 the universe becomes more and more novel each step.
01:57:32 It generates there’s more states
01:57:33 in the next step than it was before.
01:57:35 So that means bigger search.
01:57:37 So what I’m saying is that the universe
01:57:39 wasn’t capable of consciousness at day one,
01:57:43 actually, because it didn’t have enough states.
01:57:45 But today the universe is, so it’s like how?
01:57:48 All right, all right, hold on a second.
01:57:51 Now we’ve pissed off the panpsychist too, okay.
01:57:55 No, this is brilliant, sorry.
01:57:57 Part of me is just joking, having fun with this thing,
01:58:00 but because you’re saying a lot of brilliant stuff
01:58:02 and I’m trying to slow it down before my brain explodes.
01:58:05 So, because I want to break apart
01:58:08 some of the fascinating things you’re saying.
01:58:10 So novelty, novelty is increasing in the universe
01:58:14 because the number of states is increasing.
01:58:16 What do you mean by states?
01:58:18 So I think the physicists almost got everything right.
01:58:20 I can’t fault them at all.
01:58:22 I just think there’s a little bit of dogma.
01:58:24 I’m just trying to play devil’s advocate.
01:58:25 I’m very happy to be entirely wrong on this, right?
01:58:28 I’m not right on many things at all,
01:58:31 but if I can make less assumptions
01:58:34 about the universe with this,
01:58:35 then potentially that’s a more powerful way
01:58:38 of looking at things.
01:58:39 If you think of time as fundamental,
01:58:41 you can make less assumptions overall.
01:58:43 Exactly, if time is fundamental,
01:58:45 I don’t need to add on a magical second law
01:58:48 because the second law comes out of the fact
01:58:49 the universe is actually, there’s more states available.
01:58:52 I mean, we might even be able to do weird things
01:58:54 like dark energy in the universe
01:58:55 might actually just be time, right?
01:58:58 Yeah, but then you have to still have to explain
01:59:00 why time is fundamental,
01:59:02 because I can give you one explanation
01:59:04 that’s simpler than time and say God.
01:59:07 You know, like just because it’s simple
01:59:08 doesn’t mean it’s, okay, you still have to explain God
01:59:12 and you still have to explain time.
01:59:14 Like why is it fundamental?
01:59:15 So let’s just say existence is default,
01:59:18 which means time is the default.
01:59:19 So how did you go from the existence
01:59:22 of the time to the default? Well, we exist, right?
01:59:24 So let’s just be very.
01:59:26 We’re yet to talk about what exist means.
01:59:28 All right, let’s go all the way back.
01:59:30 Yeah, yeah, yeah, okay.
01:59:31 I think it’s very poetic and beautiful
01:59:32 what you’re weaving into this.
01:59:34 I don’t think this conversation is even about the assembly,
01:59:38 which is fascinating and we’ll keep mentioning it
01:59:41 in the index on this idea,
01:59:42 that I don’t think is necessarily connected to time.
01:59:46 Oh, I think it is deeply connected.
01:59:49 I can’t explain it yet.
01:59:50 So you don’t think everything you’ve said
01:59:52 about assembly theory and assembly index
01:59:56 can still be correct even if time is emergent?
01:59:58 So yeah, right now, assembly theory appears to work.
02:00:01 I appear to be able to measure objects of high assembly
02:00:04 in a mass spectrometer and look at their abundance
02:00:06 and you know, all that’s fine, right?
02:00:08 It’s a nice, if nothing else, it’s a nice way
02:00:10 of looking at how molecules can compress things.
02:00:14 Now, am I saying that a time has to be fundamental,
02:00:17 not emergent for assembly theory to work?
02:00:18 No, I think I’m saying that the universe,
02:00:23 it appears that the universe has many different ways
02:00:25 of using time.
02:00:26 You could have three different types of time.
02:00:28 You could just have time that’s,
02:00:29 the way I would think of it,
02:00:30 if you want to hold onto emergent time,
02:00:33 I think that’s fine, let’s do that for a second.
02:00:35 Hold onto emergent time
02:00:37 and the universe is just doing its thing.
02:00:39 Then assembly time only exists when the universe
02:00:41 starts to write memories through bonds.
02:00:43 So let’s just say there’s rocks running around,
02:00:45 you know, when the bond happens and selection starts,
02:00:49 suddenly there are, the universe is remembering cause
02:00:54 in the past and those structures will have effects
02:00:57 in the future.
02:00:57 So suddenly a new type of time emerges at that point,
02:01:00 which has a direction.
02:01:02 And I think Sean Carroll at this point
02:01:04 might even turn the podcast back on and go,
02:01:06 okay, I can deal with that, that’s fine.
02:01:08 But I’m just basically trying to condense the conversation,
02:01:10 say, hey, let’s just have time fundamental
02:01:13 and see how that screws with people’s minds.
02:01:14 Why?
02:01:15 You’re triggering people by saying fundamental.
02:01:17 Why not?
02:01:18 Well, you just say, like, let’s say.
02:01:19 Why am I, look, I’m walking through the wall.
02:01:21 Why should I grow up in a world where time,
02:01:26 I don’t go back in time.
02:01:28 I don’t meet myself in the past.
02:01:30 There are no one, there are no aliens coming
02:01:32 from the future, right?
02:01:34 You know, it’s just like.
02:01:35 No, no, no, but that’s not, no, no, no, hold on a second.
02:01:38 That’s like saying we’re talking about biology
02:01:41 or like evolutionary psychology
02:01:44 and you’re saying, okay, let’s just assume
02:01:46 that clothing is fundamental.
02:01:48 People wearing clothes is fundamental.
02:01:50 It’s like, no, no, no, wait a minute.
02:01:52 You can’t, like, I think you’re gonna get in a lot of trouble
02:01:55 if you assume time is fundamental.
02:01:57 Why?
02:01:58 Give me one reason why I’m getting into trouble
02:02:00 with time being fundamental.
02:02:01 Because you might not understand
02:02:04 the origins of this memory that might be deeper.
02:02:08 Like this memory, that could be a thing
02:02:11 that’s explaining the construction of these
02:02:14 higher complexities better than just saying
02:02:19 it’s a search, it’s chemicals doing a search
02:02:23 for reusable structures that they can like
02:02:30 then use as bricks to build a house.
02:02:32 Okay, so I accept that.
02:02:34 So let’s go back a second because it’s a kind of,
02:02:37 I wanted to drop the time bomb at this part
02:02:40 because I think we can carry on discussing it
02:02:42 for many, many, many, many, many days, many months.
02:02:46 But I’m happy to accept that it might be wrong.
02:02:50 But what I would like to do is imagine a universe
02:02:53 where time is fundamental and time is emergent
02:02:56 and ask, let’s just then talk about causation
02:03:00 because physicists require that causation.
02:03:02 So this is where I’m gonna go.
02:03:04 Causation emerges and it doesn’t exist at the micro scale.
02:03:08 Well, that clearly is wrong
02:03:09 because if causation has to emerge at the macro scale,
02:03:12 life cannot emerge.
02:03:13 So how does life emerge?
02:03:15 Life requires molecules to bump into each other,
02:03:17 produce replicators, those replicators
02:03:20 need to produce polymers.
02:03:21 There needs to be cause and effect at the molecular level.
02:03:24 There needs to be an agardic, non agardic
02:03:26 to an agardic transition at some point.
02:03:29 And those replicators have consequence,
02:03:35 material consequence in the universe.
02:03:37 Physicists just say, oh, you know what?
02:03:39 I’m gonna have a bunch of particles in a box.
02:03:42 I’m gonna think about it in a Newtonian way
02:03:44 and a quantum way and I’ll add on an arrow of time
02:03:48 so I can label things
02:03:50 and causation will happen magically later.
02:03:51 Well, how?
02:03:52 Explain causation and they can’t.
02:03:55 The only way I can reconcile causation
02:03:58 is having a fundamental time
02:04:00 because this allows me to have a deterministic universe
02:04:03 that creates novelty.
02:04:05 And there’s so many things to unpack here
02:04:08 but let’s go back to the point.
02:04:09 You said, can assembly theory work with emergent time?
02:04:12 Sure it can, but it doesn’t give me a deep satisfaction
02:04:16 about how causation and assembly gives rise
02:04:21 to these objects that move through time and space.
02:04:24 And again, what am I saying to bring it back?
02:04:27 I can say without fear, take this water bottle
02:04:31 and look at this water bottle
02:04:32 and look at the features on it.
02:04:32 There’s writing, you’ve got a load of them.
02:04:35 I know that causal structures gave rise to this.
02:04:38 In fact, I’m not looking at just one water bottle here.
02:04:40 I’m looking at every water bottle
02:04:42 that’s ever been conceived of by humanity.
02:04:44 This here is a special object.
02:04:46 In fact, Leibniz knew this.
02:04:48 Leibniz who was at the same time of Newton,
02:04:52 he kind of got stuck.
02:04:53 I think Leibniz actually invented assembly theory.
02:04:56 He gave soul, the soul that you see in objects
02:04:58 wasn’t the mystical soul, it is assembly.
02:05:01 It is the fact there’s been a history of objects related
02:05:03 and without the object in the past,
02:05:06 this object wouldn’t exist.
02:05:08 There is a lineage and there is conserved structures,
02:05:12 causal structures have given rise to those.
02:05:17 Fair enough.
02:05:17 And you’re saying it’s just a simpler view
02:05:20 if time is fundamental.
02:05:23 And it shakes the physicist’s cage a bit, right?
02:05:25 Because I’m gonna say, but I think that.
02:05:29 I just enjoy the fact that physicists are in cages.
02:05:32 I think that, I mean, I would say that, you know,
02:05:35 Lee Smolin, I don’t want to speak for Lee.
02:05:37 I mean, I’m talking to Lee about this.
02:05:39 I think Lee also is an agreement
02:05:41 that time has to be fundamental,
02:05:43 but I think he goes further.
02:05:45 You know, even in space,
02:05:46 I don’t think you can go back to the same place in space.
02:05:49 I’ve been to Austin a few times now.
02:05:51 This is my, I think third time I’ve been to Austin.
02:05:54 Is Austin in the same place?
02:05:55 No, the solar system is moving through space.
02:05:59 I’m not back in the same space.
02:06:01 Locally I am.
02:06:03 Every event in the universe is unique.
02:06:07 In space.
02:06:08 And time.
02:06:09 And time.
02:06:10 Doesn’t mean we can’t go back though.
02:06:13 I mean, you know, let’s just, you know,
02:06:17 rest this conversation, which was beautiful,
02:06:20 with a quote from the Rolling Stones
02:06:22 that you can’t always get what you want,
02:06:25 which is you want time to be fundamental,
02:06:27 but if you try, you’ll get what you need,
02:06:30 which is assembly theory.
02:06:32 Okay, let me ask you about,
02:06:34 continue talking about complexity,
02:06:36 and to clarify with this beautiful theory of yours
02:06:42 that you’re developing,
02:06:43 and I’m sure we’ll continue developing
02:06:45 both in the lab and in theory.
02:06:49 Yeah, it can’t be said enough,
02:06:52 just the ideas you’re playing with in your head are just,
02:06:56 and we’ve been talking about are just beautiful.
02:06:58 So if we talk about complexity a little bit more generally,
02:07:02 maybe in an admiring romantic way,
02:07:05 how does complexity emerge from simple rules?
02:07:09 The why, the how.
02:07:11 Okay, the nice algorithm of assembly is there.
02:07:14 I would say that the problem I have right now is,
02:07:17 I mean, you’re right, we can, about time as well.
02:07:20 The problem is I have this hammer called assembly,
02:07:22 and everything I see is a nail.
02:07:24 So now let’s just apply it to all sorts of things.
02:07:27 We take the Bernard instability.
02:07:28 The Bernard instability is you have oil,
02:07:32 if you heat up oil, let’s say on a frying pan,
02:07:35 when you get convection, you get honeycomb patterns.
02:07:37 Take the formation of snowflakes, right?
02:07:40 Take the emergence of a tropical storm,
02:07:45 or the storm on Jupiter.
02:07:47 When people say, let’s talk about complexity in general,
02:07:50 what they’re saying is,
02:07:51 let’s take this collection of objects
02:07:54 that are correlated in some way,
02:07:56 and try and work out how many moving parts there are,
02:08:00 how this got, how this exists.
02:08:02 So what people have been doing for a very long time
02:08:04 is taking complexity and counting what they’ve lost,
02:08:09 calculating the entropy.
02:08:11 And the reason why I’m pushing very hard on assembly
02:08:13 is entropy tells you how much you’ve lost.
02:08:16 It doesn’t tell you the microstates are gone.
02:08:18 But if you embrace the bottom up with assembly,
02:08:21 those states, and you then understand the causal chain
02:08:26 that gives rise to the emergence.
02:08:28 So what I think assembly will help us do
02:08:31 is understand weak emergence at the very least,
02:08:34 and maybe allow us to crack open complexity in a new way.
02:08:39 And I’ve been fascinated with complexity theory
02:08:42 for many years.
02:08:43 I mean, as soon as I could,
02:08:46 I learned of the Mandelbrot set,
02:08:48 and I could just type it up in my computer and run it,
02:08:52 and just show it and see it kind of unfold.
02:08:55 It was just this kind of,
02:08:58 this mathematical reality that existed in front of me,
02:09:01 I just found incredible.
02:09:03 But then I realized that actually we were cheating.
02:09:07 We’re putting in the boundary conditions all the time.
02:09:09 We’re putting in information.
02:09:11 And so when people talk to me
02:09:13 about the complexity of things,
02:09:16 I say, but relative what, how do you measure them?
02:09:18 So my attempt, my small attempt, naive attempt,
02:09:23 because there’s many greater minds than mine
02:09:25 on the planet right now thinking about this properly.
02:09:27 And you’ve had some of them on the podcast, right?
02:09:29 Just absolutely fantastic.
02:09:33 But I’m wondering if we might be able to reformat
02:09:35 the way we would explore algorithmic complexity
02:09:39 using assembly.
02:09:41 What’s the minimum number of constraints we need
02:09:45 in our system for this to unfold?
02:09:47 So whether it’s like, if you take some particles
02:09:50 and put them in a box,
02:09:52 at a certain box size, you get quasi crystallinity
02:09:55 coming out, right?
02:09:57 But that quite, that emergence, it’s not magic.
02:10:00 It must come from the boundary conditions you put in.
02:10:03 So all I’m saying is a lot of the complexity that we see
02:10:07 is a direct read of the constraints we put in,
02:10:10 but we just don’t understand.
02:10:11 So as I said earlier to the poor origin of life chemists,
02:10:14 you know, origin of life is a scam.
02:10:17 I would say lots of the complexity calculation theory
02:10:20 is a bit of a scam
02:10:21 because we put the constraints in,
02:10:22 but we don’t count them correctly.
02:10:25 And I’m wondering if…
02:10:26 Oh, you’re thinking and starting to drop
02:10:28 as assembly theory, assembly index
02:10:31 is a way to count to the constraints.
02:10:33 Yes, that’s it.
02:10:34 That’s all it is.
02:10:35 So assembly theory doesn’t do,
02:10:36 doesn’t lower any of the importance of complexity theory,
02:10:40 but it allows us to go across domains
02:10:42 and start to compare things,
02:10:44 compare the complexity of a molecule,
02:10:46 of a microprocessor, of the text you’ve writing,
02:10:49 of the music you may compose.
02:10:53 You’ve tweeted, quote,
02:10:55 “‘Assembly theory explains why Nietzsche understood
02:10:58 we had limited freedom rather than radical freedom.’
02:11:01 So we’ve applied assembly theory
02:11:03 to cellular automata in life and chemistry.
02:11:07 What does Nietzsche have to do with assembly theory?
02:11:09 Oh, that gets me into free will and everything.
02:11:13 So let me say that again.
02:11:14 Assembly theory explains why Nietzsche understood
02:11:16 we had limited freedom rather than radical freedom.
02:11:20 Limited freedom, I suppose, is referring to the fact
02:11:23 that there’s constraints or what is radical freedom?
02:11:28 What is freedom?
02:11:30 So Sartre was like believed in absolute freedom
02:11:34 and that he could do whatever he wanted in his imagination.
02:11:38 And Nietzsche understood that his freedom
02:11:41 was somewhat more limited.
02:11:44 And it kind of takes me back to this computer game
02:11:46 that I played when I was 10.
02:11:47 So I think it’s called Dragon’s Lair.
02:11:49 Okay.
02:11:51 Do you know Dragon’s Lair?
02:11:52 I think I know Dragon’s Lair, yeah.
02:11:54 Dragon’s Lair, I knew I was being conned, right?
02:11:56 Dragon’s Lair, when you play the game,
02:11:57 you’re lucky that you grew up
02:11:59 in a basically procedurally generated world.
02:12:01 That was RPG a little bit.
02:12:03 No, it’s like, is it turn based play?
02:12:05 Was it?
02:12:06 No.
02:12:07 It was a role playing game.
02:12:08 Role playing.
02:12:09 But really good graphics and one of the first laser disks.
02:12:11 And when you actually flick the stick,
02:12:13 you took, it’s like it was like a graphical adventure game
02:12:16 with animation.
02:12:17 Yeah.
02:12:18 And when I played this game, I really, you know,
02:12:19 you could get through the game in 12 minutes
02:12:22 if you knew what you were doing without making mistakes,
02:12:23 just play the disk, play the disk, play a disk.
02:12:25 So it was just about timing.
02:12:27 And actually it was a complete fraud
02:12:29 because all the animation has been prerecorded on the disk.
02:12:33 It’s like the Black Mirror, the first interactive
02:12:36 where they had all the, you know,
02:12:37 several million kind of permutations of the movie
02:12:41 that you could select on Netflix.
02:12:42 I’ve forgotten the name of it.
02:12:44 So this was exactly that in the laser disk.
02:12:47 So you basically go left, go right, fight the yoga,
02:12:50 slay the dragon.
02:12:52 And when you flick the joystick at the right time,
02:12:53 it just goes to the next animation to play.
02:12:55 Yeah.
02:12:56 It’s not really generating it.
02:12:57 Yeah.
02:12:58 And I played that game and I knew I was being had.
02:13:01 So.
02:13:02 Oh, okay.
02:13:03 I see, I see.
02:13:03 So to you, Dragon Lair is the first time you realized
02:13:07 that free will is an illusion.
02:13:09 Yeah.
02:13:10 And why does assembly theory give you hints
02:13:14 about free will, whether it’s an illusion or not?
02:13:17 Yeah, so no, so not tightly.
02:13:18 If I do think I have some will and I think I am an agent
02:13:22 and I think I can interact and I can play around
02:13:24 with the model I have of the world
02:13:27 and the cost functions, right?
02:13:28 And I can hack my own cost functions,
02:13:30 which means I have a little bit of free will.
02:13:32 But as much as I want to do stuff in the universe,
02:13:35 I don’t think I could suddenly say,
02:13:37 I mean, actually this is ridiculous.
02:13:38 Cause now I say I could try and do it, right?
02:13:39 Like I’m suddenly give up everything
02:13:41 and become a rapper tomorrow, right?
02:13:44 Maybe I could try that,
02:13:45 but I don’t have sufficient agency
02:13:48 to make that necessarily happen.
02:13:50 I’m on a trajectory.
02:13:51 So when in Dragon’s Lair,
02:13:52 I know that I have some trajectories that I can play with
02:13:56 where Sartre realized he thought
02:13:58 that he had no assembly, no memory.
02:14:00 He could just leap across and do everything.
02:14:03 And Nietzsche said, okay, I realize I don’t have
02:14:06 full freedom, but I have some freedom.
02:14:09 And the assembly theory basically says that,
02:14:11 it says, if you have these constraints in your past,
02:14:14 they limit what you were able to do in the future,
02:14:16 but you can use them to do amazing things.
02:14:19 Let’s say I’m a poppy plant and I’m creating some opiates.
02:14:23 Opiates are really interesting molecules.
02:14:25 I mean, they’re obviously great for medicine,
02:14:27 cause great problems in society.
02:14:29 But let’s imagine we fast forward a billion years,
02:14:33 what will the opioids look like in a billion years?
02:14:37 Well, we can guess because we can see
02:14:39 how those proteins will evolve
02:14:41 and we can see how the secondary metabolites will change.
02:14:44 But they can’t go radical.
02:14:46 They can’t suddenly become, I don’t know,
02:14:48 like a molecule that you find in an OLED in a display.
02:14:52 They will have some,
02:14:53 they will be limited by the causal chain that produced them.
02:14:56 And that’s what I’m getting at,
02:14:58 saying we are unpredictably predictable
02:15:03 or predictably unpredictable within a constraint
02:15:07 on the trajectory we’re on.
02:15:08 Yeah, so the predictably part
02:15:10 is the constraints of the trajectory
02:15:12 and the unpredictable part is the part
02:15:14 that you still haven’t really clarified
02:15:16 the origin of the little bit of freedom.
02:15:19 Yeah.
02:15:20 So you’re just arguing,
02:15:22 you’re basically saying that radical freedom is impossible.
02:15:26 You’re really operating in a world of constraints
02:15:29 that are constrained by the memory of the trajectory
02:15:31 of the chemistry that led to who you are.
02:15:33 Okay, but even just a tiny bit of freedom,
02:15:39 even if everything, if everywhere you are in cages,
02:15:45 if you can move around in that cage a little bit,
02:15:49 you’re free.
02:15:50 I agree.
02:15:51 And so the question is in assembly theory,
02:15:55 if we’re thinking about free will,
02:15:57 where does the little bit of freedom come from?
02:15:59 What is the eye that can decide to be a rapper?
02:16:03 What, why, what is that?
02:16:06 That’s a cute little trick we’ve convinced each other of
02:16:10 so we can do fun tricks at parties
02:16:13 or is there something fundamental
02:16:15 that allows us to feel free, to be free?
02:16:18 I think that that’s the question that I wanna answer.
02:16:21 I know you wanna answer it and I think it’s so profound.
02:16:25 Let me have a go at it.
02:16:27 I would say that I don’t take the stance of Sam Harris
02:16:30 because I think Sam Harris, when he said,
02:16:31 the way he says it is almost,
02:16:33 it’s really interesting.
02:16:34 I’d love to talk to him about it.
02:16:35 Sam Harris almost thinks himself out of existence, right?
02:16:37 Because, do you know what I mean?
02:16:40 Yeah, well, I mean, he has different views
02:16:43 on consciousness versus free will.
02:16:45 I think he saves himself with consciousness.
02:16:47 He thinks himself out of existence with free will.
02:16:49 Yeah, yeah, exactly.
02:16:50 So I mean, there’s no point, right?
02:16:53 So I…
02:16:54 He’s a leaf floating on a river.
02:16:55 Yeah, I think that he, I don’t know,
02:17:00 I’d love to ask him whether he really believes that
02:17:03 and then we could play some games.
02:17:04 Oh, yeah.
02:17:05 No, no, I then would say,
02:17:06 I’ll get him to play a game of cards with me
02:17:08 and I’ll work out the conditions on which he says no,
02:17:11 and then I’ll get him to the conditions he says yes,
02:17:13 and then I’ll trap him in his logical inconsistency
02:17:15 with that argument.
02:17:17 Because at some point when he loses enough money
02:17:19 or the prospect of losing enough money,
02:17:23 there’s a way of basically mapping out a series of…
02:17:26 So what will is about, let’s not call it free will,
02:17:30 but what will is about is to have a series of decisions
02:17:34 equally weighted in front of you.
02:17:36 And those decisions aren’t necessarily energy minimization.
02:17:39 Those decisions are a function of the model
02:17:43 you’ve made in your mind, you’re in your simulation.
02:17:45 And the way you’ve interacted in reality
02:17:48 and also other interactions you’re having
02:17:52 with other individuals and happenstance.
02:17:55 And I think that there’s a little bit of delay in time.
02:18:00 So I think what you’re able to do is say,
02:18:03 well, I’m gonna do the counterfactual.
02:18:06 I’ve done all of them.
02:18:08 And I’m gonna go this way.
02:18:10 And you probably don’t know why.
02:18:12 I think free will is actually very complex interaction
02:18:14 between your unconscious and your conscious brain.
02:18:18 And I think the reason why we’re arguing about it
02:18:20 is so interesting in that we just,
02:18:23 some people outsource their free will
02:18:26 to their unconscious brain.
02:18:28 And some people try and overthink
02:18:31 the free will and the conscious brain.
02:18:33 I would say that Sam Harris has realized
02:18:35 his conscious brain doesn’t have free will,
02:18:36 but his unconscious brain does.
02:18:38 That’s my guess, right?
02:18:39 And that he can’t have access to the unconscious brain.
02:18:42 Yeah, and that’s kind of annoying.
02:18:43 And so he’s just, he’s going to, through meditation,
02:18:46 come to acceptance with that fact.
02:18:48 Yeah, it’s just maybe okay.
02:18:50 But I do think that I have the ability to make decisions
02:18:55 and I like my decisions.
02:18:56 In fact, I mean, this is an argument I have
02:18:58 with some people that some days I feel
02:19:02 I have no free will and it’s just an illusion.
02:19:04 And this is one, and it makes me more radical,
02:19:06 if you like, you know, that I get to explore
02:19:10 more of the state space.
02:19:11 And I’m like, I’m going to try and affect the world now.
02:19:13 I’m really going to ask the question
02:19:15 that maybe I dare not ask or do the thing I dare not do.
02:19:19 And that allows me to kind of explore more.
02:19:21 It’s funny that if you truly accept
02:19:25 that there’s no free will, that is a kind of radical freedom.
02:19:31 It’s funny, but you’re, because the little bit
02:19:36 of the illusion under that framework that you have
02:19:40 that you can make choices, if choice is just an illusion
02:19:43 of psychology, you can do whatever the hell you want.
02:19:46 That’s the.
02:19:47 But we don’t, do we?
02:19:48 And I think.
02:19:49 But because you don’t truly accept
02:19:51 that you think that there’s like, you think there’s a choice
02:19:56 which is why you don’t just do whatever the hell you want.
02:20:00 Like you feel like there’s some responsibility
02:20:03 for making the wrong choice, which is why you don’t do it.
02:20:05 But if you truly accept that the choice
02:20:07 has already been made, then you can go,
02:20:12 I don’t know what is the most radical thing.
02:20:16 I mean, but yeah, I don’t, I wonder what,
02:20:19 what am I preventing myself from doing
02:20:21 that I would really want to do?
02:20:24 Probably like humor stuff.
02:20:26 Like I would love to, if I could like save a game,
02:20:31 do the thing and then reload it later,
02:20:34 like do undo, it probably would be humor.
02:20:37 Just to do something like super hilarious.
02:20:42 That’s super embarrassing.
02:20:43 And then just go, I mean, it’s basically just fun.
02:20:46 I would add more fun to the world.
02:20:47 I mean, I sometimes do that as I’ve, you know,
02:20:51 I sometimes I try and mess up my reality in unusual ways
02:20:56 by just doing things because I’m bored, but not bored.
02:20:59 I’m not expressing this very well.
02:21:00 I think that this is a really interesting problem
02:21:02 that perhaps the hard sciences don’t really understand
02:21:05 that they are responsible for
02:21:06 because the question about how life emerged
02:21:09 and how intelligence emerges and consciousness and free will
02:21:12 they’re all ultimately boiling down
02:21:14 to some of the same mechanics.
02:21:15 I think, my feeling is that they are the same problem
02:21:19 again and again and again.
02:21:20 The transition from a, you know, a boring world
02:21:24 or a world in which there is no selection.
02:21:26 So I wonder if free will has something to do
02:21:28 with selection and models.
02:21:29 And also the models you’re generating in the brain
02:21:32 and also your, the amount of memory,
02:21:34 your working memory have available at any one time
02:21:35 to generate counterfactuals.
02:21:37 Well, that’s fascinating.
02:21:38 So like the decision making process is a kind of selection
02:21:42 and that could be just another,
02:21:43 yet another manifestation of the selection mechanism
02:21:48 that’s pervasive throughout the universe.
02:21:50 Okay, that’s fascinating to think about.
02:21:54 Yeah, there’s not some kind of fundamental,
02:21:56 it’s own thing or something like that.
02:21:59 That is just yet another example of selection.
02:22:01 Yeah, and in the universe that’s intrinsically open,
02:22:06 you want to do that because you generate novelty.
02:22:08 You mentioned something about,
02:22:10 do cellular automata exist outside the human mind
02:22:13 in our little offline conversation?
02:22:17 Why is that an interesting question?
02:22:18 So cellular automata, complexity,
02:22:22 what’s the relationship between complexity
02:22:24 and the human mind and trees falling in the forest?
02:22:28 Infrastructure, so the CA,
02:22:30 so when John von Neumann and Conway and Feynman
02:22:34 were doing CA, it was doing on paper.
02:22:35 CA is cellular automata.
02:22:37 Just drawing them on paper.
02:22:38 How awesome is that, that they were doing cellular automata
02:22:41 on paper and then they were doing it on a computer
02:22:44 that takes like forever to print out anything and program.
02:22:48 Sure.
02:22:49 People are now with the TikTok,
02:22:51 kids these days with the TikTok don’t understand
02:22:54 how amazing it is to just play with cellular automata,
02:22:57 arbitrarily changing the rules as you want,
02:23:00 the initial conditions,
02:23:00 and see the beautiful patterns emerge,
02:23:04 sing with fractals, all of that.
02:23:06 You’ve just given me a brilliant idea.
02:23:07 I wonder if there’s a TikTok account that’s just dedicated
02:23:09 to putting out CA rules and if there isn’t,
02:23:11 we should make one.
02:23:12 100% and that will get.
02:23:14 So we have millions of views.
02:23:16 Millions, yes.
02:23:17 No, it’ll get dozens.
02:23:20 We’ll just have it running.
02:23:21 So look, I kind of, I love CAs.
02:23:29 Yeah, no.
02:23:30 We just have to make one.
02:23:32 I actually, a few years ago,
02:23:34 I made some robots that talk to each other,
02:23:36 chemical robots that played the game of Hex,
02:23:40 invented by John Nash, by doing chemistry.
02:23:42 And they communicated via Twitter,
02:23:44 which were experiments they were doing.
02:23:46 And they had a lookup table of experiments
02:23:49 and robot one said, I’m doing experiment 10.
02:23:51 And the other robot, okay, I’ll do experiment one then.
02:23:53 And they communicated via Twitter.
02:23:55 Publicly or DMs?
02:23:57 Yeah, yeah, yeah.
02:23:58 Can you maybe quickly explain what the game of Hex is?
02:24:01 Yes, so it’s basically a hexagonal board
02:24:04 and you try and basically you color each element
02:24:07 on the board of each hexagon
02:24:08 and you try and get from one side to the other
02:24:10 and the other one tries to block you.
02:24:12 How are they connected?
02:24:13 So what are the robots?
02:24:14 So it’s a chemical.
02:24:16 Yeah, let’s go back.
02:24:17 So there are two robots.
02:24:18 Each robot was doing dye chemistry.
02:24:20 So making RGB, red, green, blue, red, green, blue,
02:24:23 red, green, blue.
02:24:24 And they could just choose from experiments
02:24:26 to do red, green, blue.
02:24:28 Initially I said to my group,
02:24:29 we need to make two chemical robots that play chess.
02:24:31 And my group were like, that’s too hard.
02:24:33 No, go away.
02:24:35 But anyway, so we had the robot.
02:24:36 By the way, people listening to this should probably know
02:24:42 that Lee Cronin is an amazing group of brilliant people.
02:24:46 He’s exceptionally well published.
02:24:48 He’s written a huge number of amazing papers.
02:24:52 Whenever he calls himself stupid
02:24:55 and is a sign of humility,
02:24:57 and I deeply respect that and appreciate it.
02:25:00 So people listening to this should know
02:25:01 this is a world class scientist
02:25:04 who doesn’t take himself seriously,
02:25:05 which I really appreciate and love.
02:25:07 Anywho, talking about serious science,
02:25:11 we’re back to your group rejecting your idea
02:25:16 of chemical robots playing chess via dyes.
02:25:22 So you went to a simpler game of Hex.
02:25:24 Okay, so what else?
02:25:26 The team that did it were brilliant.
02:25:27 I think they still have PTSD from doing it.
02:25:31 Cause I said, this is a workshop.
02:25:32 What I’d often do is I have about 60 people on my team.
02:25:36 And occasionally before lockdown,
02:25:38 I would say, I’m a bit bored.
02:25:40 We’re gonna have a workshop on something.
02:25:41 Who wants to come?
02:25:42 And then basically about 20 people turn up to my office
02:25:44 and I say, we’re gonna do this mad thing.
02:25:46 And then it would just self organize.
02:25:49 And some of them would be like, no, I’m not doing this.
02:25:51 And then you get left with the happy dozen.
02:25:54 And what we did is we built this robot
02:25:56 and doing dye chemistry is really easy.
02:25:57 You can just take two molecules,
02:25:59 react them together and change color.
02:26:00 And what I wanted to do is have a palette
02:26:03 of different molecules.
02:26:04 You can react combinatorially and get different colors.
02:26:07 So you’ve got two robots.
02:26:08 And I went, wouldn’t it be cool
02:26:09 if the robots basically shared
02:26:12 the same list of reactions to do.
02:26:14 And they said, oh, and because of,
02:26:15 then you could do a kind of multi core chemistry.
02:26:18 Like they weren’t,
02:26:19 so you’d have two chemical reactions going on at once
02:26:21 and they could basically outsource the problem.
02:26:23 But they’re sharing the same tape.
02:26:25 Exactly.
02:26:26 Okay.
02:26:26 So robot one would say, I’m gonna do,
02:26:27 I’m gonna do experiment one.
02:26:28 And the other robot says, I’ll do experiment 100.
02:26:30 And then they could cross it off.
02:26:32 But I wanted to make it.
02:26:33 That’s brilliant, by the way.
02:26:34 I wanted to make.
02:26:35 That is genius.
02:26:36 Sorry.
02:26:37 Well, I wanted to make it groovier.
02:26:38 And I said, look, let’s have them competing to make,
02:26:41 so they’re playing a game of hex.
02:26:43 And so when the robot does an experiment
02:26:46 and the more blue the dye,
02:26:48 the more it gets the higher chance it gets
02:26:51 to make the move it wants on the hex board.
02:26:53 So if it gets a red color is like,
02:26:55 it gets down weighted in the other robot.
02:26:57 And so what the robots could do is they play,
02:26:59 each player move.
02:27:01 And cause the fitness function or the optimization function
02:27:03 was to make the color blue,
02:27:05 they started to invent reactions
02:27:09 we didn’t, weren’t on the list.
02:27:11 And they did this by not cleaning
02:27:13 because we made cleaning optional.
02:27:14 So when one robot realized if it didn’t clean its pipes,
02:27:17 it could get blue more quickly.
02:27:18 Yeah.
02:27:19 And the other robot realized that.
02:27:20 So it was like getting dirty as well.
02:27:21 And they, they.
02:27:22 Unintended consequences of super intelligence.
02:27:26 Okay.
02:27:27 But.
02:27:28 That was the game.
02:27:28 And we.
02:27:29 Communicating through Twitter though.
02:27:30 They were, they were doing it through Twitter
02:27:31 and Twitter bland them a couple of times.
02:27:33 I said, come on, you’ve got a couple of robots
02:27:34 doing chemistry.
02:27:35 It’s really cool.
02:27:36 Stop banning them.
02:27:37 Yeah.
02:27:38 But in the end they had, we had to take them off Twitter
02:27:39 and they just communicated via a server.
02:27:41 Cause it was just, there were people saying,
02:27:43 you can still find it.
02:27:43 Cronin lab one and Cronin lab two on Twitter.
02:27:46 And it was like, make move, wait, you know, mix A and B,
02:27:49 wait 10 seconds.
02:27:51 Yeah.
02:27:52 Answer blue, you know.
02:27:53 I really find it super compelling
02:27:56 that you would have a chemical entity
02:28:00 that’s communicating with the world.
02:28:03 That was one of the things I want to do
02:28:04 with my origin of life reaction, right?
02:28:05 Is basically have a, have a reactor.
02:28:10 That’s basically just randomly enumerating
02:28:12 for chemical space and have some kind of cycle
02:28:14 and then read out what the molecules reading out
02:28:17 using a mass spectrometer and then convert that to text
02:28:20 and publish it on Twitter and then wait until it says
02:28:23 I’m alive.
02:28:24 I reckon that would get, I reckon that,
02:28:27 that Twitter account would get a lot of followers.
02:28:28 Yeah.
02:28:29 And I’m still trying to convince my group
02:28:30 that we should just make an origin of life Twitter account.
02:28:32 Where it’s going blue and it’s like, hello, testing.
02:28:36 I’m here.
02:28:37 Well, I’ll share it.
02:28:38 I like it.
02:28:39 I particularly enjoy this idea
02:28:42 of a non human entity communicating with the world
02:28:46 via human designed social network.
02:28:48 It’s quite a, quite a beautiful idea.
02:28:55 How we were talking about CA’s existing
02:28:59 outside the human mind.
02:29:00 Yeah.
02:29:01 So I really admire Stephen Wolfram.
02:29:02 I think he’s a genius, clearly a genius
02:29:05 and trapped in is actually,
02:29:06 it’s like a problem with being so smart
02:29:08 is you get trapped in your own mind, right?
02:29:11 And I’ve, I tried to actually,
02:29:13 I tried to convince Stephen that assembly theory
02:29:15 wasn’t nonsense.
02:29:16 He was like, no, it’s just nonsense.
02:29:17 I was a little bit sad by that.
02:29:18 So nonsense applied,
02:29:20 even if it applied to the simplest construct
02:29:22 of a one dimensional cellular automata, for example.
02:29:25 Yeah, yeah.
02:29:25 Well, I mean, actually,
02:29:26 maybe I’m doing myself a bit too down.
02:29:28 It was just as a theory was coming through
02:29:30 and I didn’t really know how to explain it,
02:29:33 but we are going to use assembly theory
02:29:35 and CA’s in cellular automata,
02:29:36 but I wanted to,
02:29:38 what I was really curious about is why people marvel.
02:29:42 I mean, you marvel CA’s and their complexity.
02:29:44 And I said, well, hang on that complexity is baked in
02:29:47 because if you play the game of life in a CA,
02:29:50 you have to run it on a computer.
02:29:52 You have to have a,
02:29:53 you have to do a number of operations,
02:29:55 put in the boundary conditions.
02:29:57 So is it surprising that you get this structure out?
02:29:59 Is it manufactured by the boundary conditions?
02:30:02 And it is interesting because I think
02:30:06 a cellular automata running them
02:30:10 is teaching me something about
02:30:11 what real numbers are and aren’t.
02:30:14 I haven’t quite got there yet.
02:30:15 I was playing on the airplane coming over.
02:30:16 I’m just realized,
02:30:17 I have no idea what real numbers are really.
02:30:20 And I was like, well,
02:30:20 I do actually have some notion of what real numbers are.
02:30:24 And I think thinking about real numbers as functions
02:30:28 rather than numbers is more appropriate.
02:30:30 And then if you then apply that to CA’s,
02:30:33 then you’re saying, well, actually,
02:30:36 why am I seeing this complexity in this rule?
02:30:39 Is it, you know, is it,
02:30:42 you’ve got this deterministic system
02:30:44 and yet you get this incredible structure coming out.
02:30:48 Well, isn’t that what you’d get with any real number
02:30:51 as you apply it as a function
02:30:54 and you’re trying to read it out to an arbitrary position?
02:30:58 And I wonder if CA’s are just helping me,
02:31:00 well, my misunderstanding of CA’s
02:31:02 might be helping me understand them
02:31:03 in terms of real numbers.
02:31:04 I don’t know what you think.
02:31:05 Yeah, well, the functions,
02:31:07 but the devil’s in the function.
02:31:11 It’s like, which is the function
02:31:13 that’s generating your real number.
02:31:16 Like that, it seems like it’s very important
02:31:20 the specific algorithm of that function
02:31:22 because some lead to something super trivial,
02:31:25 some lead to something that’s all chaotic
02:31:27 and some lead to things that are just walked
02:31:30 that fine line of complexity and structure.
02:31:35 I think we agree.
02:31:36 So let’s take it back a second.
02:31:37 So take the logistic map or something, logistic equation,
02:31:40 where you have this equation,
02:31:42 which is you don’t know what’s gonna happen at n plus one,
02:31:46 but once you’ve done n plus one, you know full time,
02:31:48 you can’t predict it.
02:31:50 For me, CA’s and logistic equation feel similar.
02:31:53 And I think what’s incredibly interesting
02:31:57 and I share your kind of wonder at running a CA,
02:32:03 but also I’m saying, well,
02:32:05 what is it about the boundary conditions
02:32:06 and the way I’m running that calculation?
02:32:08 So in my group, with my team,
02:32:10 we actually made a chemical CA.
02:32:12 We made Game of Life.
02:32:13 We actually made a physical grid.
02:32:15 I haven’t been able to publish this paper.
02:32:16 It’s been trapped in purgatory for a long time,
02:32:18 but it might be about.
02:32:19 Yeah.
02:32:20 You wrote it up as a paper,
02:32:21 how to do a chemical formulation of the Game of Life,
02:32:23 which is played.
02:32:23 We made a chemical computer and little cells.
02:32:25 And I was playing Game of Life.
02:32:26 With the BZ reactions,
02:32:28 each cell would pulse on and off, on and off, on and off.
02:32:31 We have little stirrer bars and we have little gates.
02:32:34 And we actually played Conway’s Game of Life in there.
02:32:37 And we got structures in that.
02:32:38 We got structures in that game from the chemistry
02:32:41 that you wouldn’t expect from the actual CA.
02:32:44 So that was kind of cool in that.
02:32:46 Cause they’re interacting outside of the cells more.
02:32:50 So what’s happening is you’re getting noise.
02:32:52 So the thing is that you’ve got this BZ reaction
02:32:55 that gives on off, on off, on off,
02:32:56 but there’s also a wake
02:32:58 and those wakes constructively interfere
02:33:00 or in such a non trivial way that’s non deterministic.
02:33:07 And the non determinism in the system
02:33:11 gives very rich dynamics.
02:33:12 And I was wondering if I could physically
02:33:14 make a chemical computer with this CA
02:33:18 that gives me something different.
02:33:20 I can’t get in a silicon representation of a CA
02:33:25 where all the states are clean.
02:33:27 Cause you don’t have the noise trailing
02:33:29 into the next round.
02:33:30 You just have the state.
02:33:32 So the paper in particular,
02:33:33 so that’s just a beautiful idea to use a chemical computer
02:33:37 to construct the cellular automaton,
02:33:39 the famous one of game of life.
02:33:41 But it’s also interesting.
02:33:42 And it’s a really interesting scientific question
02:33:45 of whether some kind of random perturbations
02:33:48 or some source of randomness
02:33:51 can have a significant constructive effect
02:33:58 on the complexity of the system.
02:34:00 And indeed, I mean, whether it’s random
02:34:03 or just non deterministic
02:34:04 and can we bake in that non determinism at the beginning?
02:34:08 I wonder what is the,
02:34:10 I’m trying to think of what is the encoding space.
02:34:12 The encoding space is pretty big.
02:34:14 We have 49 stirrups of 49 cells,
02:34:19 49 chem bits all connected to one another
02:34:22 and like an analog computer,
02:34:23 but being read out discreetly as the BZ reaction.
02:34:27 So just to say the BZ reaction is a chemical oscillator.
02:34:30 And what happened in each cell
02:34:31 is it goes between red and blue.
02:34:33 So two Russians discovered it,
02:34:34 Belouzov and Sapkinsky.
02:34:36 I think Belouzov first proposed it
02:34:38 and everyone said, you’re crazy.
02:34:39 It breaks the second law.
02:34:40 And Sapkinsky said, no, it doesn’t break the second law.
02:34:42 It’s consuming a fuel.
02:34:45 And so, and then, and it’s like,
02:34:47 there’s a lot of chemistry hidden
02:34:50 in the Russian literature actually,
02:34:52 because Russians just wrote it in Russian.
02:34:54 They didn’t publish it in English speaking journals.
02:34:56 It’s heartbreaking actually.
02:34:57 Well, it’s sad and it’s great that it’s there, right?
02:35:01 It’s not lost.
02:35:02 I’m sure we will find a way of translating it properly.
02:35:05 Well, the silver lining slash greater sadness
02:35:08 of all of this is there’s probably ideas
02:35:11 in English speaking.
02:35:12 Like there’s ideas in certain disciplines
02:35:16 that if discovered by other disciplines
02:35:20 would crack open some of the biggest mysteries
02:35:22 in those disciplines.
02:35:23 Like computer science, for example,
02:35:26 is trying to solve problems
02:35:30 like nobody else has ever tried to solve problems.
02:35:32 As if it’s not already been all addressed
02:35:35 in cognitive science and psychology,
02:35:37 in mathematics, in physics,
02:35:39 in just whatever you want to, economics even.
02:35:42 But if you look into that literature,
02:35:44 you might be able to discover some beautiful ideas.
02:35:47 Obviously Russian is an interesting case of that.
02:35:51 It’s because there’s a loss in translation,
02:35:53 but you said there’s a source of fuel, a source of energy.
02:35:57 Yeah, yeah.
02:35:58 So the BZ reaction, you have an acid in there
02:36:00 called malonic acid.
02:36:02 And what happens is it’s basically like a battery
02:36:07 that powers it and it loses CO2.
02:36:09 So decarboxylates, it’s just a chemical reaction.
02:36:12 What that means we have to do is continuously feed
02:36:14 or we just keep the BZ reaction going
02:36:16 in a long enough time.
02:36:18 So it’s like it’s reversible in time.
02:36:22 But only like, yeah.
02:36:23 But only like, but it’s fascinating.
02:36:26 I mean, the team that did it,
02:36:27 I’m really proud of their persistence.
02:36:29 We made a chemical computer and it can solve
02:36:33 little problems.
02:36:34 It can solve traveling salesman problems actually.
02:36:36 Nice.
02:36:37 But like I say, it’s.
02:36:38 But not any faster than a regular computer.
02:36:41 Is there something you can do?
02:36:43 Maybe, I’m not sure.
02:36:46 I think we can come up with a way of solving problems,
02:36:49 also really complex, hard ones,
02:36:54 because it’s an analog computer and we can,
02:36:56 it can energy minimize really quickly.
02:36:59 It doesn’t have to basically go through every element
02:37:01 in the matrix, like flip it, it just reads out.
02:37:05 So we could actually do Monte Carlo
02:37:07 by just shaking the box.
02:37:10 It’s literally a box shaker.
02:37:12 You don’t actually have to encode the shaking of the box
02:37:14 in a silicon memory and then just shuffle everything around.
02:37:17 Yeah, and you can.
02:37:18 It’s analog, it’s natural.
02:37:19 So it’s an organic computer.
02:37:23 Yeah, yeah.
02:37:24 So I was playing around with this
02:37:25 and I was kind of annoying some of my colleagues
02:37:27 and wondering if we could get to chemical supremacy
02:37:29 like quantum supremacy.
02:37:31 And I kind of calculated how big the grid has to be
02:37:36 so we can actually start to solve problems faster
02:37:38 than a silicon computer.
02:37:40 But I’m not willing to state how that is yet
02:37:43 because I’m probably wrong.
02:37:44 It’s not that it’s any top secret thing
02:37:46 is I want, I think I can make a chemical computer
02:37:49 that can solve optimization problems faster
02:37:51 than the silicon computer.
02:37:54 That’s fascinating.
02:37:55 But then you’re unsure how big that has to be.
02:37:57 Yeah, I think, I mean.
02:37:58 It might be a big box, hard to shake.
02:38:00 It might be exactly a big box, hard to shake
02:38:03 and basically a bit sloppy.
02:38:05 Did we answer the question about
02:38:08 do cellular atomic exists outside the mind?
02:38:11 We didn’t, but I would posit that they don’t.
02:38:14 And I, but I think minds can, well.
02:38:17 So the mind is fundamental.
02:38:19 What’s the, why?
02:38:21 Well, I mean, sorry, let’s go back.
02:38:23 So as a physical phenomena, do CAs exist
02:38:26 in physical reality, right?
02:38:28 I would say they probably don’t exist
02:38:30 outside the human mind, but now we’ve constructed them.
02:38:33 They exist in computer memories.
02:38:34 They exist in my lab.
02:38:35 They exist on paper.
02:38:37 So they are, they emerge from the human mind.
02:38:40 I’m just interested in, because Stephen Wolfram likes CAs,
02:38:43 a lot of people like CAs and likes to think of them
02:38:46 as minimal computational elements.
02:38:49 I’m just saying, well, do they exist in reality
02:38:52 or are they a representation of a simple machine
02:38:54 that’s just very elegant to implement?
02:38:57 So it’s a platonic question, I guess.
02:38:59 I mean, it’s, there’s initial conditions.
02:39:03 There’s a memory in the system.
02:39:05 There are simple rules that dictate
02:39:07 the evolution of the system.
02:39:09 So what exists?
02:39:10 The idea, the rules, the.
02:39:12 Yeah, people are using CAs as models
02:39:15 for things in reality to say, hey, look,
02:39:18 you can do this thing in a CA.
02:39:21 And my, when I see this, I’m saying, oh, that’s cool.
02:39:24 But what does that tell me about reality?
02:39:26 Where’s the CA in space?
02:39:27 Oh, I see.
02:39:28 Well, right.
02:39:29 It’s a mathematical object.
02:39:30 So for people who don’t know cellular automata,
02:39:33 there’s usually a grid, whether it’s one dimensional,
02:39:35 two dimensional, or three dimensional.
02:39:36 And it evolves by simple local rules,
02:39:39 like you die or are born if the neighbors are alive or dead.
02:39:44 And it turns out if you have,
02:39:46 with certain kinds of initial conditions
02:39:51 and with certain kinds of very simple rules,
02:39:53 you can create like arbitrarily complex
02:39:56 and beautiful systems.
02:39:57 And to me, whether drugs are involved or not,
02:40:03 I can sit back for hours and enjoy the mystery of it,
02:40:09 how such complexity can emerge as it gives me almost like,
02:40:14 you know, people talk about religious experiences.
02:40:17 It gives me a sense that you get to have a glimpse
02:40:23 at the origin of this whole thing.
02:40:26 Whatever is creating this complexity from such simplicity
02:40:33 is the very thing that brought my mind to life,
02:40:38 this me, the human, our human civilization.
02:40:42 And yes, those constructs are pretty trivial.
02:40:49 I mean, that’s part of their magic
02:40:50 is even in this trivial framework,
02:40:54 you could see the emergence,
02:40:56 or especially in this trivial framework,
02:40:58 you could see the emergence of complexity from simplicity.
02:41:01 I guess what Lee, you’re saying is that this is not,
02:41:05 you know, this is highly unlike systems
02:41:10 we see in the physical world,
02:41:13 even though they probably carry some of the same magic,
02:41:17 like mechanistically, that’s all.
02:41:19 I mean, I’m saying that the operating system
02:41:22 that a CA has to exist on is quite complex.
02:41:26 And so I wonder if you’re getting the complexity
02:41:28 out of the CA from the boundary conditions
02:41:30 of the operating system, the underlying digital computer.
02:41:33 Oh, wow, those are some strong words against CAs then.
02:41:36 I didn’t realize. Not against.
02:41:37 I mean, I’m in love with CAs as well.
02:41:40 I’m just saying they aren’t as trivial as people think.
02:41:44 They are incredible.
02:41:45 To get to that richness,
02:41:47 you have to iterate billions of times,
02:41:51 and you need a display, and you need a math coprocessor,
02:41:54 and you need a von Neumann machine
02:41:57 based on a Turing machine
02:41:59 of digital error correction and states.
02:42:01 Wow, to think that for the simplicity of a grid,
02:42:05 you’re basically saying a grid is not simple.
02:42:08 Yeah.
02:42:09 It requires incredible complexity to bring a grid to life.
02:42:12 Yeah.
02:42:15 Yeah, that’s it.
02:42:16 Well, then what is simple?
02:42:17 That’s all I wanted to say.
02:42:18 I agree with you with the wonder of CAs, I just think.
02:42:20 But remember, we take so much for granted
02:42:22 what the CA is resting on.
02:42:24 Because von Neumann and Feynman weren’t showing,
02:42:28 weren’t seeing these elaborate structures.
02:42:30 They could not get that far.
02:42:33 Yeah, but that’s the limitation of their mind.
02:42:34 Yeah, yeah, exactly.
02:42:35 The limitation of their pencil.
02:42:37 But I think the question is
02:42:40 whether the essential elements of the cellular automata
02:42:47 is present without all the complexities
02:42:50 required to build a computer.
02:42:52 And my intuition, the reason I find it incredible
02:42:56 is that, yeah, my intuition is yes.
02:42:58 It might look different.
02:43:00 There might not be a grid like structure,
02:43:05 but local interactions operating under simple rules
02:43:09 and resulting in multi hierarchical complex structures
02:43:14 feels like a thing that doesn’t require a computer.
02:43:17 I agree, but coming back to von Neumann and Feynman
02:43:21 and Wolfram, their minds, the non trivial minds
02:43:24 to create those architectures and do it
02:43:26 and to put on those state transitions.
02:43:30 And I think that’s something
02:43:32 that’s really incredibly interesting
02:43:34 that is understanding how the human mind
02:43:38 builds those state transition machines.
02:43:41 I could see how deeply in love
02:43:43 with the idea of memory you are.
02:43:45 So it’s like how much of E equals MC squared
02:43:51 is more than an equation.
02:43:53 It has Albert Einstein in it.
02:43:57 You’re saying you can’t just say this is a,
02:44:00 like the equations of physics are a really good
02:44:06 simple capture of a physical phenomenon.
02:44:10 It is also, that equation has the memory of the humans.
02:44:15 Absolutely, absolutely, yeah.
02:44:18 But I don’t, I don’t know if you’re implying this.
02:44:21 I don’t, that’s a beautiful idea,
02:44:25 but I don’t know if I’m comfortable
02:44:27 with that sort of diminishing the power of that equation.
02:44:31 No, no, it enhances it.
02:44:31 Because it’s built on the shoulders, it enhances it.
02:44:33 I think it enhances it, it’s not,
02:44:35 that equation is a minimal compressed representation
02:44:38 of reality, right?
02:44:39 We can use machine learning or Max Tegmark’s AI Feynman
02:44:43 to find lots of solutions for gravity,
02:44:45 but isn’t it wonderful that the laws that we do find
02:44:47 are the maximally compressed representations?
02:44:50 Yeah, but that representation, you can now give it as,
02:44:54 I guess the universe has the memory of Einstein
02:44:56 with that representation.
02:44:58 But then you can now give it as a gift for free.
02:45:00 Yeah, yeah, it’s low memory.
02:45:01 To other alien civilizations.
02:45:02 Einstein had to go through a lot of pain to get there,
02:45:03 but it’s low memory.
02:45:04 So, I say that physics and chemistry and biology
02:45:07 are the same discipline.
02:45:08 They’re just physics, laws in physics.
02:45:11 There’s no such thing as a law in physics.
02:45:13 It’s just low memory stuff.
02:45:15 Because you’ve got low memory stuff,
02:45:16 you can, things reoccur quickly.
02:45:19 As you can get, build in more memory,
02:45:21 you get to chemistry, so things become more contingent.
02:45:24 When you get to biology, more contingent still,
02:45:26 and then technology.
02:45:27 So, the more memory you need,
02:45:28 the more your laws are local.
02:45:31 That’s all I’m saying.
02:45:32 And the less memory, the more the laws are universal,
02:45:35 because they’re not laws.
02:45:36 They are just low memory states.
02:45:40 We have to talk about a thing you’ve kind of mentioned
02:45:44 already a bunch of times,
02:45:45 but doing computation through chemistry,
02:45:49 chemical based computation.
02:45:51 I’ve seen you refer to it as in a sexy title
02:45:56 of Kemputation, Kemputation.
02:46:00 So, what is computation?
02:46:02 What is chemical based computation?
02:46:06 Okay, so Kemputation is a name I gave
02:46:09 to the process of building a state machine
02:46:12 to make any molecule physically in the lab.
02:46:15 And so, as a chemist, chemists make molecules by hand.
02:46:19 And they’re quite hard.
02:46:22 The chemists have a lot of tacit knowledge,
02:46:25 a lot of ambiguity.
02:46:26 It’s not possible to go uniformly to the literature
02:46:29 and read a recipe to make a molecule,
02:46:32 and then go and make it in the lab every time.
02:46:35 Some recipes are better than others,
02:46:37 but they all assume some knowledge.
02:46:43 And it’s not universal what that is.
02:46:44 Like, so it’s carried from human to human.
02:46:49 Some of that implicit knowledge.
02:46:51 And you’re saying, can we remove the human
02:46:52 from the patient?
02:46:53 Can we like a program?
02:46:55 Okay, well, by the way, what is a state machine?
02:46:58 So a state machine is a, I suppose,
02:47:01 a object either abstract or mechanical
02:47:05 where you can do a unit operation on it
02:47:10 and flick it from one state to another.
02:47:12 So a turnstile would be a good example of a state machine.
02:47:15 There’s some kinds of states
02:47:17 and some kind of transitions between states.
02:47:19 And it’s very formal in nature
02:47:23 in terms of like it’s precise,
02:47:25 how you’re doing those transitions.
02:47:25 Yes, you can mathematically precisely
02:47:28 describe a state machine.
02:47:29 So, I mean, a very simple Boolean gates
02:47:33 are a very good way of building
02:47:35 kind of logic based state machines.
02:47:38 Obviously a Turing machine,
02:47:39 the concept of a Turing machine
02:47:41 where you have a tape and a read head
02:47:43 and a series of rules in a table
02:47:46 and you would basically look at what’s on the tape.
02:47:49 And if you’re shifting the tape from left to right,
02:47:51 and if you see a zero or one,
02:47:53 you look in your lookup table and say,
02:47:54 right, I’ve seen a zero and a one.
02:47:57 I then do, I then respond to that.
02:48:01 So in the turnstile would be,
02:48:03 is there a human being pushing the turnstile
02:48:06 in direction clockwise?
02:48:09 If yes, I will open, let them go.
02:48:11 If it’s anticlockwise, no.
02:48:12 So yeah, so a state machine has some labels
02:48:15 and a transition diagram.
02:48:17 So you’re looking to come up with a chemical computer
02:48:22 to form state machines to create molecules,
02:48:25 or what’s the chicken and the egg?
02:48:29 So computation is not a chemical computer
02:48:31 because we talked a few moments
02:48:32 about actually doing computations with chemicals.
02:48:35 What I’m now saying is I want to use state machines
02:48:37 to transform chemicals.
02:48:39 And so build chemicals programmatically.
02:48:42 Yeah, I mean, I get in trouble saying this.
02:48:44 I said to my group, oh, I shouldn’t say it
02:48:47 because it’s, but I said, look, we should make the crack bot.
02:48:49 Is it in the crack robot?
02:48:51 The robot that makes crack.
02:48:52 The crack bot?
02:48:52 Oh, oh, oh, oh, crack bot.
02:48:55 The robot that makes crack,
02:48:56 but maybe we should scrub this from, but.
02:49:00 Or, well, so maybe you can educate me
02:49:03 on breaking bad with like math, right?
02:49:06 Yeah, so in breaking bad.
02:49:07 You want to make basically some kind of mix
02:49:12 of ex machina and breaking bad.
02:49:15 No, I don’t.
02:49:16 I don’t.
02:49:17 For the record, I don’t, but I said.
02:49:17 No, you don’t.
02:49:18 I said, that’s what I’m going to do
02:49:19 once you release the papers.
02:49:23 I shaved my head and I’m going to live a life of crime.
02:49:28 Anyway, I’m sorry.
02:49:29 No, no.
02:49:30 So yeah, let’s get back to, so indeed,
02:49:33 it is about making drugs, but importantly,
02:49:35 making important drugs, so let’s.
02:49:38 All drugs matter.
02:49:39 Yeah, but let’s go back.
02:49:41 So the basic thesis is chemistry is very analog.
02:49:46 There is no state machine.
02:49:48 And I wandered into the, through the paper walls
02:49:52 in the Japanese house a few years ago and said,
02:49:55 okay, hey, organic chemist, why are you doing this analog?
02:49:58 They said, well, chemistry is really hard.
02:50:00 You can’t automate it, it’s impossible.
02:50:03 I said, but is it impossible?
02:50:05 They said, yeah.
02:50:06 And they said, you know, I got the impression
02:50:07 they were saying it’s magic.
02:50:09 And so when people tell me things are magic,
02:50:12 it’s like, no, no, they can’t be magic.
02:50:14 Right, so let’s break this down.
02:50:15 And so what I did is I went to my group one day
02:50:19 about eight years ago and said, hey guys,
02:50:21 I’ve written this new programming language for you.
02:50:24 And so everything is clear.
02:50:26 And you know, you have to, you’re not allowed to
02:50:28 just wander around the lab willy nilly.
02:50:30 You have to pick up things in order,
02:50:31 go to the balance of the right time and all this stuff.
02:50:34 And they looked at me as if I was insane
02:50:36 and basically kicked me out of the lab and said,
02:50:37 no, don’t do that, we’re not doing that.
02:50:39 And I said, okay.
02:50:40 So I went back the next day and said,
02:50:43 I’m gonna find some money so we can make cool robots
02:50:45 do chemical reactions.
02:50:46 And everyone went, that’s cool.
02:50:48 And so in that process.
02:50:51 The first we tried to convert the humans to become robots
02:50:54 and next you agree you might as well just create the robots.
02:50:57 Yes, but so in that, the formalization process.
02:51:00 Yeah, so what I did is I said, look, chemical,
02:51:02 to make a molecule, you need to do four things abstractly.
02:51:04 I want to make a chemical Turing machine.
02:51:07 Cause a Turing machine, you think about this,
02:51:08 imagine a Turing machine.
02:51:10 Turing machine is the ultimate abstraction of a computation
02:51:14 because it’s been shown by Turing and others
02:51:17 that basically a universal Turing machine
02:51:19 should be able to do all computations that you can imagine.
02:51:23 It’s like, wow, why don’t I think of a Turing machine
02:51:25 for chemistry?
02:51:26 Let’s think of a magic robot that can make any molecule.
02:51:29 Let’s think about that for a second.
02:51:31 Okay, great.
02:51:32 How do we then implement it?
02:51:33 And I think it’s right.
02:51:34 So what is the abstraction?
02:51:35 So to make any molecule, you have to do a reaction.
02:51:39 So you have to put reagents together, do a reaction
02:51:41 in a flask typically.
02:51:43 Then you’re after the reaction,
02:51:44 you have to stop the reactions.
02:51:45 You do what’s called a workup.
02:51:47 So whatever, cool it down, add some liquid to it, extract.
02:51:51 So then after you do the workup, you separate.
02:51:53 So you then remove the molecules, separate them all out.
02:51:55 And then the final step is purification.
02:51:58 So reaction, workup, separate, purify.
02:52:01 So this is basically exactly like a Turing machine
02:52:05 where you have your tape, you have your tape head,
02:52:08 you have some rules, and then you run it.
02:52:10 So I thought, cool.
02:52:11 I went to all the chemists and said, look,
02:52:13 chemistry isn’t that hard.
02:52:15 Reaction, workup, separation, purification.
02:52:18 Do that in cycles, forever, for any molecule,
02:52:20 all the chemistry, done.
02:52:23 And they said, chemistry is that hard.
02:52:26 I said, but just in principle.
02:52:28 And I got a few very enlightened people to say,
02:52:30 yeah, okay, in principle, but it ain’t gonna work.
02:52:33 And this was in about 2013, 2014.
02:52:36 And I found myself going to an architecture conference
02:52:39 almost by accident.
02:52:40 It’s like, why am I at this random conference
02:52:42 on architecture?
02:52:44 And that was because I published a paper
02:52:45 on inorganic architecture.
02:52:47 And they said, come to architecture conference.
02:52:49 But the inorganic architecture is nano architecture.
02:52:51 It’s not, and I went, okay.
02:52:53 And then I found these guys at the conference,
02:52:54 3D printing ping pong balls and shapes.
02:52:57 And this is through it.
02:52:58 3D printing was cool.
02:52:59 And I was like, this is ridiculous.
02:53:00 Why are you 3D printing ping pong balls?
02:53:01 And I gave them a whole load of abuse
02:53:03 like I normally do when I first meet people,
02:53:05 how to win friends and influence people.
02:53:07 And then I was like, oh my God, you guys are geniuses.
02:53:10 And so I got from, they were a bit confused
02:53:12 because I was calling them idiots
02:53:13 and then call them geniuses.
02:53:14 It’s like, will you come to my lab
02:53:16 and we’re gonna build a robot to do chemistry
02:53:18 with a 3D printer.
02:53:19 And I said, oh, that’s cool, all right.
02:53:20 So I had them come to the lab
02:53:22 and we started to 3D print test tubes.
02:53:24 So you imagine, you know, 3D print a bottle
02:53:26 and then use the same gantry to basically,
02:53:30 rather than to squirt out a plastic out of a nozzle,
02:53:34 have a little syringe and jet chemicals in.
02:53:36 So we had the 3D printer that could simultaneously
02:53:38 print the test tube and then put chemicals
02:53:40 into the test tube.
02:53:42 And then.
02:53:42 Wow, so it’s really end to end.
02:53:44 Yeah, I was like, that would be cool
02:53:45 because they’ve got G code to do it all.
02:53:47 And I was like, that’s cool.
02:53:48 So I got my group doing this and I developed it a bit
02:53:50 and I realized that we could take those unit operations.
02:53:54 And we built a whole bunch of pumps and valves.
02:53:57 And I realized that I could basically take the literature
02:54:00 and I made the first version of the computer in 2016, 17.
02:54:05 I made some architectural decisions.
02:54:07 So I designed the pumps and valves in my group.
02:54:09 I did all the electronics in my group.
02:54:10 They were brilliant.
02:54:12 I cannot pay tribute to my group enough in doing this.
02:54:15 They were just brilliant.
02:54:16 And there were some poor souls there that said,
02:54:18 Lee, why are you making us design electronics?
02:54:21 I’m like, well, because I don’t understand it.
02:54:24 They’re like, so you’re making us design stuff
02:54:26 because you don’t understand.
02:54:26 It’s like, yeah, it’s like, but can we not just buy some?
02:54:29 I said, well, we can, but then I don’t understand
02:54:31 how to, you know, what bus they’re gonna use
02:54:34 and there’s serial ports and all this stuff.
02:54:36 I just wanted, and I made, I came up with a decision
02:54:39 to design a bunch of pumps and valves
02:54:41 and use power of the ethernet.
02:54:42 So they’ve got one cable for power and data,
02:54:45 plug them all in, plug them all into a router
02:54:48 and then I made the state machine.
02:54:51 And there was a couple of cool things I did.
02:54:53 Oh, they did actually.
02:54:55 We got the abstraction.
02:54:57 So reaction, workup, separation, purification.
02:55:02 And then I made the decision to do it in batch.
02:55:06 Now it’s in batch.
02:55:07 All chemistry had been digitized before apparently,
02:55:10 and once it’s been done, but everyone been doing it in flow
02:55:13 and flow is continuous and there are infinities everywhere
02:55:16 and you have to just, and I realized
02:55:19 that I could actually make a state machine
02:55:20 where I basically put stuff in the reactor,
02:55:24 turn it up from one state to another state,
02:55:26 stop it and just read it out.
02:55:28 And okay, and I was kind of bitching
02:55:30 at electrical engineers saying, you have it easy.
02:55:32 You don’t have to clean out the electrons, you know.
02:55:34 Electrons don’t leave a big mess.
02:55:36 They leave some EM waste.
02:55:37 But in my state machine I built in cleaning.
02:55:39 So it’s like, we do all the operation
02:55:41 and then it cleans the backbone and then can do it again.
02:55:43 So there’s no, so what we managed to do
02:55:46 over a couple of years is develop the hardware,
02:55:49 develop the state machine.
02:55:50 And we encoded three molecules.
02:55:52 We did three, the first three, we did nitole,
02:55:54 a sleeping drug, rafinamide, antiseizure and Viagra.
02:55:57 You know, and I could make jokes on the paper.
02:55:59 It’s a hard problem, blah, blah, blah, blah.
02:56:02 That’s very good.
02:56:04 And then in the next one, what we did is said, okay,
02:56:06 my poor organic chemist said, look, Lee,
02:56:09 we’ve worked with you this long.
02:56:11 We’ve made a robot that looks like
02:56:12 it’s gonna take our jobs away.
02:56:14 And not just take our jobs away, what we love in the lab,
02:56:19 but now we have to become programmers.
02:56:20 But we’re not even good programmers.
02:56:22 We just have to spend ages writing lines of code
02:56:25 that are boring and it’s not as elegant.
02:56:27 I went, you’re right.
02:56:28 So then, but I knew because I had this abstraction
02:56:32 and I knew that there was language,
02:56:34 I could suddenly develop a state machine
02:56:36 that would interpret the language,
02:56:37 which was lossy and ambiguous and populate my abstraction.
02:56:42 So I built a chemical programming language
02:56:44 that is actually gonna be recursively enumerable.
02:56:46 It’s gonna be a Turing complete language actually,
02:56:48 which is kind of cool, which means it’s formally verifiable.
02:56:51 So where we are now is we can now read the literature
02:56:55 using a bit of natural language processing.
02:56:56 It’s not the best.
02:56:57 There are many other groups have done a better job,
02:56:59 but we can use that language reading
02:57:01 to populate the state machine and basically add, subtract.
02:57:05 We got about a number of primitives that we,
02:57:09 basically program loops that we dovetail together
02:57:14 and we can make any molecule with it.
02:57:15 Okay, so that’s the kind of program synthesis.
02:57:18 So you start at like literally,
02:57:19 you’re talking about like a paper,
02:57:21 like a scientific paper that’s being read.
02:57:25 Yeah.
02:57:26 So natural language processing,
02:57:27 extracting some kind of details about chemical reactions
02:57:33 and the chemical molecules and compounds involved.
02:57:38 And then that, in GPT terms,
02:57:43 serves as a prompt for the program synthesis
02:57:47 that’s kind of trivial right now.
02:57:49 There you have a bunch of different like for loops
02:57:51 and so on that creates a program in this chemical language
02:57:56 that can then be interpreted by the chemical computer,
02:58:00 the computer.
02:58:01 Yeah, computer, that’s the word.
02:58:03 Computer, yeah.
02:58:05 Everything sounds better in your British accent,
02:58:07 but it’s, I love it.
02:58:09 So the, into the computer and that’s able to then
02:58:12 basically be a 3D printer for these, for molecules.
02:58:17 Yeah, I wouldn’t call it a 3D printer.
02:58:18 I would call it a universal chemical reaction system
02:58:21 because 3D printing gives the wrong impression, but yeah.
02:58:23 And it purifies.
02:58:25 And the nice thing is that that code now that we call it,
02:58:28 the KyDL code is really interesting because now,
02:58:34 so computation, what is computation?
02:58:36 Computation is what computing is to mathematics, I think.
02:58:41 Computation is the process of taking chemical code
02:58:44 and some input reagents and making the same molecule,
02:58:47 making the molecule reproducibly every time without fail.
02:58:52 What is computation?
02:58:53 It’s the process of using a program
02:58:55 to take some input conditions
02:58:57 and give you an output same every time, right, reliably.
02:59:02 So the problem is, now maybe you can push back
02:59:05 and correct me on this.
02:59:07 So I know biology is messy.
02:59:09 My question is how messy is chemistry?
02:59:12 So the, if we use the analogy of a computer,
02:59:15 it’s easier to make computation in a computer very precise,
02:59:21 that it’s repeatable and makes errors almost never.
02:59:26 If it does the exact same way over and over
02:59:28 and over and over.
02:59:29 What about chemistry?
02:59:30 Is there messiness in the whole thing?
02:59:32 Can that be somehow leveraged?
02:59:33 Can that be controlled?
02:59:34 Can it be that removed,
02:59:36 do we wanna remove it from the system?
02:59:38 Oh, yes and no, right.
02:59:39 Is there messiness?
02:59:42 There is messiness because chemistry is like,
02:59:45 you’re doing reactions on billions of molecules
02:59:49 and they don’t always work,
02:59:50 but you’ve got purification there.
02:59:52 And so what we found is at the beginning,
02:59:54 everyone said it can’t work.
02:59:55 It’s gonna be too messy.
02:59:56 It will just fail.
02:59:58 And I said, but you managed to get chemistry
03:00:00 to work in the lab.
03:00:00 Are you magic?
03:00:01 Are you doing something?
03:00:02 So I would say, now go back to the first ever computer
03:00:05 or the ENIAC, 5 million soldered joints,
03:00:09 400,000 valves that are exploding all the time.
03:00:12 Was that, would you have gone, okay, that’s messy.
03:00:16 So we’ve got the,
03:00:18 have we got the equivalent of the ENIAC in my lab?
03:00:21 We’ve got 15 computers in the lab now.
03:00:23 And they, are they unreliable?
03:00:24 Yeah, they fall apart here and there,
03:00:26 but are they getting better really quickly?
03:00:29 Yeah.
03:00:30 Are they now able to reliably make more,
03:00:32 are we at the point in the lab
03:00:33 where there are some molecules
03:00:34 we would rather make on the computer
03:00:37 than have a human being make?
03:00:38 Yeah, we’ve just done,
03:00:39 we’ve just made a anti influenza molecule
03:00:44 and some antivirals,
03:00:46 six steps on the computer that would take a human being
03:00:49 about one week to make Arbidol of continuous labor.
03:00:54 And all they do now is load up the reagents,
03:00:56 press go button and just go away and drink coffee.
03:00:58 Wow, so this, I mean, and this is, you’re saying
03:01:02 this computer is just the early days.
03:01:04 And so like some of the criticism just have to do
03:01:06 with the early days.
03:01:08 And yes, I would say this,
03:01:09 something like this is quite impossible.
03:01:15 So the fact that you’re doing this is incredible.
03:01:18 Not impossible, of course, but extremely difficult.
03:01:20 It did seem really difficult.
03:01:22 And I do keep pinching myself when I go in the lab.
03:01:25 I was like, is it working?
03:01:25 Like, yep.
03:01:26 And it’s not, you know, it does clog, it does stop.
03:01:30 You got to clean, this is great.
03:01:32 It’s, you know, but it’s getting more reliable
03:01:35 because I made some, we just made design decisions
03:01:38 and said, we are not going to abandon the abstraction.
03:01:40 Think about it.
03:01:41 If the von Neumann implementation was abandoned,
03:01:45 I mean, think about what we do to semiconductors
03:01:47 to really constrain them to what we do to silicon
03:01:51 in a fab lab, we take computation for granted.
03:01:55 Silicon is not in its natural state.
03:01:57 We are doping the hell out of it.
03:01:59 It’s incredible what they’re able to accomplish
03:02:00 and achieve that reliability at the scale they do.
03:02:03 Like you said, that’s after Moore’s law, what we have now.
03:02:07 And where we, you know, how it started, you know,
03:02:13 now we’re here.
03:02:14 We started at the bottom, now we’re here.
03:02:15 We have only have 20 million molecules.
03:02:17 Well, say 20 million molecules in one database,
03:02:19 maybe a few hundred million
03:02:21 in all the pharmaceutical companies.
03:02:23 And those few hundred million molecules are responsible
03:02:26 for all the drugs that we’ve had in humanity,
03:02:28 except, you know, biologics for the last 50 years.
03:02:32 Now imagine what happens when a drug goes out of print,
03:02:35 goes out of print because there’s only a finite number
03:02:37 of manufacturing facilities in the world
03:02:38 that make these drugs.
03:02:39 It goes out of print.
03:02:40 Yeah.
03:02:41 Isn’t that computer?
03:02:42 This is a printing press, but for chemistry.
03:02:44 Yeah.
03:02:45 And not only that, we can protect the KyDL
03:02:47 so we can stop bad actors doing it.
03:02:49 We can encrypt them and we can give people license.
03:02:51 KyDL, that’s the name, sorry to interrupt,
03:02:53 is the name of the programming language?
03:02:54 Yeah, the KyDL is the name of the programming language
03:02:56 and the code we give the chemicals.
03:02:58 So Ky, as in, you know, just for,
03:03:01 it’s actually like an XML format,
03:03:04 but I’ve now taken it from script
03:03:06 to a fully expressible programming language
03:03:10 so we can do dynamics and there’s for loops in there
03:03:12 and conditional statements.
03:03:13 Right, but the structure, it started out as like an XML
03:03:18 type of thing.
03:03:19 Yeah, yeah, yeah.
03:03:20 And also, the chemist doesn’t need to program in KyDL.
03:03:22 They can just go to the software and type in add A to B,
03:03:25 reflux, do what they would normally do,
03:03:27 and it just converts it to KyDL
03:03:28 and they have a linter to check it and error correct.
03:03:30 So how do you, you know, not with ASCII,
03:03:34 but because it’s a Greek letter,
03:03:36 how do you go with, how do you spell it
03:03:39 just using the English alphabet?
03:03:42 We just, XDL?
03:03:43 XDL, but all we use, we put in Ky.
03:03:46 And it was named by one of my students
03:03:47 and one of my postdocs many years ago
03:03:49 and I quite liked it.
03:03:50 It’s like, it’s important, I think,
03:03:53 when the team are contributing to such big ideas,
03:03:55 cause there’s their ideas as well.
03:03:57 I try not to just rename, I didn’t call it Cronon
03:04:00 or anything that, cause they keep saying, you know,
03:04:03 is the chemistry, when they’re putting stuff
03:04:07 in the computer, one of my students said,
03:04:08 we’re asking now, is it Cronon complete?
03:04:10 And I was like, what does that mean?
03:04:11 I said, well, can we make it on the damn machine?
03:04:13 And I was like, oh, is that a compliment or a majority?
03:04:18 But they’re like, well, it might be both.
03:04:21 Yeah, so you tweeted, quote,
03:04:24 why does chemistry need a universal programming language,
03:04:27 question mark?
03:04:29 For all the reasons you can think of.
03:04:31 Reliability, interoperability, collaboration,
03:04:35 remove ambiguity, lower cost, increase safety,
03:04:39 open up discovery, molecular customization,
03:04:42 and publication of executable chemical code.
03:04:46 Which is fascinating, by the way.
03:04:49 Just publish code.
03:04:51 And can you maybe elaborate a little bit more
03:04:56 about this CHI DL, what does the universal language
03:04:59 of chemistry look like?
03:05:01 A Cronon complete language.
03:05:04 It’s a Turing complete language, really.
03:05:07 But, so what it has, it has a series of operators in it,
03:05:11 like add, heat, stir.
03:05:14 So there’s a bunch of unit operations.
03:05:17 And all it is, really, is just,
03:05:19 it’s with chemical engineers,
03:05:21 when I talked about this,
03:05:22 that you’ve just rediscovered chemical engineering.
03:05:26 And I said, well, yeah, I know.
03:05:27 I said, well, that’s trivial.
03:05:30 I said, well, not really.
03:05:31 Well, yes, it is trivial, and that’s why it’s good,
03:05:33 because not only have we rediscovered chemical engineering,
03:05:36 we’ve made it implementable on the universal hardware
03:05:38 that doesn’t cost very much money.
03:05:40 And so the CHI DL has a series of statements.
03:05:43 Like define the reactor.
03:05:46 So defines the reagents.
03:05:49 So they’re all labels, so you assign them.
03:05:52 And what I also implemented at the beginning is,
03:05:55 because I give all the hardware IP address,
03:05:57 you put it on a graph.
03:05:59 And so what it does is like the graph is equivalent
03:06:02 to the processor firmware, the processor code.
03:06:06 So when you take your CHI DL,
03:06:08 and you go to run it on your computer,
03:06:10 you can run it on any compatible hardware
03:06:12 in any configuration, it says, what does your graph look like?
03:06:14 As long as I can solve the problem on the graph
03:06:17 with these unit operations,
03:06:17 and you have the resources available, it can compile.
03:06:20 Chem piles.
03:06:21 Ah ha.
03:06:22 Ha ha ha.
03:06:23 Ha ha ha.
03:06:24 Oh.
03:06:25 All right, we can carry on for years.
03:06:27 But it is really, it’s chempilation.
03:06:29 Chempilation, yeah.
03:06:29 And what it now does is it says, okay,
03:06:32 the problem we have before is it was possible
03:06:35 to do robotics for chemistry,
03:06:37 but the robots were really expensive.
03:06:39 They were unique.
03:06:40 They were vendor locked.
03:06:42 And what I want to do is to make sure
03:06:44 that every chemist in the world can get access
03:06:46 to machinery like this at virtually no cost,
03:06:49 because it makes it safer.
03:06:51 It makes it more reliable.
03:06:53 And then if you go to the literature
03:06:55 and you find a molecule that could potentially cure cancer,
03:06:58 and let’s say the molecule that could potentially
03:06:59 cure cancer takes you three years to repeat,
03:07:03 and maybe a student finishes their PhD in the time
03:07:06 and they never get it back.
03:07:07 So that it’s really hard to kind of get all the way
03:07:12 to that molecule, and it limits the ability
03:07:14 of humanity to build on it.
03:07:16 If they just download the code and can execute it,
03:07:19 it turns, I would say the electronic laboratory notebook
03:07:22 in chemistry is a data cemetery,
03:07:26 because no one will ever reproduce it.
03:07:28 For now, the data cemetery is a Jupiter notebook
03:07:30 and you can just execute it.
03:07:31 A notebook and people can play with it,
03:07:33 the access to it.
03:07:34 Reversion it.
03:07:35 Orders of magnitude is increased.
03:07:37 We’ll talk about the, so as with all technologies,
03:07:41 I think there’s way more exciting possibilities,
03:07:43 but there are also terrifying possibilities,
03:07:45 and we’ll talk about all of them.
03:07:47 But let me just kind of linger on the machine learning
03:07:50 side of this.
03:07:51 So you’re describing programming,
03:07:53 but it’s a language, I don’t know if you’ve heard
03:07:57 about OpenAI Codex, which is.
03:07:59 Yeah, I’m playing with it.
03:08:00 You’re playing, of course you are.
03:08:02 Yeah, you really are Rick from Rick and Morty.
03:08:07 This is great.
03:08:08 Okay, except philosophically deep.
03:08:12 I mean, he is, I guess, kind of philosophically deep too.
03:08:14 So for people who don’t know, GPT, GPT3,
03:08:18 that’s a language model that can do natural language
03:08:21 generation, so you can give it a prompt
03:08:23 and it can complete the rest of it.
03:08:26 But it turns out that that kind of prompt,
03:08:28 it’s not just completes the rest of it,
03:08:30 it’s generating like novel sounding text,
03:08:36 and then you can apply that to generation
03:08:38 of other kinds of stuff.
03:08:40 So these kinds of transformer based language models
03:08:43 are really good at forming deep representations
03:08:49 of a particular space, like a medium, like language.
03:08:54 So you can then apply it to specific subset of language
03:08:56 like programming, so you can have it learn
03:09:00 the representation of the Python programming language
03:09:03 and use it to then generate syntactically
03:09:06 and semantically correct programs.
03:09:10 So you can start to make progress on one of the hardest
03:09:13 problems in computer science, which is program synthesis.
03:09:16 How do you write programs that accomplish different tasks?
03:09:19 So what OpenAI Codex does is it to generate
03:09:24 those programs based on a prompt of some kind.
03:09:28 Usually you can do a natural language prompt,
03:09:30 so basically as you do when you program,
03:09:32 you write some comment which serves the basic documentation
03:09:37 of the inputs and the outputs and the function
03:09:40 of the particular set of code and it’s able
03:09:41 to generate that.
03:09:43 Point being is you can generate programs
03:09:46 using machine learning, using neural networks.
03:09:49 Those programs operate on the boring old computer.
03:09:56 Can you generate programs that operate,
03:09:59 this gotta be a clever version of programs for this,
03:10:01 but can you write programs that operate on a computer?
03:10:06 Yep, there’s actually software out there right now
03:10:08 you can go and do it.
03:10:10 Really?
03:10:11 Yeah, yeah, it’s a heuristic, it’s rule based,
03:10:14 but we have, what we’ve done, inspired by Codex actually,
03:10:20 is over the summer I ran a little workshop.
03:10:23 Some of my groups got this inspired idea
03:10:25 that we should get a load of students
03:10:28 and ask them to manually collect data,
03:10:30 to label chemical procedures into Kydy L.
03:10:35 And we have a cool synth reader.
03:10:38 So there’s a bunch of people doing this right now,
03:10:41 but they’re doing it without abstraction.
03:10:46 And because we have an abstraction
03:10:47 that’s implementable in the hardware,
03:10:50 we’ve developed basically a chemical analog of Codex.
03:10:54 When you say, sorry to interrupt,
03:10:56 when you say abstraction in the hardware, what do you mean?
03:10:59 So right now, a lot of people doing machine learning
03:11:01 and reading chemistry and saying,
03:11:04 oh, you’ve got all these operations,
03:11:05 add, shake, whatever, heat.
03:11:07 But because they don’t have a uniform,
03:11:11 I mean, it’s a couple of groups doing it,
03:11:12 competitors actually, and they’re good, very good.
03:11:15 But they can’t run that code automatically.
03:11:20 They are losing meaning.
03:11:24 And the really important thing that you have to do
03:11:28 is generate context.
03:11:29 And so what we’ve learned to do with our abstraction
03:11:32 is make sure we can pull the context out of the text.
03:11:36 And so can we take a chemical procedure
03:11:40 and read it and generate our executable code?
03:11:42 Yes.
03:11:43 What’s the hardest part about that whole pipeline
03:11:45 from the initial text, interpreting the initial text
03:11:48 of a paper, extracting the meaningful context
03:11:52 and the meaningful chemical information
03:11:54 to then generating the program
03:11:56 to then running that program in the hardware?
03:12:00 What’s the hardest part about that pipeline
03:12:02 as we look towards a universal Turing computer?
03:12:05 So the hardest thing with the pipeline
03:12:10 is that the software, the model gets confused
03:12:16 between some meanings, right?
03:12:18 So if, you know, chemists are very good at inventing words
03:12:21 that aren’t broken down.
03:12:22 So I would, the classic word that you would use
03:12:25 for boiling something is called reflux.
03:12:28 So reflux is, you would have a solvent
03:12:31 in a round bottom flask, at reflux it would be boiling,
03:12:33 going up the reflux condenser and coming down.
03:12:35 But that term reflux to reflux could be changed, you know,
03:12:40 to people often make up words, new words,
03:12:44 and then the software can fall over.
03:12:47 But what we’ve been able to do is a bit like in Python
03:12:50 or any programming language is identify
03:12:53 when things aren’t matched.
03:12:55 So you present the code and you say, this isn’t matched.
03:12:57 You may want to think about this.
03:12:58 And then the user goes and says, oh, I mean reflux
03:13:01 and just ticks a box and collects it.
03:13:02 So what the Codex or the Chemex does in this case
03:13:08 is it just, it suggests the first go
03:13:12 and then the chemist goes in and corrects it.
03:13:14 And I really want the chemist to correct it
03:13:16 because it’s not safe, I believe, for it to allow AI
03:13:21 to just read literature and generate code at this stage.
03:13:25 Because now you’re having actual, by the way, Chemex,
03:13:28 nice, nice name, so you are unlike, which is fascinating.
03:13:38 It’s that we live in a fascinating moment in human history.
03:13:42 But yes, you’re literally connecting AI
03:13:47 to some physical and like it’s building something
03:13:52 in the physical realm, especially in the space
03:13:55 of chemistry that operates sort of invisibly.
03:14:02 Yeah, yeah, I would say that’s right.
03:14:05 And it’s really important to understand
03:14:07 those labeling schemes, right?
03:14:09 And one of the things I was never,
03:14:11 I was always worried about the beginning
03:14:12 that the abstraction was gonna fall over.
03:14:15 And the way we did it was just by brute force to start with.
03:14:18 We just kept reading the literature and saying,
03:14:19 is there anything new?
03:14:20 Can we add a new rule in?
03:14:21 And actually our KyDL language expanded, exploded.
03:14:25 There was so many extra things we had to keep adding.
03:14:28 And then I realized the primitives still were maintained
03:14:31 and I could break them down again.
03:14:32 So it’s pretty good.
03:14:35 I mean, there are problems.
03:14:36 There are problems of interpreting any big sentence
03:14:38 and turning it into an actionable code.
03:14:40 And in Codex, it’s not without its problems.
03:14:42 You can crash it quite easily, right?
03:14:44 You can generate nonsense.
03:14:45 But boy, it’s interesting.
03:14:47 I would love to learn to program now using Codex, right?
03:14:52 Just hacking around, right?
03:14:54 And I wonder if chemists in the future will learn
03:14:55 to do chemistry by just hacking around with the system
03:15:01 and writing different things.
03:15:02 Because the key thing that we’re doing with the chemistry
03:15:04 is that where a lot of mathematical chemistry went wrong
03:15:07 is people, and I think Wolfram does this in Mathematica,
03:15:11 he assumes that chemistry is a reaction where atom A
03:15:15 or molecule A reacts with molecule B
03:15:17 to give molecule C.
03:15:18 That’s not what chemistry is.
03:15:20 Chemistry is take some molecule,
03:15:23 take a liquid or a solid, mix it up and heat it
03:15:27 and then extract it.
03:15:29 So the programming language is actually with respect
03:15:32 to the process operations.
03:15:35 And if you flick in process space,
03:15:37 not in chemical graph space, you unlock everything
03:15:41 because there’s only a finite number of processes
03:15:43 you need to do in chemistry.
03:15:45 And that’s reassuring.
03:15:47 And so we’re in the middle of it, it’s really exciting.
03:15:51 It’s not the be all and the end all.
03:15:53 And there is like I say, errors that can creep in.
03:15:55 One day we might be able to do it without human interaction
03:15:58 and you simulate it.
03:15:59 And you’ll know enough about the simulation
03:16:01 that the lab won’t catch fire.
03:16:05 But there are so many safety issues right now
03:16:07 that we’ve got to really be very careful,
03:16:09 protecting the user, protecting the environment,
03:16:11 protecting misuse.
03:16:13 I mean, there’s lots to discuss
03:16:14 if you want to go down that route
03:16:16 because it’s very, very interesting.
03:16:17 You don’t want Novichoks being made
03:16:20 or explosives being made or recreational drugs being made.
03:16:26 But how do you stop a molecular biologist making a drug
03:16:30 that’s gonna be important for them looking
03:16:32 at their particular assay
03:16:35 on a bad actor trying to make methamphetamine?
03:16:38 I saw how you looked at me when you said bad actor,
03:16:41 but that’s exactly what I’m gonna do.
03:16:42 I’m trying to get the details of this so I can be first.
03:16:45 Don’t worry, we can protect you from yourself.
03:16:47 Okay.
03:16:50 I’m not sure that’s true, but that statement gives me hope.
03:16:54 Does this ultimately excite you about the future
03:17:00 or does it terrify you?
03:17:01 So let’s, we mentioned that time is fundamental.
03:17:07 It seems like you’re at the cutting edge of progress
03:17:12 that will have to happen, that will happen,
03:17:15 that there’s no stopping it.
03:17:18 And I, as we’ve been talking about,
03:17:20 I see obviously a huge number of exciting possibilities.
03:17:24 So whenever you automate these kinds of things,
03:17:29 just the world opens up.
03:17:31 It’s like programming itself and the computer,
03:17:34 regular computer, has created innumerable applications.
03:17:39 It made the world better in so many dimensions.
03:17:43 And it created, of course, a lot of negative things
03:17:45 that we, for some reason, like to focus on
03:17:48 using that very technology to tweet about it.
03:17:52 But I think it made a much better world,
03:17:55 but it created a lot of new dangers.
03:17:57 So maybe you can speak to when you have,
03:18:02 when you kind of stand at the end of the road
03:18:07 for building a really solid, reliable, universal computer.
03:18:14 What are the possibilities that are positive?
03:18:16 What are the possibilities that are negative?
03:18:18 How can we minimize the chance of the negative?
03:18:21 Yeah, that’s a really good question.
03:18:22 So there’s so many positive things,
03:18:23 from drug discovery, from supply chain stress,
03:18:28 for basically enabling chemists
03:18:30 to basically build more productive in the lab, right?
03:18:32 Where this is, the computer’s not gonna replace the chemist.
03:18:35 There’s gonna be a Moore’s law of molecules, right?
03:18:37 There’s gonna be so many more molecules we can design,
03:18:39 so many more diseases we can cure.
03:18:41 So chemists in the lab as researchers,
03:18:43 that’s better for science.
03:18:44 So they can build a bunch of,
03:18:47 like they could do science at a much more accelerated pace.
03:18:50 So it’s not just the development of drugs,
03:18:51 it’s actually like doing the basic understanding
03:18:54 and the science of drugs.
03:18:55 And the personalization, the cost of drugs right now,
03:18:57 we’re all living longer, we’re all having more and more,
03:19:00 we know more about our genomic development,
03:19:02 we know about our predetermination,
03:19:05 and we might be able to,
03:19:06 one dream I’ve got is like,
03:19:07 imagine you can work at your genome assistant
03:19:11 tells you you’re gonna get cancer in seven years time,
03:19:14 and you have your personal computer
03:19:16 that cooks up the right molecule just for you to cure it,
03:19:20 right?
03:19:20 That’s a really positive idea.
03:19:22 The other thing is when drugs,
03:19:25 so right now I think it’s absolutely outrageous
03:19:28 that not all of humanity has access to medicine.
03:19:33 And I think the computer
03:19:34 might be able to change that fundamentally
03:19:36 because it will disrupt the way things are manufactured.
03:19:38 So let’s stop thinking about manufacturing
03:19:40 in different factories.
03:19:41 Let’s say that computers,
03:19:44 clinical grade computers or drug grade computers
03:19:47 will be in facilities all around the world,
03:19:49 and they can make things on demand
03:19:52 as a function of the cost.
03:19:54 Maybe people won’t be able to afford
03:19:55 the latest and greatest patent,
03:19:57 but maybe they’ll be able to get the next best thing
03:20:00 and will basically democratize,
03:20:02 make available drugs to everybody that they need.
03:20:06 And there’s lots of really interesting things there.
03:20:10 So I think that’s gonna happen.
03:20:12 I think that now let’s take the negative.
03:20:16 Before we do that,
03:20:18 let’s imagine what happened,
03:20:19 go back to a really tragic accident a few years ago,
03:20:21 well not accident,
03:20:23 an act of murder by that pilot on the,
03:20:26 I think it was Eurowings or Swisswings.
03:20:28 But what he did is plane took off,
03:20:30 he waited till his pilot went to the toilet,
03:20:33 he was a co pilot,
03:20:34 he locked the door and then set the autopilot
03:20:39 above the Alps,
03:20:40 he set the altimeter or the descend height to zero.
03:20:44 So the computer just took the plane into the Alps.
03:20:48 Now, I mean, that was such a tragedy
03:20:51 that obviously the guy was mentally ill,
03:20:53 but it wasn’t just a tragedy for him,
03:20:55 it was for all the people on board.
03:20:57 But what if, and I was inspired by this
03:20:58 and my thinking, what can I do to anticipate
03:21:03 problems like this in the computer?
03:21:05 Had the software,
03:21:06 and I’m sure Boeing and Airbus will be thinking,
03:21:09 oh, maybe I can give the computer
03:21:11 a bit more situational awareness.
03:21:12 So whenever one tries to drop the height of the plane
03:21:15 and it knows it’s above the Alps,
03:21:16 we’ll just say, oh no, computer says no,
03:21:18 we’re not letting you do that.
03:21:20 Of course, he would have been able to find another way,
03:21:22 maybe fly it until it runs out of fuel or something,
03:21:24 but you know.
03:21:25 Keep anticipating all the large number of trajectories
03:21:28 that can go negative,
03:21:29 all those kinds of running into the Alps
03:21:31 and try to at least make it easy
03:21:35 for the engineers to build systems that are protecting us.
03:21:38 Yeah, and let’s just think,
03:21:40 what in the computer world right now with Kydeals,
03:21:43 let’s just not think about what I’m doing right now.
03:21:45 What I’m doing right now is it’s completely open, right?
03:21:47 Everyone’s gonna know Kydeals and be playing with them,
03:21:48 making them more easier and easier and easier.
03:21:51 But what we’re gonna start to do,
03:21:53 it makes sense to encrypt the Kydeals in such a way,
03:21:59 let’s say you work for a pharmaceutical company
03:22:01 and you have a license to make given molecule,
03:22:03 well, you get issued with a license
03:22:05 by the FDA or your local authority
03:22:07 and they’ll say, right, your license to do it,
03:22:08 here it is, it’s encrypted and the Kydeal gets run.
03:22:12 So you have a license for that instance of use, easy to do.
03:22:15 Computer science has already solved the problem.
03:22:17 So the fact that we all trust online banking, right,
03:22:21 the right now, then we can secure it.
03:22:23 I’m 100% sure we can secure the computer.
03:22:26 And because of the way we have a many,
03:22:28 it’s like the same mapping problem that you,
03:22:32 to actually reverse engineer a Kydeal
03:22:34 will be as hard as reverse engineering the encryption key,
03:22:38 brute force, it will be cheaper
03:22:41 to just actually buy the regulated medicine.
03:22:44 And actually people aren’t gonna want to then
03:22:46 make their own fake pharmaceuticals
03:22:49 because it’ll be so cheap to do it.
03:22:51 We’ll drop the cost of access to drugs.
03:22:53 Now what will happen?
03:22:54 Recreational drugs.
03:22:56 People will start saying,
03:22:57 well, I want access to recreational drugs.
03:22:59 Well, it’s gonna be up to,
03:23:01 it’s gonna accelerate that social discussion
03:23:03 that’s happening in the US and Canada and UK,
03:23:06 everywhere, right?
03:23:07 Because cost goes down, access goes up.
03:23:10 Giving cannabis THC to some people who’ve got epilepsy
03:23:13 isn’t literally, forgive the term, a no brainer
03:23:16 because these poor people go from seizures like every day
03:23:19 to maybe seizures just once every few months.
03:23:22 That’s an interesting idea to try to minimize the chance
03:23:25 that it can get into like the hands of individuals
03:23:29 like terrorists or people that want to do harm.
03:23:32 Now with that kind of thing,
03:23:35 you’re putting a lot of power in the hands of governments,
03:23:39 in the hands of institutions.
03:23:40 And so then emerge the kind of natural criticism
03:23:44 you might have of governments that can sometimes use these
03:23:47 for ill, use them as weapons of war,
03:23:50 not tools of betterment.
03:23:54 So, and sometimes not just war against other nations,
03:23:59 but war against its own people
03:24:01 as it has been done throughout history.
03:24:04 Well, I’m thinking, so there’s another way of doing it,
03:24:06 a decentralized peer to peer version
03:24:09 where, and what you have to do,
03:24:11 I’m not saying you should adopt a blockchain,
03:24:13 but there is a way of maybe taking Kydeals
03:24:14 and put them in blockchain.
03:24:16 Here’s an idea, let’s just say,
03:24:17 the way we’re doing it in my lab right now
03:24:18 is we go to the literature,
03:24:20 we take a recipe to make a molecule,
03:24:23 convert that to Kydeal and diligently make it in the robot
03:24:27 and validate it.
03:24:28 We, that, so we, I would call mining proof of work,
03:24:31 proof of synthesis, right?
03:24:34 Proof of the synthesis.
03:24:35 Yeah, yeah, but this is cool because suddenly
03:24:37 when you actually synthesize it,
03:24:38 you can get the analytical data,
03:24:40 but there’s also a fingerprint in there
03:24:41 of the impurities that get carried across
03:24:43 because you can never make one, something 100% pure.
03:24:46 That fingerprint will allow you to secure your Kydeal.
03:24:49 So what you do is encrypt those two things.
03:24:51 So suddenly you can have people out there mining
03:24:54 and what you could do perhaps is do the type of thing,
03:24:58 we need to basically look at the way that contact tracing
03:25:01 should have been done in COVID
03:25:03 where people are given the information.
03:25:05 So you have just been in contact with someone COVID,
03:25:07 you choose, I’m not telling you to stay at home,
03:25:10 you choose, right?
03:25:12 So now if we could imagine a similar thing,
03:25:14 like, you know, you have got access to these chemicals,
03:25:17 they will have these effects,
03:25:18 you choose and publicize it,
03:25:20 or maybe it’s out somewhere, I don’t know.
03:25:22 I’m not a policymaker on this.
03:25:25 And what my job here is
03:25:26 to not just make the technology possible,
03:25:29 but to have as open as a discussion as possible
03:25:31 with people to say, hey,
03:25:33 can we stop childhood mortality with this technology?
03:25:36 And do those benefits outweigh the one off
03:25:40 where people might use it for terrorism
03:25:42 or people might use it for recreational drugs?
03:25:45 Chemify, which is the name of the entity
03:25:47 that will make this happen,
03:25:48 I think we have some social responsibilities as an entity
03:25:51 to make sure that we’re not enabling people
03:25:53 to manufacture personal drugs, weapons at will.
03:25:56 And what we have to do is have a discussion with society,
03:25:59 with the people that invest in this,
03:26:01 with people that are gonna pay for this,
03:26:03 to say, well, do you wanna live longer?
03:26:05 And do you wanna be healthier?
03:26:07 And are you willing to accept some of the risks?
03:26:09 And I think that’s a discussion to have.
03:26:11 So by the way, when you say personal drugs,
03:26:14 do you mean the illegal ones?
03:26:16 Or do you have a concern of just putting the manufacturer
03:26:19 of any kind of illegal drugs
03:26:22 in the hands of regular people?
03:26:25 Cause they might, like dose matters.
03:26:28 They might take way too much.
03:26:29 I mean, I would say, to be honest,
03:26:31 the chances of computers being,
03:26:34 well, shouldn’t always never.
03:26:35 So the fact I can now say this means
03:26:37 it’s totally gonna come true, right?
03:26:39 And I’m going to do it.
03:26:40 I cannot imagine that computers will be
03:26:43 in people’s houses anytime soon,
03:26:45 but they might be at the local pharmacy, right?
03:26:48 And if you’ve got a drug manufacturing facility
03:26:51 in every town, then you just go
03:26:53 and they give you a prescription.
03:26:54 They do it in such a way, they format it
03:26:56 so that you don’t have to take 10 pills every day.
03:26:59 You get one manufactured for you
03:27:01 that has all the materials you need
03:27:03 and the right distribution.
03:27:04 Got it.
03:27:05 But you mentioned recreational drugs.
03:27:07 And the reason I mention it,
03:27:09 cause I know people are going to speak up on this.
03:27:12 If the drug is legal, there’s to me,
03:27:14 no reason why you can’t manufacture it for recreation.
03:27:18 I mean, you can do it right now.
03:27:19 What do you have against fun, Lee?
03:27:22 I have, so I mean, I’m a chemistry professor
03:27:26 in a university who’s an entrepreneur as well.
03:27:29 I just think I need to be as responsible
03:27:31 as I can in the discussion.
03:27:33 Sure, no, sure, sure.
03:27:35 But I know, so let me be the one that says
03:27:37 like there’s nothing, cause you have said
03:27:40 recreational drugs and like terrorism in the same sentence.
03:27:44 I think let’s make sure we draw a line
03:27:47 that there’s real dangers to the world
03:27:50 of terrorists of bio warfare.
03:27:53 And then there’s a little bit of weed.
03:27:55 So I haven’t, I mean, I think it’s up to the society
03:27:59 to tell his governments what it wants,
03:28:03 what’s acceptable, right?
03:28:04 And if it becomes, let’s say that THCs
03:28:07 become heavily acceptable and that you can modify them.
03:28:12 So let’s say there’s, let’s say it’s like blood type.
03:28:15 There’s a particular type of THC
03:28:17 that you tolerate better than I do.
03:28:20 Then why not have a machine that makes the one you like?
03:28:23 And then, and why not?
03:28:24 It’s the perfect brownie.
03:28:26 Yeah, and I think that that’s fine.
03:28:29 But I’m, we’re so far away from that.
03:28:32 I can barely get the thing to work in the lab, right?
03:28:34 And I mean, it’s reliability and all this other stuff,
03:28:36 but what I think is gonna happen in the short term,
03:28:39 it’s gonna turbocharge molecular discovery reliability
03:28:43 and that will change the world.
03:28:45 That’s super exciting.
03:28:46 You have a draft of a paper titled
03:28:49 Autonomous Intelligent Exploration,
03:28:50 Discovery and Optimization of Nanomaterials.
03:28:53 So we are talking about
03:28:55 automating engineering of nanomaterials.
03:28:58 How hard is this problem?
03:29:01 And as we continue down this thread of the positives
03:29:04 and the worrisome,
03:29:06 what are the things we should be excited about?
03:29:09 And what are the things we should be terrified about?
03:29:12 And how do we minimize the chance
03:29:13 of the terrifying consequences?
03:29:18 So in this robot, the robot does all the heavy lifting.
03:29:21 So the robot basically is an embodied AI.
03:29:24 I really like AI in a domain specific way.
03:29:29 One of the, as you should say at this point,
03:29:31 there was an attempt in the 60s,
03:29:34 Joshua Leidenberg and some really important people
03:29:37 did this that made an AI to try and guess
03:29:40 if organic molecules and the mass spectrometer
03:29:42 were alien or not.
03:29:43 Yes.
03:29:44 And they failed because they didn’t have assembly theory.
03:29:47 I see.
03:29:48 And when I, and I, and that.
03:29:49 Wait, what does assembly theory
03:29:51 give you about alien versus human life?
03:29:53 Well, no, it just, it tells you about unknown,
03:29:55 the degree of unknowns.
03:29:56 You can fingerprint stuff.
03:29:57 They weren’t looking at,
03:29:58 they were trying to basically just look at the corpus
03:30:01 of complex organic molecules.
03:30:04 So when I was a bit down about assembly theory,
03:30:06 cause I couldn’t convince referees
03:30:08 and couldn’t convince computational people
03:30:11 interested in computational complexity,
03:30:14 I was really quite depressed about it.
03:30:16 And I mean, I’ve been working with Sarah Walker’s team
03:30:20 and I think she, you know,
03:30:21 I think she also invented an assembly theory somewhere.
03:30:23 We can talk about it later.
03:30:25 When I found the AI not working for the dendrial project,
03:30:30 I suddenly realized I wasn’t totally insane.
03:30:34 Coming back to this nano robot.
03:30:37 So what it does is it basically, like a computer,
03:30:40 but now what it does is it squirts a liquid
03:30:42 with gold in it in a test tube
03:30:45 and it adds some reducing agents,
03:30:49 so some electrons to make the gold
03:30:51 turn into a nanoparticle.
03:30:53 Now, when gold becomes a nanoparticle,
03:30:54 it gets a characteristic color, a plasmon.
03:30:56 So it’s a bit like if you look at the sheen
03:30:58 on the gold wedding ring or gold bar or something,
03:31:01 those are the ways that conducting electrons
03:31:03 basically reflect light.
03:31:05 What we did is we randomly squirt the gold,
03:31:08 the gold particle and the reducing agent
03:31:10 and then we measure the UV, we measure the color.
03:31:13 And so what we do is we’ve got, the robot has a mind.
03:31:16 So it has a mind where in a simulation,
03:31:20 it randomly generates nanoparticles and the plasmon,
03:31:23 the color that comes out, randomly imagines in its head.
03:31:27 It then with the others,
03:31:28 that’s the imaginary side of the robot.
03:31:29 In the physical side of the robot,
03:31:30 it squirts in the chemicals and looks at the color
03:31:34 and it uses a genetic algorithm
03:31:36 and a map elite actually on it.
03:31:38 And it goes around in cycles and refines
03:31:43 the color to the objective.
03:31:45 Now we use two different points.
03:31:46 We have an exploration and an optimization.
03:31:50 They’re two different.
03:31:51 So the exploration just says, just do random stuff
03:31:54 and see how many different things you can get.
03:31:55 And when you get different things,
03:31:57 try and optimize and make the peak sharper, sharper, sharper.
03:32:00 And what it does after a number of cycles
03:32:03 is it physically takes a sample
03:32:05 of the optimized nanomaterial,
03:32:07 resets all of the round bottom flasks, cleans them
03:32:10 and puts the seed, physical seed back in.
03:32:14 And then what this robot is able to do
03:32:16 is search a space of 10 to the 23 possible reactions
03:32:20 in just a thousand experiments in three days.
03:32:24 And it makes five generations of nanoparticles
03:32:26 which get nicer and nicer in terms of shape
03:32:28 and color and definition.
03:32:30 And then at the end, it outputs a Kydl code.
03:32:33 That could then be.
03:32:34 Wow, it’s doing the search for programs
03:32:38 in the physical space.
03:32:39 So it’s doing a kind of reinforcement learning.
03:32:42 Yeah, yeah, in the physical space.
03:32:44 With the exploration and the optimization.
03:32:46 And that Kydl will work on any computer
03:32:48 or any qualified hardware.
03:32:49 So now that’s it.
03:32:50 That’s now that’s a general piece of code
03:32:53 that can replicate somewhat maybe perfectly
03:32:57 what it created.
03:32:58 That’s amazing.
03:32:59 That’s incredible.
03:33:00 But the nanoparticles themselves are done.
03:33:02 The robot has all the thinking.
03:33:03 So we don’t try and imply any self replication
03:33:06 or try and get the particles to make themselves.
03:33:09 Although it would be cool to try.
03:33:11 So, well, there you go.
03:33:13 That’s, those are famous last words
03:33:14 for the end of human civilization.
03:33:16 Would be cool to try.
03:33:17 So is it possible to create molecules
03:33:21 that start approaching this question
03:33:24 that we started this conversation,
03:33:26 which is the origin of life.
03:33:29 To start to create molecules that have lifelike qualities.
03:33:33 So have the replication, have like complex,
03:33:37 start to create complex organisms.
03:33:40 So we have done this with the oxides.
03:33:42 I talked about earlier with the moxides
03:33:43 and the rings and the bulls.
03:33:45 And the problem is that, well, they do,
03:33:49 they auto catalytically enhance one another.
03:33:52 So they would, I guess you would call it self replication.
03:33:55 But because there’s limited function and mutation,
03:34:01 they’re pretty dumb.
03:34:02 So they don’t do very much.
03:34:04 So I think the prospect of us being able to engineer
03:34:10 a nano material life form in the short term,
03:34:13 like I said earlier,
03:34:14 my aim is to do this, of course.
03:34:16 I mean, on one hand, I’m saying it’s impossible.
03:34:18 On the other hand, I’m saying I’m doing it.
03:34:19 So which is it, Lee?
03:34:20 It’s like, well, I think we can do it,
03:34:23 but only in the robot.
03:34:24 So the causal chain that’s gonna allow it is in the robot.
03:34:27 These particles, if they do start to self replicate,
03:34:30 the system’s gonna be so fragile
03:34:32 that I don’t think anything dangerous will come out.
03:34:35 It doesn’t mean we shouldn’t treat them
03:34:38 as potentially, I mean, I don’t want to scare people
03:34:42 like gain of function.
03:34:43 We’re gonna produce stuff that comes out.
03:34:45 Our number one kill switch is that we always try
03:34:48 to search a space of objects
03:34:52 that don’t exist in the environment.
03:34:55 So even if something got out, it just would die immediately.
03:34:58 It’s like making a silicon life form or something.
03:35:02 Which is the opposite of oftentimes
03:35:04 gain of function research is focused on
03:35:06 how do you get a dangerous thing
03:35:09 to be closer to something that works with humans?
03:35:11 Yeah.
03:35:12 To have it jump to humans.
03:35:13 So that’s the one good mode to operate on
03:35:16 is always try to operate on chemical entities
03:35:22 that are very different than the kind of chemical environment
03:35:25 that humans operate in.
03:35:26 Yeah, and also, I mean, I’ll say something dramatic,
03:35:29 which may not be true.
03:35:33 So I should be careful.
03:35:35 If let’s say we did discover a new living system
03:35:39 but it was made out of a shadow biosphere
03:35:42 and we just released it in the environment,
03:35:44 who cares?
03:35:45 It’s gonna use different stuff.
03:35:48 Yeah, it’ll just live.
03:35:50 Just live, yeah.
03:35:51 I found one of my biggest fantasies
03:35:53 is actually is like a planet
03:35:55 that’s basically half in the sun,
03:35:57 it doesn’t rotate, right?
03:35:59 And you have two different origins of life on that planet
03:36:03 and they don’t share the same chemistry.
03:36:05 Yeah.
03:36:05 And then the only way time they recognize each other
03:36:08 is when they become intelligent, they go,
03:36:09 well, what’s that moving?
03:36:10 Yeah.
03:36:12 So they co evolve and that’s fascinating.
03:36:14 I mean, so one fascinating thing to do
03:36:17 is exactly what you were saying, which is a life bomb,
03:36:20 which is like try to focus on atmospheres
03:36:25 or chemical conditions of other planets
03:36:29 and try within this kind of exploration optimization system
03:36:34 try to discover life forms that can work in those conditions
03:36:40 and then you send those life forms over there
03:36:43 and see what kind of stuff they build up.
03:36:44 Like you can do like a large scale,
03:36:47 it’s kind of a safe physical environment
03:36:50 to do large scale experiments, it’s another planet.
03:36:53 Yeah, so look, I’m gonna say something quite contentious.
03:36:55 I mean, Elon wants to go to Mars,
03:36:57 I think it’s brilliant wants to go to Mars,
03:36:59 but I would counter that and say,
03:37:01 is Elon just obsessed with getting humanity?
03:37:03 Or Earth, or what about just technology?
03:37:06 So if we do technology, so Elon either needs
03:37:09 to take a computer to Mars
03:37:10 because he needs to manufacture drugs on demand,
03:37:12 because zero cost payload and all that stuff is just code.
03:37:16 Or what we do is we actually say, hang on,
03:37:18 it’s quite hard for humans to survive on Mars.
03:37:21 Why don’t we write a series of origin of life algorithms
03:37:24 where we embed our culture in it?
03:37:26 It’s a very Ridley spot Prometheus,
03:37:28 which is a terrible film by the way, but anyway.
03:37:31 And dump it on Mars and just terraform Mars.
03:37:37 And what we do is we evolve life on Mars
03:37:39 that is suited to life on Mars,
03:37:42 rather than brute forcing human life on Mars.
03:37:44 So one of the questions is, what is human culture?
03:37:48 What are the things you encode?
03:37:50 Some of it is knowledge, some of it is information.
03:37:52 But the thing that Elon talks about,
03:37:55 the thing I think about, I think you think about as well
03:37:58 is some of the more unique aspects of what makes us human,
03:38:06 which is our particular kind of consciousness.
03:38:09 So he talks about the flame of human consciousness.
03:38:13 That’s one of the questions is,
03:38:15 can we instill consciousness into other beings?
03:38:22 Because that’s a sad thought that whatever this thing
03:38:26 inside our minds, that hopes and dreams and fears
03:38:30 and loves can all die.
03:38:33 Yeah, but I think you already know
03:38:35 the answer to that question.
03:38:37 I have a robot lawnmower at home.
03:38:40 My kids call it CC, cool car.
03:38:42 It’s a robo mower.
03:38:44 And the way it works, it has an electric field
03:38:47 around the perimeter and it just tell it the area.
03:38:49 And it goes out and goes from its base station,
03:38:52 just mows a bit.
03:38:54 Gets to the perimeter, detects perimeter,
03:38:55 then chooses a random angle, rotates around and goes on.
03:38:58 Yeah.
03:39:00 My kids call it cool cutter.
03:39:02 It’s a she.
03:39:02 I don’t know why it’s a she.
03:39:03 They just, when they were like quite young,
03:39:05 they called it, I don’t want to be sexist there.
03:39:08 It could be a he, but they liked.
03:39:11 They gendered the lawnmower?
03:39:13 They gendered the lawnmower.
03:39:14 Okay.
03:39:14 Yeah, why not?
03:39:15 But I was thinking this lawnmower,
03:39:17 if you apply integrated information theory to lawnmower,
03:39:20 the lawnmower is conscious.
03:39:22 Now, integrated information theory is,
03:39:26 people say it’s a flawed way of measuring consciousness,
03:39:28 but I don’t think it is.
03:39:29 I think assembly theory actually measures consciousness
03:39:32 in the same way.
03:39:33 Consciousness is something that is generated
03:39:35 over a population of objects, of humans.
03:39:38 Consciousness didn’t suddenly spring in.
03:39:40 Our consciousness has evolved together, right?
03:39:43 The fact we’re here and the robots we leave behind,
03:39:45 they will have some of that.
03:39:47 So we won’t lose it all.
03:39:49 Sure, consciousness requires
03:39:50 that we have many models being generated.
03:39:52 It’s not just one domain specific AI, right?
03:39:55 I think the way to create consciousness,
03:39:57 I’m going to say unashamedly,
03:39:58 the best way to make a consciousness is in a chemical system
03:40:02 because you just have access to many more states.
03:40:05 And the problem right now,
03:40:06 we’re making silicon consciousness
03:40:08 because you just don’t have enough states.
03:40:10 So there are more possible states,
03:40:12 or sorry, there are more possible configurations possible
03:40:14 in your brain than there are atoms in the universe.
03:40:17 And you can switch between them.
03:40:20 You can’t do that on a core I10.
03:40:22 It’s got 10 billion, 12 billion, 14 billion transistors,
03:40:25 but you can’t reconfigure them as dynamically.
03:40:28 Well, you’ve shared this intuition a few times already
03:40:31 that the larger number of states
03:40:34 somehow correlates to greater possibility of life,
03:40:38 but it’s also possible the constraints are essential here.
03:40:42 Yeah, yeah.
03:40:43 I mean, but coming back to the,
03:40:45 you worry that something’s lost.
03:40:46 I agree, but I think that we will get to an AGI,
03:40:53 but I wonder if it’s not,
03:40:56 it can’t be separate from human,
03:40:58 it can’t be separate from human consciousness
03:41:00 because the causal chain that produced it came from humans.
03:41:03 So what I kind of try and suggest heavily
03:41:06 to people worry about the existential threat of AI saying,
03:41:11 I mean, you put it much more elegantly earlier,
03:41:13 like we should worry about algorithms on, dumb algorithms
03:41:16 written by human beings on Twitter driving us insane, right?
03:41:21 And doing acting in odd ways.
03:41:23 Yeah, I think intelligence,
03:41:24 this is what I have been in eloquent
03:41:27 in trying to describe it partially
03:41:30 because I try not to think too deeply through this stuff
03:41:34 because then you become a philosopher.
03:41:36 I still aspire to actually building a bunch of stuff.
03:41:40 But my sense is super intelligence leads
03:41:44 to deep integration to human society.
03:41:48 So like intelligence is strongly correlated.
03:41:51 Like intelligence, the way we conceive of intelligence
03:41:56 materializes as a thing that becomes a fun entity
03:42:03 to have at a party and with humans.
03:42:06 So like it’s a mix of wit, intelligence, humor,
03:42:09 like intelligence, like knowledge,
03:42:11 ability to do reasoning and so on,
03:42:14 but also humor, emotional intelligence,
03:42:17 ability to love, to dream, to share those dreams,
03:42:23 to play the game of human civilization,
03:42:28 the push and pull, the whole dance of it,
03:42:30 the whole dance of life.
03:42:31 And I think that kind of super intelligent being
03:42:35 is not the thing that worries me.
03:42:38 I think that ultimately will enrich life.
03:42:41 It’s again, the dumb algorithms,
03:42:43 the dumb algorithms that scale in the hands of people
03:42:46 that are too, don’t study history,
03:42:48 that don’t study human psychology and human nature,
03:42:51 just applying too broadly for selfish near term interests.
03:42:57 That’s the biggest danger.
03:42:58 Yeah, I think it’s not a new danger, right?
03:43:01 I now know how I should use Twitter
03:43:04 and how I shouldn’t use Twitter, right?
03:43:07 I like to provoke people into thinking.
03:43:09 I don’t want to provoke people into outrage.
03:43:11 It’s not fun.
03:43:12 It’s not a good thing for humans to do, right?
03:43:14 And I think that when you get people into outrage,
03:43:16 they take sides and taking sides is really bad.
03:43:20 But I think that we’re all beginning to see this.
03:43:22 And I think that actually I’m very optimistic
03:43:24 about how things will evolve because, you know,
03:43:28 I wonder how much productivity has Twitter
03:43:32 and social media taken out of humanity?
03:43:33 Because how many now, I mean,
03:43:36 so the good thing about Twitter is it gives power,
03:43:38 so it gives voice to minorities, right?
03:43:41 And that’s good to some degree.
03:43:44 But I wonder how much voice does it give
03:43:47 to all sorts of other problems
03:43:52 that don’t need this emerge?
03:43:54 By the way, when you say minorities,
03:43:55 I think, or at least if I were to agree with you,
03:44:00 what I would say is minorities broadly defined
03:44:02 in these small groups of people that it magnifies
03:44:09 the concerns of the small versus the big.
03:44:12 That is good to some degree.
03:44:15 But I think, I mean, I have to be careful
03:44:17 because I think I have a very,
03:44:20 I mean, I think that the world isn’t that broken, right?
03:44:23 I think the world is pretty cool place.
03:44:25 I think academia is really great.
03:44:26 I think climate change presents
03:44:29 a really interesting problem for humanity
03:44:32 that we will solve.
03:44:33 I like how you said it.
03:44:34 It’s a pretty cool problem for civilization.
03:44:37 It’s a big one.
03:44:38 Well, it’s a bunch of it.
03:44:39 There’s a bunch of really, really big problems
03:44:42 that if solved can significantly improve
03:44:45 the quality of life or learn.
03:44:47 That ultimately is what we’re trying to do,
03:44:49 improve how awesome life is
03:44:51 for the maximum number of people.
03:44:53 Yeah, and I think that the coming back to consciousness,
03:44:56 I don’t think the universe is doomed to heat death, right?
03:45:00 It’s one of the optimists.
03:45:01 That’s why I want to kind of nudge you
03:45:03 into thinking that time is fundamental
03:45:04 because if time is fundamental,
03:45:05 then suddenly you don’t have to give it back.
03:45:09 The universe just constructs stuff.
03:45:11 And what we see around us in our construction,
03:45:13 I know everyone’s worried about how fragile civilization is.
03:45:16 And I mean, look at the fundamentals.
03:45:17 We’re good until the sun expands, right?
03:45:22 We’ve got quite a lot of resource on earth.
03:45:23 We’re trying to be quite cooperative.
03:45:25 Humans are nice to each other
03:45:27 when they’re not under enormous stress.
03:45:31 But coming back to the consciousness thing,
03:45:33 are we going to send human beings to Mars
03:45:36 or conscious robots to Mars?
03:45:38 Or are we gonna send some hybrid?
03:45:40 And I don’t know the answer to that question right now.
03:45:43 I guess, you know,
03:45:44 Elon is gonna have a pretty good go at getting there.
03:45:46 I’m not sure whether,
03:45:49 I have my doubts, but I’m not qualified.
03:45:52 I’m sure people have their doubts that computation works,
03:45:56 but I’ve got it working.
03:45:58 And I, you know.
03:45:59 And most of the cool technologies we have today
03:46:03 and take for granted,
03:46:05 like the airplane, a aforementioned airplane,
03:46:08 were things that people doubted.
03:46:11 Like majority of people doubted
03:46:13 before they came to life and they come to life.
03:46:16 And speaking of hybrid AI and humans,
03:46:19 it’s fascinating to think about all the different ways
03:46:21 that hybridization, that merger can happen.
03:46:25 I mean, we have, currently have the smartphone,
03:46:27 so there’s already a hybrid,
03:46:28 but there’s all kinds of ways that hybrid happens.
03:46:31 How we and other technology play together,
03:46:34 like a computer, how that changes
03:46:37 the fabric of human civilization is like wide open.
03:46:40 Who knows?
03:46:41 Who knows?
03:46:42 If you remove,
03:46:46 if you remove cancer,
03:46:47 if you remove major diseases from humanity,
03:46:53 there’s going to be a bunch of consequences
03:46:55 we’re not anticipating.
03:46:57 Many of them positive, but many of them negative.
03:47:01 Many of them, most of them, at least I hope,
03:47:04 are weird and wonderful and fun
03:47:06 in ways that are totally unexpected.
03:47:08 And we sitting on a porch with a bottle of Jack Daniels
03:47:11 and a rocker will say,
03:47:13 kids these days don’t appreciate
03:47:15 how hard we had it back in the day.
03:47:17 I gotta ask you, speaking of nudging,
03:47:21 you and Joscha Bach nudge each other on Twitter quite a bit
03:47:25 in wonderful intellectual debates.
03:47:29 And of course, for people who don’t know Joscha Bach,
03:47:31 he’s this brilliant guy.
03:47:32 He’s been on the podcast a couple times.
03:47:35 You tweeted, or he tweeted,
03:47:38 Joscha Bach, everyone should follow him as well.
03:47:41 You should definitely follow Mr. Lee Cronin, Dr. Lee Cronin.
03:47:44 He tweeted, dinner with Lee Cronin.
03:47:48 We discussed that while we can translate
03:47:50 every working model of existence into a Turing machine,
03:47:54 the structure of the universe might be given
03:47:56 by weeks of nonexistence in a pattern generated
03:47:59 by all possible automata, which exist by default.
03:48:05 And then he followed on saying face to face is the best.
03:48:09 So the dinner was face to face.
03:48:12 What is Joscha talking about in weeks, quote,
03:48:16 weeks of nonexistence in a pattern generated
03:48:19 by all possible automata, which exist by default.
03:48:25 So automata exist by default, apparently.
03:48:29 And then there’s weeks of nonexistence.
03:48:31 What the hell is nonexistence in the universe?
03:48:34 That’s, and also in another conversation,
03:48:39 you tweeted it’s state machines all the way down,
03:48:44 which presumably is the origin story of this discussion.
03:48:47 And then Joscha said, again, nudging, nudging,
03:48:53 nudging slash trolling, Joscha said,
03:48:56 you’ve seen the light, welcome friend.
03:48:59 Many foundational physicists effectively believe
03:49:01 in some form of hyper computation.
03:49:04 Lee is coming around to this idea.
03:49:07 And then you said, I think there are notable differences.
03:49:10 First, I think the universe does not have to be a computer.
03:49:13 Second, I want to understand how the universe emerges,
03:49:16 constructors that build computers.
03:49:18 And third is that there is something below church touring.
03:49:24 Okay, what the heck is this dinner conversation about?
03:49:30 Maybe put another way, maybe zooming out a little bit.
03:49:34 Are there interesting agreements or disagreements
03:49:37 between you and Joscha Bach that can elucidate
03:49:41 some of the other topics we’ve been talking about?
03:49:44 Yeah, so Jascha has an incredible mind
03:49:46 and he has, he’s so well read
03:49:49 and uses language really elegantly.
03:49:53 It bamboozles me at times.
03:49:54 So I’m, so often I’m using, I’m describing concepts
03:49:59 in a way that I built from the ground up.
03:50:03 And so we misunderstand each other a lot.
03:50:05 And he’s floating in the clouds, is that what you’re saying?
03:50:08 Something like, not quite, but I think,
03:50:09 so this concept of a Turing machine.
03:50:11 So a Turing machine, Turing machines, I would argue,
03:50:15 and I think this is not, the Turing machine,
03:50:18 the universe is not a Turing machine.
03:50:21 Biology is not even a Turing machine, right?
03:50:23 And because Turing machines don’t evolve, right?
03:50:25 There is this problem
03:50:27 that people see Turing machines everywhere,
03:50:28 but isn’t it interesting the universe gave rise to biology
03:50:31 that gave rise to intelligence,
03:50:32 that gave rise to Alan Turing,
03:50:34 who invented the abstraction of the Turing machine
03:50:37 and allowed us to digitize.
03:50:39 And so I’ve been looking for the mystery
03:50:43 at the origin of life, the origin of intelligence
03:50:45 and the origin of this.
03:50:46 And I, when I discussed with Yasha,
03:50:48 I think Yasha, he was saying, well, the universe,
03:50:51 of course the universe is a Turing machine.
03:50:53 Of course there’s a hyper computer there.
03:50:56 And I think we got kind of trapped in our words and terms
03:50:59 because of course it’s possible for a Turing machine
03:51:02 or computers to exist in the universe.
03:51:04 We have them.
03:51:05 But what I’m trying to understand is
03:51:07 where did the transition of continuous discrete occur?
03:51:11 And I’ve been, and this is because of my general foolishness
03:51:14 of understanding the continuous.
03:51:19 But I guess what I’m trying to say is
03:51:23 there were constructors before there were abstractors
03:51:26 because how did the universe abstract itself into existence?
03:51:31 And it goes back to earlier saying,
03:51:32 could the universe of intelligence have come first?
03:51:35 What’s a constructor, what’s an abstractor?
03:51:37 So the abstractor is the ability of say,
03:51:40 of Alan Turing and Gödel and Church
03:51:45 to think about the mathematical universe and to label things.
03:51:50 And then from those labels to come up with a set of axioms
03:51:54 with those labels and to basically understand
03:51:57 the universe mathematically and say, okay,
03:51:59 I can label things.
03:52:01 Where did the labeler come from?
03:52:03 Where is the prime labeler?
03:52:04 Even if the universe is not a Turing computer,
03:52:12 does that negate the possibility
03:52:14 that a Turing computer can simulate the universe?
03:52:16 Just because the abstraction was formed at a later time,
03:52:20 does that mean that abstraction,
03:52:22 this is to our cellular automata conversation.
03:52:25 You were taking away some of the magic
03:52:26 from the cellular automata because very intelligent
03:52:29 biological systems came up with that cellular automata.
03:52:32 Well, this is where the existence is the default, right?
03:52:34 Is it, does the fact that we exist
03:52:36 and we can come up with a Turing machine,
03:52:38 does that mean the universe has to be
03:52:40 a Turing machine as well?
03:52:41 But can it be a Turing machine though?
03:52:44 That’s a, so the has to be and the can it be.
03:52:46 Can it be?
03:52:47 Sure.
03:52:50 I don’t know, I don’t understand
03:52:52 if it has to be or not, can it be?
03:52:54 But can the universe have Turing machines in it?
03:52:57 Sure, they exist now.
03:53:01 I’m wondering though, maybe,
03:53:04 and this is where things get really hairy,
03:53:07 is I think the universe maybe in the past
03:53:09 did not have the computational power that it has now.
03:53:17 This is almost like a law of physics kind of,
03:53:21 so the computational power is not,
03:53:24 you can get some free lunch.
03:53:28 Yeah, I mean, the fact that we now,
03:53:30 we sit here in this period in time
03:53:32 and we can imagine all these robots
03:53:33 and all these machines and we built them.
03:53:36 And so we can easily imagine going back in time
03:53:38 that the universe was capable of having them,
03:53:39 but I don’t think it can.
03:53:41 So the universe may have been a lot dumber computationally.
03:53:45 And I think that’s why,
03:53:46 I don’t want to go back to the time discussion,
03:53:48 but I think it has some relationship with it.
03:53:50 The universe is basically smarter now than it used to be
03:53:53 and it’s going to continue getting smarter over time
03:53:57 because of novelty, generation,
03:53:59 and the ability to create objects
03:54:00 within objects within objects.
03:54:02 You know, there’s a, perhaps it’s grounded in physics,
03:54:05 there’s this intuition of conservation.
03:54:07 Yeah. That stuff is conserved.
03:54:09 Like you’re not, you’ve always had all,
03:54:12 everything, you’re just rearranging books
03:54:15 on the bookshelf through time.
03:54:18 So, okay. But you’re saying like
03:54:19 new books are being written.
03:54:21 Which laws do you want to break?
03:54:22 At the origin of the big bang,
03:54:25 you had to break the second law
03:54:27 because we got order for free.
03:54:28 Yeah.
03:54:29 Well, what I’m telling you now
03:54:30 is that the energy isn’t conserved in the universe.
03:54:33 Oh, it’s the second law. Okay. I got you.
03:54:35 So because, but not in a mad way.
03:54:38 Okay. So computation potentially is not conserved,
03:54:44 which is a fascinating idea.
03:54:46 Intelligence is not conserved.
03:54:49 Complexity is not conserved.
03:54:54 I suppose that’s deeply connected
03:54:57 to time being fundamental.
03:55:01 The natural consequence of that
03:55:03 is if time is fundamental
03:55:05 and the universe is inflating in time, if you like,
03:55:09 then there are one or two conservation laws
03:55:11 that we need to have a look at.
03:55:14 And I wonder if that means the total energy
03:55:16 of the universe is actually increasing over time.
03:55:18 And this may be completely ludicrous,
03:55:21 but we do have all this dark energy.
03:55:25 We have some anomalies, let’s say,
03:55:28 dark matter and dark energy.
03:55:29 If we don’t add them in,
03:55:30 galaxies, so dark matter, I think doesn’t hold.
03:55:35 You need to hold the galaxies together
03:55:36 and there’s some other observational issues.
03:55:38 Could dark energy just be time?
03:55:42 So figuring out what dark energy is
03:55:44 might give us some deep clues
03:55:47 about this, not just time, but the consequences of time.
03:55:53 So it could be that, I mean,
03:55:55 I’m not saying there’s perpetual motions allowed
03:55:57 and it’s free lunch, but I’m saying
03:55:59 if the universe is intrinsically asymmetric
03:56:02 and it appears to be, and it’s generating novelty
03:56:07 and it appears to, couldn’t that just be mechanistically
03:56:11 how reality works?
03:56:13 And therefore I don’t really like this idea that the,
03:56:18 so I want to live in a deterministic universe
03:56:21 that is undetermined, right?
03:56:25 The only way I can do that is if time is fundamental.
03:56:28 Because otherwise it’s all the rest of us,
03:56:30 it’s just sleight of hand because the physicists will say,
03:56:33 yes, everything’s deterministic.
03:56:35 Newtonian mechanics is deterministic.
03:56:38 Quantum mechanics is deterministic.
03:56:40 Let’s take the Everettian view.
03:56:42 And then basically we can just draw out
03:56:44 this massive universe branching, but it closes again
03:56:46 and we get it all back.
03:56:48 And don’t worry, your feeling of free will is effective.
03:56:51 But what the physicists are actually saying
03:56:53 is the entire future is mapped out.
03:56:55 And that is clearly problematical.
03:57:00 And clearly.
03:57:03 That’s not so clear.
03:57:05 Yeah.
03:57:05 It’s just problematic.
03:57:07 Well, yeah, yeah, so it’s.
03:57:10 Because that maybe is just the way it is.
03:57:12 It’s problematic to you, a particular creature
03:57:14 along this timeline.
03:57:15 I want to reduce the number of beliefs
03:57:16 I need to understand the universe.
03:57:18 So if time is fundamental, I don’t need
03:57:21 to have magic order at the beginning,
03:57:24 and I don’t need a second law.
03:57:25 But you do need the magical belief
03:57:27 that time is fundamental.
03:57:28 Well, I need the observation that I’m seeing
03:57:32 to be just how it is all the way down.
03:57:34 But the Earth also looks flat
03:57:37 if you agree with your observation.
03:57:40 So we can’t necessarily trust our observation.
03:57:43 I know the Earth isn’t flat
03:57:44 because I can send a satellite into space.
03:57:46 No, but now you see, now you’re using the tools
03:57:49 of science and the technology of science.
03:57:51 But I’m saying I’m going to do experiments
03:57:53 that start to show.
03:57:55 I mean, I think that it’s worth.
03:57:57 So if you can’t, so if I cannot do an experiment
03:58:01 or a thought experiment that will test this assumption,
03:58:04 then the assumption is without merit really in the end.
03:58:07 You know, that’s fine.
03:58:09 Yeah.
03:58:10 That’s a beautiful ideal you hold yourself to.
03:58:12 That’s given that you think deeply in a philosophical way,
03:58:18 you think about some of these really important issues
03:58:21 and you have theoretical frameworks like assembly theory.
03:58:27 It’s really nice that you’re always grounded
03:58:29 with experiment.
03:58:31 That’s all I have.
03:58:32 That’s so refreshing.
03:58:33 That’s so beautifully refreshing.
03:58:35 Now that we’re holding you to the grounded
03:58:39 in an experiment to the harsh truth of reality,
03:58:42 let me ask the big ridiculous question.
03:58:45 What is the meaning of this whole thing?
03:58:47 What’s the meaning of life?
03:58:48 Why?
03:58:49 This time is fundamental.
03:58:52 It’s marching forward.
03:58:54 And along this long timeline come along a bunch
03:58:58 of descendants of apes that have come up
03:59:03 with cellular automata and computers and now computers.
03:59:07 Why?
03:59:09 I have so many different answers to this question.
03:59:11 It depends on what day.
03:59:13 I would say that given the way of the conversation
03:59:16 we had today, I’d say the meaning,
03:59:18 well, we make our own meaning.
03:59:19 I think that’s fine.
03:59:20 But I think the universe wants to explore
03:59:24 every possible configuration that it’s allowed us
03:59:27 to explore.
03:59:28 And this goes back to the kind of question
03:59:30 that you were asking about Yasha and the existence
03:59:33 and non existence of things, right?
03:59:35 So if the universe is a Turing machine is churning
03:59:37 through a lot of states and you think about
03:59:41 combinatorial theory before assembly theory,
03:59:43 so everything is possible.
03:59:45 What Yasha and I were saying is, well,
03:59:48 not everything is possible.
03:59:49 We don’t see the combinatorial explosion.
03:59:52 We see something else.
03:59:53 And what we see is evidence of memory.
03:59:57 So there clearly seems to be some interference
04:00:00 between the combinatorial explosion of things
04:00:04 and what the universe allows.
04:00:06 And it’s like this kind of constructive,
04:00:08 destructive interference.
04:00:10 So maybe the universe is not just about,
04:00:14 it is assembling objects in space and time.
04:00:18 And those objects are able to search more space and time.
04:00:22 And the universe is just infinitely creative.
04:00:24 And I guess I’m searching for why the universe
04:00:27 is infinitely creative.
04:00:28 It is infinitely creative.
04:00:29 And maybe the meaning is just simply to make
04:00:31 as many objects, create as many things as possible.
04:00:34 And I see a future of the universe that doesn’t result
04:00:37 in the heat death of the universe.
04:00:38 The universe is gonna extract every ounce
04:00:41 of creativity it can out of it,
04:00:43 because that’s what we see on Earth, right?
04:00:45 And if you think that almost like intelligence
04:00:49 is not conserved, that maybe creativity isn’t either.
04:00:52 Maybe like it’s an infinite well.
04:00:56 So like creativity is ultimately tied to novelty.
04:01:00 You’re coming up with cool new configurations of things,
04:01:03 and maybe that just can continue indefinitely.
04:01:06 And this human species that was created along the way
04:01:09 is probably just one method,
04:01:13 like that’s able to ask the universe about itself.
04:01:16 It’s just one way to explore creativity.
04:01:19 Maybe there’s other meta levels on top of that.
04:01:22 Like obviously, as a collective intelligence
04:01:24 will create organisms, maybe there’ll be organisms
04:01:27 that ask themselves questions about themselves
04:01:33 in a deeper, bigger picture way than we humans do.
04:01:38 First to ask questions about the humans,
04:01:39 and then construct some kind of hybrid systems
04:01:42 that ask themselves about the collective aspect.
04:01:45 Just like some weird stacking
04:01:47 that we can’t even imagine yet.
04:01:49 And that stacking, I mean, I have discussed this stacking
04:01:51 a lot with Sarah Walker, who’s a professor of physics
04:01:54 and astrobiology at ASU.
04:01:57 And we argue about how creative the universe is gonna be,
04:02:02 and is it as deterministic as all that?
04:02:03 Because I think she’s more of a free will thinker,
04:02:07 and I’m of a less free will thinker,
04:02:10 but I think we’re beginning to converge
04:02:12 and understanding that.
04:02:13 Because there’s simply a missing understanding.
04:02:15 Right now, we don’t understand how the universe,
04:02:19 we don’t know what rules the universe has
04:02:21 to allow the universe to contemplate itself.
04:02:23 So asking the meaning of it
04:02:25 before we even know what those rules are
04:02:27 is premature, but my guess is that it’s not meaningless,
04:02:30 and it isn’t just about that.
04:02:32 And there are three levels of meanings.
04:02:33 Obviously, the universe wants us to do stuff.
04:02:35 We’re interacting with each other,
04:02:36 so we create meaning in our own society
04:02:38 and our own interactions with humanity.
04:02:41 But I do think there is something else going on.
04:02:44 But because reality is so weird,
04:02:47 we’re just scratching at that.
04:02:49 And I think that we have to make the experiments better.
04:02:52 And we have to perhaps join across,
04:02:56 not just for the computation lists.
04:02:58 And what I tried to do with Yashua is meet him halfway,
04:03:01 say, well, what happens if I become a computation list?
04:03:03 What do I gain?
04:03:04 A lot, it turns out,
04:03:05 because I can make Turing machines in the universe.
04:03:08 Because on the one hand, I’m making computers
04:03:09 which are state machines inspired by Turing.
04:03:12 On the other hand, I’m saying they can’t exist.
04:03:14 Well, clearly, I can’t have my cake and eat it,
04:03:16 so there’s something weird going on there.
04:03:18 So then, did the universe have to make a continuous
04:03:21 to a discrete transition, or is the universe just discrete?
04:03:23 It’s probably just discrete.
04:03:25 So if it’s just discrete, then there are,
04:03:27 I will then give Yashua his Turing like property
04:03:31 in the universe.
04:03:32 But maybe there’s something else below it,
04:03:33 which is the constructor that constructs a Turing machine
04:03:36 that then constructs, you know,
04:03:38 it’s a bit like you generate a computing system
04:03:42 that then is able to build an abstraction
04:03:44 that then recognizes it can make a generalizable abstraction
04:03:48 because human beings with mathematics
04:03:50 have been able to go on and build physical computers.
04:03:55 If that makes any sense.
04:03:57 And I think that’s the meaning.
04:03:58 I think that’s, you know, as far as we can,
04:04:00 the meaning will be further elucidated
04:04:02 with further experiments.
04:04:06 Well, you mentioned Sarah.
04:04:08 I think you and Sarah Walker
04:04:11 are just these fascinating human beings.
04:04:14 I’m really fortunate to have the opportunity
04:04:18 to be in your presence, to study your work,
04:04:20 to follow along with your work.
04:04:21 I’m a big fan.
04:04:23 Like I told you offline,
04:04:25 I hope we get a chance to talk again
04:04:27 with perhaps just the two of us,
04:04:29 but also with Sarah.
04:04:30 That’s a fascinating dynamic for people who haven’t heard.
04:04:35 I suppose on Clubhouse is where I heard you guys talk,
04:04:38 but you have an incredible dynamic.
04:04:39 And I also can’t wait to hear you and Yashua talk.
04:04:43 So I think if there’s some point in this predetermined
04:04:48 or yet to be determined future where the three of us,
04:04:54 you and Sarah, or the four of us with Yashua
04:04:56 could meet and talk would be a beautiful future.
04:04:59 And I look forward to most futures,
04:05:02 but I look forward to that one in particular.
04:05:04 Lee, thank you so much
04:05:06 for spending your valuable time with me today.
04:05:08 Thanks, Lex.
04:05:09 It’s been a pleasure.
04:05:10 Thanks for listening to this conversation with Lee Cronin.
04:05:13 To support this podcast,
04:05:15 please check out our sponsors in the description.
04:05:18 And now let me leave you with some words
04:05:20 from the math scientist, Rick Sanchez
04:05:22 of Rick and Morty fame.
04:05:25 To live is to risk it all.
04:05:28 Otherwise you’re just an inert chunk
04:05:31 of randomly assembled molecules
04:05:34 drifting wherever the universe blows you.
04:05:36 Thank you for listening and hope to see you next time.