Lex Fridman Podcast - #404 – Lee Cronin: Controversial Nature Paper on Evolution of Life and Universe

Starting point is 00:00:00 The following is a conversation with Lee Cronin. It's third time in this podcast. He is a chemist from University of Glasgow, who is one of the most fascinating, brilliant, and fun to talk to scientists have ever had the pleasure of getting to know. And now, a quick few second mention of each sponsor. Check them out in the description.

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Starting point is 00:09:18 And now, dear friends, here's Lee Cronin. So your big assembly theory paper was published in Nature. Congratulations. Thanks. It created, I think it's fair to say a lot of controversy, but also a lot of interesting discussion. So maybe I can try to summarize assembly theory and you tell me if I'm wrong. I forgot.

Starting point is 00:09:55 So assembly theory says that if we look at any object in the universe, any object, that we can quantify how complex it is by trying to find the number of steps it took to create it. And also, we can determine if it was built by a process akin to evolution by looking at how many copies of the object there are. Yeah, that's spot on. Yeah, spot on. That was not expecting that. Okay. So let's go through definitions. So there's a central equation that I'd love to talk about, but definition wise, what is an object? Yeah, an object. So if I'm going to try to be as meticulous as possible, objects need to be finite, and they need to be decomposable into subunits. All human-made artifacts are

Starting point is 00:10:49 objects. Is a planet an object? Probably yes, if you scale out. So an object is finite and countable and decomposable, I suppose mathematically. But yeah, I still wake up some days and go to think to myself, what is an object? Because it's a non-trivial question. Persists over time, I'm quoting from the paper here, an object that's finite is distinguishable. I'm sure that's a weird adjective distinguishable. We've had so many people help offering to rewrite the paper after it came out. You wouldn't believe it's so funny. Persist over time and is breakable such that the set of constraints to

Starting point is 00:11:35 construct it from elementary building blocks is quantifiable. Such that the set of constraints to construct it from elementary building blocks is quantifiable. The history is in the objects. It's kind of cool, right? So, okay, so what defines the object is its history or memory, which covers the sexier word. I'm happy with both, depending on the day. Okay. So, the set of steps that took to create the object, so there's a sense in which every object in the universe has a history. And that is part of the thing that is used to describe its complexity, how complicated it is. Okay. What is an assembly index?

Starting point is 00:12:22 So the assembly index, if you take the object apart and be super lazy about it or minimal, say what it, because it's like you've got a really short term memory. So what you do is you lay all the parts on the path and you find the minimum number of steps you take on the path to add the parts together to reproduce the object, and that minimum number is the assembly index. It's a minimum bound. It was always my intuition, the minimum bound in assembly theory was really important. I only worked out why a few weeks ago, which is kind of funny, because I was just like, no, this is sacrosanct. I don't know why. It will come to me one day, and then when I was pushed by a bunch of mathematicians, we came up with the correct physical explanation

Starting point is 00:13:08 which I can get to, but it's the minimum, and it's really important as the minimum. And the reason I knew the minimum was right is because we could measure it. So almost before this paper came out, we've published papers explain how you can measure the assembly index of molecules. Okay, so that's not so trivial to figure out. So when you look at an object, we can say molecule, we can say object more generally, to figure out the minimum number of steps

Starting point is 00:13:33 that takes to create that object. That doesn't seem like a trivial thing to do. So with molecules, it's not trivial, but it is possible because what you can do, and because I'm a chemist, so I'm kind of like I see the lens of the world for just chemistry. I break the molecule part and break bonds. And if you break up, if you take a molecule and you break it all apart, you have a bunch of atoms, and then you say, okay, I'm going to then form, take the atoms and form bonds

Starting point is 00:14:04 and go up the chain of events to make the molecule. And that's what made me realize, take a toy example, literally toy example, take a Lego object, which is broken up of Lego blocks. So you could do exactly the same thing. In this case, the Lego blocks are naturally the smallest, they're the atoms in the actual composite Lego architecture. But then if you maybe take a couple of blocks and put them together in a certain way, maybe they're offset in some way, that offset is on the memory.

Starting point is 00:14:36 You can use that offset again with only a penalty of one and you can then make a square triangle and keep going. And you remember those motifs on the chain. So you can then leap from the start with all the Lego blocks or atoms just laid out in front of you and say, right, I'll take you, you connect and do the least amount of work. So it's really like the smallest steps you can take on the graph to make the object. And so for molecules it came relatively intuitively and then we started to apply it to language. We've even started to apply it to you can take on the graph to make the object. And so for molecules, it came relatively intuitively.

Starting point is 00:15:05 And then we started to apply it to language. We've even started to apply it to mathematical theorems. But I'm so out of my depth, but it looks like you can take minimum set of axioms and then start to build up kind of mathematical architectures in the same way. And then the shortest path to get there is something interesting that I don't yet understand.

Starting point is 00:15:23 So what's the computational complexity of figuring out the shortest path to get there is something interesting that I don't yet understand. So what's the computational complexity of figuring out the shortest path? And with molecules, with language, with mathematical theorems, it seems that once you have the fully constructed Lego castle or whatever your favorite Lego world is figuring out how to get there from the basic building blocks. Isn't it like a, is that an empty heart problem? It's a hard problem, but actually if you look at it, so the best way to look at it for this take a molecule. So if the molecule has 13 bonds, first of all, take 13 copies of the molecule and just cut all the bonds, so take cut 12 bonds, and then you just put them in order.

Starting point is 00:16:04 And then that's how it works. So, and you keep looking for symmetry or copies, so you can then shorten it as you go down, and that becomes combinatorially quite hard. For some natural product molecules, it comes very hard, it's not impossible, but we're looking at the bounds on that at the moment. But as the object gets bigger, it becomes really hard. And, but that's the bad news, but the good news is there are shortcuts. And we might even be able to physically measure the complexity without computationally calculating it, which is kind of insane. Where would you do that? Well, in the case of molecule, so if you shine light on a molecule,

Starting point is 00:16:46 let's take an infrared, the molecule has each of the bonds absorbs the infrared differently in what we call the fingerprint region. And so it's a bit like, because it's quantized as well, you have all these discrete kind of absorbences. And my intuition after we realized we could cut molecules up in mass spec, that was the first go at this. We did it with using infrared and the infrared gave an even better correlation, assembly index and we used another technique as well. In addition to infrared called NMR, nuclear magnetic resonance, which tells you about the number of different magnetic environments in the molecule. And that also worked out. So we have three techniques, which each of them independently gives us the same or tending towards the same assembly index from molecule that we can calculate mathematically.

Starting point is 00:17:34 Okay. So these are all methods of mass spectrometry, mass spec, you scan a molecule, it gives you data in the form of a mass spectrum. And you're saying that the data correlates to the assembly index. Yeah. How generalizable is that short cut? First of all, to chemistry. It's not going to be on that. Because that seems like a nice hack. And you're extremely knowledgeable about various aspects of chemistry. So you can say, okay, it kind of correlates. But, you know, the whole idea behind a suddenly theory paper and perhaps why it's so controversial is

Starting point is 00:18:11 that it reaches bigger. It reaches for the bigger general theory of objects in the universe. Yeah, I'd say so. I'd agree. So I've started assembly theory of emoticons with my lab, believe it or not, so take emojis, pixelate them, and work out the assembly index of emoji. And then work out how many emojis you can make on the path of emoji. So there's the uber emoji from which all other emoji emojis emerge. And then you can, so you can then take a photograph and by looking at the shortest path on, or by reproducing the pixels to make the image you want, you can measure that. So then you start to be able to take spatial data. Now there's some problems there. What is then the definition of the object? How many pixels? How do you break it down? And so we're just learning all this right now. So how do you compute the, how would you begin to compute the assembly index of Graphical like a set of pixels on a 2d plane that form a thing? So you would first of all determine the resolution. So then how, how is your xy and what the number on the x and y plane?

Starting point is 00:19:24 And then look at the surface area and then you take all your emojis and make sure they're all looked at the same resolution. Yes. And then we were basically then do the exactly the same thing we would do for cutting the bonds you'd cut bits out of the emoji on and look at the you have a bag of pixels and you would then add those pixels together to make the overall emoji. Well, first of all, not every pixel, I mean, this is at the core sort of machine learning and computer vision. Not every pixel is that important and there's like macro features, there's micro features and all that kind of stuff. Exactly.

Starting point is 00:20:03 Like, the eyes appear in a lot of them. The smile appears in a lot of them. So in the same way in chemistry, we assume the bond is fundamental. What we do in there here is we assume the resolution at the scale that we should do it is fundamental. And we're just working that out and that you're right, that will change, right? Because as you take your lens out a bit, it will change dramatically. But it's just a new way of looking at not just compression,

Starting point is 00:20:28 what we do right now in computer science and data. One big kind of misunderstanding as assembly theory is telling you about how compressed the object is. That's not right. It's say how much information is required on a chain of events because the nice thing is if in when you do compression and computer science, we're wandering a bit here, but it's kind of worth wondering, I think. And you you assume you have instantaneous access to all the information in the memory. Yeah.

Starting point is 00:20:59 Assembly theory, you say, no, you don't get access to that memory until you've done the work. And then you don't access that memory, you can have access, but not to the next one. And this is how in assembly theory, we talk about the four universes, the assembly universe, the assembly possible, and the assembly contingent, and then the assembly observed. And they're all, all scales in this combinatorial universe. Yeah. Can you explain each one of them? Yep. So the assembly universe is like anything goes just is just combinatorial kind of explosion in everything. That's the biggest one. That's the biggest one's massive. Assembly universe, assembly possible, assembly contingent,

Starting point is 00:21:35 assembly observed. And on the y-axis is assembly steps in time. Yeah. And, you know. And the x-axis as the thing expands through time, more and more unique objects appear. So, yeah, so assembly universe, everything goes. Yep. Assembly possible, laws of physics come in, in this case in chemistry bonds. In assembly, so that means... Those are actually constraints, I guess. Yes, and they're the only constraints. They're the constraints of the base. So the way to look at it, you've got all your atoms, their conties, you can just bung them together. So then you can become a kind of.

Starting point is 00:22:11 So in the way in computer science, I suppose the assembly universe is just like no laws of physics. Things can fly through mountains beyond the speed of light. In the assembly possible, you have to apply the laws of physics, but you can get access to all the motifs instantaneously with no effort. That means you could make anything. Then the assembly contingent says, no,

Starting point is 00:22:34 you can't have access to the highly assembled object in the future until you've done the work in the past on the causal chain. And that's really the really interesting shift where you go from assembly possible to assembly contingent. That is really the key thing in assembly theory that says you cannot just have instantaneous access to all those memories. You have to have done the work somehow. The universe has to somehow built a system

Starting point is 00:23:03 that allows you to select that path rather than other paths. And then the final thing, the assembly observed is basically saying, oh, these are the things we actually see. We can go backwards now and understand that they have been created by this causal process. Wait a minute. So when you say the universe has to construct a system that does the work, is that like the environment that allows for selection? Yeah. The best thing that does the selection. You could think about in terms of a von Neumann constructor, first of all, selection

Starting point is 00:23:36 of ribosome, Tesla assembling testlers. You know, the difference between the assembly universe in Tesla land and the the test of factory is Everyone says no testers are just easy. They just spring out. You know how I make them all the test of factory You have to put things in sequence and outcomes of Tesla. So you talk about the factory. Yes. This is this is really nice Super important point is that when I talk about the universe having a memory or there's some magic. It's not that. It's that the universe having a memory or there's some magic, it's not that, it's that tells you that there must be a process encoded somewhere in physical reality, be it a cell, a Tesla factory, or something else that is making that object. I'm not saying there's some kind of woo, woo memory in the universe, you know, morphic resonance or something. I'm saying

Starting point is 00:24:22 that there is an actual causal process that is being directed constrained in some way. So it's not kind of just making everything. Yeah, but Lee, what's the factory they made the factory? So what is the, so first of all, you assume the laws of physics is just sprung to the existence at the beginning. Those are constraints. But what makes the factory the environment that does its election? This is the question or... Well, it's the first interesting question that I want to answer. Out of four, I think the factory emerges in the interplay between the environment and the objects that are being built. And here, let me, I'll have a go at explaining to you the shortest path. So why is the

Starting point is 00:25:10 shortest path important? Imagine you've got, I'm going to have to go chemistry for a moment and abstract it. So imagine you've got an environment, a given environment that you have a budget of atoms, you're just flinging together. Yep. And the objective of those atoms that are being flung together and say molecule A, they decompose. So molecules decompose over time. So the molecules in this environment, in this magic environment, have to not die, but

Starting point is 00:25:43 they do die. There's a half life. So the only way the molecules can get through that environment out the other side, that's to pretend the environment is a box, you can go in and out without dying. And there's a, there's just an infinite supply of atoms coming or a, well, a large supply. The, the molecule gets built, but the molecule that is able to template itself being built gets built, but the molecule that is able to template itself being built and survives in the environment will basically range supreme. Now, let's say that that molecule takes 10 steps. Now, and it's using finite set of atoms, right? Or now let's say another molecule,

Starting point is 00:26:21 smart-ass molecule, we'll call it comes in. And can survive in that environment and can copy itself, but it only needs five steps. The molecule that only needs five steps, because both molecules have been destroyed, but they're creating themselves faster they can be destroyed. You can see that the shortest path reigns supreme. So the shortest path tells us something super interesting about the minimal

Starting point is 00:26:46 amount of information required to propagate that motif in time and space. And it's just like a kind of, it seems to be like some kind of conservation law. So one of the intuitions you have is the propagation of motifs in time will be done by the things that can construct themselves in this shortest path. So like, you can assume that most of the objects in the universe are built in the shortest, in the most efficient way. So big leap I just took there. Yeah, no, yes and no, because there are other things. So in the limit, yes, because you want to tell the difference between things that have required a factory to build them and just random processes. But you can find instances where the shortest path isn't taken for an individual object,

Starting point is 00:27:39 an individual function. And people go, ah, that means a short path isn't right. And then I say, well, I don't know. I think it's right still because, so, of course, because there are other driving forces, it's not just one molecule. Now, when you start to, now you start to consider two objects, you have a joint assembly space. And it's not, now it's a compromise between not just making A and B in the shortest path. You want to make A and B in the shortest path, which might mean that A is slightly longer. You have a compromise. So when you see slightly more nesting in the construction,

Starting point is 00:28:16 when you take a given object, that can look longer, but that's because the overall function is the object is still trying to be efficient. Yeah. And this is still very hand-wavy, and maybe I have no legs to stand on, but we think we're getting somewhere with that. And there's probably some parallelization. Yeah, right. So this is all, this is not sequential. The building is, I guess, when you're talking about complex objects,

Starting point is 00:28:42 you don't have to work sequentially. You can work in parallel. You can get your friends together. Yeah. And the thing we're working on right now is how to understand these parallel processes. Now there's a new thing we've introduced called assembly depth.

Starting point is 00:28:58 And assembly depth can be lower than the assembly index for a molecule when they're cooperating together because exactly this parallel processing is going on. And my team have been working this out in the last few weeks because we're looking at what compromises does nature need to make when it's making molecules in the cell? And I wonder if, you know, I may be like,

Starting point is 00:29:22 well, I'm always leaping out of my complex. But in economics, I'm just wondering if you could apply this in economic process. It seems like capitalism is very good at finding shortest path, you know, every time. And there are ludicrous things that happen because actually the cost function has been minimized. And so I keep seeing parallels everywhere where there are complex nested systems, where if you give it enough time and you introduce a bit of heterogeneity, the system readjusts and finds a new shortest path, but the shortest path isn't fixed on just one molecule now, it's in the actual existence of the object over

Starting point is 00:29:56 time, and that object could be a city, it could be a cell, it could be a factory, but I think we're going way beyond molecules and my competence to probably should go back to molecules, but hey All right before we get too far. Let's talk about the assembly equation Okay, how should we do this now? Let me just even read that part of the paper We define assembly as the total amount of selection necessary to produce an ensemble of observed objects Quantified using equation one. The equation basically has A on one side, which is the assembly of the ensemble. And then a sum from one to N, where N is the total number of unique objects.

Starting point is 00:30:42 And then there is a few variables in there that include the assembly index, the copy number, which we'll talk about. That's an interesting, I don't remember you talking about that. That's an interesting addition and a thing of powerful one has to do with what that you can create pretty complex objects randomly. And in order to know that they're not random, that there's a factory involved, you need to see a bunch of them. That's the intuition there. It's an interesting intuition. And then some normalization. What else is it? And- In minus one, just to make sure that I'm more than one object, one object could be a one-off

Starting point is 00:31:20 and random. And then you have more than one identical object. That's interesting. When there's two over thing. Two other thing is super important, especially if the index assembly index is high. So we could say several questions here. Why let's talk about selection? What is this term selection? What is this term evolution that we're referring to? Which aspect of Darwinian evolution that we're referring to, that's interesting here. So, yeah, so this is probably what you know, the paper, we should talk about the paper, second the paper, what it did is it kind of annoyed, we didn't know it. I mean, it got intention and obviously angry people, the angry people were annoyed.

Starting point is 00:32:01 There's angry people in the world, that's good. So what happened is the evolutionary biologist got angry. We were not expecting that because we thought evolutionary biologists would be cool. I knew that some, not many, computational, complexity people will get angry because I've kind of been poking them and maybe I deserved it. But I was trying to poke them in a productive way. And then the physicist kind of got grumpy because the initial conditions tell everything. The pre-bottied chemist got slightly grumpy because there's not enough chemistry in there.

Starting point is 00:32:30 And then finally when the creationist said it wasn't creationist enough, I was like, I've done my job. The physics, you see, the physics they say, because you're basically saying that physics is not enough to tell the story of how biology emerges. I think so, kind of. And then they said, a few physics is the beginning in the end of the story. Yeah. So what happened is a reason why people put the phone down

Starting point is 00:32:54 on the call of the paper, if you view the reading the paper like a phone call, they got to the abstract. And in the abstract, it's for sentences, pretty strong. The first two sentences caused everybody. Scientists have grappled with reconciling biological evolution with the immutable laws of the universe defined by physics. True, right?

Starting point is 00:33:13 There's nothing wrong with that statement, totally true. Yeah. These laws underpin life's origin, evolution and the development of human culture and technology, yet they do not predict the emergence of these phenomena. Wow. First of all, we should say the title of the paper. This paper was accepted and published in Nature. The title is assembly theory explains and quantifies selection and evolution, very humble title. And the entirety of the paper, I think,

Starting point is 00:33:48 And the entirety of the paper I think presents interesting ideas but reaches high. I am not. I would do it all again. This paper was actually on the pre-print server for over a year. You regret nothing. Yeah, I think, yeah, I don't regret anything. You and Frank Sinatra did it your way. What I love about being a scientist is kind of sometimes I'm because I'm a bit dim, I'm like, and I don't understand what people tell me, I want to get to the point. This paper says,

Starting point is 00:34:10 hey, laws of physics are really cool, the universe is great, but they don't really, it's not intuitive that you just run the standard model and get life out. I think most physicists might go, yeah, there's this, you know, it's not just we can't just go back and say that's what happened because physics can't explain the origin of life yet. There's a, doesn't mean it won't or can't okay? Just to be clear, sorry intelligent designers, we are going to get there. Second point, we say that evolution works, but we don't know how evolution got going, so biological evolution and biological selection. So for me this seems like a simple continuum. So when I mentioned selection and evolution in the title, I think, and in the Amstrat,

Starting point is 00:34:55 we should have maybe prefaced that and said non-biological selection and non-biological evolution. And then that might have made it even more crystal clear, but I didn't think that biology, evolutionary biology, should be so bold to claim ownership of selection and evolution. And secondly, a lot of evolutionary biologists seem to dismiss the origin of life questions, I say it's obvious. And that causes a real problem scientifically, because when two different, when the physicists are like, we own the universe, universe is good, we explain all of it, look at us. And the biologists say we can explain biology. And the poor chemistry in the middle, go, but hang on.

Starting point is 00:35:32 And this paper kind of says, hey, there is an interesting disconnect between physics and biology. And that's at the point in which memories get made in chemistry through bonds, and hey, let's look at this closely if we can quantify it. So, yeah, I mean, I never expected the paper to kind of get that much interest. And still, I mean, it's only been published just over a month ago now.

Starting point is 00:35:59 It's just the link on the selection. What is the broader sense of what selection means? Yeah, that's really good. For selection, selection, so I think for selection, unique, so this is where for me, the concept of an object is something that can persist in time and not die, but basically can be broken up. So if I was going to kind of bolster the definition of an object. So if something can form and persist for a long period of time, under an existing environment that could destroy other, and I'm going to use Amphropomorphic terms,

Starting point is 00:36:44 I apologize, that weaker objects, or less robust, then the environment could have selected that. So good chemistry examples, if you took some carbon and you made a chain of carbon atoms, whereas if you took some, I don't know, some carbon nitrogen and oxygen and made change from those, you start to get different reactions and rearrangements. So a chain of carbon atoms might be more resistant to falling apart under acidic or basic conditions versus another set of molecules.

Starting point is 00:37:19 So it survives in that environment. So the acid pond, the molecule, the resistant molecule can get through. And, and then, then that molecule goes into another environment. So that my environment now may be being an acid pond is a basic pond, or maybe it's an oxidizing pond. And so if you've got carbon, and it goes an oxidizing pond, maybe the carbon starts to oxidize and break apart. So you go through all these kind of obstacle courses, if you like, given by reality. So selection is the ability for happens when an object survives in an environment for some time. But, and this is the thing that's

Starting point is 00:37:56 super subtle, the object has to be continually being destroyed and made by process. So it's not just about the process, the object now's about the process and time that makes it. Because a rock could just stand on the mountain side for four billion years and nothing happened to it. And that's not necessarily really advanced selection. So for selection to get really interesting, you need to have a turn over in time. You need to be continually creating objects, producing them, what we call discovery time. So there's a discovery time for an object. When that object is discovered, if it's a molecule that can then act on itself, or the chain of events that cause itself

Starting point is 00:38:36 to bolster its formation, then you go from discovery time to production time, and suddenly you have more of it in the universe. so it could be a self-replicating molecule. And the interaction of the molecule in the environment in the warm little pond or in the sea or wherever in the bubble could then start to build a proto-factory, the environment. So really to answer your question, what the factory is, the factory is the environment, but it's not very autonomous, it's not very redundant, there's lots of things that could go wrong. So once you get high enough up the hierarchy of networks of interactions, something needs to happen. That needs to be compressed into a small of volume and made resistant robust. Because in biology, selection and evolution is robust.

Starting point is 00:39:22 That you have error correction built in. You have you have really you know that there's good ways of basically making sure propagation goes on to really the difference between in organic a biotic selection evolution and evolution and stuff in biology is robustness. to propagate over the ability to survive in lots of different environments, whereas our poor little and organic soul molecule, whatever, just dies in lots of different environments. So there's something super special that happens from the inorganic molecule in the environment that kills it to where you've got evolution and cells can survive everywhere. How special is that? How do you know those kinds of evolution factors are everywhere in the universe? I don't and I'm excited because I think selection isn't special at all. I think what is special is the history of the environments on Earth that gave rise to the first cell that now has taken all those environments and is now more autonomous. And I would like to think that this paper could be very wrong.

Starting point is 00:40:42 But I don't think it's very wrong. It means certainly wrong, but it's less wrong than some other ideas, I know, right? And if this allows, inspires us to go and look for selection in the universe, because we now have an equation where we can say, we can look for selection going on and say, oh, that's interesting. We seem to have a process that's giving us high copy number objects, also a highly complex, but that doesn't look like life as we know it. And we use that. So there's a hydrophermal vent, all there's a process going on, there's molecular networks, because the assembly equation is not only meant

Starting point is 00:41:17 to identify at the higher end, advanced selection, what you get, I record in biology, you super advanced selection. And even, I mean, you could use your assembly equation to look for technology and go for a bid we could talk about consciousness and abstraction, but let's keep it primitive, molecules and biology. So I think the real power of the assembly equation is to say how much selection is going on in this space. And there's a really a really simple for experiment I could do is you, you know, have a little petri dish and on that petri dish you put some simple food.

Starting point is 00:41:50 So the assembly index of all the sugars and everything is quite low. So then and you put a single cell of Ecoli cell. And then you say, I'm gonna measure the assembly and this amount of assembly in the box. So it's quite low, but the rate of change of assembly in the box. So it's quite low, but the

Starting point is 00:42:06 rate of change of assembly, DADT, will go, VUM, SICK, MOIDL, as it eats all the food, and the number of coli cells will replicate, because they take all the food, they can copy themselves, the assembly index of all the molecules goes up, up, up, and up, until the food is exhausted in the box. So now the colcoli's stop, I mean, die is probably a strong word, they stop respiring because all the food is gone, but suddenly the amount of assembly in the box has gone up gigantically because of that one Ecoli factory

Starting point is 00:42:37 has just eaten fruit, milled lots of other Ecoli factories run out of food and stopped. And so that looking at that, so in the initial box, although the amount of assembly was really small, it was able to replicate and use all the food and go up. And that's what we're trying to do in the lab actually is kind of make those kind of experiments and see if we can spot the emergence of molecular networks that are producing complexity as we feed in raw materials and we feed a challenge and environment,

Starting point is 00:43:07 you know, we try and kill the molecules. And really that's the main kind of idea for the entire paper. Yeah, and see if you can measure the changes in the assembly index throughout the whole system. Okay, what about if I show up to a new planet, we'll go to Mars or some other planet from a different solar system. And how do we use a somebody index there to discover alien life? In very simply, actually, if we, let's say we'll go to Mars with a mass spectrometer with a sufficiently high resolution. So what you have to be able to do, so good thing about mass spec is that you can select the molecule from the mass, and then if it's high enough resolution, you can be more and more sure that you're just

Starting point is 00:43:52 seeing identical copies, you can count them, and then you fragment them and you count the number of fragments and look at the molecular weight, and the higher the molecular weight and the higher the number of fragments, the hire the assembly index. So if you go to Mars and you take a mass spec or hire enough resolution and you can find molecules and I'll give you guide on earth if you could find molecules say greater than 350 molecular weight or more than 15 fragments. You have found artifacts that can only be produced at least on earth by life. Now you would say, oh, maybe the geological process, I would argue very vehemently that that is not the case, but we can say, look, if you don't like the cut off on Earth, go up higher, 30, 100, right?

Starting point is 00:44:39 Because there's going to be a point where you can find a molecule with so many different parts, the chances of you getting a molecule that has a hundred different parts and finding a million identical copies, you know, that's just impossible, that could never happen in an infinite set of universes. Can you just linger on this copy number thing? A million different copies. What do you mean by copies and why is the number of copies important? Yeah, that was so interesting. And I always understood the copy number was really important, but I never explained it properly for ages.

Starting point is 00:45:22 And I kept having this, it goes back to this, if I give you a, I don't know, a really complicated molecule, and I say it's complicated. You could say, hey, that's really complicated, but is it just really random? And so I realized the ultimate randomness and ultimate complexity are indistinguishable. Until you can see a structure in the randomness. So you can see copies. So copies implies structure. Yeah. The factory. There's a deeper found thing in there. Because if you just have a random process, you're going to get a lot of complex, beautiful, sophisticated things. What makes them complex in the way we think life is complex or something like a factory that's operating under a selection process, there should be copies. Is there like some looseness about copies?

Starting point is 00:46:26 processes, there should be copies. Is there like some looseness about copies? What does it mean for two objects to be equal? It's all to do with the telescope or the microscope you're using. At the maximum resolution, so in the nice thing about chemists, as they have this concept of the molecule and they are all familiar with the molecule, and molecules you hold, you know, and your hand and lots of them identical copies. A molecule is actually a super important thing in chemistry to say, look, you can have a mole of a molecule, an avogadro is number of molecules, and they're identical.

Starting point is 00:46:55 What does that mean? That means that they're molecular composition, the bonding and so on, the configuration is all, is indistinguishable, you can hold them together, you can overlay them. So the way of doing it is if I say, here's a bag of 10 identical molecules. Let's prove they're identical.

Starting point is 00:47:11 You pick one out of the bag and you basically observe it using some technique and then you take it away and then you take another one out. If you observe it using technique you can see no differences, they're identical. It's really interesting to get right because if you take say two molecules,

Starting point is 00:47:26 molecules can be in different vibrational and rotational states, they're moving all the time. So with this respect, identical molecules have identical bonding. In this case, we don't even talk about chirality because we don't have a chirality detector. So two identical molecules in one conception assembly theory, basically,

Starting point is 00:47:51 considers both hands as being the same. But of course, they're not. They're different. As soon as you have a chiral to distinguish it, detect the left and the right hand, they become different. And so it's to do with the detection system that you have and the resolution. So I wonder if there's an art and science to the which detection system is used when you show up to a new planet. Yeah, yeah, yeah. So like you're talking about chemistry a lot today. We have kind of standardized detection systems, right?

Starting point is 00:48:19 Of how to compare molecules. So, you know, when you start to talk about emojis and language and mathematical theorems and, I don't know, more sophisticated things at a different scale, a smaller scale of the molecules, a larger scale of the molecules, like word detection. If we look at the difference in you and me, lex flexibly, are we the same? Are we different? Sure, I mean, of course we're different close up,

Starting point is 00:48:48 but if you zoom out a little bit, we'll morphologically look the same. Yeah. You know, high characteristics, hair lengths, stuff like that. We'll also like the species and. Yeah, yeah, yeah. And also, there's a sense why we're both from Earth.

Starting point is 00:49:04 Yeah, I agree. I mean, this is the power of assembly theory in that regard. So if everything, so the way to look at it, if you have a box of objects, if they're all indistinguishable, then using your technique, what you then do is you then look at the assembly index. Now, if the assembly index of them is really low, and they're all in distinguishing pool, then it's telling you that you have to go to another resolution. So that would be, it's kind

Starting point is 00:49:35 of a sliding scale. It's kind of nice. So those two are a tension with each other. Yeah, the number of copies on the assembly index. Yeah.'s really really interesting So okay, so you short turn your planet you'll be doing what I would do mass back I would bring on a sample of what like first of all like how big of a scoop do you take did you take a scoop like what like So we're looking for primitive life I Would I would look yes, so if we're just going to Mars

Starting point is 00:50:06 or Titan or Enceladus or somewhere, so a number of ways of doing it. So you could take a large scoop or you could go for the atmosphere and detect stuff. So you could make a life meter, right? So one of Sarah's colleagues, A.S.U. Paul, keeps calling it a life meter. Which is quite a nice idea because you think about it.

Starting point is 00:50:31 If you've got a living system that's producing these highly complex molecules and they drift away and they're in a highly kind of demanding environment, they could be burnt, right? So they could just be falling apart. So you want to sniff a little bit of complexity and say warmer, warmer, warmer, oh, we found life. We found the alien, we found the alien Elon Musk smoking a joint in the bottom of the cave on Mars or Elon himself, whatever, right?

Starting point is 00:50:56 And say, okay, we found it. So what you can do is the mass spectrometer, you could just look for things in the gas phase or you go on the surface, drill down, because you want to find molecules that are, you've either got to find the source living system, because the problem with just looking for complexity, is it gets burned away.

Starting point is 00:51:16 So in a harsh environment on, on, on, say, on the Mars, surface of Mars, there's a very low probability that you're going to find really complex molecules because of all the radiation and so on. If you drill down a little bit, you could drill down a bit into a soil that's billions of years old. Then I would put in some solvent, water, alcohol, something, or take a scoop, make it volatile, put it into the mass spectrometer and just try and detect high complexity, high abundant molecules. And if you get them, hey presto, you can have evidence of life. Wouldn't that then be great if you could say, okay, we've found evidence of life.

Starting point is 00:51:56 Now we want to keep the life meat, to keep searching for more and more complexity until you actually find living cells. You can get those new living cells and then you can bring them back to Earth or you could try and sequence them. You could see that they have different DNA and proteins. Go along the gradient of the life meter. How would you build a life meter? Let's say we're together starting a new company launching a life meter. Mass spectrometer would be the first way of doing it. No, no, but that's one of the major components of it. But I'm talking about like, I would, if it's a device, we've got it in branding logo, we've got to talk about that later. But what's the input? What's the, like, how do you get to the,

Starting point is 00:52:35 a metered output? So I would, I would take a life, so my, my life meter, our life meter, there you go. Thank you. Yeah, you're welcome. Would have both infrared and mass spec. So it would have two ports so it could shine the light. And so what it would do is you would have a vacuum chamber and you would have an electrostatic analyzer and you'd have a monochromator to producing infrared. You'd add the sum. So you'd take a scoop of the sample, put it in the life meter, it would then add a solvent or heat up the sample, so some volatiles come off.

Starting point is 00:53:13 The volatiles would then be put into the mass spectrometer into the electrostatic trap, and you'd weigh the molecules and fragment them. Alternatively, you'd shine infrared light on them, you'd count number of bands, but you'd have to. In that case, do some separation, but you'd have to. In that case, do some separation because you want to separate in, and so in mass spec, it's really nice and convenient because you can separate electrostatically, but you need to have

Starting point is 00:53:33 that. Can you do it in real time? Yeah, pretty much. Yeah, so let's go all the way back. So this, okay, we're really going to get this. Let's go. The Lexus life meat, Lexus leaves. No, no, actually.

Starting point is 00:53:43 It's good. It's a good good ring to it. All right. So you have a vacuum chamber. You have a little nose. The nose would have a packing material. So you would take your sample, add it onto the nose, add a solvent or a gas.

Starting point is 00:54:02 It would then be sucked up the nose. And that would be separated using Chrome using what we call chromatography. And then as each band comes off the nose, we would then do mass spec and infrared. And in the case of infrared, count the number of bands, in the case of mass spec, count the number of fragments and weigh it. And then the further up in molecular weight range for the mass spec and the number of bands you go up and up and up from the, you know, dead interesting interesting over the threshold. Oh my gosh earth life and then right up to the batshit crazy. This is definitely, you know, alien intelligence that's made this life, right? You could almost go all the way there, same in the infrared and it's pretty simple. The thing that It's really problematical is that for many years, decades, what people have

Starting point is 00:54:48 done, and I can't blame them, is that rather than being obsessing about small biomarkers on that we find on Earth, for amino acids, like single amino acids or evidence of small molecules and these things, and looking for there is run, looking for those, Ron looking for complexity. It will be, if it's a beautiful thing about this, is you can look for complexity without Earth chemistry bias, or Earth biology bias. So assembly theory is just a way of saying, hey, complexity and abundance is evidence of selection. That's how our universal life meter will work. Complexity and abundance is evidence of selection.

Starting point is 00:55:30 will work. Complexity in abundance is evidence of selection. Okay, so let's apply our life meter to earth. So what, you know, if we were just to apply assembly index measurements to earth, what, what, what kind of stuff are going to be get? Are going to get what's impressive? So some of the complexity on earth. So we did this a few years ago in the when I was trying to convince NASA and colleagues that this technique could work and honestly It's so funny because everyone's like now I'm gonna work. I Know it's just like because the chemist was saying of course there are complicated molecules out there You can detect that just form randomly. I was like, really? That was like, you know,

Starting point is 00:56:10 as a bit like a, I don't know, someone saying, of course Darwin textbook was just written randomly by some monkeys in a typewriter. I was just, for me, it was like, really. And I pushed a lot on the chemist now, and I think most of them are on board, but not totally. It really had some big arguments, but the copy number

Starting point is 00:56:30 caught there, because I think I confused the chemist by saying one off, and then when I made clear about the copy number, I think that made it a little bit easier. Just to clarify, chemists might say that, of course, out there, outside of earth, there's complex molecules. Yes. Okay. And then you're saying, wait a minute, that's like saying, of course, there's aliens out there. Yeah, exactly that. Okay. Exactly. But you're you say you clarify that that's actually a very interesting question and we should be looking for complex molecules of which the copy number is two or greater.

Starting point is 00:57:07 Yeah, exactly. So, on Earth, the coming back to Earth, what we did is we took a whole bunch of samples, and we were running pre-bodic chemistry experiments in the lab. We took various inorganic minerals and extracted them, look at the volatile, because there's a special way of treating minerals and polymers them. Look at the volatile because there's a special way of treating minerals and polymers in assembly theory. In our life machine, we're looking at molecules. We don't care about polymers because they don't volatile. You can't hold them. How can you make, if you can't discern that they are identical, then it's very difficult for you to work out

Starting point is 00:57:45 if this undergone selection or they're just a random mess, same with some minerals, but we can come back to that. So basically what you do, we got a whole load of samples in organic ones, we got a load of, we got Scotch Whiskey, and also got, it took a hard bag, which is one of my favourite Whiskey, which is very peaty, and another. It is like, so the way that on, in Scotland in Eilor, which is a little island, the Scotch, the whisky is, let to mature in barrels,

Starting point is 00:58:16 and the, it's said that the peak, the complex molecules in the pit, might find their way through into the whiskey, and that's what gives it this intense brown color and really complex flavor. It's literally molecular complexity that does that. And so, you know, vulca is the complete opposite. It's just pure, right? So, the higher the whiskey, the higher the summing index, the higher the summing index, the better the whiskey.

Starting point is 00:58:42 That's what I mean, I really love deep PTs, Scottish whiskeys. Near my house, there is a one of the lowland distilleries called Glen Goin. It's still beautiful whiskey, but not as complex. So for fun, I cooked up some Glen Goin whiskey in our bag and put them into the mass spec at measure of the assembly index. I also got Ecoli.

Starting point is 00:59:02 So the way we do it, take the Ecoli, break the the cell apart, take it all apart, and also got some beer. And people were ridiculing us saying, oh, beer is evidence of complexity. One of the computational complexity people was just throwing, yeah, we were kind of, kind of he's very vigorous in his disagreement of assembly theory was just saying, you know, you don't know what you're doing, even beer is more complicated than human. We didn't realize it's not beer, per se, it's taking the east extract, taking the extract, breaking the cells, extracting the molecules, and just looking at the profile of the molecules,

Starting point is 00:59:41 see if there's anything over the threshold. And we also put in a really complex molecule tax on. So we took all of these, but also NASA gave us, I think, five samples, and they wouldn't tell us what they are. They said, no, we don't believe you can get this to work. And they really, they gave us some super complex samples. And they gave us two fossils, one that was a million years old

Starting point is 01:00:02 and one was at 10,000 years old, see something from Antarctica, see, bad. They gave us an emergency and meteorite and a few others. Put them through the system. So we took all the samples, treated them all identically, put them into mass spec, fragmented them, counted them. And in this case, implicit in the measurement was, you're in mass spec, you only detect peaks when you've got more than say,

Starting point is 01:00:27 let's say, 10,000 identical molecules. So the copy numbers already baked in. There wasn't quantified, which is super important there. This is in the first paper because I guess abundant, of course. And when you then took it all out, We found that the biological samples gave you molecules that had an assembly index greater than 15 and all the abart examples were less than 15 and then we took the NASA samples and we looked at the ones that were more than 15 and less than 15 and we gave them back to NASA and they were like, oh gosh, yeah, dead, living, dead, living, you got it. And that's what we found on earth. That's a success. Yeah. Oh yeah, resounding success.

Starting point is 01:01:10 Well, can you just go back to the beer and the Ekolye? So what's the assembly index on those? So what you were able to do is like the assembly index of, we found high assembly index molecules originating from the beer sample and the E. coli sample. So, I mean, I didn't know which one was higher. We wouldn't really do any detail there, because now we are doing that, because one of the things we've done, it's a secret, but I can tell you. I think it's a... No, nobody's listening. Well, is that we've just mapped the Tree of Life using a assembly theory, because everyone said, oh, that you can't do in phenomenology. And what we're able to do is, so I think there's three ways, well, two ways doing Tree of Life, well, three ways, actually.

Starting point is 01:01:59 Yeah, what's the Tree of Life? So the Tree of life is basically tracing back the history of life on earth for all different species going back, who evolved from what? And it all goes all the way back to the first kind of life forms. And they branch off. And like you have plant kingdom, the animal kingdom,

Starting point is 01:02:17 the fungi, exist the kingdom, and different branches all the way up. And the way this was classically done, and I'm no evolutionary biologists, the evolution biologists, it's a very, tell me every day, at least 10 times. I want to be one though, I kind of like biologists, it's kind of cool, but yeah, it's very cool. But basically, what Darwin and Mendelay have and all these people do, is just they draw pictures, right? And they they're taxa, they just tax it. They were able to draw pictures and say,

Starting point is 01:02:45 and say, oh, these look like common classes. Yeah. Then, there are artists really, there are just, you know. But they're, they're, they're, they're able to find out a lot, right? And looking at verbrates and verbrates, camera and explosion, and all this stuff. And then, then came the genomic revolution.

Starting point is 01:03:03 And suddenly everyone used gene sequencing and Craig Ventors is a good example. I think he's gone around the world and he's yacht just taking up samples looking for new species where he's just found new species of life just from sequencing. It's amazing. So you have taxonomy, you have sequencing and you can also do a little bit of kind of molecular um uh kind of archaeology like you know measure the samples and and kind of molecular kind of archaeology, like, you know, measure the samples and kind of form some inference. What we did is we were able to fingerprint through the load of random samples from all of biology and we use mass spectrometry and what we did now is not just look for individual molecules, but we looked for

Starting point is 01:03:53 coexisting molecules where they had to look at their joint assembly space and where we were able to cut them apart and undergo recursion in the mass spec and infer some relationships and we were able to recapitulate the tree of life using mass spectroscopy No sequencing and no drawing All right, can you try to say that again, with a little more detail? So recreating what is the detector we create the tree of life? What is the reverse engineering process look like here? So what you do is you take an unknown sample, you plug it into the mass spec, you get a because this comes from what you're asking like what you see in E. Coli and so in E. Coli

Starting point is 01:04:23 You don't just see it's not it not, it's not that the most sophisticated cells on, on Earth make the most sophisticated molecules. It is the coexistence of lots of complex molecules above a threshold. And so what we realize is you could fingerprint different life forms. So fungi make really complicated molecules. Why can't they move? They have to make everything on site. Whereas some animals are like lazy. They can just go eat the fungi. They don't need to make very much. And so what you do is you look at the,

Starting point is 01:04:57 so you take, I don't know, the fingerprint, maybe the top number of high molecular white molecules you find in the sample, you fragment them to get their assembly indices. And then what you can do is you can infer common origins of molecules. You can do a kind of molecular, when the reverse engineering of the assembly space, you can infer common roots and look at what's called the joint assembly space.

Starting point is 01:05:23 But let's translate that into the experiment. Take a sample, bung it in the mass spec, take the top, say, 10 molecules, fragment them, and then, and that gives you one fingerprint. Then you do it for another sample, you get another fingerprint. Now the question is you say, hey, are these samples the same or different? And that's what we may not do. And by basically looking at the assembly spaces, these molecules create. Without any knowledge of assembly theory, you are unable to do it.

Starting point is 01:05:53 With an knowledge of assembly theory, you can reconstruct the tree. How does knowing if they're the same or different give you the tree? Let's go to two leaves on different branches on the tree, right? What you can do by counting the number of differences, you can estimate how far away their origin was. Got it. And that's all we do. And it just works. But when we realized you could even use

Starting point is 01:06:15 a semi-threatary to recapitulate the tree of life from no gene sequencing, we were like, oh, so this, this is looking at samples that exist today in the world. What about like things that are not longer existing? I mean, the tree contains information about the past. I would, some of it is gone. Yeah, absolutely. I would love to get old fossil samples and apply a assembly theory mass spec and see if we can find new forms of life. That have, there are no longer amenable to gene sequencing

Starting point is 01:06:44 because the DNA is all gone. There's DNA, DNA and RNA is quite unstable, but some of them are complex molecules, might be there, they might give you a hint, something new, or wouldn't it be great if you, if you find a sample that's worth really persevering and doing, you know, doing the proper extraction to wreak to, you know, PCR and so on and then sequence it and then put it together. So, one thing dies, you can still get some information about this complexity. Yeah, and it appears that you can do some dating. Now, there are really good techniques. There's radio carbon dating. There is longer dating, going looking at radioactive minerals and so on.

Starting point is 01:07:26 And you can also, in bone, you can look at what happens after something dies, is the immediate, you get what's called rastomization, where the chirality in the polymers basically changes and you just get decomposition. And the deviation from the pure enantiomer to the mixture, you can have a, it gives you a time scale on it, a half life, so you can date when it died. I want to use assembly theory to see if I can date, use it, date death and things and trace the tree of life and also decomposition of molecules. You think it's a puzzle? Oh, yeah.

Starting point is 01:08:09 Without doubt. It may not be better than what, because like the, I was just at a conference, where some brilliant people were looking at isotope and wrenchment and looking at how life enriches isotopes and they're really sophisticated stuff that they're doing. But I think there's some fun to be had there because we gives you another dimension of dating how old is this molecule? In terms of more importantly, how long ago was this molecule produced by life? The more complex the molecule, the more prospect for decomposition, oxidation, reorganization, loss of chirality, and all that jazz. But what life also does is it enriches, as you get older,

Starting point is 01:08:46 the amount of carbon 13 and you goes up because of the way the metabolites, because of the way the bonding is in carbon 13. So it has a slightly different strength, one strength, and you is called a kinetic isotope effect. So you can literally date how old you are, you know, or when you stop metabolizing. So you could date someone as literally date how old you are, you know, or when you stop metabolizing, so you could date someone's debt, how old they are, I think I'm making this up. This might be right. But I think it's roughly right. The amount of carbon 13 you have in you, you can kind of estimate how old you are. How old living organs are? Humans are. Yeah, like you could say, oh, this person is 10 years old and this person 30 years old because they'll be

Starting point is 01:09:26 Metabolizing more carbon and they've accumulated it. That's the basic idea. It's probably completely wrong timescale of chemistry or fasting. Yeah, so you've been saying a lot of chemistry examples For assembly theory what if we zoom out and look at a bigger scale of an object? You know like really complex objects, like humans, or living organisms that are made up of, you know, millions or billions of other organisms, how do you try to apply summary theory to that? At the moment, we're, we should be able to do this to morphology in cells, so we're looking

Starting point is 01:10:06 at cell surfaces and really trying to extend further. It's just that we work so hard to get this paper out and people to start discussing the ideas. But it's kind of funny because I think the penny is falling on this. So, yeah, so was it? What was it mean for a penny? I mean no the the penny's dropped right because a lot of people like it's rubbish It's rubbish. You've insulted me. It's wrong and I'm and then you know I mean the paper got published on the fourth of October

Starting point is 01:10:38 It had 2.3 million engagements on Twitter, right? And it's been downloaded over a few hundred thousand times. And someone actually said to me, wrote to me and said, this is an example of really bad writing and what not to do. And I was like, if all of my papers got read this much, because that's the objective of I have a publishing a paper on people to read it, I want to write that badly again. I don't know what's the deep inside here about the negativity in the space. I think it's probably the immune system of the scientific community making sure that there's no bullshit that gets published. And then it can overfire, it can do a lot of damage, it can shut down conversations in a way that's not productive.

Starting point is 01:11:15 We go back, coming on, to your question about the hierarchy and assembly, but let's go back to the perception. People saying that paper was badly written, I mean, of course we could improve it. We can always improve a clarity. Let's go there before we go to the hierarchy. You know, it has been criticized quite a bit the paper. What has been some criticism that you found most powerful? Like that you can understand and can you explain it? Yes, the most exciting criticism came from the evolutionary biologist telling me that they thought that that it would origin of life was a solved problem. And I was like, whoa, we're really on something because it's clearly not. And when you poke them on that, they just said, no, you don't understand evolution. And I said, no, no, I don't think you understand the evolution had to occur before biology.

Starting point is 01:12:06 And there's a gap. That was really, for me, that misunderstanding, and that that did cause an immune response, which was really interesting. The second thing was the fact that physicists, the physicists were actually really polite, right? Really nice about it. But they just said,

Starting point is 01:12:25 we're not really sure about the initial conditions thing, but this is a really big debate that we should certainly get into because the emergence of life was not encoded in the initial conditions of the universe. And I think assembly theory shows why it can't be. I'll say that. I'll say that, sure, if you could say that again. The origin of the emergence of life was not and cannot,

Starting point is 01:12:53 in principle, be encoded in the initial conditions of the universe. Just to clarify what I mean by life is like what high assembly index objects. Yeah. And this goes back to your favorite subject. What's that time? Right. So why? So why? What does time have to do with it? We probably can come back to it later, but I think it might be, if we have time. But I think I now understand how to explain how, you know, lots of people got angry with the assembly paper, but also the ramifications of this is how time is fundamental in the

Starting point is 01:13:34 universe and this notion of combinatorial spaces. And there are so many layers on this, but you have to become an intuition, I think you have to become an intuitionist mathematician and you have to abandon platonic mathematics and also platonic mathematics is their physics astray, but there's a lot of them back there. So we can go to the... Atonic mathematics. Okay, there's okay. The evolution of biologist criticized because the origin of life is understood and not it doesn't require an explanation of the involves physics. Yeah, basically. Basically, I realized the evolutionary biology community that were vocal and some of them really rude, really spiteful,

Starting point is 01:14:25 and needlessly so, right? Because like, you know, I didn't, people really misunderstand publication as well. Some of the people have said, how dare this be published in nature. This is, you know, how, what a terrible journal. And I, and it really, and I want to say that people look, this is a brand new idea that's not only potentially going to change the way we look at biology, it's going to change the way we look at the universe. And everyone's like saying, how dare you, how dare you be so grandiose?

Starting point is 01:15:02 I'm like, no, no, no, this is not hype. We're not, we're not not like saying we've invented some, I don't know, we've discovered alien in a closet somewhere just for hype. We've genuinely mean this to genuinely have the impact or ask the question. And the way people jumped on that was a really bad precedent for young people

Starting point is 01:15:21 who want to actually do something new because this makes a bold claim. And the chances are that it's not correct. But what I wanted to do is a couple of things. As I want to make a bold claim that was precise and testable and correctable, not a woolly another woolly information in biology argument information, Turing machine blah blah blah blah blah. A concrete series of statements that can be falsified and explored,

Starting point is 01:15:50 and either the theory could be destroyed or built upon. What about the criticism of you're just putting a bunch of sexy names and something that's already obvious? Yeah, that's really obvious. Yeah, that's really good. So, so the assembly index of a molecule is not obvious. No one has measured it before. And no one has thought to quantify selection, complexity and copy number before in such a primitive, quantifiable way. I think the nice thing about this paper, this paper is a tribute to all, we're not to all the people that understand that the biology does something very interesting. Some people call it neg entropy. Some people call it think about, you know, organizational

Starting point is 01:16:39 principles that lots of people were not shocked by the paper because they've done it before. A lot of the arguments we got, some people said, oh, it's rubbish. Oh, by the way, I had this idea 20 years before. I was like, which one? Is it the rubbish part or the really revolutionary part? So this kind of clucked two strings at once. It plucked the... There is something interesting that biology is as we can see around this, but we haven't quantified yet. And what this is, the first stab at quantifying that. So the fact that people said this is obvious, but it's also, so with it's obvious, why have

Starting point is 01:17:19 you not done it? Sure, but there's a few things to say there. One is, you know, this is in part of philosophical framework because, you know, it's not like you can apply this generally to any object in the universe. It's very chemistry focused. Yeah, well, I think you will be able to. We just haven't got their robustly. So if we can say, how can we, let's go up a level. So if we go up from level, we go up, let's go up from molecules to cells because you would jump to people and I jumped from motorcons and both are good and they will be a sample. Let's go from it.

Starting point is 01:17:53 If we go from, so if we go from molecules to assemblies and let's take a cellar assembly, a nice thing about a cell is you can tell the difference between a u-carriote and a pro-carriote. Right? The organelles are specialized differently. We then look at the cell surface, and the cell surface has different glycosolation patterns, and these cells will stick together. Now, let's go up a level with multicellular creatures. You have cellular differentiation.

Starting point is 01:18:19 Now, if you think about how embryos develop, you go all the way back. Those cells undergo differentiation on a causal way that's biomechanically a feedback between the genetics and biomechanics. I think we can use assembly theory to apply to tissue types. We can even apply it to different cell disease types. So that's what we're doing next, but we're trying to walk, you know, the thing is I'm trying to leap ahead, I want to leap ahead to go, well, we'll apply it to culture, but clearly you can apply it to memes and culture. And we've also applied assembly theory to CAs.

Starting point is 01:18:54 And not as you think. Celery or Talmud about that. Yeah, yeah. To say what I'm not just as you think, we're different CAs rules. We're invented by different people at different times. And one of my, one of my co-workers, very talented chap, basically, was like, oh, I can realize that different people had different ideas with different rules, and they copied each other, and made slightly different, different cellular automata rules, and they, and public, and looked

Starting point is 01:19:19 at them online. And so he was able to further assembly index and copy number of rule whatever doing this thing. But I digress But it does show you can apply it at a higher scale So what do we need to do to apply assembly theory two things? We need to agree there's a common set of building blocks So in a cell well in a in a multicellular creature you need to look back in time So there is the the initial

Starting point is 01:19:43 Cell which the creature is fertilized and then starts to grow, and then there is cell differentiation. And you have to then make that causal chain both on those. So I requires development of the organism in time. Or if you look at the cell surfaces and the cell types, they've got different features on the cell, what's the walls and inside the cell. So we're building up, but obviously I want a leap to things like emoticons, language, mathematical theory. That's a very large number of steps to get from a molecule to the human brain.

Starting point is 01:20:23 Yeah. And I think they are related, but in hierarchies and emergence, right? So you shouldn't compare them. I mean, the assembly index of a human brain, what does that even mean? Well, maybe we can look at the morphology of the human brain, say, all human brains have these number of features in common. If they have those number of, and then let's look at a brain in a whale, or a dolphin, or chimpanzee, or a bird, say, okay, let's look at the assembly indices, number of features

Starting point is 01:20:50 in these. And now the copy number is just a number of how many birds are there, how many chimpanzees are there, how many humans are there. But then you have to discover for that the features that you would be looking for. Yeah. And that means you need to have a unit of some idea of the anatomy. But is there an automated way to discover features? that you would be looking for. Yeah. And that means you need to have a unit of some idea of the anatomy. But is there an automated way to discover features?

Starting point is 01:21:08 I guess so. I mean, and I think this is a good way to apply machine learning and image recognition to specific characteristics. So apply compression to it to see what emerges and then use the thing, the features used as part of the compression as the measurement of, as the thing that is searched for when you're measuring assembly index and copy.

Starting point is 01:21:31 And the compression has to be, remember, the assembly universe, which is you have to go from assembly possible to assembly contingent. And that jump from a, because assembly possible, all possible brains, all possible features all the time. But we know that on the tree of life and also on the lineage of life going back to Luca, the human brain just didn't spring into existence yesterday, it is a long lineage of brains going all the way back. And so if we could do assembly theory to understand the development, not just an evolutionary history, but in biological development as you grow, we're going to learn something more. What would be amazing is if you can use a zombie theory, this framework to show the increase in the assembly index, associated with, I don't know, cultures or pieces of text like language or images and so on and illustrate without knowing

Starting point is 01:22:29 the data ahead of time, just kind of like you do with NASA that you're able to demonstrate that it applies in those other contexts. And that probably wouldn't at first and you have to evolve the theory somehow, you have to change it, you have to expand it. I think so. But like that, I guess this is as a paper of first step in saying, okay, can we create a general framework for measuring complexity of objects, for measuring life, the complexity of living organisms?

Starting point is 01:23:00 Yeah, that's what this is reaching for. That is the first step. And also to say, look, we have a way of quantifying selection and evolution in a fairly, in a fairly, not mundane, but a fairly mechanical way. Because before now, you know, this, it wasn't very, the ground truth for it was very subjective, whereas here we're talking about clean observables. And there's going to be layers on that. I mean, we're talking about clean observables. And there's going to be layers on that. I mean, we're, we've collaborators right now. We already think we can do a

Starting point is 01:23:29 semifereon language. And not only that, wouldn't it be great if we can put it so the, if we can figure out how under pressure, language is going to involve and be more efficient because you're going to want to transmit things. And again, it's not just about compression. It is about understanding how you can make the most of the, in the architecture you've already built. And I think this is something beautiful that evolution does with we're reusing, reusing those architectures. We can't just abandon our evolutionary history. And if you don't want to abandon your evolutionary history and you know that evolution has been happening, then assembly theory works. I think that's a key comment I want to make.

Starting point is 01:24:08 Assembly theory is great for understanding where evolution has been used. The next jump is when we go to technology. Of course, if you take the M3 processor, I want to buy it, I'm bought one, yeah, I can't justify it, but I want to at some point. The M3 processor arguably is quite a lot of features, quite a large number. The M2 came before it then, the M1 all the way back. You can apply assembly theory to micro-processor architecture. It doesn't take a huge leap to see that.

Starting point is 01:24:37 I'm a Linux guy, by the way, so your examples go way over and there. Well, whatever is that like a, is that a fruit company or something? I don't even know. Yeah, there's a lot that like is that a fruit company or some sorry? I don't even know Yeah, there's a lot interesting stuff to ask about language like you could look at How would that work you go like a GPT1 GPT2 GPT3354 And try to analyze the kind of language it produces I mean, that's almost trying to look at assembly index of intelligence systems. Yeah I mean I think the thing about large language models and this is a whole hobby horse I have at the moment is that obviously they're all about the evidence of evolution in the large language model

Starting point is 01:25:27 comes from all the people that produced all the language. That's really interesting, and all the corrections in the mechanical Turk. That's part of the history, part of the memory of the system. Exactly. It would be really interesting to basically use an assembly-based approach to making language in a hierarchy, right?

Starting point is 01:25:52 I think my guess is that we might be able to build a new type of large language model that uses assembly theory that it has more understanding of the past and how things were created. Right. Basically, the thing with LLMs is they're like everything, everywhere, all at once, splat, and make the user happy. So there's not much intelligence in the model. The model is how the human interacts with the model, but wouldn't it be great if we could understand how to embed more intelligence in the system? What do you mean by intelligence there? Like you seem to

Starting point is 01:26:31 associate intelligence with History. Yeah. Well, I'm really I think selection produces intelligence Wait, you almost implying this selection is Intelligence no, yeah kind of I would go that I would go out and live and say that, but I think it's a little bit more human beings have the ability to abstract and they can break beyond selection. And this is what like Darwinian selection, because human being doesn't have to basically do trial and error. Like, they can think about that. That's a bad idea when do that and then technologies and so on. So we escaped Darwinian evolution. And now we're onto some other kind of evolution.

Starting point is 01:27:06 I guess higher level. And then we'll assembly theory will measure that as well, right? Because it's all lineage. OK, another piece of criticism, or by way of question, is how is assembly theory, or maybe assembly index different from Commograve complexity?

Starting point is 01:27:23 So for people who don't know, Commograve complexity of an object is the length of a shortest computer program that produces the object is output. Yeah, I, I seem to, there seems to be a disconnect between the computational approach. So, yeah, so comagolar of measure requires a cheering machine requires a computer and that's one thing and the other thing is assembly theory is supposed to trace the process by which life evolution emerged. Right, there's a main thing there. There are lots of other layers. So, so CommaGolarOff complexity, you can, you can approximate CommaGolarOff complexity, but it's not really telling you very much about the actual, it's really telling you about like your date, your dataset, compression of your dataset. And so that doesn't really help you identify

Starting point is 01:28:26 the turtle in this case as the computer. And so what Assembly Theory does is, I'm gonna say, it's a trigger warning for anyone listening who loves complexity theory. I think that we're gonna show that AIT is a very important subset of assembly theory, because here's what happens. I think that assembly theory allows us to build, understand when

Starting point is 01:28:53 we're selections occurring, selection produces factories and things, factories in the end produce computers, and you can go, then algorithmic information theory comes out of that. The frustration I've had with looking at life through this kind of information theory is it doesn't take into account causation. The main difference between assembly theory and all these complexity measures is there's no causal chain. I think that's the main... As the causal chain the at the core of Assembly theory exactly and if you're in if you've got your your data in a computer memory all the data

Starting point is 01:29:32 The same you can access it in the same type way there's you don't care you just compress it and and you either look at the program runtime or the shortest program and that for me It can it is absolutely not capturing what it is, what its selection does. But a certainly theory looks at objects. It doesn't have information about the object history. It's going to try to infer that history by looking for the shortest history. The object doesn't have a Wikipedia page that goes with it. Oh, I would say it does in a way, and it is fascinating to look at. So you've just got the objects, and you have no other information about the object.

Starting point is 01:30:19 What assembly theory allows you to do with just what the object is to, and the word infer is correct. I agree with him, for, you're like, say, well, that's not the, that's not the history, but, but something really interesting comes from this. The shortest path is inferred from the object. That is the worst case scenario if you have no machine to make it. So that tells you about the depth of that object in time. And so what assembly theory allows you to do without considering any other circumstances, to say from this object, how deep is this object in time, if we just treat the object as itself without any other constraints. And that's super powerful

Starting point is 01:31:01 because the shortest path then says, allows you to say, oh, this object wasn't just created randomly, there was a process. And so assembly theory is not meant to, you know, one up, AIT, or to ignore the factory. It's just to say, it's just to say, hey, there was a factory. That, and how big was that factory and how deep in time is it? But it's still computationally very difficult to compute that history for complex objects. It is and becomes harder. One of the things that's super nice is that it constrains your initial conditions. It constrains where you're going to be. If you take say, imagine, so one of the things we're doing right now is applying assembly

Starting point is 01:31:47 theory to drug discovery. Now what everyone's doing right now is taking all the proteins and looking at the proteins and looking at molecules, docker proteins. Why not instead take the molecules that are involved in interacting with the receptors over time, rather thinking about and use the molecules evolve over time as a proxy for how the proteins evolved over time and then use that to constrain your drug discovery process. You flip the problem 180 and focus on the molecule evolution rather than the protein and so you can guess in the future what might happen.

Starting point is 01:32:22 So that so that so you rather than having to consider all possible molecules, you know where to focus. And that's the same thing if you're looking in assembly spaces for like object where you don't know the entire history, but you know that, you know, in the history of this object is not gonna have some other motif that there that doesn't apply,

Starting point is 01:32:42 it doesn't appear in the past. But just even for that drug discovery point you made, don't you have to simulate all of chemistry for to figure out how to come up with constraints? No. The molecules and the... No. I mean, I don't know enough about protein.

Starting point is 01:32:58 Well, this is another thing that I think causes, because this paper goes across 70 boundaries. So, chemists have looked at this and said, this is not a reaction, this is not correct reaction. It's like, no, it's a graph. Sure, there's a, there's a assembly index and shortest path examples here on chemistry. Yeah. And so, and what you do is you look at the minimal

Starting point is 01:33:23 constraints on that graph Of course, I have some mapping to the synthesis But actually you don't have to know all of chemistry. You just have to understand you can build up the constraint space rather nicely But this is just at the beginning right there are so many directions this could go in and I said it it could all be wrong But hopefully it's less wrong. What about the little criticism I saw of you by way of question? Do you consider the different probabilities of each reaction in the chain? So like that there could be different. When you look at a chain of events that led up to the creation of an object, doesn't it matter that some parts in the chain are less likely

Starting point is 01:34:07 than others? No, it doesn't matter. No, no. Well, let's go back. So no, not less likely, but react. So, so no. So let's go back to what we're talking about. So the assembly index is the minimal path that could have created that object probabilistically. So imagine you have all your atoms in a plasma, you've got enough energy, you've got enough, there's collisions. What is the quickest way you could zip out that molecule with no reaction constraints? How do you define quickest there then? It's just basically what a walk on a random graph. So we make an assumption that basically the time scale for forming the bonds. So

Starting point is 01:34:44 no, I don't want to say that because it's going to have people getting obsessing about this point and your criticism is really good one. What we're trying to say is like, this is, this puts a lower bound on something. Of course, some reactions are less possible than others, but actually, I don't think chemical reactions exist. Oh boy. What does that mean? Okay. Why don't come clear reactions exist? I'm writing a paper right now that I keep being told I have to finish. It's called the origin of chemical reactions. And it merely says that reactivity exists as controlled by the laws of quantum mechanics. And reactions,

Starting point is 01:35:19 we put names, chemists put names on reactions like so you could have like, I don't know, the VITIC reaction, which is by, you know, VITIC, you could have the Suzuki reaction, which is by Suzuki. Now, what are these reactions? So these reactions are constrained by the following. They're constrained by the factor on planet Earth, 1G, 298 Kelvin, 1 bar. So these are constraints. They're also constrained by the chemical

Starting point is 01:35:45 composition of earth, oxygen, availability, all this stuff, and that then allows us to focus in our chemistry. So when a chemist does a reaction, that's a really nice, compressed, shorthand for constraint application, glass flask, pure reagent, temperature pressure, bum bum bum, bomb, bomb, control, control, control, control, control. So, of course, we have bond energies. So the bond energies are kind of intrinsic in a vacuum, if you say that. So the bond energy, you have to have a bond. And so, for assembly theory to work, you have to have a bond,

Starting point is 01:36:22 which means that bond has to give the molecule certain laugh life. So, you're probably going to find later on that some bonds are weaker and that you are going to miss in mass spectra when you count, look at the assembly of some molecules, you're going to miscount the assembly of the molecule because it falls apart too quickly because the bonds just form. But you can solve that with looking infrared. So, when people think about the probability, they're kind of misunderstanding. Assembly theory says nothing about the chemistry, because chemistry is chemistry and their constraints are put in

Starting point is 01:36:55 bi biology. There was no chemist in the origin of life, baking unless you believe in the chemist in the sky. And they were, you know, it's like Santa Claus, they had a lot of work to do. But chemical reactions do not exist in the constraints that allow chemical transformations to do exist. Okay, okay. So it's constrained of what's a different word for chemical reaction transformation transformation. Yeah, like a function. It's a function. But no, but I love chemical reactions to the shorthand. And so the chemists don't all go mad. I mean, of course chemical reactions exist on it. It's a shorthand for his constraints. For, for, right. So assuming all these constraints that we've been using for so long, that we just assume that that's always the case. Yeah. In natural language conversation. Exactly. The grammar of chemistry, of course, emerges in reactions and we can use them reliably.

Starting point is 01:37:59 But I do not think the vitic reaction is accessible on Venus. Right. And this is useful to remember, to frame it as constraint application is useful for when you zoom out to the bigger picture of the universe and looking at the chemistry of the universe and then starting to apply some with theory. That's interesting. That's really interesting. But we've also pissed off the chemist now. Oh, I'm pretty happy, but what most of them? Nice.

Starting point is 01:38:27 Everybody, everybody deep down is happy, I think. They're just sometimes feisty. That's how they show, that's how they have fun. Everyone is grumpy on some days when you challenge. The problem with this paper is you, what I was like, it's almost like I went to a part, it's like you, I do used to do this occasionally. You want to go to a meeting and just find a way to find, offend everyone at the meeting simultaneously.

Starting point is 01:38:49 Even the factions that don't like each other, they're all unified in their hatred of you, just defending them. This paper, it feels like the person that went to the party and offended everyone simultaneously, so stop fighting with themselves and just focus on this paper. Maybe just a little insider interesting information. What were the editors of Nishir, like what their reviews and so on, how difficult was that process? This is a pretty like big paper. Yeah, I mean, so when we originally sent the paper, we sent the paper and the editor said, you know, this was like, this is a quite a long process.

Starting point is 01:39:29 We sent the paper and the editor gave us some feedback and said, you know, I don't think is that interesting. It's not, you know, it's hard, it's a hard concept. And we asked, and the editor gave us some feedback. And we. And Sarah and I took a year to rewrite the paper. Was the nature of the feedback very specific and like this part, this part, or was it like, what do you guys smoke? It was kind of the latter. What are you smoking? Okay.

Starting point is 01:39:58 And, you know, we're polite in this promise. Yeah, well, the thing is, the editor was really a, but in a really professional way. Yeah. And I mean, for me, this was the way science should happen. So when it came back, you know, we had too many equations in the paper. If you look at the pre print, they're just equations everywhere, like the twenty three equations. And when I said to Abyshek, he was the first author, we got to remove all the equations. But my assembly equations, staying in Abyshek was like, you know, no, we can't. I said, well, look, if we want to explain us to people, there's a real challenge. And so Sarah and I went through the, I think it

Starting point is 01:40:33 was actually 160 versions of the paper, but we basically, we got to version 40 or something. We said, right, zero, it start again. So we wrote the whole paper again. We knew the entire, amazing. And we just went spit by bit by bit. And so what does it we want to say? And then we send the paper in. And to us, we expected it to be rejected. And not even go to review. And then the, we got notification back at Gondra review.

Starting point is 01:40:58 And we were like, oh my god, it's so going to get rejected. How's it going to get rejected? Because the first assembly paper that were on the mass spec, we sent to nature, got went through six rounds of review and rejected. And by a chemist, you just said, I don't believe you, you must be committing fraud. A long story, probably a boring story. But in this case, it went out to review, the comments came back, and the comments were incredibly... the comments came back and the comments were incredibly, they were very, they were very deep comments from all the reviewers.

Starting point is 01:41:34 But the, but the, but the, but the nice thing was, the reviewers were kind of very critical, but not dismissive. They were like, oh, really? Explain this, explain this, explain this. Are you sure it's not comagolar off? Are you sure it's not this? And we went through, I think, three rounds of review,

Starting point is 01:41:54 pretty quick. And the editor went, yeah, it's in. But maybe you could just come in on the whole process. You've published some pretty huge papers and all kinds of topics within chemistry and beyond. Some of them have some little spice in them, a little spice of crazy. Like Tomway says, I like my Tom a little drop of poison. It's not a mundane paper. So what's it like psychologically to go through all this process to keep getting

Starting point is 01:42:26 rejected, to get reviews from people that don't get the paper or all that kind of stuff, just from a question of a scientist, like, what is that like? It's, I think it's, I mean, this paper for me kind of, because this wasn't the first time we tried to publish assembly theory at the highest level, the Nature Communications paper we on the mass spec on the idea went through, went to nature and got rejected, went through six rounds of review and got rejected. And it's, and I just was so confused when the chemist said, this can't be possible.

Starting point is 01:43:08 I do not believe you can measure complex that you use in mass spec. And also, by the way, molecules, complex molecules can randomly form. And we're like, but look at the data. The data says, and they said, no, no, we don't believe you. And we went and I just wouldn't give up. The edit and the edit in the end was just like the different editors actually. Right.

Starting point is 01:43:31 What's behind that never giving up? Like when you're sitting there, 10 o'clock in the evening, there's a melancholy feeling that comes over you. And you're like, okay, this is rejection number five. Or it's not rejection, but maybe it feels like a rejection because the comments or that you totally don't get it. Like, what gives you strength to keep going there? Yeah, I don't normally get emotional about papers, but it's not about giving it up because we want to get it published because we want the glory or anything. It's just like, why don't you understand? And so, so what I would just try to be as rational as

Starting point is 01:44:37 possible and say, yeah, you didn't like it. Tell me why. And then, sorry, silly. Never get emotional about papers normally, but I think what we do, you just compress like five years of angst from this. So it's been rough. It's not just rough, it came up with the assembly equation, remote from Sarah in Arizona and the people SFI, I felt like I was a mad person, like the guy in depicted in a beautiful mind who was just like, not the actual genius part, but just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the,

Starting point is 01:45:24 because I kept writing expanded and I have no mathematical ability at all and I was expand, actual genius part, but just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the,

Starting point is 01:45:32 just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, just the, number fell out of the equation and everything collapsed down. I was like, oh, that works kind of. So we submitted the paper.

Starting point is 01:45:47 And then when it was almost accepted, right, the mass spec one, and it was astrobiologists at gray, you know, a mass spectroscopist at gray and the chemist went nonsense, like biggest pile of nonsense ever fraud, you know. And I was like, but why fraud? And they just said, just because. And I was like, well, and so, well, and so, and I could not convince the editor in this case. The edit was just so pissed off,

Starting point is 01:46:12 because they see it as like a kind of, you know, a, you're wasting my time. And I would not give up. I wrote, I went and dissected, you know, all the parts. And I think, although I mean, I got upset about it, you know, it was kind of embarrassing actually, actually, but I guess it's beautiful. But it was just trying to understand why they didn't like it. So they were part of me was like, really devastated.

Starting point is 01:46:38 And the part of me was super excited. I'm like, huh, they can't tell me why I'm wrong. And this kind of goes back to, you know, when I was at school, I was kind of learning difficulties class and I kept going to the teacher and say, you know, you know, what do I do today to prove I'm smart? And they were like, nothing, you can't. I was like, give me a job, you know, give me something to do. Give me a job to do, something to do as we,

Starting point is 01:47:03 and I kind of felt like that a bit when I was arguing with the, I'm not arguing, there's no ad hominem, I wasn't telling the editor, they were idiots, something like this or the reviewers, I kept it strictly like factual, and all I did is I just kept knocking it down, bit by bit by bit by bit, it was ultimately rejected and it got published, they'll elsewhere, and then the actual experimental data. So this is kind of in this paper, the experimental justification was already published. So when we did this one, and we went through the versions,

Starting point is 01:47:33 and then we sent it in, and in the end, it just got accepted. We were like, well, that's kind of cool, right? This is kind of like, you know, some days you had, you know, the students, sorry, the first author was like, I can't believe I got accepted. I was like, you know, my, it's great. It's like, it's good. And then when the paper was published, I was not expecting the backlash. I was expecting computational, what, no, actually, it was just expecting one person who'd been

Starting point is 01:48:01 trolling me for a while about it, just to carry on trolling. But I didn't expect the backlash. And then I wrote the edit and apologized. And the edit was like, well, you're apologizing for what was a great paper. Of course, it's going to get backlash. You said some controversial stuff, but it's awesome. And so it's, I think is a beautiful story of perseverance. And the backlash is just a negative word for discourse, which I think is beautiful. I think you, as I said to, you know, when it got accepted and people were saying, we're kind of like hacking on it. And I was like, papers are not gold medals. The reason I want to publish that paper in nature is because it says, Hey, there's something before biological evolution. You have to have that if you're not a creationist,

Starting point is 01:48:53 by the way. This is an approach. First time someone has put a concrete mechanism or, sorry, a concrete quantification. And what comes next, you're pushing on is a a mechanism and that's what we need to get to is an auto-candidic set self-replicating molecules some other features that come in and the fact that this paper has been so discussed for me is a dream come true like you it doesn't get better than that if you can't accept a few people hating it, and the nice thing is, the thing that I really makes me happy is that no one has attacked the actual physical content. Like, you can measure the assembly index, you can measure selection now.

Starting point is 01:49:35 So either that's right or it's, well, either that's helpful or unhelpful. If it's unhelpful, this paper will sink down and no one will use it again. If it's helpfulhelpful, this paper will sink down and no one will use it again. If it's helpful, it'll help people scaffold on it and we'll start to converge to a new paradigm. So I think that that's the thing that I wanted to see, you know, my colleagues, authors, collaborators, and people who were like, you've just published this paper, you're a chemist. Why have you done

Starting point is 01:50:02 this? Like, who are you to be doing evolutionary theory? Mike, well, I don't know. I mean, sorry, did I need to get anyone to do anything? Well, I'm glad you did. Let me just before coming back to origin of life and these kinds of questions, you mentioned learning difficulties. I didn't know about this. So what was it like?

Starting point is 01:50:22 I wasn't very good. That's cool, right? This is when you're very young. Yeah, yeah, yeah, when I was in primary school, my handwriting was really poor, and apparently I couldn't read, and my mathematics was very poor. So they just said, this is a problem, they identified it.

Starting point is 01:50:40 My parents kind of at the time were confused because I was busy taking things apart, buying electronic junk from a shop, trying to build computers and things. And then what's I got out of, when I was I think about the major transition in my stupidity, like, you know, everyone thought I wasn't that stupid,

Starting point is 01:50:58 well, basically everyone thought I was faking, I like stuff and I was faking wanting to be, it's always what a be a scientist. So five, six, seven years, I'll be a scientist, take things apart. And everyone's like, yeah, this guy wants to be a scientist, but he's an idiot. And so everyone was really confused, I think at first,

Starting point is 01:51:16 that I wasn't smarter than I was claiming to be. And then I just basically didn't do well in the attest. I went down and down and down and down. And then, and I was kind of like, huh, this is really embarrassing. I really like maths and everyone says, I can't do it. I really like kind of, you know, physics and chemistry and all that in science.

Starting point is 01:51:36 And people say, you can't read and write. And so I found myself in a learning difficulties class at the end of primary school in the beginning of secondary school in the UK secondary school is like 11, 12 years old. And I remember being put in the remedial class. And the remedial class was basically full of, were two types, three types of people. There were people that had quite violent, right? And there were people who couldn't speak English

Starting point is 01:52:09 and there were people that really had learning difficulties. The one thing I can objectively remember was, I mean, I could read. I like reading. I read a lot. But something in me, I'm a bit of a rebel. I refused to read while I was told to read. And I found it difficult to read individual words in the way that I told. But anyway, I got caught one day teaching someone else to read. And they said, okay, we don't understand this. I always know what to be a scientist, but didn't really know what that meant. And I realized you had to get university, and I thought, I can just go university, it's like curious people like,

Starting point is 01:53:06 no, no, no, you need to have these, you have to be able to enter these exams to get this great point average. And the fact is the exam should be entered into, you're not, you're just going to get C, D or E, you can't even get A, B or C, right? This is the UKG CS C's. And I was like, oh, shit. And I said, can you just put me into the high exam? I said, no, no, you're going to fail. There's no chance. So my father, I'm in to Veein and said, you know, just let him go on the exams. And they said, he's definitely going to fail. It's a waste of time, waste of money. And he said, well, what if we paid? So they said, well, okay. So you didn't actually have to pay, you had to pay if I failed.

Starting point is 01:53:45 So I took the exams and passed them fortunately. I didn't get the top grades, but I got into A levels. But then that also kind of limited what I could do at A levels. I wasn't allowed to do A level maths. So I mean, you were allowed to. Because I had such a bad math grade from my GCSE, and I had a C,

Starting point is 01:54:03 but they wouldn't let me go into the ABC for math because of some kind of coursework requirement back then. So the top grade I could have got was a C, so C, dual E. So I got a C, and then let me do a kind of AS level math, which is this half intermediate and go university. But in the I could like chemistry, I had a good chemistry teacher, so in the end I got to university to chemistry. So through that kind of process, I think for kids in that situation, it's, it's easy to start believing that you're not, well, how do I put it? That you're stupid. And basically give up that you're just not good at math. You're not good at school. So this is by way of advice for people, for interesting

Starting point is 01:54:44 people, for interesting young kids right now Experience in the same thing. Where was the place? What was the source of you not giving up there? I have no idea other than I I was really I really like not understanding stuff. For me, when I not understand something, I didn't understand, I feel like I didn't understand anything. But now, but back then, I was so, I remember when I was like, I don't know,

Starting point is 01:55:15 I trialled, I tried to build a laser when I was like eight. And I thought, how hard could it be? Like, and I basically, I was going to build a CO2 laser. I was like, right, I think I need some partially coated mirrors and need some carbon dioxide. And I need a high voltage. So I kind of, and I was like, I didn't have a, and I was so stupid, right? I was kind of so embarrassed. I had to make enough CO2, I actually set fire and try to filter the flame. Oh, nice. The syrup to crack.

Starting point is 01:55:50 I've trapped enough CO2, and I was like completely failed, and I bent but half the garage down. So my parents were not very happy about that. But, so that was one thing. I was like, I really like first principle thinking, and so, you know, so I remember being super curious and being determined at finances. And so, when people do a give advice about this, why I ask for advice about this? I don't really have that much advice other than don't give up. And one of the things I try to do as a chemistry professor in my group is I don't hire people that I

Starting point is 01:56:29 think that, you know, I'm kind of home, I, if they're persistent enough, who am I to deny them the chance? Because, you know, people gave me a chance and I was able to do stuff. Do you believe in yourself essentially? I like, so I love being around smart people and I love confusing smart people. And when I'm confusing smart people, you know, not by stealing their wallets and hiding it somewhere,

Starting point is 01:56:52 but if I can confuse smart people, that is the one piece of hope that I might be doing something interesting. That's quite brilliant, because a gradient to optimize, hang out with smart people and confuse them. And the more confusing it is, the more there's something there. And as long as they're not telling you just a complete idiot,

Starting point is 01:57:11 and they give you different reasons. And I mean, I'm, you know, if everyone, it's like with assembly theory, and people said, oh, it's wrong. And I was like, why? And they're like, and no one could give me a consistent reason. They said, oh, because it's been done before, or it's just comagolar offer, or it's just there, that, and the other. So I think the thing that I like to do is, and in academia,

Starting point is 01:57:31 it's hard, right? Because people are critical, but I mean, you know, the criticism, I mean, although I got kind of upset about it earlier, which is kind of silly, but not silly, because obviously, it's hard work being on your own or with a team spatially separated like during lockdown and try to keep everyone on board and be in a have some faith that I've always wanted to have a new idea. And so, you know, I like a new idea and I want to nurture it as long as possible. And if someone

Starting point is 01:58:03 can give me actionable criticism, that's why I think I was trying to say earlier when I was kind of like stuck for words, give me actionable criticism. You know, it's wrong. Okay, why is it wrong? So it doesn't, your equations incorrect for this or your method is wrong.

Starting point is 01:58:20 And then say, so what I try and do is get enough criticism from people to then try and go back. And I've been very fortunate in my life that I've got great colleagues, great collaborators, funders, mentors and people that will take the time to say, you're wrong because. And then why you have to do is integrate the wrongness and go, oh, cool. Maybe I can fix that. And I think criticism is really good. People have a go at me because I'm really critical. And like, but I'm not criticizing, you know,

Starting point is 01:58:50 you as a person, I'm just criticizing the idea and trying to make it better and say, well, what about this? And, you know, and sometimes I'm kind of, you know, my filters are kind of, you know, truncated in some ways. I'm just like, that's wrong, that's wrong, that's wrong, what to do there. Some people are like, oh my God, you just told me, you destroyed my life's work, I'm like, relax, no, I'm just like, let's make it better. And I think that we don't do that enough, because we're, you know, we, we're, we're, we're either personally critical, which isn't helpful, or we don't give any criticism at all, because we're too scared. Yeah, I've seen you be pretty aggressively critical, but it's every time I've seen it's the idea and not the person. I'm sure I make mistakes on that. I argue lots with Sarah.

Starting point is 01:59:45 She's kind of shocked. I've argued with Yashar in the past. And he's like, you're just making Gashabark. And you're just making that up. I'm like, no, not quite. But kind of, I had a big argument with Sarah about time. She's like, no, time doesn't exist. I'm like, no, time does exist.

Starting point is 02:00:02 And now, as she realized, the her conception of assembly theory, and my conception of assembly theory was the same thing, necessitated us to abandon the fact that time is eternal, to actually really fundamentally question how the universe produces combinatorial novelty. So time is fundamental for some of the theory. I'm just trying to figure out where you insert a conversion. So I think assembly theory is fine in this time right now, but I think it helps us understand that something interesting is going on. So there's, and I'm really inspired by a guy called Nick Kizn.

Starting point is 02:00:39 I'm going to butcher his argument, but I love his argument a lot. So I hope he forgives me if he hears about it. But basically, if you want free will, time has to be fundamental. And we can go, and if you want time to be fundamental, you have to give up on plutononic mathematics, and you have to use intuitions, mathematics, by the way, and again, I'm going to butcher this, but basically Hilbert said that, you know, infinite numbers are allowed. And I think it was Browar, said no, you can't, all numbers are finite. So they're kind of like, we're, so let's go back a step because I was like, people are going to say,

Starting point is 02:01:27 assembly theory seems to explain that large commentorial space allows you to produce things like life and technology. And that large commentorial space is so big, is not even accessible to a Sean Carroll David Deutsch multiverse that physicists saying that all of the universe already exists in time is probably, provably, that's strong word, Not correct. The way I'm going to know that the universe, as it stands, the present, the way the present

Starting point is 02:02:10 builds the future, so big, the universe can't ever contain the future. And this is a really interesting thing. I think Max Techmark has this mathematical universe. He says, you know, the universe is kind of like a block universe. And I apologize to Max if I'm getting it wrong, but people think you can just move. You have the stat, you have the initial conditions, and you can run the universe right to the end

Starting point is 02:02:35 and go backwards and forwards in that universe. That is not correct. Well, let me load that in. The universe is not big enough to contain the future. Yeah, that's why. So that's another, that's a beautiful way of saying that time is fundamental. Yes, and that you can have,

Starting point is 02:02:51 and that's what, this is why the law of the excluded middle, something is true or false, only works in the past. Is it gonna snow in New York next week or in Austin? You might in Austin say, probably not in New York, you might say yeah. If you go forward to next week and say, did it snow in New York last week? True or false, you can answer that question. The fact that the law of the excluded middle cannot apply to the future explains why time is fundamental.

Starting point is 02:03:21 Well, I mean, that's a good example, intuitive example, but it's possible that we might be able to predict, you know, whether it's going to snow if we had perfect information. I think we're saying it not impossible. Impossible. So here's why. I'll make a really quick argument and this argument isn't mine. It's it'six and a few other people. Can you can you explain his view on fundamental and time being fundamental? Yeah, so I'll give my view, which kind of resonates with his, but basically it's very simple actually, he would say that free will, that your ability to design and do an experiment is an exercising free will. So he used that thought process. I never really

Starting point is 02:04:05 thought about it that way, and that you actively make decisions. I do think that I used to think that free will was a kind of consequence of just selection, but I'm kind of understanding that human free will something really interesting. And he very much inspired me, but I think that Sarah Walker said that inspired me as well, that these all converges that I think that the universe in the universe is very big, huge, but actually the place is largest in the universe right now, the largest place in the universe is Earth. Yeah, I've seen you say that. And boy, does that... That's an interesting one of the process.

Starting point is 02:04:50 What do you mean by that? Earth is the biggest place in the universe. Because we have this combinatorial scaffolding, going all the way back from Luka, so you've got cells that can self replicate, and then you go all the way to terraforming the Earth, you've got all these architectures, the amount of selection that's going on, biological selection, just to be clear, biological

Starting point is 02:05:09 evolution. And then you have multicellularity, then animals, and abstraction, and when abstraction, there was another kick, because you can then build architectures and computers and cultures and language. And these things are the biggest things that exist in the universe, because we can just build architectures that couldn't naturally arise anywhere, and the further that distance goes in time, and this kind of is just, it's gigantic. And from a complexity perspective.

Starting point is 02:05:39 Yeah, okay, wait a minute, but I mean, I know you're being poetic, but how do you know there's not other earth like, like how do you know? You're basically saying earth is really special. It's awesome stuff as far as we look out. There's nothing like it going on but how do you know there's not nearly infinite number of places where cool stuff like this is going on? I agree and I would say, I'll say again, that earth is the most gigantic thing we know in the universe, commentarily. We know. We know. Now. Now, I guess this is just purely a guess. I have no data, but other than hope. Well, maybe

Starting point is 02:06:18 not hope. Maybe, no, I have some data that every star in the sky probably has planets. Yep. And life is probably emerging on these planets. But the amount of contingency that is associated with life is that I think the commentorial space associated with these planets is so different. We are never going to, our causal cones are never going to overlap or not easily. And this is a thing that makes me sad about alien life, why we have to create alien life in the lab as quickly as possible.

Starting point is 02:06:51 Yeah. Because I don't know if we are going to be able to be able to build architectures that will intersect with alien intelligence and architectures. And just say, you don't mean in time or space. Time and the ability to communicate. The ability to communicate. Yeah. My biggest fear in a way is that life is everywhere,

Starting point is 02:07:15 but we become infinitely more lonely because of our scaffolding in that combinatorial space. Because it's so big. And because of... So you're saying the constraints created by the environment that led to the factory of Darwinian evolution are just like the little tiny cone in a nearly infinite combinatorial space. Exactly. So there's other cones like it. And why can't we communicate with other? Like just because we can't create it

Starting point is 02:07:46 Doesn't mean we can't appreciate the creation right like that Sorry detect the creation I I truly don't know but I it's an excuse for me to ask for people to give me money to make a planet simulator Yeah, right if I can make with a different I'm different like another shameless like give me money. I need to say. This was all a long plug for a planet simulator. It's like, hey, I won't be the first in my, to do it. My, my, my, my, Rick, my Rick garage has run out of room, you know? Yeah.

Starting point is 02:08:16 No, um, and this is a planet simulator, you mean like a different kind of planet? Yeah. Well, different sets of environments and pressures. Exactly. If we could basically recreate the selection before biology, as we know it, that gives rise to a different biology, we should be able to put the constraints on where I look in the universe. So here's a thing.

Starting point is 02:08:37 Here's my dream. My dream is that by creating life in the lab, based upon constraints, we understand. There's a go for Venus type life, or Earth type life, or something. Again, do upon constraints we understand. There's like, over Venus type life or Earth type life or something. Again, do f2.0, screw it, let's do f2.0. And f2.0 has a different genetic alphabet. Fine, that's fine. Different protein at alphabet, fine. Have cells and evolution and all that stuff.

Starting point is 02:09:00 We will then be out of say, OK, life is a more general phenomena. Selection is more general than what we think is the chemical constraints on life. And we can point to James Webb, another telescope to other planets that we are in that zone, we are most likely to combinatorially overlap with. Right? Because, you know, we basically, so they're a chemistry. You're looking for some overlap. And then we can then basically shine light on them literally and white look at light coming back

Starting point is 02:09:30 and apply advanced assembly theory to a general theory of language that we will get and say, Ha, we in that signal, it looks random, but there's a copy number. Oh, this random set of things that shouldn't be, that looks like a true random number generator has structure as a not common goaler of, AIT type structure, but evolutionary structure given by assembly theory, and we start to, but I would say that because I'm a shameless assembly

Starting point is 02:10:02 theorist. Yeah. It just feels like the cone that might be misusing the word cone here, but the width of the cone is growing faster. It's going really fast to where eventually all the cone's overlap. Even in a very, very, very large combinatorial space. It just, but then again, if you're saying the universe is also growing very quickly in terms of possibilities, that's right. I hope that as we build, as we build abstractions, the main, I mean, one idea is that as we go to intelligence,

Starting point is 02:10:47 intelligence allows us to look at the regularities around us in the universe, and that gives us some common grounding to discuss with aliens. And you might be right, that we will overlap there, even though we have completely different chemistry, literally completely different chemistry, that we will be at a past information from one another. But it's not a given. And I have to kind of try and divorce hope and emotion away from what I can logically justify. It's just hard to intuit a world, a universe

Starting point is 02:11:27 where there's nearly infinite complexity objects and they somehow can't detect each other. But the universe is expanding, but the nice thing is that I would say, I would look, you see, I think Carl Sagan did the wrong thing, well, not the wrong thing. He flicked the Voyager pro brand and it's a pale blue dot instead, look how big the universe is. I would've done it the way around it, He flicked the Voyager pro brand and it's a pale blue dot. Instead, look how big the universe is.

Starting point is 02:11:46 I was done it the way it ran. So look at the Voyager pro that came from the planet Earth that came from Luka. Look at how big Earth is. They produced that. It produced that. Yeah. And that I think is like completely amazing.

Starting point is 02:11:59 And then that should allow people on their have to think about, well, probably we should try and get causal chains, author, thanta mars, onto the moon, wherever. Well, it's human life or Martian life that we create, it doesn't matter. But I think this commentorial space tells us something very important about the universe. And I realized in the assembly theory that the universe is too big to contain itself. And I think this is, and now coming back and I want to kind of change your mind about

Starting point is 02:12:32 time because I'm guessing that your time is just a coordinate. So I'm going to change your mind. I'm going to change your mind in real time, at least attempt. Oh, in real time, there you go. I already got the tattoo, so this is going to be embarrassing in future. But you can just add a row of time onto it, right? Yeah, just a month. Or raise it a bit. So, and the argument that I think that is really most interesting is like, people say the initial conditions specify the future of the universe. Okay, fine. Let's say that's the future of the universe.

Starting point is 02:13:05 Okay, fine. Let's say that's the case for a moment. Now, let's go back to Newtonian mechanics. Now, the uncertainty between the Newtonian mechanics is this. If I give you the coordinates of an object moving in space and the coordinates of another object and they collide in space. And you know those initial conditions, you should know exactly what's going to happen.

Starting point is 02:13:30 However, you cannot specify these coordinates to infinite precision. Now everyone said, you know, oh, this is kind of like, you know, the KL Siri argument. No, no, it's deeper than that. Here's a problem with numbers. This is how this is where Hilbert and Browah fell out. To have the coordinates of this object, to give an old Joseph colliding, you have to have them to infinite precision. That's what Hilbert says. This is no problem. Infinite precision is fine. Let's just take that for granted. But when the object is finite and it can't store its own coordinates, what do you do?

Starting point is 02:14:11 So, in principle, if a finite object cannot be specified to infinite precision, in principle, the initial conditions don't apply. Well, how do you know I can't store it? Well, how do you store it? Infinitely long number in a finite size? well We're using infinity very loosely here. No, no, we use infinite precision. I mean not loosely But very precisely you think infinite precision is required well

Starting point is 02:14:40 Let's let's take the object to say the object is a golf ball Golf balls a few centimeters in diameter, we can work out how many atoms are on the golf ball. And let's say we can store numbers down to atomic dislocations. So we can work out how many atoms are on the golf ball and we can store the coordinates in that golf ball down to that number, but beyond that, we can't. Let's make the golf ball smaller. And this is where I think that we think that we get randomness in quantum mechanics, and some people say, you can't get random as quantum mechanics deterministic.

Starting point is 02:15:12 But aha, this is where we realize that classical mechanics and quantum mechanics suffer from the same uncertainty principle. And that is the inability to specify the conditional conditions to precise enough degree to give you determinism. The universe is intrinsically too big and that's why time exists. It's non-deterministic. Looking back into the past, you can look at the, you can use logical arguments because you can say, was it true or false? You really know. But this is the fact we are unable to predict the future with the precision is not evidence of lack of knowledge. It's evidence the universe is generating new things.

Starting point is 02:16:00 Okay, so to you, first of all quantum mechanics, you can just say statistically what's going to happen in two golf balls hit each other statistically for that but it but sure I can say statistic what's going to happen, but then what they do happen. Yeah, and then and then you keep nesting it together You can't I mean it goes almost back to look at look at look at let's think about entropy in the universe So how do you what how do we how do we understand? in the universe. So how do we understand entropy change? Well, we could do the look at or process. We can use the aggurdic hypothesis. We can also have, we can also have the counterfactuals where we have all the different states and we can even put that in the multiverse. States, and we can even put that in the multiverse, right? But both those are kind of, they're non-physical. The multiverse kind of collapses back to the same problem about the precision. So all that, what you, if you accept, you don't have to have true and false going forward

Starting point is 02:17:01 into the future, the real numbers are real. They're just, they're observables. We're trying to see exactly where time being fundamental sneaks in. In this difference between the golf ball can't contain its own position perfectly precisely. perfectly precisely. If how that leads to time needing to be fun. Let me, I've quit. Do you believe or do you accept you have free will? Yeah, I think at this moment in time, I believe that I have free will. So then you are then you have to believe that time is fundamental. I understand that's the state where you've made it. Well no, we can logically follow us because if you don't have free will, so like if you're in a universe that has no time, the universe is deterministic.

Starting point is 02:17:56 If it's deterministic, then you have no free will. I think the space of how much we don't know is so vast. That saying the universe is deterministic, from that jumping, there's no free will, is just too difficult to believe. No, I logically follows. No, no, I don't disagree. I'm not saying any, I mean, it's deep and it's important. All I'm saying, and it's the difference to, it's actually different what I've said before,

Starting point is 02:18:22 is that if you don't require platonistic mathematics and accept that non-determinism is how the universe looks, and that gives us our creativity in the way the universe is getting novelty, it's kind of really deeply important in assembly theory, because assembly theory starts to actually give you a mechanism why you go from boring time, which is basically initial condition, specify everything, to a mismatch in creative time. And I hope we'll do experiments. I think it's really important to, I would love to do an experiment that prove that time is fundamental and the universe is generating novelty. I don't know all the

Starting point is 02:19:02 features of that experiment yet, but by having these conversations openly and getting people to think about the problems in a new way, better people, more intelligent people, were good mathematical backgrounds, and say, oh, hey, I've got an idea. I'd love to do an experiment that shows that, universe is too big for itself going forward in time. And I really, you know, this is why I really hate the idea of the Boltzmann brain. The Boltzmann brain makes me super kind of like, you know, everyone's having a free lunch. It's like saying, it's like, let's break the laws of physics. So Boltzmann brain is this idea that in a long enough universe, a brain will just

Starting point is 02:19:43 emerge in the universe as conscious. Without neglect, the cause will change, evolution required to produce that brain. And this is where the computational argument really falls down because the computation is because I can calculate the probability of a Boltzmann brain. And I can, and they'll give you a probability, but I can calculate the probability of a Boltzmann brain, zero. Just because the space of our ability is so large. Yeah, it's like when we start falling ourselves with numbers, that we can't actually measure and we can't ever conceive of.

Starting point is 02:20:12 I think it doesn't give us a good explanation. And I've become, I want to explain why life is in the universe. I think life is actually novelty minor. I mean, life basically minds novelty, almost from the future, and makes it actualizes in the present. Okay, life is a novelty minor from the future that is actualized in the present.

Starting point is 02:20:42 Yep. I think novelty minor. First of all, novelty. What's the origin of novelty when you go from boring time to creative time? Where is that? Is it as simple as as randomness like you refer into? I'm I I'm really struggling around this because I had a really good argument with Yasha Bark about randomness.

Starting point is 02:21:07 Necesa said, randomness doesn't give you free will. That's insane because you just be random. But I think he's right at that level. But I don't think he is right on another level. And it's not about randomness. It's about constrained, I'm going to sound like constrained. I'm making this up. It's like, oh, I'm gonna sound looks constrained, I'm making this up as I go along, so making this up constrained opportunity.

Starting point is 02:21:30 So what I mean is like, so you have to have, so that the novelty, what is novelty? You know, this is what I think is the funny thing, you ever wanna discuss AI, why I think everyone's kind of gone AI mad mad is that they're misunderstanding novelty. But let's think about novelty. That's what is novelty. So I think novelty is a genuinely new configuration that is not predicted by the past, right? And that you discover in the present, right? And that is truly different, right? Now everyone says that some people

Starting point is 02:22:06 say that novelty doesn't exist. It's always with president. I want to do experiments that show that that is not the case. And it goes back to a question you asked me a few moments ago, which is, where is the factory? Right? Because I think the same mechanism that gives us a factory gives us novelty. And I think that that is why I'm so deeply hung up on time. I mean, of course I'm wrong, but how wrong? And I think that life opens up that common-torial space in a way that our current laws of physics, although as contved, in a deterministic initial condition universe, even with the get out of the multiverse, David Deutsch style, which I hate love, by the

Starting point is 02:22:51 way, but I don't think he's correct. But it's, it's kind of, it's really beautiful. I love it. The, the, the, David Deutsch's conception of the multiverse is kind of like given. But I think that the problem with wave particle, duality and quantum mechanics, is not about the multiverse, it's about understanding how determined the past is. Well, I don't think just think that actually this is a discussion I was having with Sarah about that, right? Which she was like, ah, I think we've been debating this for a long time now about how do we reconcile novelty to determinism in

Starting point is 02:23:33 determinism. It's okay, just to clarify, both you and Sarah think the universe is not deterministic. I won't speak for Sarah, but I think roughly, I think that the universe, I think the universe is deterministic looking back in the past, but undetermined going forward in the future. So I'm kind of having my cake and eat it, eating it here. This is because I fundamentally don't understand randomness, right? As Yasha told me or other people told me. But if I adopt a new view now, which the new view is the universe is just non-deterministic, but I'd like to refine that and say, the universe appears deterministic going back in the past, but it's undetermined going forward

Starting point is 02:24:18 in the future. So how can we have a determinist universe that has deterministically working rules? There's non-determined going in the future. It's this breakdown and precision in the initial conditions. And we have to just stop using initial conditions and start looking at trajectories and how the commentorial space behaves in expanding universe in time and space. An assembly theory helps us quantify the

Starting point is 02:24:46 transition to biology. And biology appears to be in novelty mining because it's making crazy stuff. You know, I'm that we are unique to earth, right? There are objects on earth that are unique to earth. They will not be found anywhere else because you can do the combinatorial math. What was that statement you made about life is novelty mining from the future? Yeah. What's the little element of time that you're introducing? What I'm kind of meaning is because the future is bigger than the present. In a deterministic universe, how do the states go from one to another?

Starting point is 02:25:22 I mean, there's a mismatch, right? That must mean that you have a little bit of indeterminism, whether that's randomness or something else, I don't understand. I want to do experiments to formulate a theory to refine that as we go forward, that my helpers explain that. And I think that's why I'm so determined to try and crack the non-life-life to life transition, looking at networks and molecules, and that might help us think about it, the mechanism. But certainly the future is bigger than the past, in my conception of the universe, and some conception of the universe. And... By the way, that's not obvious, right? That's what was just kind of the future being bigger than the past.

Starting point is 02:26:04 Well, that, that's one statement, and the statement that the universe is not big enough to contain the future is another statement. Yeah. Yeah, yeah, yeah. That one is a big one. That one's a really big one. I think so, I think it, but I think it's entirely, because look, we have the second law.

Starting point is 02:26:20 And right now, I mean, we don't need the second law if the future is bigger than the past. It follows naturally. Right. So why are we retrofitting all these, these sticking past is on to our reality to hold on to a timeless universe. Yeah, but that's because it's kind of difficult to imagine the universe that's, they can't contain the future. But it's not really exciting. It's very exciting, but it's hard. I mean, we're humans on Earth, and we have a very kind of four-dimensional conception of the world of 3D plus time.

Starting point is 02:26:59 It's just hard to intuit a world where, what does it even mean? A universe that can't contain the future. Yeah, it's kind of, it's kind of crazy, but obvious. I mean, I suppose it sounds obvious, yeah, if it's true. But the nice thing is you can, so the reason why assembly theory turned me onto that was that you, let's just start in the present and look at all the complex molecules and go backwards in time and understand how evolutionary

Starting point is 02:27:30 processes gave rise to them. It's not at all obvious. The tax-hole, which is a complex, one of the most complex natural products produced by biology, was going to be invented by biology. It's an accident. You know, taxile is unique to Earth. There's no taxile elsewhere in the universe. And taxile was not decided by the initial conditions. It was decided by this kind of this interplay between the, so the past simply is embedded in the present. It gives some features, but why the past doesn't map to the future, one to one, is because the universe is too big to contain itself. That gives space for creativity, novelty, and some things which are unpredictable.

Starting point is 02:28:19 Well, okay. So given that you're disrespecting the power of the initial conditions, let me ask you about what, so I'd explain that cellular terminaries are able to produce such incredible complexity, given just basic rules and basic initial conditions. I think that this falls into the Broward Hilbert trap. So how do you get a cellular automata-produced complexity? You have a computer, you generate a display, and you map the change of that in time.

Starting point is 02:28:51 There are some CAs repeat, like functions. It's fascinating to me that for Pi, there is a formula where you can go to the millionth decimal place of Pi and read out the number without having to go there. But there are some numbers. Well, you can't do that. You have to just crank through. Whether it's Wolframian computation or irreducibility or some other thing, that doesn't matter. But these CAs,

Starting point is 02:29:17 that complexity, is that just complexity or a number that is basically your mining that number in time. Is that just a display screen for that number, that function? Well, again, you see the same thing with a complexity on earth then? No, because the complexity on earth has a copy number and an assembly index associated with it. That CA is just a number running. You don't think it has a copy number? Wait a minute. Well, it does in the human, where we're looking at humans producing different rules, but then it's nested on selection. So those CAs are produced by selection. Yeah. I mean, the CAs such a fascinating pseudo complexity generator. What I would love to do is

Starting point is 02:30:00 understand, quantify the degree of surprise in a CA, right? That long enough. But what that, I guess that means is we have to instantiate, we have to have a number of experiments where we're generating different rules and running them time-spare steps. But, oh, I got it. CAs are mining novelty in the future, you know, in the future, by iteration, right? And you're like, oh, that's great. That's great. You didn't predict it. Some rules you can predict the what's going to happen. Other rules you can't. So for me, if anything, CAs are evidence that the the universe is too big to contain itself. Because otherwise, you'd know what the rules are going to do forever more.

Starting point is 02:30:36 Right. I guess you were saying that the physicists saying that all you need is initial conditions and the rules of physics is somehow missing the bigger picture. Perhaps, yeah. And if you look at CA's, all you need is the initial condition and the rules and then run the thing. You need three things. You need the initial conditions. You need the rules and you need time, iteration to mine it out.

Starting point is 02:31:04 Without the coordinate, you can't get it out. need time iteration to mind it out without the coordinate, you can't get it out. Sure. And that's that, that to use for them. And you can't predict it from initial conditions. If you could, then it'd be fun. And that time is a resource. A foundation of, this is the history, the memory of each of the things that created.

Starting point is 02:31:21 It has to have that memory of all the things that are led up to it. I think it's, yeah, you have to have the resource. Yeah. Because time is a fundamental resource. Yeah, I'm becoming, I think I had a major epiphany about randomness, but I keep doing that every two days and then that goes away again it's random. You're a time fundamentalist. You should be as well. If you believe in free will, the only conclusion is there is time as fundamental, otherwise

Starting point is 02:31:55 you cannot have free will. It logically follows. Well, the foundation of my belief of free will is just observation driven. But that's, I think if you use logic, it's like, logically seems like the universe is deterministic. Looking back was in time, and that's correct. The universe is. And then everything else is kind of leap. It requires a leap. I mean, I think that it's kind of, this is what I think machine learning is going to provide a big chunk of

Starting point is 02:32:36 that, right? Because it helps us explain this. So the way I say, if you take, that's interesting. Why? Well, let's, let let's just, um, my favorite one is because I'm, I'm the AI dooms are driving me mad. And in fact, that we don't have any intelligence. Yeah, I call AI autonomous informatics just to make people grumpy. Yeah. Um, and they're, you're saying we're quite far away from AGI. I think that we have no conception of intelligence. And I think that we don no conception of intelligence. And I think that we don't understand how the human brain does what it does.

Starting point is 02:33:09 I think that we are neurosciences making great advances, but I think that we have no idea about AGI. So I am a technological, I guess, optimist. I believe we should do everything. The whole regulation of AI is nonsensical. I mean, why would you regulate Excel, other than the fact that Clippy should come back and I love Excel 97 because we can play, you know, we can do the flight simulator. I'm sorry, Excel. Yeah, have you not played the flight

Starting point is 02:33:35 simulator in 97? Yeah. Was that look like? It's like wire frame, very, very basic, but basically I think it's X0, Y0, shift, and it opens up and you can play the fight simulator. Oh, wow. Well, is it using Excel? Excel, Excel 97. Okay. I resurrected it the other day and saw Clippy again for the first time in a long time.

Starting point is 02:33:59 Well, Clippy is definitely coming back. But you're saying we don't have a great understanding of what is intelligence, what is the intelligence. I am very frustrated. I'm underpinning the human mind. I'm very frustrated by the way that we're AI-Duming right now and people are bestowing some kind of magic. Now, let's go back a bit.

Starting point is 02:34:22 So you said, are we far away from AI? Yes, I do not think we're going to get to Agi anytime soon. I've seen no evidence of it. And the AI Doom scenario is nonsensical in the extreme. And the reason why I think it's nonsensical, but it's not non-s... And I don't think there isn't things we should do and be very worried about, right?

Starting point is 02:34:42 I mean, there are things we need to worry about right now, what AI are doing, whether it's fake data, fake users, right? I want authentic people, authentic data. I don't want everything to be faked and I think it's a really big problem and I absolutely want to go on the record to say, I really worry about that. What I'm not worried about is that some fictitious entity is going to turn us all to paper clips some fictitious entity is going to turn us all to paper clips or detonate nuclear bombs. I don't know. Maybe I don't know. Anything you can't think of. Why is this? I'll take a very simple series of logical arguments. And this is the AI dooms have not had the correct epistemology. They do not understand what knowledge is.

Starting point is 02:35:32 Until we understand what knowledge is, they're not going to get anywhere because they're applying things falsely. So let me give you a very simple argument. People talk about the probability, p-dume, AI. We can work out the probability of a asteroid hitting the planet. Why? Because it's happened before. We know the mechanism. We know that there's a gravity world or that space time is bent and stuff falls in. We don't know the probability of AGI because we have no mechanism.

Starting point is 02:35:59 So let me give you another one which is like, I'm really worried about AG. What's AG? AG is anti-gravity. One day we could wake up and anti-gravity, you know, is discovered. We're all going to die. The atmosphere is going to float away. We're going to float away. We're all doomed. What is the probability of AG?

Starting point is 02:36:16 We don't know because there's no mechanism for AG. Do we worry about it? No. And I don't understand the current reason for the, for certain people in certain areas to be generating this nonsense. I think they're not doing it maliciously. I think we're observing the emergence of new religions,

Starting point is 02:36:39 how religions come, because religions are about kind of some controls. So you've got the optimist saying, AI is gonna curisole, AI is going to kill us all. What's the reality? Well, we don't have AI. We have really powerful machine learning tools, and they will allow us to do interesting things.

Starting point is 02:36:53 And we need to be careful about how we use those tools in terms of manipulating human beings and faking stuff, right? Right. Well, let me try to sort of steal man the AI D ad rumors argument. And actually, I don't know. Our ad rumors in the Yadkowski camp saying it's definitely going to kill us because there's a spectrum. 95% I think is the limit. Yeah. And 95% plus. That's not not plus. I think I don't know. I was seeing on Twitter today various

Starting point is 02:37:20 things. But I think Yadkowski is at you. Yadkowski is at 95%. But to belong to the AI general club, is there a threshold? I don't know what the membership is. Maybe. And what are the fees? I think, well, I think it's got Aronson. Like I was quite surprised, I saw this online, so it could be wrong. So sorry if it's wrong, says 2%. But the thing is, if you were to, if someone said there's a 2% chance you can

Starting point is 02:37:44 die going into the lift. Would you go into the lift? In the elevator for the American English speaking audience. Well, no, not for the elevator. So I would say anyone higher than 2%. I mean, I think there's a 0% chance of AGI to zero. Just to push back on the argument where the end of zero on the AGI. We can see on Earth that there is increasing levels of intelligence of organisms.

Starting point is 02:38:10 We can see what humans with extra intelligence were able to do to the other species. So that is a lot of samples of data what a Delta in intelligence gives you. When you have an increase in intelligence, how you're able to dominate a species on Earth. And so the idea there is that if you have a being that's 10x smarter than humans, we're not going to be able to predict what that's going to. be able to predict what that's going to do. With that being, it's going to be able to do, especially if it has the power to hurt humans. You can imagine a lot of trajectories in which the more benefit AI systems give, the more control would give to those AI systems over our power grid, over our nuclear weapons, or weapons of any sort. And then it's hard to know what an ultra intelligence system would be able to do in that case.

Starting point is 02:39:10 You don't find that convincing. I think this is it. I would fail that argument 100%. Here's a number of reasons to fail it on. First of all, we don't know where the intention comes from. The problem is that people think they keep, you know, with all the, I think watching all the Huxters online with the prompt engineering and all this stuff. Where, when I talk to a typical AI computer scientist, they keep talking about the AIs having some kind of decision-making

Starting point is 02:39:36 ability. That is a category error. There's decision-making ability comes from human beings. We have no understanding of how humans make decision. We've just been discussing free will for last half an hour, right? We don't even know what that is. So the intention, I totally agree with you, people who intend to do bad things, can do bad things and we should not let that risk go. That's totally here and now. I do not want that to happen and I'm happy to be regulated to make sure that systems I generate, whether they're like computer systems or, you know, I'm working on a new project

Starting point is 02:40:11 called Chem Macchina. Nice. Well done. Yeah, yeah, which is basically a... For people who don't understand the point, the ex-market knife is a great film about, I guess, a GI embodied and chemistry version of that. And I only know one way to embody intelligence lasting chemistry in human brains. So category error number one is agents that they have agency.

Starting point is 02:40:37 Category error number two is saying that assuming that anything we make is going to be more intelligent. Now, you didn't say super intelligent. I'll put the words into our going to be more intelligent. Now you didn't say super intelligent. I'll put the words into our mouths here, super intelligent. That, I think that there is no reason to expect that we are going to make systems that are more intelligent. More capable, you know, when people play chess computers,

Starting point is 02:41:02 they don't expect to win now, right? They just, the chess computer, computer is very good at chess. That doesn't mean it's super intelligent. So I think that super intelligence, I mean, I think even Nick Bostrom is pulling back on this now, because he invented this, so I see this a lot. When did it see first happen? Eric Drexler, Nia Technology, atomically precise machines. He came up with a world where we had these atom cogs everywhere.

Starting point is 02:41:25 They were going to make self-replicating nano-bots. Not possible. Why? Because there's no resources to build these self-replicating nano-bots. You can't get the precision. It doesn't work. It was a major category error in taking engineering principles

Starting point is 02:41:39 down to the molecular level. The only functioning molecular technology we know, sorry, the only functioning nano-molecular technology we know, sorry, the only functioning now in molecular technology we know produced by evolution. There. Now let's go forward to AI. What is AI? We don't know, it's super, it can do this. Humans can't think that I would argue the only AI's that exist in the universe are produced by evolution. And sure, we may be, I may car working memory better, we may be able to make our working memory better. We might be able to do more things.

Starting point is 02:42:08 Human brain is the most compact computing unit in the universe. It uses 20 watts. It uses a really limited volume. It's not like a chat GPT cluster, which has to have thousands of watts, some model that's generated, and it has to be corrected by human beings. You are autonomous and embodied intelligence. So I think that there are so many levels that we're missing out.

Starting point is 02:42:30 We've just kind of went, oh, we've discovered fire. Oh gosh, the planet's just going to burn one day randomly. I mean, I just don't understand that leap. There are bigger problems we need to worry about. So what is the motivation? Why are these people, let's assume they have their earnest, have this conviction? Well, I think it's kind of, they're making leaps that, they're trapped in a virtual reality, that isn't reality. Well, I mean, I can continue to say arguments here, but also it is true that ideologies that fear monger are dangerous because you can then use it to control, to regulate in a way that calls progress, to control people, to cancel people, all that kind of stuff. So you have to be careful because you reason ultimately wins, right? But there is a lot of concerns with super intelligent systems very capable systems when you I think when I

Starting point is 02:43:31 When you hear the word super intelligent you're hearing like it's smarter than humans in every way that humans are smart but The paperclip manufacturing system doesn't need to be smart in every way. It needs to be smart in other specific ways. And the more capable the AI systems become, the more you could see us giving them control over, like I said, our power grid, a lot of aspects of human life. And that means they will be able to do more and more damage when there's unintended consequences that come to life. I think that that's right. The unintended consequences we have to think about and I'm that I fully agree with. But let's go back a bit. Sentient. I mean,

Starting point is 02:44:18 I'm going on far away from my comfort zone and all this stuff. But hey, let's talk about it because I'll give myself a qualification. Yeah, we're both qualified in sentience, I think. Yeah, so as much as anyone else. I think the paper clip scenario is just such a poor one because let's think about how that would happen. And also, let's think about we are being so unrealistic about how much of the earth's surface we have common dead. And you know, for paper mitt, clip manufacturing to really happen, I mean, do the math. It's like, it's not gonna happen. There's not enough energy, there's not enough resource where they're all gonna come from.

Starting point is 02:44:54 I think that what happens in evolution is really, why is a killer virus not killed out all of, not killed all life on earth? Well, what happens is, sure, super killer viruses that kill the ribosome have emerged. You know what happens? They nuke a small space because they can't propagate. They will die. So there's this interplay between evolution and propagation, right? And death. And so in evolution, it you know, it's possible to engineer, for example, sorry to interrupt, but like a perfect virus. No. There's deadly enough.

Starting point is 02:45:25 No. No, it's not insensical. Okay. I think that just wouldn't, again, it wouldn't work. It was too deadly. It would just kill the radius and not replicate it. Yeah. I mean, you don't think it's possible to get a...

Starting point is 02:45:36 You know, I mean, if you were soup, I mean, I... If you were... I... I kill all of life on Earth, but kill all humans. There's not many of us. There's only like all humans. There's not many of us. There's only like 8 billion. There's so much more ants. I mean, I don't, I, so many more ants.

Starting point is 02:45:53 And they're pretty smart. I think we, the nice thing about what we, where we are, I would love for the AI crowd to take a leaf out of the book of the bio warfare, chemical warfare crowd. I mean not love because actually people have been killed with chemical weapons in the first and second world war and people and bio weapons have been made and you know we can argue about COVID-19 and all this stuff. Let's not go

Starting point is 02:46:17 there just now. But I think there is a consensus that some certain things are bad and we shouldn't do them. Right. And sure, it would be possible for a bad actor to engineer something bad, but the damage would be, we would see it coming and we would be able to do something about it. Now I guess what I'm trying to say is, people talk about doom and they just when you ask them for the mechanism they just say, you know, they just make something up. I mean, in this case, I'm, we Yann LeCoon. I think we put out a very good point about trying to regulate jet engines before we've even vented them.

Starting point is 02:46:59 And I think that's what I'm saying. I'm not saying we should, I just don't understand why these guys are going round, making, literally making stuff up about us all dying. When basically we need to actually really focus on, now let's say there's some actors are earnest, all right, let's say Yodakowski has been earnest, right? And he really cares. But he loves it, he goes, and then you're all gonna die.

Starting point is 02:47:23 It's like, you know, why don't we try and do the same thing, say, you could do this, and then you're all going to be happy forever after. Yeah. Well, I think there's several things to say there. One, I think there is a role in society for people that say, well, I'm going to die. As I think it filters through as a message, as a viral message, that gives us the proper amount of concern. Okay. all right.

Starting point is 02:47:46 Meaning not the, it's not 95%, but when you say 95% and it filters through society, you'll give an average of like a 0.03% an average. So it's nice to have people that are like, we're all going to die, then we'll have a proper concern. Like, for example, I do believe we're not properly concerned about the threat of nuclear weapons currently. Like, it just seems like people have forgotten that that's the thing.

Starting point is 02:48:13 And, you know, there's a war in Ukraine with the nuclear power involved. There's nuclear power throughout the world. And it just feels like we're in the brink of a potential world war to a percentage that I don't think people are properly calibrating like in their head. We're all thinking it's a Twitter battle as opposed to like actual threat. So like it's nice to have that kind of level of concern.

Starting point is 02:48:37 But to me like what I when I hear AI rumors what I'm imagining is with unintended consequences, a potential situation where, let's say, 5% of the world suffers deeply because of a mistake made of unintended consequences. I don't imagine the entirety of human civilization dying, but there could be a lot of suffering if this is done. I understand that. And I kind of, I guess, I mean, I'm involved in the whole hype cycle.

Starting point is 02:49:06 Like why I would like us to, I don't want us to, so what's happening right now? Is there seems to be, so let me, let's say, having some people saying AI, AI, do him is a worry. Fine, let's give them that.

Starting point is 02:49:21 But what seems to be happening is there seems to be people who don't think AI is doing. They're trying to use that to control regulation and to push people to regulate which stops humans generating knowledge. And I am an advocate for generating as much knowledge as possible. When it comes to nuclear weapons, I grew up in the 70s and 80s where the nuclear doom, a lot of adults really had existential fear. Almost as bad as now with AI do, they were really worried, right? There was some great, well not great, there was some horrific documentaries, I think there's one called

Starting point is 02:49:54 Fred's that was generated in the UK, wishing it was like, it was terrible, it was like so scary. And I think that the correct thing to do is obviously get rid of nuclear weapons, but let's think about unintended consequences. We've got rid of, this is the social non-secretary, we've got rid of all the sulfur particles in the atmosphere, right, or the, or the sir. And what's happened in the last couple of years is global warming is accelerated because we've cleaned up the atmosphere too much. So, sure, I mean, the same thing if you get rid of a new co-op as you can do.

Starting point is 02:50:27 Exactly. That's my point. So what we could do is if we actually started to put the AI in charge, which is I really like an AI to be in charge of all world politics. And this sounds ridiculous just like it hang on. But if we could all agree on the... Yeah, I do. We're just woke up. Yeah, yeah, yeah. That statement. But I really don't like politicians who up. Yeah, yeah, yeah. That statement.

Starting point is 02:50:45 But I really don't like politicians who are basically just looking at local sampling. But if you could say globally, look, here's some game theory here. What is the minimum number of nuclear weapons we need to distribute around the world to everybody? To basically reduce war to zero. I mean, just the start experiment of the United States and China and Russia and major nuclear powers get together and say, all right, we're going to distribute nuclear weapons to everybody. Every single nation on earth.

Starting point is 02:51:14 Yeah. Oh, boy. I mean, that has a probably greater than 50% chance of eliminating major military conflict. Yeah, but it's not 100%. But I don't think anyone will use them. Because I think, I think, and look, what you've got to try and do is, to qualify for these nuclear weapons, this is a great idea. The game theorist could do this, right? I think the question is this. I really buy your question, we have too many nukes. From just from a feeling point of view

Starting point is 02:51:48 that we've got too many of them. So let's reduce the number, but not go rid of them because we'll have too much conventional warfare. So then what is the minimum number of nuclear weapons we can just do it around to remove, what humans hurting each other is something we should stop doing.

Starting point is 02:52:03 It's in, it's not out with our conceptual capability, but right now, what about the nation's, certain nations that are being exploited for their natural resources in the future because for a short term gain because we don't want to generate knowledge. And so if everybody had an equal doomsday switch, I predict the quality of life

Starting point is 02:52:24 that every human will go up faster. I am an optimist and I believe that humanity is going to get better and better and better, that we're going to eliminate more problems. But I think yeah, let's but the probability of a bad actor of one of the nations setting off a nuclear weapon. I mean, you have to you have to integrate that into the, but we, we, we get, we just give you the new knooks like population, right? We give what we do is we, but anyway, let's just just go there. Let's say, so if a, if a small nation,

Starting point is 02:52:58 with a couple of knooks, uses one because they're a bit bored or annoyed, they're going to, they, the likelihood that they're likely to be pummeled out of existence, immediately, is 100%. And yet, they've only nuked one other city. I know this is crazy, and I apologize. Well, no, no, I think it's just to be clear, we're just having a thought experiment that's interesting, but there's terrorist organizations that would take that trade. Yeah, I mean, I'm, and we have to ask ourselves a question of how many, which percentage of humans would be suicide bombers essentially? Where they would sacrifice their own life to, to, uh, because they hate another group of people.

Starting point is 02:53:40 And that, I believe it's a very small fraction, but is it large enough to, uh, if you give out nuclear weapons? I can predict a future where we take all nuclear material when we burn it for energy, right? As we're getting there and the other thing you can do is say, look, there's a gap. So if we get all the countries to sign up to the virtual nuclear agreement where we all exist, we have a simulation where we can nuke each other in the simulation and the economic consequences are catastrophic. where we can nuke each other in the simulation and the economic consequences are catastrophic. Sure, in the simulation, I love it. It's not gonna kill all humans,

Starting point is 02:54:08 it's just going to have economic consequences. Yeah, yeah. I don't know, I just made it up. It seems like it's interesting. I mean, it's interesting whether that would have as much power in human psychology as actual physical nuclear. I think so.

Starting point is 02:54:22 It's possible, but people don't take economic consequences. I seriously think as actual nuclear weapons. physical nuclear. It's possible, but people don't take economic consequences as seriously, I think, as actual nuclear weapons. I think they're doing Argentina, and they do in Somalia, and they're doing a lot of these places where, no, I think this is a great idea. I'm a strong advocate now for, so what have we come up with? Burning all the nuclear material to have energy. And before we do that, because Mad is good, mutually assured destruction is very powerful. Let's take it into the metaverse and then get people to kind of subscribe to that. And if they actually nuke each other, even for fun in the metaverse, there are dire consequences. Yeah. Yeah. So it's like a video game. We're all

Starting point is 02:55:01 to join this metaverse video game. Yeah. I can't believe it's our economic consequences. I don't know how and it's all run by AI as you mentioned. So the AI tumors are really terrified at this point. Now they're happy to have a job for another 50 years, right? Oh, I'll be fear mongering. Yeah, yeah, yeah. I'm a believer in equal employment. You've mentioned that, what you call, cam machiner.

Starting point is 02:55:28 Yeah. Yeah. So you've mentioned that a chemical brain is something you're interested in creating. And that's the way to get conscious AI soon. Can you explain what a chemical brain is? I want to understand the mechanism of intelligence that's gone through evolution, right? Because the way that intelligence was produced by evolution appears to be the following.

Starting point is 02:55:55 Origin of life, multicellularity, locomotion, sensors, once you can start to see things coming towards you and you can remember the past and interrogate the present and imagine the future. You can do something amazing, right? So, and I think only in recent years did humans become cheering complete. Right? Yeah. Yeah. Right, and we'll go and so that cheering completeness kind of gave us another kick up. But our ability to process that information is produced in a wet brain.

Starting point is 02:56:40 And I think that we are not getting going, we do not have the correct hardware architectures to have the domain flexibility and the ability to integrate information. I think intelligence also comes at a massive compromise of data. Right now we're obsessing about getting more and more data, more and more processing, more and more tricks to get dopamine hits. So when we look back on this, going, oh yeah, that was really cool because when I've checked our chat GPT, it made me really feel really happy. I got a hit from it, but actually it just exposed how little intelligence I use in every moment, because I'm easily fooled. So what I would like to do is to say, well, hey, hang on, what is it about the brain?

Starting point is 02:57:25 So, the brain has this incredible connectivity, and it has the ability to, you know, as I said earlier, about my nephew, you know, I just went from Bill to Billy and he went, alright, Leroy. Like, how did he make that leap? Then he was able to basically, without any training. I extended his name, he went gay, and he doesn't like. He wants wants me called Bill, he went back and said, you like to be called Lee, I'm going to call you Leroy. So human beings have a brilliant ability or intelligent beings appear to have a brilliant ability to integrate across all domains all at once

Starting point is 02:58:01 and to synthesize something which allows us to generate knowledge and becoming cheering complete on our own. I don't, although AI is a built and cheering complete thing, their thinking is not cheering complete, in that they are not able to build universal explanations. And that lack of universal explanation means that they're just inductivists. Inductivism doesn't get you anywhere. It's just basically a party trick. It's like, I think it's in the fabric

Starting point is 02:58:35 of reality from David Deutsch, where basically the farmer is feeding the chicken every day and the chicken's getting fat and happy. And the chicken's like, I'm really happy. Every time the farmer comes in, it feeds me, and then one day the chicken every day and the chicken is getting fat and happy. The chicken is like, I'm really happy every time the farmer comes in and feeds me and then one day the farmer comes in and doesn't, instead of feeding the chicken, just rings its neck. You know, and that's kind of, and the chicken had an alternative understanding of why the

Starting point is 02:58:57 farmer was feeding it. It's interesting, though, because we don't know what's special about the human mind and the table to come up with these kind of generalities This universal theories of things so that's what come up with novelty. I can imagine because you gave an example in you know about William and Leo I I feel like Example like that will be able to see in future versions of large language models will be really, really, really impressed by the humor, the insights, all of it, because it's fundamentally

Starting point is 02:59:37 trained on all the incredible humor and insights that's available out there on the internet, right? So we'll be impressed. I think we'll be impressed. Oh, I'm impressed. Oh, I'm impressed. Right. I'm impressed. Increasingly so. But we're mining the past.

Starting point is 02:59:50 Yes. And what the human brain appears to be out of do is mine the future. Yes. So novelty, it is interesting whether these large language models will ever be able to come up with something truly novel. I can show on the back of a piece of paper

Starting point is 03:00:04 what that's impossible. And it's like the problem is that, and again, this domain experts kind of bullshitting each other. The term generative. Yes. Right? Average person, they're, oh, it's gen- it's no, no, no. If I take the numbers between 0 and 1000, and I train a model to pick out the prime numbers by giving them all the prime numbers between 0 and 1000 and I train a model to pick out the prime numbers

Starting point is 03:00:25 by giving them all the prime numbers between 0 and 1000. It doesn't know what prime number is. Occasionally, if I can cheat a bit, it will start to guess. It never will produce anything out with the dataset because you mind the pass. The thing that I'm getting to is I think that actually current machine learning technologies might actually help reveal why time is fundamental. It's like I'm even saying because they tell you about what's happened in the past, but they can never help you understand what's happening in the future without training examples.

Starting point is 03:00:56 Sure, if that thing happens again, it's like, so I think, so let's think about what large learning models are doing. We have the, we have the the, we have all the internet as we know it, you know, language, but also they're doing something else. We're having human beings correcting it all the time. Those models are being corrected. Steered. Corrected. Modified.

Starting point is 03:01:20 Tweaked. It's, well, yeah, but, but I mean cheating. Well, you could say that training on human data in the first place is cheating. Well, let me, but humans in the loop, sorry, I'm trying to. Yes. So human is definitely in the loop. But it's not just human is in the loop. A very large collection of humans is in the loop. Look, I'm turning it.

Starting point is 03:01:43 And that could be, I mean, mean to me it's not intuitive that you said prime numbers that the system can generate an algorithm, right? That the algorithm that can generate prime numbers or the algorithm that can tell you for numbers, and so on. And generate algorithms that generate algorithms that generate algorithms that that start to look a lot like human reasoning, you know, I don't think I think again we can show that on a piece of paper that sure I think that has you have to have so this is the failure in epistemiology like I'm glad I even say that word that and what it means for us is set of multiple times I know it's like three times now without failure

Starting point is 03:02:21 that word, that name, what it means. That's what I said multiple times. I know, it's like three times now. Without failure. Oh, you're a quid while you're ahead. Stop saying it again. All right. You did really well. It thanks.

Starting point is 03:02:31 So, but I think the, so what is reasoning? So coming back to the chemical brain, if I could basically, if I could show the inner, because I mean, I'm never going to make an intelligence in in cam macchina, because we don't have brain cells. They don't have guile cells. I don't have neurons. But if I can make if I can take a matric gel and engineer the gel to have it be a hybrid hardware for reprogramming, which I think I know how to do, I will be at a process a lot more information and train

Starting point is 03:03:01 that they train models billions of times cheaper and use cross-domain knowledge. And there's certain techniques I think we can do, but they're still missing, though the abilities of human beings have had to become true and complete. And so I guess the question to give back at you is like, how do you tell the difference between trial and error? And the generation of new knowledge. I think the way you can do it is this is that you come up with a theory and explanations, inspiration comes from out. Yeah.

Starting point is 03:03:35 And then you then test that. And then you see that's going towards the truth. And human beings are very good at doing that in the transition between philosophy, mathematics, physics, and natural sciences where where, and I think that we can see that. Where I get confused is why people misappropriate the term artificial intelligence to say, hey, there's something else going on here, because I think you and I both agree, machine learning is really good. It's only can get better, we can get happier with the outcome. But why would you ever think the model is thinking or reasoning, reasoning requires intention. And the intention, if

Starting point is 03:04:17 the model isn't reasoning, the intention has come from the prompt, and the intention has come from the person who programmed it to do it. So I, um, but don't you think you can prompt it to have intention, basically start with the initial conditions and get it going, where the, you know, currently large language models, chat GPT only talks to you when you talk to it. There's no reason why you can't just start it talking. But those initial conditions came from someone starting it. And that calls a chain in there. So that intention comes from the outside.

Starting point is 03:05:00 I think that there is something in that calls causal chain of intention that's super important. I don't disagree we're going to get to AGI. It's a matter of when and what hardware. I think we're not going to do it in this hardware, and I think we're unnecessarily fetishizing really cool outputs and dopamine hits, because obviously that's what people want to sell us. Well, but there could be, I mean, AGI is a lot of term, but there could be incredibly I mean, AGI is a loaded term, but there could be incredibly super

Starting point is 03:05:25 and impressive intelligence systems on the way to AGI. So these large language models, I mean, if it appears conscious, if it appears super intelligent, poor we'd to say it's not. I agree, but the super intelligence I want, I want to be able to have a discussion with it about coming up with fundamental new ideas that generate knowledge. And if the super intelligence would generate, can my level even the future that I didn't see in its training set in the past, I would agree that something really interesting is coming on. I'll say that again, if the intelligent system, if a human being, a chat bar, something else is able to produce something truly novel that we could not predict even

Starting point is 03:06:16 having full audit trail from the past, then I would be sold. Well, so we should be clear that it can currently produce, it can currently produce things that are in a shallow sense novel that are not in the training set, but you're saying truly novel. I think they are in the training set. I think everything it produces comes from a training set. They might be in turn. There's a difference between interpreting novelty and interpolation.

Starting point is 03:06:42 We do not understand where these leaps come from yet. That is what intelligences I would argue. Those leaps, and some people say, no, it's actually just what will happen if you just do cross-domain training and all that stuff, and that may be true, and I may be completely wrong. But right now, the human mind is able to mind novelty in a way that artificial intelligence systems cannot, and this is why we still will have a job and we're still doing stuff. And, you know, I used chat GBT for a few weeks, well, this is cool.

Starting point is 03:07:09 And then it took me two, I had to, well, what happened is it took me too much time to correct it, then it got really good. And now they've done something to it. It's not actually that good. Yeah, right. I don't know what's going on. That's a good answer, yeah.

Starting point is 03:07:20 Yeah, it's so, I mean, that's interesting, but it will push us humans to characterize novelty better like characterize the novel like what is novel? What is truly novel? What's the difference to novelty and interpolation? I think that this this is the thing that makes me most excited about these technologies is they can help me Demonstrate to you that time is fundamental and the unit future is bigger than the than the present Which is why why we are human beings are quite good at generating novelty because we have to expand our data set. And to cope with unexpected things in our environment, our environment throws them all

Starting point is 03:07:56 at us. Again, we have to survive in that environment. And I mean, I'd never say never, I would be very interested in how we can get cross-domain training cheaply in chemical systems, because I'm a chemist and can't break the only thing I know of is human brain, but maybe that's just me being boring, predictable, and not novel. Yeah, you mentioned GPD for election audacity. So a GPD like system for generating molecules that can bind to host automatically? I mean, that's interesting. That's really interesting. Applying this same kind of transform mechanism. Yeah, I mean, this is one of, it goes my team. I try and do things that are non obvious,

Starting point is 03:08:40 but non obvious in certain areas. And one of the things I was always asking about in chemistry, people like to represent molecules as graphs. And it's quite difficult. It's really hard. And if you're doing AI in chemistry, you really want to basically have good representations. You can generate new molecules. They're interesting.

Starting point is 03:08:57 And I was thinking, well, molecules aren't really graphs. And they're not continuously differentiable. Could I do something that was continuously differentiable? I was like, well, molecules are actually made up of electron density. So they got thinking, say, well, okay, could there be a way where we could just basically take a database of readily solved electron densities

Starting point is 03:09:17 for millions of molecules? So we took the electron density for millions of molecules and just trained the model to learn what electron density is. And so, what we built was a system that you literally could give it a, let's say you could take a protein, a particular active site or, you know, a cup of the certain whole in it, you pour noise into it and with a GPT you turn the noise into electron density. And then, in this case, it hallucinates like all of them do.

Starting point is 03:09:46 But hallucinations are good because it means I don't have to train on such a large number, such a huge data set, because these data sets are very expensive, because how do you produce it? So go back a step. So you've got all these molecules in this data set. But what you've literally done is a quantum mechanical calculation where you produce electron densities reach molecule. So you say, oh, this representation of this molecule in this dataset. But what you've literally done is a quantum mechanical calculation,

Starting point is 03:10:05 we produce electron densities for each molecule. So you say, oh, this representation of this molecule has these electron densities associated with it. So you know what the representation is and you train the neural network, you know what electron density is. So then you give it an unknown pocket. You pour in noise and you say, right, produce me electron density, produces electron density that doesn't look ridiculous. And what we did in this case is we produce a electron density that maximizes the electrostatic potentials to the stickiness, but minimizes

Starting point is 03:10:34 what we call the steric hindrance of the overlap, so it's repulsive. So you know, make the perfect fit. And then we then use the kind of a trend, kind of like a chat GPT type thing to turn that electron density into what's called a smile. A smile string is a, is a, is a, a way of representing a molecule and letters. And then we can then, it's just generates them, just generates them. And then the other thing is,

Starting point is 03:10:57 and we bang that into the computer, and then it just makes it. Yeah. The computer being the thing that, right, that the good general. We've got the can basically just do chemists. So kind of we've kind of got this end-to-end drug discovery machine where you can say, oh, you want to buy into this active site. Here you go. I mean, it's a bit leaky and things kind of break, but it's a proof of principle. Well, what were the hallucinations? What are those still accurate? Well, the hallucinations are really great in this case, because in the case of a large average model, the hallucinations just like just make everything up to when it doesn't just make everything up, but it gives you an output that you're plausibly comfortable with.

Starting point is 03:11:34 Yeah. But things you're doing probabilistically. The problem on these earth-ondensity models is it's very expensive to solve a shredding equation going up to many heavy atoms and large molecules. And so we wondered if we trained the system on up to nine heavy atoms, whether it would go beyond nine. And it did. It started to generate molecules of 12. No problem. They looked pretty good.

Starting point is 03:12:01 And I was like, well, this hallucination I will take for free. Thank you very much because it just basically, this is a case where interpolation, extrapolation, worked relatively well. And we were able to generate the really good molecules. And then what we were able to do here is, and this is a really good point, what I was trying to say earlier, that we were able to generate new molecules

Starting point is 03:12:23 from the known data set that would bind to the host. So a new guest would bind. Were these truly novel? Not really, because they were constrained by the host. Were they new to us? Yes. So I do understand, I can concede that machine learning systems, artificial intelligence systems can generate new entities, but how novel are they? It remains to be seen. Yeah, and how novel the things that humans generate is also difficult to quantify. They seem novel. That's what a lot of people say. So the way to really get to genuine novelty, and assembly theory shows you the way, is to have different causal chains overlap. And this really resonates with the time is fundamental argument. And if you're bringing together

Starting point is 03:13:27 is fundamental argument. And if you're bringing together a couple of object objects with different initial conditions coming together, when they interact, the more different their histories, the more novelty they generate in time going forward. And so it could be that genuine novelty is basically about mix it up a little. And the human brain is able to mix it up a little and the human brain is able to mix it up a little and all that stimulus comes from the environment. But all I think I'm saying is the universe is deterministic going back in time, non deterministic going forward in time because the future is the universe is too big in the future to contain in the present. Therefore, these collisions of known things generate unknown things that then become part of your data set and don't appear weird.

Starting point is 03:14:10 That's how we give ourselves comfort. The past looks consistent with this initial condition hypothesis, but actually we're generating more and more novelty. And that's how it works. Simple. So, it's hard to quantify novelty looking backwards. I mean, the present and the future of the novelty generators. But I like this whole idea of mining novelty.

Starting point is 03:14:30 I think it is going to reveal why the limitations of current AI is a bit like a printing press, right? Everyone thought that when the printing press came, that writing books is going to be terrible, that you had evil spirits and all this, they were just books. And same with AI. But I think they're just a scale you can achieve

Starting point is 03:14:53 in terms of impact with AI systems is pretty never-acting. But that's what the big companies want you to think. But not like in terms of destroy all humans, but you could have major Consequences and the way social media has had major Consequences both positive and negative and so you have to kind of Think about and worry about it, but yeah people that fear monger, you know my pet theory Yeah, for this you want to know yeah, is I think that a lot and maybe I'm being and I think I really do respect, you know, a lot of the people out there who are trying to have discourse about the positive future.

Starting point is 03:15:31 So open AI guys, meta guys and all this. And what I wonder if they're trying to cover up for the fact that social media has had a pretty disastrous effect at some level. Yeah. And they're just trying to say, yeah, we should do this because covering up for the fact that we have got some problems with teenagers and Instagram and Snapchat and all this stuff and maybe they're just overreacting now. Yeah. It's like, oh, yeah, sorry, we made the bubonic

Starting point is 03:15:57 played and gave it to you all and you were all dying and oh, yeah, but look at this over here, it's even worse. Yeah, there's a little bit of that, but there's also not enough celebration of the positive impact that all these technologies have had. We tend to focus on the negative and tend to forget that it, in part because it's hard to measure, like it's very hard to measure the positive impacts which are made ahead on the world.

Starting point is 03:16:20 Yeah, I agree. But what I worry about right now is like, I'm really, I do care about the ethics of what we're doing and then one of the reasons why I'm so open about the things we're trying to do in the air, make life, look at intelligence, all this is so people say, what are the consequences of this. And you say, what the consequences are not doing it. And I think that what worries me right now in the present is lack of authentic AI users and authentic data and human users. Yeah, human. I still think that there will be AI agents that appear to be conscious, but they would have to be also authenticated and labeled as such. There's too much value in that, you know, like friendships with AI systems. There's too much meaningful human experiences to have with the AI systems that I just... But that's like a tool right. It's a bit like a meditation tool right?

Starting point is 03:17:12 Sure. Some people have a meditation tool, it makes them feel better, but I'm not sure you can ascribe, certainly, and some legal rights to a chatbot that makes you feel less lonely. Essentially, yes, I think legal rights, no. I think it's the same. You can have a really deep meaningful relationship with a dog. And with a dog set in.

Starting point is 03:17:32 Yes. The chat box, not what right now, using the technology we use, is not going to be sent in. Ah, there's going to be a fun, continue conversation on Twitter that I look forward to. Since you've had also, from another place, some debates that were inspired by the Assembly Theory paper, let me ask you about God. Is there any room for notions of God in Assembly Theory? I was God. Yeah, I don't know what God is a, I mean, so God exists in our mind created by selection. So human beings have created the concept of God in the same way that human beings have

Starting point is 03:18:17 created the concept of superintelligence. Sure, but does it mean, does it not, It still could mean that that's a projection from the real world with like we're just assigning words and concepts to a thing that is Fundamental to the real world that there is something out there That is a creative force underlying the universe Um, I think the universe it there is a great force in the universe, but I don't think it's sent in. I mean, I think the, so I do not understand the universe. So who am I to say, you know, that God doesn't exist? I am an atheist, but I'm not an angry atheist, right? I have lots of...

Starting point is 03:19:07 I have lots of... There's some people I know that are angry atheists, and say, you know... Thank you. ...that say that religious people are stupid. I don't think that's the case. I have faith in some things, because I don't... I mean, when I was a kid, I kept like... I was like... I need to know what the charge of electron is like, I can't measure the charge charge of electron. That was, you know, I just gave up and had faith. Okay, you know, resistors worked. So when it comes to, I want to know why the universe is growing in the future

Starting point is 03:19:35 and what humanity is going to become. And I've seen that the acquisition of knowledge via the generation of novelty to produce technology has uniform made humans lives better. I would love to continue that tradition. And you said that there's that creative force. Do you think, just to think on that point, do you think there's a creative force? Like, is there like a thing, like a driver that's a driver that's creating stuff?

Starting point is 03:20:07 Yeah, I think that, so I think that... And where? What is it? So I can describe it like Mathematical. Well, I think selection. I think selection is the force. Selection is the force in the universe that creates novelty. So is selection somehow fundamental?

Starting point is 03:20:23 Like what? Yeah, I think persistence of objects that could decay into nothing through operations that maintain that structure. I mean, think about it. If it's amazing that things exist at all, that we're just not a big commentorial mess. Yes. So the fact that there exist a thing that exists persistent time. Yeah. Maybe the universe is actually in the present,

Starting point is 03:20:52 the things everything that can exist in the present does exist. What that would mean is deterministic, right? No, I think the universe is mic, so the university started super small. The past was deterministic. There wasn't much going on. And it was able to mind, mind, mind, mind, mind. And so the process, I mean, is somehow generating, um, the university is basically, I can't, I'm trying to put this into work.

Starting point is 03:21:24 Did you just say there's no free will though? No, I didn't say that. I mean, I can't put this into words. Did you just say there's no free will though? No, I didn't say that. As if I, I mean, I can't exist. I said there is free will. I think I think I, I, I, I'm saying that free will occurs at the boundary between the, the present future, the past and the future. Yeah, I got you, but everything that can exist does exist.

Starting point is 03:21:45 Everything that is, so everything that's possible to exist at this, so no, I'm really putting a lot of loaded words there. So what I mean is there's a time element loaded into that. I think that the universe is able to do what it can in the present, right? Yeah. And then I think in the future there are other things that could be possible. We can imagine lots of things, but they don't all happen. Sure.

Starting point is 03:22:08 So that's what I guess we're doing. That's what you're doing. Sneaking free will right there. Yeah. So I guess what I'm saying is what what exists is a. Com is a convolution of the past with the present and the free will going into the future. Well, we can still imagine stuff, right? We can imagine stuff from the wrap.

Starting point is 03:22:25 And it's amazing force because you're imagining this is the most important thing that we don't understand is our imaginations can actually change the future in a tangible way, which is what the initial conditions and physics cannot predict. Your imagination has a causal consequence in the future. Isn't that weird too?

Starting point is 03:22:48 Yeah. How do you... It breaks the laws of physics as we know them right now. Yeah. So you think the imagination is a causal effect in the future. Yeah. But it does exist in there in the head.

Starting point is 03:23:06 There must be a lot of power in whatever is going on. There could be a lot of power in whatever is going on in there. If we then go back to initial conditions, and that's simply not possible, that can happen. But if we go into a universe where we accept that there is a finite ability to represent numbers and you have rounding, we're not rounding errors, you have some, that the sum, what happens, the, your ability to make decisions, imagine and do stuff is that that interface between the certain and the uncertain, it's not as yasha was saying to me randomness goes and you just, you know, randomly do random stuff. It is that you are set free a little on your trajectory. Free will is about being able to explore

Starting point is 03:23:49 on this narrow trajectory that allows you to build, you have a choice about what you build, all that choice is you interacting with a future in the present. What do you most beautiful about this whole thing? The universe. The fact it seems to be very undecided, very open, and the fact that every time I think I'm getting to answer to a question, there are so many more questions that make the

Starting point is 03:24:22 chase. Do you hate that it's going to be over at some point? No, for me. So, I think if you think about it, is it over for Newton now? Newton has had causal consequences in the future. We discuss him all the time. He's had ideas, but not the person. The person just had a lot of causal power when he was alive, but oh my God, one of the things

Starting point is 03:24:47 I want to do is leave as many Easter eggs in the future when I'm gone to go, oh that's cool. Would you be very upset as somebody made a good, large language model that's fine tuned to Lekona? It would be quite boring, because I mean, I mean, I'm a... No novelty generation. I mean, if it's a faithful representation of what I've done in my life, that's great.

Starting point is 03:25:08 That's an interesting artifact. But I think the most interesting thing about, I mean, each other's, we don't know what we're gonna do next. Sure. Sure. I mean, within some constraints, I've got, you know, you might, I can predict some things about you, you can predict some things about me.

Starting point is 03:25:24 We can't predict everything. And it's because we can't predict everything is why we're exciting to come back and discuss and see it. So yeah, I'm kind of happy that it will be interesting that some things that I've done can be captured, but I'm pretty sure that my Angle one mining novelty for the future will not be captured. Yeah, yeah That's what life is is just some novelty generation than you've done Each one of us just generally a little bit I think think the capacity to do at least. I think life is a selection produces life and life affects a universe. Universes with life in them are materially, physically, fundamentally different than universes of our life.

Starting point is 03:26:19 And that's super interesting. And I have no beginnings of understanding. I think maybe this is like in a thousand years there'll be a new discipline in the humans we are. Yeah, of course, this is how it all works, right? And in retrospect, there will all be obvious, I think. I think a 70 theories obvious. That's why a lot of people got angry, right? They were like, oh my god, this is such nonsense. Yeah. You know, like, oh, you know, actually it's not quite. But the writing's really bad.

Starting point is 03:26:47 Well, I can't wait to see where it evolves. Lee, and I'm glad I get to exist in this universe with you. You're a fascinating human. This is always a pleasure. I hope to talk to you many more, many more times. And I'm a huge fan of just watching you create stuff in this world, and thank you for talking today. It's a pleasure to always like to thanks for having me on. Thanks for listening to this conversation with League of Thrones. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Carl Sagan.

Starting point is 03:27:19 We can judge your progress by the courage of our questions and the depth of our answers. Our willingness to embrace what is true rather than what feels good. Thank you for listening, and hope to see you next time. you

Lex Fridman Podcast - #404 – Lee Cronin: Controversial Nature Paper on Evolution of Life and Universe

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