#404 – Lee Cronin: Controversial Nature Paper on Evolution of Life and Universe

28:23Yeah. 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, you don't have to work sequentially. You can work in parallel. You can get your friends together and they can. 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. An 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.

29:09And 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'm maybe like, well, I'm always leaping out of my compass. 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. But 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 re -adjusts and finds a new shortest path.

29:49But the shortest path isn't fixed on just one molecule now. It's in the actual existence of the object over 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, probably should go back to molecules. But hey, 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.

30:33And then a sum from one to n, where n is the total number of unique objects. 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?

31:15And in minus one, just to make sure that I'm more than one object, one object could be a one off and random. Yep. And then you have more than one identical object, that's interesting. When there's one, 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 don't we talk about selection? What is this term selection? What is this term evolution that we're referring to? Which aspect of Darwinian evolution are we 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 did what it did is it kind of annoyed.

31:55We didn't know it. I mean, it got intention. And obviously angry people, the angry people were annoyed. There's angry people in the world. That's good. So what happened is the evolutionary biologists 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 no enough chemistry in there.

32:30Then 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. And then they said a few physics is the beginning and the end of the story. Yeah. So what happened is a reason why people put the phone down on the call of the paper. I mean, 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.

33:04Scientists have grappled with reconciling biological evolution with the immutable laws of the universe defined by physics. True. Right. 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 is paper was accepted and published in Nature. The title is assembly theory explains and quantifies selection and evolution, very humble title. And the the entirety of the paper, I think, presents interesting ideas, but reaches high.

33:47I 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, 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.

34:31There's 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 abstract, 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.

35:11And secondly, a lot of evolutionary biologists seem to dismiss the origin of life questions, I say is 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, but hang on. 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.

35:51So 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. So 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, you need, so this is where 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, and an existing environment that could destroy other, and I'm going to use anthropomorphic terms, I apologize, that weaker objects, or less robust, then the environment could have selected that.

36:52So 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. So it survives in that environment. So the acid pond, the molecule, the resistent molecule can get through. And then that molecule goes into another environment. So that environment now may be being an acid pond, it's a basic pond, or maybe it's an oxidizing pond.

37:36And 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 happens when an object survives in an environment for some time. But, and this is the thing that's 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 is about the process and time that makes it because a rock could just stand on the mountainside for four billion years and nothing happened to it.

38:14And 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 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 protofactory, the environment.

38:56So 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, evolved, and made resistant robusts. Because in biology, selection and evolution is robust. That you have error correction built in. You have really, there's good ways of basically making sure propagation goes on. So really the difference between inorganic, abiotic selection, evolution, and evolution and stuff in biology is robustness.

39:38The ability to propagate over the ability to survive in lots of different environments. Whereas our poor little inorganic, so 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.

40:34And I would like to think that this paper could be very wrong. But I don't think it's very wrong. It meets certainly wrong, but it's less wrong than some other ideas. And if this allows 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 are 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 to identify at the higher end advanced selection.

41:21What you get I record in biology, you super advanced selection. And even, I mean, you could use the 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 this is a really simple for experiment I could do is you have a little petri dish. And on that petri dish you put some simple food. So the assembly index of all the sugars and everything is quite low. So then and you put a single eco cell of E.

41:56coli cell. And then you say, I'm going to I'm going to measure the assembly and this amount of assembly in the box. So it's quite low. But the 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 now the coli'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 E.

42:35coli factory has just eaten fruit, milled lots of other E. coli factory and 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, you know, we try and kill the molecules. And really that's the main kind of idea for the entire paper.

43:14Yeah, 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 seeing identical copies.

43:55You 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 higher the assembly index. So if you go to Mars and you take a mass spec or high enough resolution and you can find molecules and I'll give a 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. And now you would say, oh, maybe the geological process, I would argue very vehemently that that is not the case.

44:32But we can say, look, if you don't like the cutoff on Earth, go up higher, 30, 100, right? Because that's going to be a point where you can find a molecule so many different parts, the chances of you getting a molecule that has 100 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. I always understood the copy number was really important, but I never explained it properly for ages.

45:22I kept having this, it goes back to this, if I give you 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? 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 yeah, something like a factory that's operating under a selection process is there should be copies.

46:22Is 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. And so at the maximum resolution, so in the nice thing about the nice thing about chemists is they have this concept of the molecule and they are all familiar with the molecule and molecules you can hold, you know, on 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's number of molecules and they're identical. What does that mean?

46:56That means that the 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. You pick one out of the bag and you basically observe it using some technique and then you put it, 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, molecules can be in different vibrational or rotational states, they're moving all the time.

47:31So through 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 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 detect the left and the right hand, they become different. 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.

48:10Yeah. So like you're talking about chemistry a lot today. We have kind of standardized detection systems of how to compare molecules. So 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 that are largest scale of the molecules. Like what detection, if we look at the difference in you and me, lexanly, are we the same? Are we different? Sure. I mean, of course, we're different close up. But if you zoom out a little bit, morphologically look the same. Yeah. You know, high characteristics, hair lengths, stuff like that.

48:57Well, also like the species and yeah, yeah, yeah. And also there's a sense why we're both from Earth. Yeah, I agree. I mean, this is the power of assembly theory in that regard that you, 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 indistinguishable, then it's telling you that you have to go to another resolution. So that would be, it's kind of a sliding scale. It's kind of nice. So those two kind of are attention with each other.

49:40Yeah, the number of copies on the assembly index. Yeah. That's really, really interesting. So, okay. So you show up turning your planet, you'll be doing what? I would do mass back how it brings on a sample of what? First of all, how big of a scoop do you take? Did you take a scoop? Like what? So we're looking for primitive life. I would, I would look, yeah. So if we're just going to Mars or Titan or Enceladus or somewhere, so the number of ways are 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, ASU Paul Davies, keeps calling it a life meter.

50:27A life meter, which is quite a nice idea because you think about it. 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? So okay, we found it. So what you can do is a mass spectrometer, you could just look for things in the gas phase or you're going to surface drill down because you want to find molecules that are where you've either got to find the source living system because the problem with just looking for complexity is it gets burnt away.

51:17So 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 into soil that's billions of years old. Then I would put in some solvent, water, alcohol or something or take a scoop, put it in, make it volatile, put it into the mass spectrometer and just trying to 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.

51:56Now we want to keep the life meter, keep searching for more and more complexity until you actually find living cells. You can get those new living cells and then, 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 on the gradient of the life meter. How would you build the 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. Just take it. No, no, but that's that's one of the major components of it. But I'm talking about like, if it's a device, we've got it in branding logo, we've got to talk about that later.

52:30But what's the input? What's the like, how do you get to the, I'm a meter output. So I would take a life, so my life meter, our life meter, thank you. You're welcome. I 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. The volatiles would then be put into the into the mass spectrometer into electrostatic trap and you'd weigh the molecules and fragment them.

53:20Alternatively, you'd shine infrared light on them, you count number of bands, 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 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. The Lexus life meat, Lexus leaves. No, absolutely. 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.

53:57So you would take your sample, add it onto the nose, add a solvent or a gas, it would then be sucked up the nose and that would be separated using chrome, what we call chromatography. And then as each band comes off the nose, we would then do mass spec and infrared. And in the 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.

54:29And then right up to the batshit crazy, this is definitely, you know, eagerly an 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 is really problematical is that for many years decades, what people have done, and I can't blame them, is there's rather, there've been obsessing about small biomarkers on that we find on earth, amino acids, like single amino acids or evidence of small molecules and these things. And looking for those, run looking for complexity, that would have been, if it, beautiful thing about this is you can look for complexity without earth chemistry bias or earth biology bias.

55:12So assembly theory is just a way of saying, hey, complexity and abundance is evidence selection. That's how our universal life meter will work. Complexity in abundance is evidence of selection. Okay, so let's apply our life meter to earth.

55:35So 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 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 going to work. And it was just like, because the chemists were saying, of course, there are complicated molecules out there, you can detect that just form randomly. I was like, really, that's like, that was like, you know, 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.

56:19It 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, it really had some big arguments, but the copy number 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.

56:54Okay. 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. Yeah. Exactly. So on earth, to come back to earth, what we did is we took a whole bunch of samples, 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 in assembly theory. Where in this in our life machine, we're looking at molecules. We don't care about polymers, because they don't, they don't volatile, you can't hold them.

57:37They're not like, how, how can you make, if you can't discern that they are identical, then it's very difficult for you to, to, to work out if this undergone selection, or they're just around a mess, same with some minerals, but we can come back to that. So basically what you do, we got a whole load of samples inorganic ones. We got a load of, we got Scotch whiskey, and also got, it took a hard bag, which is one of my favorite whiskeys, which is very peaty, and another whisks, it's peaty, means. So the way that on, in Scotland in Eilert, which is a little island, the Scotch, the whisky is, let to mature in barrels, and the, the, it said that the peak, the, the, the, the complex molecules in the peat, might find their way through into the whisky, and that's what gives it this intense brown color, and really complex flavor, is literally molecular complexity that does that.

58:34And so, you know, vulca is the complete opposite, it's just pure, right? So the, what are the whisky, the higher the semi -index, the higher the semi -index, the better the whisky. That's what I mean, I really love deep, peaty Scottish whiskeys. Near my house, there is a, like, one of the, the lowland distilleries called Glen Goin, it's still beautiful whisky, but not as complex. So for fun, I cooked some Glen Goin whiskey in our bag and put them into the mass spec at Measure the Assembly Index. I also got Ecoli, so the way we do it, take the Ecoli, break the cell apart, take it all apart, and also got some beer, and, and people were ridiculing us saying, oh, beer is evidence of complexity, one of the, 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 complicate than human.

59:30We didn't realize is that 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, you'll see if there's anything over the fresh old. 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, you know, they gave us some super complex samples, and they gave us two fossils, one that was a million years old, and one was at 10 ,000 years old, see something from Antarctica, see bed, they gave us an merious and meteorite and a few others.

1:00:10Put them through the system, so we took all the samples, treated them all identically, put them into mass spec, fragmented them, counted, 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, 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 abartic samples 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're like, oh gosh, yep, dead, living, dead, living, you got it.

1:01:03And that's what we found on Earth. That's a success. Yeah, oh yeah, resounding success. Well, can you just go back to the beer and the Ekoi? 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 Ekolyse sample. So the yeast and the beer. 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. No, nobody's listening. Well, is that we've just mapped the tree of life using assembly theory, because everyone said, oh, that you can't do infan biology.

1:01:53And what we're able to do is, so I think there's three way, well, two ways of doing tree of life traffic, well, three ways actually. 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, what, 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, the fungi, exist the kingdom, you know, and different, and different branches all the way up. And the way this was classically done, and I'm no evolutionary biologist, the evolution biologist, a very, tell me every day, at least 10 times.

1:02:31I want to be one though. I kind of like biology. It's kind of cool, but yeah, it's very cool. But basically, what Darwin and Mendeleev and all these people do is just they draw pictures, right? And they, they tax it. They just, they were able to draw pictures and say, and say, oh, these look like common classes. Then, they're artists really, invertebrates, camera and explosion, and all this stuff. And then, then came the genomic revolution. 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.

1:03:14It's amazing. So you have taxonomy, you have sequencing, and you can also do a little bit of 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, we took a 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 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.

1:04:02All right. Can you try to say that again, with a little more detail? So, recreating, what does it take to recreate the tree of life? What does the reverse engineering process look like here? So what you do is you take an unknown sample, you pung 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, you don't just see, it's not, it's not that the most sophisticated cells 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.

1:04:40So 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, 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.

1:05:23But what, 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've been able to do. And by basically looking at the assembly spaces, these molecules create without any knowledge of assembly theory, you are unable to do it. With knowledge of assembly theory, you can reconstruct the tree. How does, how does knowing if they're the same or different, give you the tree?

1:06:00Let'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 that origin was. And that's all we do. And it just works. But when we realized you could even use a assembly theory 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 no longer exist? I mean, the tree contains information about the past. I would, some of it is gone. Yeah, yeah, absolutely. I would love to get old fossil samples and apply assembly theory mass spec and see if we can find new forms of life that have, that are no longer amenable to gene sequencing because the DNA is all gone.

1:06:46There'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, doing the proper extraction to reek 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 we can, and it appears that you can do some dating. Now, there are really good techniques as radiocarbon dating. There is longer dating going looking at radioactive minerals and so on.

1:07:27And you can also, in bone, you can look at the, what happens in, after something dies, is the, you get what's called rastomization where the chirality in the polymers basically changes and you just get, you get decomposition. And the rate of, the deviation from the pure inantium to the mixture, you can have a, you give you a time, time scale on it, 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 and molecules. Do you think it's possible? Oh, yeah. Without doubt. It may not be better than what, because like, the, I was just at conference, whereas some brilliant people were looking at isotope and enrichment and, and looking at how life and, and riches isotopes and they're really sophisticated stuff that they're doing.

1:08:22But I think there's some fun to be had there because we give you another dimension of dating. How old is this molecule? In terms of, in, or 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, the, the amount of carbon 13 and you goes up. Because of the, because of the way the metabolite, because of the way the, the bonding is in, in carbon 13. So it has a slightly different strength, bond strength, and you, is called a kinetic isotope effect.

1:09:01So you can literally date how old you are, you know, or when you stop metabolizing. So you could date someone's death. 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, all this person is 10 years old and this person is 30 years old because they'll be metabolizing more carbon and they've accumulated it. That's the basic idea. It's probably completely wrong timescale. Signatures of chemistry are fascinating.

1:09:34So 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 assembly theory to that? At the moment, we're, we should be able to do this to morphology in cells. So we're looking at cell surfaces and really trying to extend further. It's just that, you know, 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.

1:10:24So, yeah, so was it mean for a penny? No, the penny's dropped, right? Because a lot of people are 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. 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, if I have a publishing of people and people want people to read it, I want to write that badly again.

1:10:59I 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. That's, and then it can overfire, it can do a lot of damage, it can shut down conversations in a way that's not productive. 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 the clarity. Let's go there before we go to the hierarchy.

1:11:29You 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 it would origin of life was a solve 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. And we need, there's a gap. That was really, for me, that misunderstanding and that that did cause an immune response, which was really interesting.

1:12:18The second thing was the fact that physicists, the physicists were actually really polite, right? Really nice about it. But they just said, we're not really sure about the initial conditions thing, but this is a really big debate that we should certainly get into because, you know, the emergence of life was not encoded in the initial conditions of the universe. And it can't, and I think assembly theory shows why it can't be. I'll say that. Okay. Sure. If you could say that again. The origin of the emergence of life was not and cannot, in principle, be encoded in the initial conditions of the universe.

1:12:57Just a clear follow me in my life is like what high assembly index objects. Yeah. And this goes back to your favorite subject. What's that time?

1:13:09Right. So why? So why, what does time have to do with it? Well, we, I mean, probably we can come back to it later, but I think it might be, if we have time. But I think that 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 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 back there.

1:13:55So we can go to the atomic mathematics. Okay. Hey, there's okay. The evolution of biologists criticize because the origin of life is understood. And not it doesn't require an explanation of the involves physics. Yeah. Yeah. They basically statement. Well, I mean, it was, I think they said lots of confusing statements. Basically, I realized the evolutionary biology community that were vocal and some of them really rude, really spiteful and needlessly so, right? Because like, you know, I didn't, people really misunderstand publication as well. Some of the people has said, how dare this be published in nature?

1:14:39This is, you know, how to call it 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? I'm like, no, no, no, this is not hype. We're not, we're not like saying we've invented some, I don't know, we've discovered it 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.

1:15:21We 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 cheering machine blah, blah, blah, blah, blah, a concrete series of statements that can be falsified and explored. And either the theory could be destroyed or built upon. Well, what about the criticism of you're just putting a bunch of sexy names and something that's already obvious? Yeah, that's really good.

1:16:05So, 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 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 organizational 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.

1:16:48Oh, by the way, I had this idea 20 years before. I was like, which one? Is it your rubbish part or the really revolutionary part? So this kind of plucked two strings at once. It plucked the, there is something interesting. The 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 this obvious, why have you not done it? Sure, but there's a few things to say there. One is this is in part of philosophical framework because it's not like you can apply this generally to any object in the universe.

1:17:36It's very chemistry focused. Yeah, well, I think you will be able to. We just haven't got their robustly. So we can say, how can we, let's go up a level. So we go up from level, we go up, let's go up from molecules to cells because you jump to people and I jump to emoticons and both are good and they will be a symbol. Let's look what cells. Yeah, let's go from it. If we go from, so if we go from molecules to assemblies and let's take a cell or assembly, a nice thing about a cell is you can tell the difference between a eukaryote and a prokaryote. Right? The organelles are specialized differently.

1:18:09We 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. Now, if you think about how embryos develop, you go all the way back, those cells undergo differentiation in 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, whoa, we apply it to culture, but clearly you can apply it to memes and culture and we've also applied assembly theory to CAs and not as you think.

1:18:55Cellular terminology. Yeah, yeah, yeah, to say what I'm not just as you think, we're different CA rules were 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 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.

1:19:30So what do we need to do to apply assembly theory to things? We need to agree there's a common set of building blocks. So in a cell, well, in a multicellular creature, you need to look back in time. So there is the initial 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 rules and inside the cell. So we're building up. But obviously I want a leap to things like emoticons, language, mathematical theory.

1:20:15But that's a very large number of steps to get from a molecule to the human brain. 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 numbers and then let's look at a brain in a whale or a dolphin or a chimpanzee or a bird, say, okay, let's look at the assembly indices, number of features in these. And now the copy numbers, just a number of what how many birds are there?

1:20:54How many chimpanzees are there? How many humans are there? 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? 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 number.

1:21:31And 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 or possible brains or 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.

1:22:07What would be amazing is if you can use assembly 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 the data ahead of time, just kind of like you do with NASA that you able to demonstrate that it applies in those other contexts. I mean, 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?

1:23:01Yeah, 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, not mundane, but a fairly mechanical way. Because before now, 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 collaborating right now, we already think we can do assembly theory on language. And not only that, wouldn't it be great if we can, so that if we can figure out how under pressure language is going to evolve and be more efficient because you're going to want to transmit things.

1:23:42And again, it's not just about compression, it is about understanding how you can make the most of the, the architecture you've already built. And I think this is something beautiful that evolution does with, we're 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. And I think that's, that's a key comment I want to make is that assembly theory is great for understanding where evolution has been used. The next jump is when we go to technology because of course, if you take the M3 processor, I want to buy, I haven't bought one yet, I can't justify it, but I want to at some point, the M3 processor arguably is, there's quite a lot of features, a quite large number, the M2 came before it, then the M1 all the way back.

1:24:31You can apply assembly theory to micro processor architecture. It doesn't take a huge leap to see that. I'm a Linux guy, by the way, so your examples go away. Is that a fruit company or some sorry? I don't even know. Yeah, there's a lot of interesting stuff to ask about language. You could look at how that work. You could look at GPT1, GPT2, GPT3, 354, and try to analyze the kind of language it produces. I mean, that's almost trying to look at assembly index of intelligent systems. 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 comes from all the people that produced all the language.

1:25:31That's really interesting, and all the corrections in the mechanical Turk.

1:25:39That'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. 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. 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?

1:26:25What do you mean by telling us, though? You seem to associate intelligence with history. Yeah, well, I think selection produces intelligence. You're almost implying that selection is intelligence. No. Yeah, kind of. I would go out and limit 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. This is what Darwinian selection, because the human being doesn't have to basically do trial and error. They can think about it. They say, oh, that's a bad idea. When do that? And then technologies and so on. We escaped Darwinian evolution, and now we're onto some other kind of evolution.

1:27:06I guess higher level level. And assembly theory will measure that as well, right? Because it's all lineage. Okay. Another piece of criticism, or by way of question, how is assembly theory, or maybe assembly index different from Commodore of complexity? So for people who don't know, Commodore complexity of an object is the length of a shortest computer program that produces the object as output. Yeah, I seem to, there seems to be a disconnect between the computational approach. So yeah, so Commodore off 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.

1:28:02There's a main thing there. There are lots of other layers. So so Commodore off complexity, you can you can approximate Commodore off 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 the turtle in this case as the computer. And so what assembly theory does is I'm going to say, this is a trigger warning for anyone listening who loves complexity theory. I think that we're going to show that AIT is a very important subset of assembly theory because here's what happens that I think that assembly theory allows us to build, understand when with 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.

1:29:04The frustration I've had with, with looking at life through this kind of information theory is it doesn't take into account causation. So the main difference between assembly theory and all these complexity measures is there's no cortisol chain. And I think that's the main. As the causal chain is at the core of assembly theory. Exactly. If you're in, if you've got your data in a computer memory, all the data is the same. You can access it in the same type way. You don't care. You just compress it and you either look at the program runtime or the shortest program. And that for me, it is absolutely not capturing what it is, what its selection does.

1:29:50But assembly 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, the object doesn't have a Wikipedia page that goes with it. 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. What assembly theory allows you to do with just what the object is to and the word infer is correct. I agree with him. You're like, say, well, that's not the, that's not the history. But something really interesting comes from this.

1:30:32The 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 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 is just to say, it's just to say, hey, there was a factory.

1:31:20How 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. So if you take say, imagine so one of the things we're doing right now is applying assembly theory to drug discovery. Now, what everyone's doing right now is taking all the proteins and looking at the proteins and and looking at molecules, docker proteins. Why not instead take the, look at 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.

1:32:09And then use that to constrain your drug discovery process. You flip the problem, one AIT and focus on the molecule evolution rather than the protein. And so you can guess in the future what might happen. 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 at an assembly space as for an object where you don't know the entire history, but you know that, you know, in the history of this object, it's not going to have some other motif that there that doesn't apply, 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?

1:32:54No. The molecules and the, no, I mean, I don't know enough about protein. 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 react, this is not correct reaction. It's like, no, it's a graph.

1:33:14Sure, 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 constraints on that graph. Of course, there has 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 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?

1:33:55So, 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 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?

1:34:34How 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, 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 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 chemical reactions exist? I'm writing a paper right now that I keep being told I have to finish.

1:35:10It's called the origin of chemical reactions. And it merely says that reactivity exists as control by the laws of quantum mechanics. And we put names, chemists put names on reactions. 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 fact they're on planet Earth, 1G, 298 Kelvin, 1 bar. So, these are constraints. They're also constrained by the chemical composition of Earth, oxygen, availability, all this stuff.

1:35:50And 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, bomb, bomb, bomb, bomb, 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, which means that bond has to give the molecule certain half -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.

1:36:33When you 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 bi biology. There was no chemist in the origin of life, 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 occur, do exist.

1:37:14Okay, okay. So, it's constraint -application. So, there's no chemical reactions. It's all constraint application, which enables the emergence of the, of what's the different word for chemical reaction? Transformation. Yeah, like a function. It's a function. But no, but I love chemical reactions in a shorthand. And so the chemists don't all go mad. I mean, of course chemical reactions exist on earth. It's a shorthand for these constraints. For it right. So, assuming all these constraints that we've been using for so long, that we just assume that that's always the case in natural language conversation.

1:37:52Exactly. The premise of chemistry, of course, emerges in reactions. And we can use them reliably. But I do not think the vitic reaction is accessible on Venus. Right. And this is useful to remember, you know, 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 something with theory. That's interesting. That's really interesting. But we've also pissed off the chemists now. Oh, I'm pretty happy. But what most of them, everybody, everybody deep down is happy. I think there's just sometimes feisty.

1:38:33That's how they show. That's how they have fun. Everyone is grumpy on some days when when you challenge the problem with this paper is you what is 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, find, offend everyone at the meeting simultaneously. Even the, 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.

1:39:02Maybe just a little insider interesting information. What were the editors of Nisha, what their reviews and so on, how difficult was that process? This is a pretty big paper.

1:39:18When we originally sent the paper, we sent the paper and the editor said, this was a quite a long process. We sent the paper and the editor gave us some feedback and said, I don't think is that interesting. It's hard concept. We asked and the editor gave us some feedback and Sarah and I took a year to rewrite the paper. Was the nature of the feedback very specific on this part or was it like, what are you guys smoking? What kind of were polite in this promise? Yeah, well, the thing is the, the editor was really critical, but in a, but in a really professional way. And I mean, for me, this was the way science should happen.

1:40:12So when it came back, you know, we had too many equations in the paper. If you look at the preprint, they're just equations everywhere, like the 23 equations. And when I said to Abyshek, he was the first author, we got to remove all the equations. But my assembly equations, saying Abyshek was like, you know, no, we can't. I said, well, look, if we want to explain this to people, it's a real challenge. And so Sarah and I went through the, I think it 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.

1:40:42We knew the entire, amazing. And we just went spit by bit by bit. So what is 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 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. Right. And there's by a chemist, you just said, I don't believe you, you must be committing fraud. A long story, probably a boring story.

1:41:18But in this case, it went out to review. The comments came back and the comments were incredibly, they were very, there were very deep comments from all the reviewers. There were, and 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, 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 pretty quick. And the other went, yeah, it's in. Well, maybe you could just comment on the whole process.

1:42:03You've published some pretty huge papers and all kinds of topics with the chemist chain 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. So, you know, it's not a mundane paper. So, where, what's it like psychologically to go through all this process to keep getting 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, what, 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 a assembly theory at the highest level.

1:42:48The Nature Communications paper we on the mass spec on the, on the idea went through, went to nature and got rejected, went through six rounds of review and got rejected. And, and it, and it's, and I, I just was so confused when the, when the chemist said this can't be possible. I do not believe you can measure complex user mass spec and also by the way molecules, 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, 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?

1:43:31What's behind that never giving up? Is it 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 of the, you know, the, the comments or the you totally don't get it. Like, what gives you strength to keep going there? Yeah, I don't know.

1:44:02I don't normally get emotional about papers, but, um, 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, um, so why I did, so why I would just try to be as, as, as, um, as rational as possible and say, yeah, you didn't like it. Um, tell me why. And then, um, sorry, I'm sorry. Silly. Never get emotional about papers normally, but, but you, but I think what we do, you just, you just compress like five years of angst from this. So it's been, it's been rough. It's not just rough. It's like, it happened, you know, I came up with the assembly equation, you know, remote from Sarah in Arizona and the people, SFI, I feel like I was a mad person, like, you know, the guy in depicted in, you know, in a beautiful mind, he was just like, not, not the actual genius part, but just the, just the, just the, just the, just the, because I kept writing expanded and I have no mathematical ability at all.

1:45:28And I was expand, I was making these mathematical expansions where I kept seeing the same motif again. I was like, oh, I think this is a copy number, the same string is coming and going again and again. I kept, I couldn't do the math. And then I realized the copy number fell out of the equation, and everything collapsed down. I was like, oh, that works kind of. So we submitted the paper. And then when it was almost accepted, right, the mass spec one, and it was astrobiologists, a great, you know, a mass spectroscopist said great. And the chemist went nonsense, like biggest pile of nonsense ever fraud, you know.

1:46:00And I was like, but why fraud? And they just said, just because. And I was like, well, and so, so, and the, and I could not convince the editor in this case, the editor was just so pissed off, 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, but, but I guess. Beautiful. But it was just trying to understand why they didn't like it. So they were part of me was like really devastated. And a part of me was super exciting.

1:46:39I'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 in a kind of learning difficulties class and I kept going to the teacher and say, you know, you know, how, 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, 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, anything like this or the, the reviewers, they kept it strictly like factual.

1:47:13And all I did is I just kept knocking it down bit by bit by bit by bit by bit. It was ultimately rejected and it got published elsewhere. And then the actual experiment or 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 and, 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, the, the student, sorry, the, the first author was like, I can't believe it got accepted. I was like, no, my, it's great.

1:47:50It'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's just expecting one person who'd been trolling me for a while about it, just to carry on trolling. But I didn't expect the backlash. And then I wrote, 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 it's a beautiful story of perseverance. And the backlash is just a negative word for discourse, which I think is beautiful.

1:48:29I think you, as I said to, you know, when it got accepted, and people were saying were 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, 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 mechanism. And that's what we need to get to is an auto -candidic set, self -replicating molecules, some other features that come in.

1:49:11And the fact that this paper has been so discussed for me is a dream come true. Like, 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. 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 helpful, it'll help people build scaffold on it and we'll start to converge to a new paradigm.

1:49:50So I think that that's the thing that I wanted to see, you know, my colleagues, authors, collaborators, and people were like, you've just published this paper, you're a chemist. Why have you done this? Like, who are you to be doing evolutionary theory? Like, 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 the origin of life and these kinds of questions, you mentioned learning difficulties. I didn't know about this. So what was it like? I wasn't very good. It's cool, right? This is when you're very young. Yeah, yeah.

1:50:28One but 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. 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 did I go out of when I was I think about the major transition in my stupidity? Like, you know, I everyone thought I wasn't that stupid. Well, basically everyone thought I was faking. I like stuff and I was faking wanting to be it. So I always want to be a scientist.

1:51:04So 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, and so, so everyone was really confused, I think at first, but I wasn't smarter than I, you know, it 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. And people say, you're not, you can't, you can't read and write.

1:51:40And 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 in the remedial class. And the remedial class was basically full of, were two types of three types of people. There were people that had quite violent, right? And there were people who couldn't speak English. And there were people that really had learning difficulties. So, 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.

1:52:39I 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, 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 exams you've been entered into, you're not, you're just going to get C, D or E.

1:53:17You can't even get A, B or C, right? This is the UKG CSC. And I was like, oh, shit. And I said, can you just put me into the high exams? I said, no, no, you're going to fail. There's no chance. So my, my father kind of intervened and said, you know, just let him go in 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. So I took the exams and passed them, fortunately. I didn't get the top grades, but I, you know, I got into A levels.

1:53:51But then that also kind of limited what I could do at A levels. I wasn't allowed to do A level maths. Because I had such a bad math grade from my GCSE, and he had a C. But I, they wouldn't let me go into the ABC for maths because of some kind of coursework requirement back then. So the top grade I could have got was a C, C, D or E. So I got a C. And then let me do a kind of A S level maths, which is this half intermediate and get to go university. But in the I could like chemistry. I had a good chemistry teacher. So in the end, I got to university to do 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?

1:54:34That 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 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 was really, I really like not understanding stuff. For me, when I did 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, I trialled, I tried to build a laser when I was like eight.

1:55:19And I thought, how hard could it be? 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 high high voltage. So I kind of, when I was like, I didn't have an, and I was so stupid, right? I was kind of so embarrassed. To make enough CO2, I actually set a fire and try to filter the flame. Oh, nice. So I was like completely, completely failed. And I bent, but half the 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.

1:56:03And so, you know, so I remember being super curious and being determined at fine answers. And so the kind of, when people do a give advice about this, why I ask 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, I don't, I hire people that I think that, you know, I'm kind of home. I, if there's 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'm, I like, I love being around smart people and I love confusing smart people.

1:56:47And when I'm confusing smart people, you know, not by stealing their wallets and hiding it somewhere. 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. Yeah. Hang out with smart people and confuse them. Yeah. 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 and they give you different reasons. Yeah. And I mean, I'm, you know, if everyone is like with assembly theory and people said, oh, it's wrong. And I was like, why?

1:57:20And 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 off or it's just there that and the other. So I think the, the, the thing that I like to do is and in academia, 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 and and and be, and I have some faith that I've always wanted to have a new idea.

1:57:57And so, you know, I like a new idea and I want to, I don't want to nurture it as long as possible. And if someone 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. And then say if, and so why 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.

1:58:38And 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, 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 and just like that's wrong. That's wrong. That's wrong. What do they do? And people are, oh my God, you just told me you destroyed my life's work. I'm like, relax.

1:59:10No, 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 or because we're too scared. Yeah, I see. Yeah, the I've seen you be pretty aggressively critical, but it's every time I've seen it, it's the idea and not the person. I'm sure I make mistakes on that. I mean, I, you know, I argue, I argue lots with, with lots, I mean, I argue lots with Sarah. And she's like kind of shocked. I've argued with Yashar in the past and he's like, you're just making, Gashabark, and you're like, you're just making that up.

1:59:50I'm like, no, not, not quite. But kind of, yeah. You know, I had a big argument with Sarah about time. She's like, no, time, time doesn't exist. I'm like, no, time does exist. And now, and as she realized, the her conception of assembly theory and my conception of assembly theory was the same thing necessitated us to abandon the fat 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 trying to figure out where you and Sarah converge. 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.

2:00:34So there's, and I mean, really inspired by a guy called Nick Gizzen. I'm going to butcher his argument, but I love his argument a lot. So, however, 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 polystonic 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 of 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, assembly theory seems to explain that common, large common, territorial space allows you to produce things like life and technology.

2:01:37And that large common, territorial 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 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.

2:02:28You have the stat, you have the initial conditions, and you can run the universe right to the end and go back was and forwards in that universe. That is not correct. Let me load that in. The universe is not big enough to contain the future. Yeah, that's why that's it. That's another, that's a beautiful way of saying that time is fundamental. Yes, and that you can have, and that's what, this is why the law of the excluded middle, something is true or false, only works in the past.

2:03:01Is it going to 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. Well, I mean that 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 next and a few other people.

2:03:45Can you can you explain his view on fundamental on 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 full process, but I never really 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 and boy, does that, that's an interesting one of the process.

2:04:50What 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 Luca, 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 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 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.

2:05:39Yeah, 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, the earth is the most gigantic thing, we know in the universe, commentarily, we know. We know. Now, I guess, this is just purely a guess, I have no data, but other than hope, well maybe not hope, maybe, no, I have some data, that every star in the sky probably has planets, and life is probably emerging on these planets, but the amount of contingency that has looked associated with life is that I think the commentorial space associated with these planets is so different.

2:06:40We 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, 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. Intersect, you don't mean in time or space. Time and the ability to communicate. My biggest fear in a way is that life is everywhere, but we become infinitely more lonely because of our scaffolding in that commentorial space, because it's so big. 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, and so there's other cones like it.

2:07:39Why can't we communicate with other? Just because we can't create it doesn't mean we can't appreciate the creation, right? I decided to detect the creation. I truly don't know, but it's an excuse for me to ask for people to give me money to make a planet simulator. If I can make with a different kind of shameless thing, give me money. This was all a long plug for a planet simulator. It's like, hey, I won't be the first in my day. My Rick garage has run out of room. This is a planet simulator, you mean like a different kind of planet? 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.

2:08:35So here's a thing. Here's my dream. My dream is that by creating life in the lab, based upon constraints, we understand. There's like a for 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. It's fine. Different protein at alphabet. Fine. Have cells and evolution and all that stuff. We will then be out of say, okay, life is a more general phenomena. Selection is more general than what we think is the chemical constraints on life. And we can point the genes where another telescope to other planets that we are in that zone.

2:09:15We are most likely to combinatorially overlap with. So 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 and apply advanced assembly theory to general theory of language that we will get and say, huh, 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, not common goal or off a it type structure, but evolutionary structure given by assembly theory.

2:09:58And we start to, but I would say that because I'm a shameless assembly theorist. Yeah. It just feels like the, 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 cones 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.

2:10:37That's going to be built as we build abstractions. The main, I mean, one, one idea is that as we go to intelligence, 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 that we will overlap there, even though we have completed different chemistry, literally 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. But it's just hard to intuit a world, a universe where there's nearly infinite complexity objects and they somehow can't detect each other.

2:11:34But 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. Not the wrong thing. He flicked the Voyager pro brand and pale blue dot. Instead, look how big the universe is. I would have done it the way around it. 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. And then that should allow people on to think about, well, probably we should try and get causal chains, offer on to Mars, onto the moon, wherever.

2:12:09Well, 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 time, because I'm guessing that your time is just coordinate. So I'm going to change your mind. I'm guessing you're one of those. 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 if you change your mind.

2:12:49But you can just add, you can just add an arrow time onto it. Right. Just a mask. 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 case for a moment. Now let's go back to Newtonian mechanics. Now, the uncertainty between, for example, in Newtonian mechanics is this. If I give you the coordinates of your 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.

2:13:30However, you cannot specify these coordinates to infinite precision. Now everyone said, you know, oh, this is kind of like, you know, the chaos theory argument. No, no, it's deeper than that. Here's a problem with numbers. This is how this is where Hilbert and Broward fell out.

2:13:49To have the coordinates of this object to give an object as a 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?

2:14:10So, 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 it can't store its, well, how do you store it? Infinitely, long number in a finite size.

2:14:30Well, we're using infinity very loosely here. No, no, we're using infinite precision. I mean, not loosely, but very precisely. You think infinite precision is required. Well, let's take the object. Let's 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.

2:15:10And some people say you can't get random as quantum mechanics deterministic. 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 initial 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.

2:15:53It's evidence of the universe is generating new things. Okay, so to you, first of all, quantum mechanics, you can just say statistically what's going to happen when two golf balls hit each other statistically. But that, but sure, I can say statistic what's going to happen. But then what they do happen. 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 we, how do we understand entropy change? Well, we could do the look at or process. We can use the agguradic hypothesis. We can also have, we can also have the counterfactuals where we have all the different states.

2:16:40And we could 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 into future. The real numbers are real. They're just, they're the observables. We're trying to see exactly where time being fundamental sneaks in in this difference between the golf wall can't contain its own position 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?

2:17:34Yeah, 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 statement you've made. Well, no, that we can logically follow, because if you don't have free will, so like, if you're in a, if you're in a universe that has no time, the universe is deterministic. 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.

2:18:11No, 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 of, it's actually different what I've said before, 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.

2:18:49And 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 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, with good mathematical backgrounds, can say, I've got an idea. I'd love to do an experiment that shows that the universe, I mean, 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.

2:19:31The 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 order laws of physics. So Boltzmann brain is this idea that in a long enough universe, a brain will just emerge in the universe as conscious without, and that neglects the cause of a chain of evolution that required to produce that brain. And this is where the computational argument really falls down because the computation is because they say, 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.

2:20:02Just 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, I think it, I think it, it, it, 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. Not, I mean, life basically minds novelty almost from the future and makes it, I actualizes it in the present. Okay. Life is a novelty minor from the future that is actualized in the present. Yeah.

2:20:45I think so. 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're referring to? I'm, I, I'm really struggling around this because I had a really good argument with Yasha Bach about randomness. And he said randomness doesn't give you free will. That's insane because you just be random. But I think, and I think he's right at that level. But I don't think we, I don't think he is right on another level. And it's not about randomness is about, it's about constrained, I'm going to sound like constrained.

2:21:26I'm making this up as I go along. So making this up, constrained opportunity. So what I mean is like, so you have to have, so that the, the novelty, what is novelty? You know, this is what I think is the funny thing. You ever want to discuss AI? Why I think everyone's kind of gone AI mad is that they're misunderstanding novelty. But let's think about novelty. Yes, 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 say that novelty doesn't exist.

2:22:07There'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 combinatorial space in the way that our current laws of physics, although as contrived, in a deterministic initial condition universe, even with the get out of the multiverse, David Deutsch style, which I hate love, by the way, but I don't think he's correct.

2:22:54But it's really beautiful. But the fact that 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, oh, I think we've been debating this for a long time now about how do we reconcile novelty to determinism in determinism? It's okay, just to clarify, both you and Sarah think the universe is not deterministic.

2:23:41I won't speak for Sarah, but I roughly can't. 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 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, 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 in the future. So how can we have a determinist, a universe that has deterministically looking rules?

2:24:24There'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 commentarial space behaves in expanding universe in time and space. An assembly theory helps us quantify the transition to biology. And biology appears to be in novelty mining because it's making crazy stuff. 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 commentarial math. What was that statement you made about life is novelty mining from the future?

2:25:09Yeah. What's the little element of time that you're introducing? So what I'm kind of meaning is because the future is bigger than the present. In a deterministic universe, how do you go from the state's going from one to another? I mean, there's a mismatch, right? So 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 to life transition looking at networks and molecules and that my helpers think about it, the mechanism.

2:25:51But certainly the future is bigger than the past in my conception of the universe and some conception of the universe. And... which is kind of the future being bigger than the past. Well, 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 was a really big one. I think so. But I think it's entirely... Because we have the second law. 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 sticking -plasters onto our reality to hold on to a timeless universe?

2:26:35Yeah, but that's because it's kind of difficult to imagine the universe that's that can't contain the future. But it's not really exciting. It's very exciting, but it's... It's hard. I mean, we're humans on earth and we have a very kind of four -dimensional conception of the world of three -deep -less time. 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 on to that was that you...

2:27:23Let's just start in the present and look at all the complex molecules and go backwards in time and understand how evolutionary processes gave rise to them. It's not 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, tax -hole is unique to earth. There's no tax -hole elsewhere in the universe. And tax -hole 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.

2:28:12That gives space for creativity, novelty, and some things which are unpredictable. Well, okay. So given that you're disrespecting the power of the initial conditions, let me ask you about... So I had to explain that cellular terminary 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. 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 the millionth decimal place of Pi and read out the number without having to go there.

2:29:04But there are some numbers where you can't do that. You have to just crank through. Whether it's Wolframian computation, or we reduce ability, or some other thing, that doesn't matter. But these CAs, 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 say the same whether complexity and earth then? No, because the complexity on earth has a copy number and an assembly index associated with it. That CAs just a number running. You don't think it has a copy number? Wait a minute.

2:29:45Well, 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. I mean, the CAs such a fascinating pseudo complexity generator. What I would love to do is 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 by iteration. And you're like, oh, that's great.

2:30:22That's great. You didn't predict it. Some rules you can predict that what's going to happen. Other rules you can't. So for me, if anything, CAs are evidence that the universe is too big to contain itself. Because otherwise, you'd know what the rules are going to do forever more. Right. I guess you were saying that the physicist saying that all you need is the initial conditions and the rules of physics is somehow missing the bigger picture. Yeah. And if you look at CAs, all you need is the initial condition and the rules and then run the thing. You need three things. You need the initial conditions.

2:31:01You need the rules and you need time iteration to mine 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. Yeah. If you could, then to be sure. And that time is a resource. Foundation of this is the history of memory of each of the things that created. It has to have that memory of all the things that led up to it. I think it's yeah, you have to have the resource. Yeah. Because time is a fundamental resource. And 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.

2:31:45It's random. You're you're a time fundamentalist. You should be as well. If you believe in free will, yeah, the only conclusion is there is time is fundamental. Otherwise, you cannot have free will. It logically follows. Well, my my foundation of my belief of free will is just is 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 a kind of leap. It requires a leap. I mean, I I I think that it's kind of this is what I think machine learning is going to provide a big chunk of that, right?

2:32:37Because it helps us explain this. So the way I say, if you take, that's interesting. Why? Well, let's let's just my favorite one is because I'm the AI dooms are driving me mad. And in fact, we don't have any intelligence. Yeah, I call AI autonomous informatics just to make people grumpy. Yeah. And they're because 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't understand how the human brain does what it does. 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.

2:33:19I 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 flight simulator. I'm sorry, Excel. Yeah. Have you not played the flight simulator in like so? Yeah, yeah, yeah. Yeah. What does that look like? It's like wireframe, very, very basic. But basically, I think it's X zero, Y zero, shift. And it opens up and you can play the flight simulator. Oh, 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.

2:33:59Well, 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 underpinning the human mind. I'm very frustrated by the way that we're AI doing right now. And people are bestowing some kind of magic. Now, let's go back a bit. So you said, AGI, are we far away from AGI? 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, and I don't think there isn't things we should do and be very worried about.

2:34:42Right? 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 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, and this has not had the correct they do not have the correct epistemology.

2:35:29They do not understand what knowledge is. And 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 doom, AI. We can work out the probability of 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 AI because we have no mechanism. So let me give you another one, which is like, I'm really worried about AG. What's AG?

2:36:04AG is anti -gravity. One day we could wake up an anti -gravity. It's 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? 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. How religions come because religions are about kind of some controls. You've got the optimist saying, AI is going to curusole and AI is going to kill us all.

2:36:46What'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. 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, let me try to sort of steal man the AI Dumer's argument. Actually, I don't know. Our AI Dumer's in the Idkowski camp saying it's definitely going to kill us because there's a spectrum. 95 % I think is the limit. Yeah. And they 5 % plus. No, not plus. I think I don't know. I was seeing on Twitter today various things, but I think your Kowski is at 95%.

2:37:24But to belong to the AI Dumer club, is there a threshold? I don't know what the membership may be. And what are the fees? I think well, I think it's got Aronson. I was quite surprised. I saw this online. It could be wrong. So sorry if it's wrong. It says 2%. But the thing is if you were to get, if someone said there's a 2 % chance you're going to die going into the lift, would you go into the lift? In the elevator for the elevator. American, English speaking audience. Well, no, not for the elevator. So I would say anyone higher than 2%. I mean, like I, I mean, I think there's a 0 % chance of AI to zero.

2:37:59Just to push back on the argument, where the end of zero on the EGI, we can see on Earth that there's increasing levels of intelligence of organisms. 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 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 do. With that being, it's going to be able to do, especially if it has the power to hurt humans.

2:38:49Which 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. 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 watching all the Huxters online with the prompt engineering and all this stuff.

2:39:27When I talk to a typical AI computer scientist, they keep talking about the AIs having some kind of decision -making ability. That is a category error. The 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 called Chem Machiner.

2:40:14Nice. Yeah, yeah, which is basically a... For people who don't understand the point of the X -Markiner has a great film about, I guess, AGI 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. 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 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.

2:40:58More capable, you know, when people play chess computers, they don't expect to win now, right? The chess 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, now technology, atomically precise machines. He came up with a world where we had these atom cogs everywhere. They were going to make self replicating nanobots. Not possible. Why? Because there's no resources to build these self replicating nanobots.

2:41:33You can't get the precision. It doesn't work. It was a major category error in taking engineering principles down to the molecular level. The only functioning 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. So humans can't think that I would argue the only AI is that exists in the universe and produced by evolution. And sure, we may be, I may call working memory better. We might be able to do more things. Human brain is the most compact computing unit in the universe.

2:42:12It 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. 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?

2:42:48Well, I think it's just, 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 set of 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. I think when I, when you hear the word super intelligent, you're hearing like it's smarter than humans in every way that humans are smart.

2:43:40But the paperclip manufacturing system doesn't need to be smart in every way. It needs to be smart. So that's 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'll 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, I'm going on far away from my comfort zone and all this stuff.

2:44:21But 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 paperclip 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 did. And you know, for papermit clip manufacturing to really happen, I mean, do the math. It's like, it's not going to happen. There's not enough energy. There's not enough resource where they're all going to come from. I think that what happens in evolution is really why is why is a killer virus not killed out all of you, not killed all life on earth?

2:45:03What 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 is possible to engineer, for example, sorry to interrupt, but like a perfect virus. No, there's deadly enough. No, I think nonsense. Cool. Okay. I think that just wouldn't again, it wouldn't work. It was too deadly. I would just kill the radius and not replicate it. Yeah. I mean, you don't think it's possible to get a, I mean, if you were soup, I mean, I, if you were, it not kill all of life on earth, but kill all humans.

2:45:44There'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. 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 there just now. But I think there is a consensus that some certain things are bad and we shouldn't do them.

2:46:22Right. And, and sure, it would be possible for a bad actor to, to engineer something bad. But the, 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 when 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, Jan LeCoon. I think we put out a very good point about trying to regulate jet engines before we've even vented them. 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.

2:47:08When basically we need to actually really focus on. Now, let's say there's some actors are earnest. All right. Let's say Yutakowski has been earnest, right? And he really cares. But he loves it. He goes, and then you're all going to die. It's like, you know, why don't we try and do the same thing and say, you could do this. And then you're going to be happy forever after. Yeah. 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.

2:47:45Okay. All right. 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 that, it just seems like people have forgotten that that's the thing. 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.

2:48:29We'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. 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 human civilization dying. But there could be a lot of suffering if this is done. I understand that. And I'm kind of I guess, I mean, I'm involved in the whole hype cycle. Like why I would like us to I don't want us to.

2:49:10So what's happening right now is this seems to be so let me let's say having some people saying AI AI do is a worry. Fine, let's give them that. 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 where 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 threat. Almost as bad as now with AI do, they were really worried, right?

2:49:50There was some great, well not great. There was some horrific documentaries. I think there's one called Fred's that was generated in the UK, wishing it was like, it was terrible.

2:50:07It was unenterned consequences. We've got rid of all the sulfur particles in the atmosphere, or the other, and what's happened in the last couple of years is global warming has accelerated because we've cleaned up the atmosphere too much. Sure. I mean, the same thing if you get rid of nuclear weapons, you can. 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. Let's just hang on. But if we could all agree on the ad we're just woke up. Yeah, yeah, yeah, yeah, yeah.

2:50:44But 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. There's what is the minimum number of nuclear weapons we need to just 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. Yeah. Oh boy, I mean, that has a probably greater than 50 % chance of eliminating major military conflict.

2:51:27Yeah. 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 like 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 that we've got too many of them. So let's reduce the number, but not greater than 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.

2:52:03It'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 your average 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 do it. But the probability of a bad actor of one of the nations setting off a nuclear weapon.

2:52:44I mean, you have to you have to integrate that into the, but we get we just give you the nuclear nukes like population, right? We give what we do is we, anyway, let's just go there. Let's say so if a small nation with a couple of nukes uses one because they're a bit bored or annoyed, they're going to they the likelihood that they are going to be pummeled out of existence immediately is 100%. And yet they've only 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 you know, there's terrorist organizations that would take that would take would take that trade.

2:53:24Yeah, 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 life to to because they hate another group of people. And that I believe it's a very small fraction, but is it large enough to if you give out nuclear weapons? I can predict a future where we take all nuclear material and we burn it for energy, right? As we're because 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.

2:54:05Sure. In the simulation, I love it. It's not going to kill all humans is 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. 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're doing 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?

2:54:39Burning 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, they're die consequences. Yeah. Yeah. So it's like a video game. We all have 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, which so the AI tumors are really terrified at this point. Now they're happy to have a job for another 50 years, right?

2:55:17Oh, I'll be fear mongering. Yeah, yeah, yeah. We got I'm a believer in equal employment. You've mentioned that what you call cam machiner. 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. 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?

2:56:12So and I think only in recent years did humans become cheering complete, right? Yeah. Yeah. Right. 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. And I think that we are not getting going to 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.

2:56:59So when we look back on this, going, oh yeah, that was really cool. Because when I chat, I'll chat GPT, it made me 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? 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 I went from Bill to Billy and he went, oh, right, Leroy, like how did he make that leap? Then he was able to basically without any training.

2:57:42I extended his name. He went gay and he doesn't like. He 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 and to synthesize something which allows us to generate knowledge and becoming true and complete on our own. I don't, although AIs are built and true and complete things, their thinking is not true and complete, in that they are not able to build universal explanations. And that lack of universal explanation means that they're just inductivists.

2:58:27Inductivism doesn't get you anywhere. It's just basically a party trick. It's like, you know, I think it's in the fabric of reality from David Deutsch where basically, the farmer is feeding the chicken every day and the chicken is getting fat and happy and 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 instead of feeding the chicken just rings its neck. You know, and that's kind of, and had the chicken had an alternative understanding of why the 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.

2:59:08So that's what I mean. And we'll come up with novelty. I can imagine, because you give an example, in, you know, about William and Leo, I feel like, example like that will be able to see in future versions of large language models. We'll be really, really, really impressed by the humor, the insights, all of it, because it's fundamentally 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. Right. I'm impressed. Increasingly so. But we're mining the past. Yes. And what the human brain appears to be able to do is mine the future.

2:59:53Yes. 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 what that's impossible. And it's like the problem is and again, there's a domain experts kind of bullshitting each other. The term generative. Yes. Right. Average person. Oh, it's generous. No, no, no. If look, if I take the numbers between zero and 1 ,000 and I train a model to pick out the prime numbers by giving all the prime numbers between zero and 1 ,000, he doesn't know what prime number is. Occasionally, if I can cheat a bit, it will start to guess that it never will produce anything out with the data set because you mind the past.

3:00:38The 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. 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 language, 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.

3:01:13Those models are being corrected. Steered. Corrected. Modified. Tweets. Yeah, but I mean, cheating. Well, you could say the training on human data in the first place is cheating. Well, let me, but the human is in the loop. Sorry, I'm sorry. Yes, so human is definitely in the loop. But it's not just human is in the loop. A very large collection of humans. Look, I'm turning that could be. I mean, to me, it's not intuitive that you said prime numbers that the system can generate an algorithm. Right? That that the algorithm that can generate prime numbers or the algorithm that can tell you for numbers, prime and so on and generate algorithms that generate algorithms that generate algorithms that I can start to look a lot like human reasoning, you know, I don't think I think again, we can show that on the piece of paper.

3:02:12That's short. I think there has, you have to have, so this is the failure in epistemiology. I'm glad I even say that word. I mean, what it means, right? I said multiple times. I know. It's like three times now. Without failure. Quilt while you're ahead. Stop saying it again. You did really well. It thanks. So I, 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. They don't have neurons.

3:02:47But if I can make, if I can take a, a gel and engineer the gel to have it be a hybrid hardware for reprop, reprogramming, which I think I know how to do, I will be, I process a lot more information and train, 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, the abilities of human beings have had to become true and complete. And so I guess the question to give back at you, and I, 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 explanation, inspiration comes from out, yeah.

3:03:35And then you then test that, and then you, you see that's going towards the truth. And human beings are very good at doing that in, and the transition between philosophy, mathematics, physics, and natural sciences where, and I think that we, 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 get better, we're going to get happier with the outcome. But why would you ever think the model was thinking or reasoning, reasoning requires intention.

3:04:15And the intention, if the model isn't reasoning, the intentions come from the prompt her. And the intention has come from the person who programmed it to do it. So I, 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 with, with, with those initial conditions, conditions came from someone starting it. Yes. And that calls all chain in there. So that intention comes from the outside.

3:05:00I think that there is something in that calls all chain of intention that's super important. I don't disagree. We're going to get to AGI is 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 load of term, but there could be incredibly super 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.

3:05:43I agree. But I, the super intelligence I want, I want to, I want to be able to have a discussion with it about coming up with fundamental new ideas at generate knowledge. And if the, if the super intelligence would generate can mind novel, 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, if the intelligent system be a human being, a chap, chap, or something else is able to produce something truly novel that we, I could not predict, even having full audit trail from the past, then I'd be sold.

3:06:20Well, 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.

3:06:45There's a 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 -traumating 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 have a job and we're still doing stuff. And you know, I used chat GBT for a few weeks. Well, this is cool. And then it took me to, I had to, I, well, what happened is it took me too much time to correct it. Then it got really good.

3:07:14And 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. 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 going to help me demonstrate to you that time is fundamental and the unit future is bigger than the than the present, which is why we are human beings are quite good at generating novelty because we have to expand our dataset.

3:07:52And to cope with unexpected things in our environment, our environment throws them all at us. Again, we have to survive in that environment. And I mean, either I never say never, I would be very interested in how we can get cross -domain training cheaply in chemical systems. Because I'm against 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 combine to host automatically. I mean, that's interesting. That's really interesting. Applying this same kind of transform mechanism.

3:08:32Yeah. I mean, this is one that goes my team. I try and do things that are obvious, but not 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. And I was thinking, well, molecules aren't really graphs and they're not continuously different, they're not interchangeable. Could I do something that was continuously different, you're saying, well, molecules are actually made up of electron density.

3:09:08So they got thinking, say, well, okay, could there be a way where we could just basically take a database of readily solved electron densities for millions of molecules? So we took the electron density for millions of molecules and just train 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 a cup of the certain hole 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. But hallucinations are good because it means I don't have to train on such a large num, such a huge dataset.

3:09:52Because these datasets are very expensive because how do you produce it? So go back a step. So you've got all these molecules in this dataset. But what you've literally done is a a quantum mechanical calculation where you produce electron densities reach 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 to know what electron density is. So then you give it an unknown pocket. You pour in noise and you say, right, produce me a electron density. It produces electron density that doesn't look ridiculous.

3:10:25And what we did in this case is we produce electron density that maximizes the electrostatic potentials to the stickiness. But minimizes what we call the steric hindrance. So the overlap is repulsive. So you know, make the perfect fit. And then we then use the kind of a 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 just generate them. Just generate some. And then the other thing is then we bung that into the computer and then just makes it. Yeah. The computer being the thing that right.

3:11:03Yeah, 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 bind to 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 amount of 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.

3:11:34Yeah, thanks. You're doing probabilistically. The problem on these electron density models is it's very expensive to solve a stradding equation going up to many heavy atoms and and large molecules. And so we wondered if we trained the the the system on up to nine heavy atoms, whether it would go beyond nine. And it did. It started to generate molecules or 12. No problem. They look pretty good. 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.

3:12:13And 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 from the known dataset that would bind to the host. So a new guest would bind. Were these truly novel? Not really because they 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.

3:13:01That's what a lot of people say. Like, you know, 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 the time 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 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.

3:13:49But 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. 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.

3:14:27But I like this whole idea of mining novelty. I think it is. 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 the AI. But I think they're just the scale you can achieve in terms of impact with AI systems is pretty nerve -wracking. 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 in the way social media has had major consequences, both positive and negative.

3:15:12And 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 of, 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. So open AI guys, meta guys and all this. 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. And they're just trying to say, yeah, we should do this because and covering up for the fact that we have got some problems with, you know, teenagers and Instagram and Snapchat and, you know, all this stuff.

3:15:52And maybe they're just overreacting now. Yeah. It's like, oh, yeah, sorry, we made the bubonic play and gave it to you all and you all dying. And no, 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 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 impact social media had on the world. 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.

3:16:26One of the reasons why I'm so open about the things we're trying to do in the lab, 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 authenticate data and human users. Yeah, human. I still think that there will be AI agents that appear to be cautious, but they would have to be also then to get it labeled as such. There's too much, there's too much value in that, you know, like friendships with the AI systems.

3:17:04There'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? Some people have a meditation tool, it makes them feel better, but I'm not sure you can ascribe sentient and some legal rights to a chatbot that makes you feel less lonely. So 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. Yes. The chatbot's not, right now using the technology we use is not going to be sent in. There's going to be a fun, continue conversation on Twitter that I look forward to again.

3:17:46Since 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 the assembly theory? I was God. Yeah, I don't know what God is, I mean, so God exists in our minds, created by selection. So human beings have created the concept of God in the same way that human beings have 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.

3:18:43I think the universe, there is a creative 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, I have lots of, there are some people I know that are angry atheists, say, you know, I think, 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, you know, it's like, I need to know what the charge of electron is, like, I can't make it the charge of electron, that was, you know, I was just gave up and had faith, okay?

3:19:27You know, resistors worked. So when it comes to, I want to know why the universe is growing in the future 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 uniformly 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 like that's creating stuff? Yeah, I think that, so I think that I'm aware what it is. So what can describe it like mathematical?

3:20:13Well, I think selection, I think selection is the force. Selection is the force in the universe that creates novelty. So is selection somehow fundamental? 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 exists a thing that exists persistent time. Yeah. Maybe let's think maybe the universe is actually in the present, the things, everything that can exist in the present does exist.

3:21:01Well, that would mean it's deterministic, right? No, I think the universe is my, so the universe started super small. The past was deterministic. There wasn't much going on. It was able to mind, mind, mind, mind, mind. And so the process, I mean, is somehow generating universes basically, I can't, I'm trying to put this into words. Did you just say there's no free will though? No, I didn't say that. I said, there is free will. I think I think I, I'm saying that three will occurs at the boundary between the present future, the past and the future. Yeah. I got you, but everything that can exist does exist.

3:21:45Everything 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. So that's what I guess we're getting sneak in free will right there. Yeah. So I guess what I'm saying is what what exists is a, is a convolution of the past with the present and the free will going into the future.

3:22:22But we can still imagine stuff, right? We can imagine stuff from the wrap. 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 fit the initial conditions and physics cannot predict. Like your imagination has a causal consequence in the future. Isn't that weird too? Yeah.

3:22:54It 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. I mean, there must be a lot of power in whatever is going on. There could be a lot of power 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, if we go into a universe where we accept that there is a finite ability to represent numbers and you have round it, we're not rounding errors, you have some that the some what happens, the your ability to make decisions, imagine and do stuff is that that interface between the certain and the uncertain.

3:23:37It'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 on this narrow trajectory that allows you to build you have a choice about what you build. All that choice is a you interacting with a future in the present. What do you as most beautiful about this whole thing? The universe. The the the fact it seems to be very undecided, very open. The fact that every time I think I'm getting towards an answer to a question, there are so many more questions that make the the chase.

3:24:23You know, do you hate that it's going to be over at some point? No, I well for me, I don't 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. It's 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 I want to do is leave as many Easter eggs in the future when I'm gone to go, that's cool. Would you be very upset if somebody made a like a good, large language model that's fine tuned to Lekona? It would be quite boring because I mean, I'm a non -ravity generation.

3:25:04I mean, if it's a faithful representation of what I've done in my life, that's great. That's a interesting artifact, but I think the most most interesting thing about not knowing each other is we don't know what we're going to do next. Sure. I mean, within some constraints, I've got, you know, I can predict some things about you, you can predict some things about me. We can't predict everything. Everything. 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 on mining novelty for the future will not be captured.

3:25:50Yeah. Yeah. That's what life is. It's just some novelty generation that you've done. Each one of us just generate a little bit of the capacity to at least. I think life is a selection produces life and life affects universe. Universes with life in them are materially, physically, fundamentally different in universes of our life. That's super interesting. I have no beginnings of understanding. I think maybe this is like in a thousand years, there'll be a new discipline in humans. Yeah, of course. This is how it works. Right. In retrospect, there will all be obvious, I think. I think a 70 theories, obviously, that's why a lot of people got angry, right?

3:26:38They were like, oh my god, this is such nonsense. You know, like, oh, you know, actually it's not quite. But the writing's really bad. 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. I'm a huge fan of just watching you create stuff in this world. And thank you for talking to me. It's a pleasure. It's always like thanks for having me on. Thanks for listening to this conversation with Lee Kronin to support this podcast. Please check out our sponsors in the description.

3:27:15And now, let me leave you with some words from Carl Sagan. 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.