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

Yeah, that spot on. Yeah, spot on.

Yeah, an object, so if I'm going to try to be as meticulous as possible, objects need to be finite and they need to be decomposable into subunits. All human-made artifacts are objects. Is a planet an object, probably yes, if you scale out. So an object is finite and countable and decomposable. I suppose mathematically, but yeah, I still wake up some days ago to think to myself what is an object because it's it's a non-review question persists over time I'm quoting from the paper here an object is finite is distinguishable, so that's a weird adjective distinguishable We've had so many people help offering to rewrite the paper after it came out and you wouldn't believe it's so funny.

The history is in the objects.

So the assembly index, if you take the object apart and be super lazy about it, or minimal, say, well, it's like you've got a really short term memory. So what you do is you lay all the parts on the path, and you find the minimum number of steps you take on the path to add the parts together to reproduce the object, and that minimum number is the assembly index. It's a minimum bound. And it was always my intuition. The minimum bound in assembly theory was really important. That only worked out why a few weeks ago, which was kind of funny. Because I was just like, no, this is sacrosanct. I don't know why. It all comes to me one day. And then when I was pushed by a bunch of mathematicians, we came up with the correct physical explanation, which I can get to. But it's the minimum. And it's really important to the minimum. And the reason I knew the minimum was right is because we could measure it. So almost before this paper came out, with published papers explain how you can measure the assembly index with molecules.

So with molecules, it's not trivial, but it is possible because what you can do, and because I'm a chemist, so I'm kind of like, I see the lens of the world for just chemistry. I break the molecule and break bonds. And if you break up, if you take a molecule and you break it all apart, you have a bunch of atoms. And then you say, OK, I'm going to then form bot, take the atoms and form bonds and go up the chain of events to make the molecule. And that's what made me realize, take a toy example, literally a toy example, take a Lego object, which is broken up of Lego blocks. So you could do exactly the same thing. In this case, the Lego blocks are naturally the smallest, they're the atoms in the actual composite. let go architecture, but then if you maybe take a couple of blocks and put them together in a certain way, maybe there will have a offset in some way. That offset is on the memory. You can use that offset again with only a penalty of one, and you can make a square triangle and keep going, and you remember those motifs on the chain, so you can then leap from the the start with all the Lego blocks or atoms, just laid out in front of you and say, right, I'll take you, you, you connect and do the least amount of work. So it's really like the smallest steps you can take on the graph to make the object. And so for molecules it came relatively intuitively. And then we started to apply to language. We've even started applying to mathematical theorems. But I'm so aware of my depth, but it looks like you can take minimum set of axioms and then start to build up. kind of mathematical architectures in the same way. And then the shortest path to get there is something interesting that I don't yet understand.

It's a hard problem, but actually if you look at it, so the best way to look at it for this take a molecule. So if the molecule has 13 bonds first all take 13 copies of the molecule and just cut all the bonds so take 12 bonds and then you just put them in order yeah and then that's how it works so and you keep looking for symmetry or or copies so you can then shorten it as you go down and that becomes commentary quite hard for some natural product molecules Um, it comes very hard. It's not impossible, but we're looking at the bounds on that at the moment. But as the object gets bigger, it becomes really hard. And, but that's the bad news, but the good news is there are shortcuts. And we might even be able to physically measure the complexity of out computationally calculating it, which is kind of insane.

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

Yeah, I'd say so, I agree. So I've started assembly theory of emoticons with my lab, believe it or not, so take emojis, pixelate them, and work out the assembly index of emoji. And then work out how many emojis you can make on the path of emoji. So there's the Uber emoji from which all other emojis emerge. And then you can, so you can then take a photograph and by looking at the shortest path, on by reproducing the pixels to make the image you want, you can measure that. So then you start to be able to take spatial data. Now there's some problems there. What is then the definition of the object? How many pixels? How would you break it down? And so we're just learning all this right now.

So you would first of all determine the resolution. So then, how, how, what is your x, y? Well, the number on the x and y plane. And then look at the surface area. And then you take all your emojis and make sure they're all looked at the same resolution. Yes. And then we were based at the then. do the exactly the same thing we would do for cutting the bonds. You'd cut bits out of the emoji and look at them. You'd have a bag of pixels. And you would then add those pixels together to make the overall emoji.

So in the same way in chemistry, we assume the bond is fundamental, what we do in there here is we assume the resolution at the scale that we should do it is fundamental. And we're just working that out and that you're right, that will change, right? Because as you take your lens out a bit, it will change dramatically. But it's just a new way of looking at not just compression, what we do right now in computer science and data. One big kind of... kind of misunderstanding as assembly theory is telling you about how compressed the object is. That's not right. It's a how much information is required on a chain of events, because the nice thing is if when you do compression in computer science, we're wondering a bit here, but it's kind of worth wondering, I think, and you, you, um, assume you have instantaneous access to all the information in the memory. Yeah. In assembly theory, you say, no, you don't get access to that memory until you've done the work. And then you don't access that memory, you can have access, but not to the next one. And this is how in assembly theory, we talk about the four universes, the assembly universe, the assembly possible, and the assembly contingent, and then the assembly observed. And they're all all scales in this combinatorial universe.

Yep, so the assembly universe is like anything goes, just as just combinatorial kind of explosion in everything. That's the biggest one. That's the biggest one.

So, yeah. So, assembly universe, everything goes. Yeah. Assembly possible, laws of physics come in in this case in chemistry bonds in assembly.

Yes, and they're the only constraints, they're the constraints of the base, so the way to look at it, as you've got all your atoms, they're quantized, you can just bung them together, so then you can become a kind of, so in the way in computer science speakers, the assembly universe is just like no laws of physics, things can fly through mountains, beyond the speed of light, in the assembly possible, you have to apply the laws of physics, but You can get access to all the motifs instantaneously with no effort. That means you could make anything. Then the assembly contingent says no, you can't have access to the highly assembled object in the future until you've done the work in the past on the causal chain. And that's really the really interesting shift where you go from assembly possible to assembly contingent. That is really the key thing in assembly theory that says you cannot just have instantaneous access to all those memories. You have to have done the work somehow. The universe has to somehow built a system that allows you to select that path rather than other paths. And then the final thing the assembly observed is basically us saying, oh, these are the things we actually see. We can go backwards now and understand that they have been created by this causal process.

Yeah, yes, that's the thing that does the selection. You could think about in terms of a Von Neumann constructor versus selection, a ribosome, a Tesla, a set-plan assembling, Tesla's, you know, the difference between the assembly universe and Tesla land and the test of factory is Everyone says, no, testers are just easy. They just spring out. You know how I make them all. They test the factory. You have to put things in sequence and outcomes a Tesla. Yes, this is this is really nice. Super important point is that when I talk about the universe having a memory or their some magic, it's not that it's that tells you that there must be a process encoded somewhere in physical reality, be it a cell, a Tesla factory, or something else that is making that object. I'm not saying there's some kind of woo woo memory in the universe, you know, morphic resonance or something. I'm saying that there is an actual causal process that is being directed, constrained in some way. So it's not kind of just making everything.

This is the question, oh, well, it's the first interesting question that I want to answer out of four. I think the factory emerges in the environment and the objects that are being built. And here, let me, I'll have a go explain to you the short as path. So why is the short as path important? Imagine you've got, I'm going to have to go chemistry from moment on abstract it. So imagine you've got an environment that you have a budget of atoms, you're just flinging together and the objective of those atoms that being flung together and say molecule A. have to make that they have that they decompose so molecules decompose over time so the molecules in this environment in this magic environment have to not die but they do die there's a there's a they have a half life so the only way the molecules can get through that environment out the other side that's a pretend the environment is a box can go in and out without dying and there's a there's just an infinite supply of atoms coming or a fuck well a large supply the the molecule gets built But the molecule that is able to template itself being built and survives in the environment will basically reign supreme. Now, let's say that that molecule takes 10 steps. Now, and it's using a finite set of atoms, right? Now, let's say another molecule, smart, or smaller molecule, will call it comes in and can survive in that environment and can copy itself, but it only needs five steps. The molecule that only these five steps, because it's both molecules are being destroyed, but they're creating themselves faster, they can be destroyed. You can see that the shortest path reigns supreme. So the shortest path tells us something super interesting about the minimal amount of information required to propagate that motif in time and space. And it seems to be like some kind of conservation law.

Yeah, yes and no, because there are other things. So in the limit, yes, because you want to tell the difference between things that have required a factory to build them and just random processes. But you can find instances where the shortest path isn't taken for an individual object in the visual function. And people go, ah, That means the shortest path isn't right. And then I say, well, I don't know. I think it's right still because so of course, because there are other driving forces. It's not just one molecule. Now when you start to, now you start to consider two objects. You have a joint assembly space. And it's not, now it's a compromise between not just making A and B in the shortest path. You want to make A and B in the shortest path, which might mean that A is slightly longer. You have compromise. So when you're slightly more nesting in the construction, when you take a given object, that can look longer, but that's because the overall function is the object is still trying to be efficient. Yeah. And this is still very hand-wavey. And maybe I don't look to stand on, but we think we're getting somewhere with that.

Yeah. 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. And assembly depth can be lower than the assembly index for a molecule. when they're cooperating together, because exactly this parallel processing is going on. And my team have been working this out in the last few weeks because we're looking at what compromises does nature and meat need to make when it's making molecules in the cell. And I'm wondering, you know, I maybe like, well, I'm always leaving out of my compass. But in economics, I'm just wondering if you could apply this in economic processes. It seems like capitalism is very good at finding shorts path. you know every time and there are ludicrous things that happen because actually the cost function has been minimized and so I keep seeing parallels everywhere where there are complex nested systems where if you give it enough time and you introduce a bit of heterogeneity the system readjusts and finds a new shorts path but the shorts 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 confidence probably should go back to molecules, but hey, I before we get too far, let's talk about the assembly equation.

And 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.

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 We didn't know I mean you got intention and obviously angry people that angry people wearing noise there's anger people in the world. That's good So what happened is the evolutionary biologist got angry. We were not expecting that because before evolutionary biologists would be cool. I knew that some not many computational complexity people would get angry because I'd 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-bodic chemists got slightly grumpy because there's no enough chemistry in there. And then finally, when the creationist said it wasn't creationist enough, I was like, no, I've done my job.

I think so.

Yeah. So what happened is the reason why people put the phone down on the core of their paper. I mean, if you if you view the reading the paper like a phone call, they got to the abstract. Yep.

True. Right. There's nothing wrong with that statement. Totally true.

I am not. I would do it all again. This paper was actually on the pre-print server for over a year.

Yeah, I think, yeah, I don't regret anything.

What I love about being a scientist is kind of sometimes because I'm a bit dim, I'm like, and I don't understand what people tell them 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, 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. It doesn't mean it won't, or can't. This would 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. And secondly, And a lot of evolutionary biologists seem to dismiss the origin of life questions, just say it's obvious. And that causes a real problem scientifically, because when the physicists are like, we own the universe, the 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 game. 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 closeness if we quantify it. So, yeah, I mean, I never expected the paper to kind of get that much interest and still. I mean, it's only been published just over a month ago now.

Yeah, that's a really good. For selection, selection, so I think for selection you need, so this is where for me the concept of an object is something that can persist in time and not die, but basically can be broken up. So if I was going to kind of bolster the definition of an object. So if something can form and persist for a long period of time, and exist in the 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. So good chemistry examples, if you took some carbon, and you made a chain of carbon atoms, whereas if you took some carbon nitrogen and oxygen and made chains from those, you start to get different reactions and rearrangements. So a chain of carbon atoms might be more resistant to falling apart under a single basic conditions, versus another set of molecules. So it survives in that environment. So the acid pond, the molecule, the resistant molecule can get through. And then that molecule goes into another environment. So that environment now maybe being acid pond is a basic pond or maybe it's an oxidizing pond. And so if you've got carbon and it goes an oxidizing pond, maybe the carbon starts to oxidize and break apart. So you go through all these kind of obstacle courses if you like given by reality. So selection is the ability for happens when object survives in your 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 mountain side for four billion years and nothing happened to it. And that's not necessarily really advanced selection. So for selection to get really interesting, you need to have a turnover 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 say a molecule that can then act on itself or the chain of events that caused 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. So really, to answer your question, what the factory is, the factory is the environment, but it's not very autonomous. It's not very redundant. There's lots of things that could go wrong. So once you get high enough up the hierarchy of networks of interactions, something needs to happen. That needs to be compressed into a smaller volume and made resistant robust. Because in biology, selection and evolution is robust, that you have error correction built in. You have really, you know, that there's good ways of basically making sure propagation goes on. So really, the difference between inorganic, a biotic selection and evolution and evolution and stuff in biology is robustness, the ability to kind of propagate over the ability to survive in lots of different environments, whereas are poor little inorganic, so molecule whatever just dies in lots of different environments. So there's something super special that happens from the inorganic environment, molecule in the environment, kills it to where you've got evolution and cells can survive everywhere.

I don't, and I'm excited because I think selection isn't special at all. I think what is special is the history of the environments on Earth that gave rise to the first cell that now has taken all those environments and is now more autonomous. And I would like to think that this paper could be very wrong. 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 inspires us to go and look for selection in the universe, because we now have an equation where we can say, we can look for selection going on and say, oh, that's interesting. We seem to have a process that's given it because giving us high-copy number objects, also a highly complex, but that doesn't look like life as we know it. And we use that. So, oh, there's a hydrothermal vent. Oh, 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, what 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 bit, we could talk about consciousness and abstraction. But let's keep it primitive, molecules and biology. So I think the real power of the assembly equation is to say how much selection is going on in this space. And there's a really simple, four experiment I could do. You know, 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 you put a single eco-licel. And then you say, I'm going to measure the assembly in this amount of assembly in the box. So it's quite low, but The rate of change of assembly, DADT will go VUMSIC Moidal as it eats all the food, and the number of coal ice cells will replicate because they take all the food, they 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 coal ice stop. I mean, die is probably a strong way. They stop respiring because all the food is gone. But suddenly, the amount of assembly in the box is gone up gigantic, because of that one E. coli factory has just eaten through, milled lots of other E. coli factories run out of food and stopped. And so that, looking at that, so in the initial box, although the amount of assembly was really small, It was able to replicate and use all the food and go up. And that's what we're trying to do in the lab actually is kind of make those kind of experiments and see if we can spot the emergence of molecular networks that are producing complexity as we feed in raw materials and we feed a challenge and environment, you know, we try and kill the molecules and really that's the main kind of idea for the entire paper.

Um, 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, um, is that you can, um, 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, um, identical copies. You can count them. And then you fragment them and you count number of fragments. and look at the molecular weight and the higher the molecular weight and the higher the number of the fragments or 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 with 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, well, maybe the geological process, I would argue very, very, very, really, that that is not the case. But we can say, look, if you don't like the cut off on Earth, go up higher, 30, 100, right? Because there's going to be a point where you can find the molecules 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.

Yeah, that was so interesting. And I Always understood the copy number is really important, but I never explained it properly for ages. And I 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? And so I realized that ultimate randomness and ultimate complexity are indistinguishable. Until you can see a structure in the randomness, so you can see copies.

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 are. And molecules actually are super important thing in chemistry to say, look, you can have a mole of a molecules and have a garrows number of molecules. And they're identical. What does that mean? That means that the molecular composition, the bonding and so on, the configuration is all is in distinguishable. You can hold them together. You can overlay them. So the way I do it is if I say, here's a bag of 10 identical molecules. That's pretty, they're identical. You pick one out of the bag and you basically observe it using some technique and then you take it away and then you pick 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. So 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, I met clinical 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, to detect the left and the right hand, they become different. And so, it's to do with the detection system that you have and the resolution.

Sure, I mean, of course, we're different close up, but if you zoom out a little bit, we'll morphologically look the same. You know, high characteristics, hair lengths, stuff like that.

Yeah, I agree. I mean, this is the power of assembly theory in that regard. So if everything, so the way to look at it, if you have a box of objects, if they're all if they're all indistinguishable, then using your technique, you then what you then do is you then look at the assembly index. Now, if the assembly index of them is really low, right, and they're all indistinguishable, then it's telling you that you have to go to another resolution. So that would be, you know, it's kind of a sliding scale. It's kind of nice. So you got it.

Yeah.

I would, I would look, yeah, so if you're just going to Mars or Titan or in Salazar or somewhere. So a number of ways are doing it. So you can take a large scoop or you go for the atmosphere and detect stuff. So you can make a life meter, right? So one of Sarah's colleagues at ASU Pool Davies keeps calling it a 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've found life. We've found the alien. We've found the alien Elon Musk smoking a joint in the bottom of the cave on Mars, or Elon himself, whatever, right? So okay, found it. So what you can do is a mass spectrometer, You could just look for things in the gas phase. Or you go on the surface, drill down, because you want to find molecules where you, you've either got to find the source living system, because the problem with just looking for complexity is it gets burnt away. So in a harsh environment on, on, on, on, say on the mar 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 now we want to keep the life meter keep searching for more and more complexity until you actually find living cells you 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 legs

Mass spectrometer would be the first way doing it.

So I would take my life meter, our life meter.

Yeah, 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. Alternatively, you'd shine infrared light on the new count number of bands, but you'd have to, in that case, do some separation, because you want to separate input. And so in my spec, it's really nice and convenient, because you can separate it later, statically. But you need to have that. Can you do it in real time? Yeah, pretty much, pretty much. Yeah, so let's go all the way back. So this, okay, we're really going to get this. Let's go. The Lexus life me Lex and Lee.

All right, so you have a, you have a vacuum chamber, you have a little nose and nose would have some, a, a, packing material. So you would take your sample, add it onto a nose, add a solvent or a gas, it would then be sucked up to 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 case of the infrared, count the number of bands, in the case of the mass spec, count the number of fragments and weigh it. And then the further up in molecular weight range for the mass spec and the number of bands you go up and up and up from the, you know, dead interesting, interesting, over the threshold, oh my gosh, earth life. And then right up to the batshit crazy, this is definitely, you know, alien intelligence that's made this life, right? You could almost go all the way there, same in the infrared. And it's pretty simple. The thing that is really problematic is for many years, decades. what people have done, and I can't blame them, is there rather that they'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 there is run looking for complexity. The beautiful thing about this is you can look for complexity without earth chemistry bias or earth biology bias. So assembly theory is just a way of saying, hey, complexity in abundance is evidence selection. That's how all universal life meat will work.

So we did this a few years ago when I was trying to convince NASA and colleagues that this technique could work. And honestly, it's so funny because everyone's like, man, I ain't going to work. I don't know, there's like, because the chemist was saying, of course, they're a complicated molecules out there. You can detect that just form randomly. And it 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 on a typewriter. Just for me, it was like really. And I pushed a lot on the chemist now. And I think most of them are on board, but not totally. It really had some big arguments, but the copy number caught there. Because I think I confused the chemist by saying one off. And then when I'm made clear about the copy number, I think that made it a little bit easier. Just a glorify.

Yeah, exactly that. Okay.

Yeah, exactly. So on Earth, to come back to Earth, what we did is we took a whole bunch of samples, and we were running pre-bodic chemistry experiments in the lab. We took various inorganic minerals and extracted them, look at the volatile, because there's a special way of treating minerals and polymers in the assembly theory. 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, they're not how, how can you make, if you can't assert that they're identical, then it's very difficult for you to work out if this undergone selection or they're just around the mess, same with some minerals, but we can come back to that. So basically what you do, we got a whole larger samples in organic ones. We've got a load of, we've got Scotch whiskey, and also got, I took a hard bear, which is one of my favorite whiskey, which is very pity, and another whisked PD mean. It's like, so the way that on in Scotland in Isla, which is little island, the Scotch, the whiskey is led to mature and barrels, and the, it's said that the peak, 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 and so you know Volkers the complete opposite it's just pure right with a lot of the whiskey the higher the something so that's the higher something is the better the whiskey That's what I mean, I really love deep PT, Scottish whiskeys. Near my house, there is a lowland distilleries called Glen Goine. It's still beautiful whisky, but not as complex. So, for fun, I took some Glen Goine whisky in our bear and put them into the mass spec and measure the assembly index. I also got Ecoly. So, the way we do take the Ecoly, break the seller part, take it all apart, and also got some beer. And people were ridiculing us saying, oh, bear is evidence of complexity. One of the computational complexity people who's just throwing... Yeah, we kind of kind of his very vigorous and his disagreement of assembly theory was just saying, you know, you don't know what you're doing, even beer is more complicated than human. We didn't realize it's not beer, per se, it's taking the yeast extract, taking the extract, breaking the cells, extracting the molecules and just looking at the profile of the molecules, see if there's anything over the threshold. And we also put in a really complex molecule taxol. 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 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. Something from Antarctica, C-Bad. They gave us a merciless and meteorite and a few others. Put them through the system. So we took all the samples, treat them all identically, put them into mass spec, fragmented them, count them, and in this case, implicit in the measurement was we you in mass spec you only to text um 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 we should super important there this is in the first paper because I guess in abundant of course um 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 A-botic samples were less than 15 and then we took the NASA samples and we looked at the ones with 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. And that's what we found on Earth. That's a success. Yeah, oh yeah, resounding success.

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 Ecoli sample. So he's done the beer. That mean there. I didn't know which one was higher. We didn'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.

Well, is that we've just mapped the Tree of Life using a semi theory because everyone said that you can't do infant biology and what we're able to do is, so I think there's two ways of doing Tree of Life and what three ways actually. What's the Tree of Life? So the Tree of Life is basically tracing back the history of life on a full different species going back, who have evolved from what? And it all goes all the way back to the first kind of life forms, and they branch off, and you have plant kingdom, the animal kingdom, the fungi, the kingdom, and different branches all the way up. And the way this was classically done, and I'm no evolutionary biologists, the evolutionary biologists, it's a very, tell me, every day, at least 10 times. I want to be one though, I kind of like biologists, it's kind of cool, but yeah, it's very cool. But basically, what Darwin and Mendelaev and all these people do is they draw pictures, right? And they text her. They just can't, they were able to draw pictures and say, and say, oh, this looks like common classes.

But they're, they're, they're able to find out a lot, right? And looking at vertebrates, inverbrates, camera and exposure and all this stuff. And then, um, then came the genomic revolution and suddenly everyone used gene sequencing and Craig Venter's a good example. I think he's gone around the world and he's yacht just picking up samples, looking for new species, where he's just found new species of life, just from sequencing. It's amazing. So you have taxonomy, you have sequencing, and then you can also do a little bit of molecular kind of archaeology like 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 used 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 were able to recapitulate the tree of life using mass spectroscopy. No sequencing and no drawing.

So what you do is you take an unknown sample, you plug it into the mass spec. You get a, because this comes from what you're asking like, what do you see in your co-line? And so in your co-line, you don't just see, it's not the most sophisticated cells on, on a, make the most sophisticated molecules. It is the coexistence of lots of complex molecules above a threshold. And so what we realize is you could fingerprint different life forms. So fungi make really complicated molecules. Why? Because they can't move. They have to make everything on site. Whereas, you know, some animals are like lazy. They can just go eat the fungi. You know, 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 routes and look at what's called the joint assembly space. But let's translate that into the experiment. Take a sample, bang it 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 mean they want to do. And by basically looking at the assembly space, these molecules create. Without any knowledge of assembly theory, you are unable to do it. With an knowledge of assembly theory, you can reconstruct the tree.

Let's go to two leaves on different branches on the tree. Right? What you can do by counting the number of differences, you can estimate how far away their origin was. Got it. And that's all we do. And it just works. But when we realized, you could even use a semi-series to recapitulate the tree of life, for noting sequencing.

I would love to get old fossil samples and apply a semi theory aspect 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. The DNA DNA and RNA is quite unstable. But some of the more complex molecules might be there, might give you a hint, something new, or wouldn't it be great if you, if you find a sample that's worth really persevering and doing, you know, doing the proper extraction to wreak to, you know, PCR and so on, and then sequence it and then put it together.

Yeah, and we can, and it appears that you can do some dating. Now, there are really good techniques. There's radio carbon dating. There is longer dating going looking at radioactive minerals and so on, and you can also in bone. you can look at the what happens in after something dies is the you get what's called rationalization where the the the chirality in the polymers basically changes and you just get you get decomposition and the rate of the deviation from the pure In Antima to the mixture, you can give you a time scale on it, a half-life. So you can date when it died. I want to use assembly theory to see if I can date, use it date death and things and trace the tree of life and also decomposition of molecules. You think it's possible. Oh yeah, we've outed out. It may not be better than what, because like the I was just at conference where some brilliant people were looking at isotope and Richmond and looking at how life enriches isotopes and they're really sophisticated stuff that they're doing. But I think there's some fun to be had there because we 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 amount of carbon 13 in you goes up. Because of the way the metabolic, because of the way the bonding is in carbon 13. So it has a slightly different strength, bond strength than you is called a kinetic isotope effect. So you can literally date how old you are. Or when you stop metabolizing, so you could date someone as dead, how old they are, I think, are 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.

Yeah, like you could say all this person is 10 years old and this person 30 years old because they've been metabolizing more carbon and they've accumulated. That's the basic idea. It's probably completely wrong timescales.

At the moment, we should be able to do this to morphology in cells, so we're looking at cell surfaces, and really I'm trying to extend further. It's just that we work so hard to get this paper out, and people to start discussing the ideas. But it's kind of funny, because I think the penny is falling on this. So, yeah, so was there anything worse in me for a penny? I mean, though, 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 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 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 a paper on people to read it, I want to write that badly again.

We go back, come in on, see your question about the high rock in 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.

The, yes, the most exciting criticism came from the evolutionary biologist telling me that they thought that it would origin of life was a solved problem. And I was like, whoa, we're really on something because it's clearly not. And when you poke them on that, they just said, no, you don't understand evolution. And I said, no, no, I don't think you understand the evolution had to occur before biology. And we need, there's a gap. That was really for me. that misunderstanding and that did cause immune response, which was really interesting. The second thing was the fact that 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 the emergence of life was not encoded in the initial conditions of the universe. And it can't and I think a 73 show is white can't be.

The emergence of life was not and cannot, in principle, be encoded in the initial conditions of the universe.

Yeah. And this goes back to your favorite subject. That's that.

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 there's notion of commentorial 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 of stray.

It's their 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 were 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 have said, how dare this be published in nature? This is, you know, how what the terrible journal. And, 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 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 who want to actually do something new because this makes a bold claim. And the chances are that it's not correct, but what I wanted to do is a couple of things that I want to make a bold claim that was precise and testable and correctable, not a woolly, another woolly information-inbiology argument, information-turing 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.

Yeah, that's really good. The assembly index of a molecule is not obvious, nor what it measures 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 the people that understand that the biology does something very interesting, some people call it neganthropy, some people call it think about, you know, organizational principles, that lots of people were not shocked by the paper because they're done it before. A lot of the arguments we got, some people said, oh, it's rubbish. Oh, by the way, I had this idea 20 years before. I was like, Which one? You'll write the rubbish part or the revolutionary part. So this kind of plucked two strings at once. It plucked the, there is something interesting the biologies are as we can see around this, but we haven't quantified yet. And what this is, the first stab at quantifying that. So the, the fact that people said, um, this is obvious, but it's also, um, so if it's obvious, why have you not done it?

Yeah. Well, I think you will be able to. We just haven't got there robustly. So if 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 motocons. And both are good. And they will be a symbol.

Let me go from if we go from. So if we go from molecules to assemblies. and let's take a cellar assembly and I think about a cell, as you can tell the difference between a u-carrier on a pro-carrier. The organelles are specialized differently when they look at the cell surface. The cell surface has different glycosylation patterns and these cells will stick together. Now let's go up a level in multi-cellular 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 tissue types. We can even apply it to different cell disease types. So that's what we're doing next, but we're trying to walk You know, the thing is, I'm trying to leap ahead. I want to leap ahead to go, well, we apply it to culture. Clearly, you can apply it to memes and culture. And we've also applied assembly theory to CAs and not as you think. Yeah, yeah, so someone not just 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 were different rules and they copied each other and made slightly different bit different cellular automata rules and they and public and looked at them online and so he was able to a third assembly index and copy number of rule whatever doing this thing but I don't grasp But it does show that you can apply it at higher scale. So what do we need to do to apply assembly theory two things? We need to agree there's a common set of building blocks. So in a cell, well, in a multi cell of the creature, you need to look back in time. So there is the initial cell, which the creature is fertilized and then starts grow. And then there is cell differentiation. And you have to then make that causal chain both on those. So it requires development of the organism in time. Or if you look at the cell surfaces and the cell types, they've got different features on the cell, what's the walls and inside the cell. So we're building up. But obviously I want a leap to things like emoticons, language, mathematical theory.

Yeah, and I think they are related, but in hierarchies of 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 a 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. I say, okay, let's look at the assembly indices, number of features in these, and now the copy numbers, just a number of how many birds are there, how many chimpanzees are there, how many humans are there?

Yeah. And that means you need to have some idea of the anatomy.

I guess so. I mean, and I think this is a good way to apply machine learning and image recognition, just the basic character rights thing.

And the compression has to be, remember the assembly universe, which is you have to go from assembly possible to assembly contingent. And that jump from a, because assembly possible or possible brains or possible features all the time. But we know that In 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 are going to learn something more.

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've collaborated right now. We already think we can do a 70 theory on language. And not only that, wouldn't be great if we can, so the, if we can figure out how under pressure, language is going to involve and be more efficient, because you're going to want to transmit things. And again, it's not just about compression. It is about understanding how you can make the most of the architecture you've already built. And I think this is something beautiful that evolution does. We're using 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 the key comment I want to make is that assembly theory is great for understanding when 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 and bought one, yeah, I can't justify it, but I want to at some point. The M3 processor arguably is quite a lot of features, a quite large number. The M2 came before it, then the M1, all the way back. You can apply assembly theory to my co-processer architecture. It doesn't take a huge leap to see that.

Yeah, I mean, I think the thing about large language models, and this is a whole hobby horse I have at the moment, is that obviously they're all about the evidence of evolution in the large language model comes from all the people that produce all the language. And that's really interesting and all the corrections in the mechanical Turk. Right, sure.

Exactly. So it would be really interesting to basically use an assembly-based approach to making language in a hierarchy, right? I think my guess is that You could, we might be able to build a new type of large language model that uses assembly theory that it has more understanding of the past and how things were created, right? Basically, what the thing with LLMs is 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 be great if we could understand how to embed more intelligence in the system.

Yeah. Well, I'm ready. I think selection produces intelligence.

Kind of I would go that I would go out and live and say that but I think it's a little bit more human beings have the ability to abstract and they can break beyond selection and this is what like Darwinian selection because a human being doesn't have to basically do trial and error like they can think about that that's a bad idea when do that and then technologies and so on.

Yeah, I, I, I seem to there seems to be a disconnect between the computational process. So yeah, so a common goal are 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. There's a main thing there. There are lots of other layers. So common goal or off complexity, you can approximate common goal of complexity, but it's not really telling you very much about the actual, it's really telling you about like your data set, compression of your data set. 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, It's 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. 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 then algorithmic information theory comes out of that. The frustration I've had with looking at life through this kind of information theory is it doesn't take control count causation. So the main difference between assembly theory and all these complexic measures is there's no core zool chain.

Exactly, if you've got your data in a computer memory, all the data is the same. You can access it in the same type of way. You don't care, you just compress it and you either look at the program run time or the shortest program. And that, for me, It is absolutely not capturing what it is what its selection does.

Oh, I would say it doesn't away. And it is fast man. Look at it. So you've just got the objects. And you have no other information about the object. What the assembly theory allows you to do would just with the object is to, and the word in fur is correct. I agree with him fur. You're like, say, well, that's not the history, but something really interesting comes from this. The shortest path is inferred from the object. That is the worst case scenario if you have no machine to make it. So that tells you about the depth of that object in time. And so what Assembly Theory allows you to do is 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, hey, there was a factory. And how big was that factory and how deep in time is it?

It is and becomes harder. One thing 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 looking at molecules' doctor proteins. Why not instead take the molecules that are involved in interacting with the receptors over time, rather thinking about and use the molecules evolve over time as a proxy for how the proteins evolve over time? and then use that to constrain your drug discovery process. You flip the problem one A, E, and focus on the molecule evolution, right on 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 in assembly spaces 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.

No the molecules and the no I don't know enough about approaching 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 this is not a react this is not correct reaction.

Yeah. And so, and what you do is you look at the minimal constraints on that graph. Of course, it 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 constraints space rather nicely. But this is just at the beginning, right? There are so many directions just could go in and I'll say it. It could all be wrong, but hopefully it's less wrong.

No, no. Well, let's go back. So no, not less likely. 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?

It's just basically what will kind of random graph. So we make an assumption that basically the timescale 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.

I'm writing a paper right now that I keep being told I have to finish, and it's called the origin of chemical reactions. And it merely says that reactivity exists as controlled by the laws of quantum mechanics. And reactions, we put names on reactions like so you can have like, I don't know, the vittic reaction, which is by vittic. 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 that 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, or this stuff. And that then allows us to focus in our chemistry. So when a chemist does a reaction, that's a really nice, compressed, short hand for constraint application. Glass flask. pure reagent, temperature pressure, bomb, bomb, bomb, control, control, control, control, control. So of course, we have bond energies. So the bond energies are kind of intrinsic in a vacuum, if you say that. So the bond energy you have to have a bond. And so for assembly theory to work, you have to have a bond, which means that bond has to give them molecule, certain life, a 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 when you count, look at the assembly of some molecules, you're going to miss count the assembly of the molecule because it falls apart too quickly because the bonds just fall. But you can solve that with looking at 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 biology. There was no chemist in the origin of life, baking unless you believe in the chemist in the sky and they were, you know, it's like Santa Claus. They had a lot of work to do, but chemical reactions do not exist. in the constraints that allow chemical transformations to do exist.

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 countries.

The grammar 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.

Oh, okay. They're pretty happy, but what most of them.

Everyone is grumpy on Sundays when you challenge. The problem with this paper is you what I was like, it's almost like I went to a part. It's like you, I do used to do this occasionally when as long as go to a meeting. and just find a way to find a friend, everyone at the meeting simultaneously, even though 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.

Yeah, I mean, so when we originally sent the paper, and we sent the paper, and the editor said, this was like, this is a quite a long process. We sent the paper and the editor gave us some feedback and said, I don't think it's that interesting. It's hard concept. And we asked, and the editor gave us some feedback, And we, and Sarah and I took a year to rewrite the paper.

Yeah, it was fun of the latter. What are you smoking? Okay.

Yeah, well, the thing is there was really critical, but in a really professional way. Yeah. And I mean, for me, this was the way science should happen. So when it came back, you know, we had too many equations in the paper. If you look at the preprint, they're just equations everywhere. I don't know, 23 equations. And when I said to Abysheck, it was the first door for it. We've got to remove all the equations. But my assembly equations staying in Abysheck are like, You know, no, we can't. I said, well, look, if we want to explain this to people, there'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 started again. So we wrote the whole paper again. We knew the entire, amazing. And we just went spit by bit by bit. And so what does it we want to say? And then we send the paper in. And we expected it to be rejected. And not even go to review. And then we got notification back at a Gondra review. We were like, oh my god, it's so going to get rejected. How is 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 a biochemist who just said, I don't believe you. You must be committing fraud. a long story, probably a boring story, but in this case it went out to review the comments came back and the comments were incredibly, they were very deep comments from all the reviewers. 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 common goal or 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.

It's I think it's I mean this paper for me kind of because this wasn't the the first time we tried to publish assembly theory at the highest level the nature communications paper we on the mass spec on the on the idea went through went to nature and got rejected look went through six rounds of reviewing got rejected 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 it using mass spec and also by the way molecules molecules molecules complex molecules can randomly form and we'll I 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

I don't normally get emotional about papers, but it's not about giving it up because we want to get it published because we want the glory or anything. It's just like why don't you understand? And so So what I did, so what I would just try to be as rational as possible and say, yeah, you didn't like it. Tell me why. And then, sorry, silly. Can you ever get emotional about papers normally? But I think what we do is you've just compressed like five years of angst from this.

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 it was a mad person, like, you know, the guy in depicted in, you know, in a beautiful mind, he was just like, not the actual genius part, but just the, just, just, just, just to create. because I kept writing expanded and I have no mathematical ability or and I was expanding. I was making these mathematical expansions where I kept seeing the same motif again. I was like, I think this is a copy number, the same string is carrying again again. Again, 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 Astrobarges, a great, you know, a mass spectroscopist, a great, and the chemists went nonsense, like biggest pile of nonsense ever fraught, you know. And I was like, but why fraught? And they just said, just because. And I was like, well, and so, and I could not convince the editor in this case, they had it was just so pissed off, because they see it as like a kind of, you know. You're wasting my time and I would not give up I wrote I went and did 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 excited because I'm like huh, they can't tell me why I'm wrong And this kind of goes back to, you know, when I was at school, I was, you know, kind of learning difficulties class and I kept going to the teaching and say, you know, you know, how what 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 add home, I wasn't telling the editor, they were idiots for anything like this or the reviewers, I kept it strictly like factual. And all I did is I just kept knocking it down, bit by bit by bit by bit 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 experiment or justification was already published. So when we did this one and we went through the versions 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 have, you know, the students, sorry, the first author was like, I can't believe it got accepted like normal. It's great. It's like, it's good. And then when the paper was published, I was not expecting the backlash. I was expecting computational, well, no, actually, I was 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 to the editor and apologize. And the editor was like, well, you're apologizing for, it was a great paper. Of course, it's going to get backlash. You said some controversial stuff.

I think as I said to when it got accepted and people were saying what kind of like hacking on it. I was like Papers are not gold medals. The reason I wanted 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. It's an order-colored exercise, self-replicating molecules, some other features that come in. And the fact that this paper has been so discussed for me is a dream come true. Like, 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 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 scaffold on it and we'll start to converge from new paradigm. So I think that that's the thing that I wanted to see You know, my colleagues, authors, collaborators, and people who are 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 wasn't very good. It's cool, right?

Yeah, yeah, one, 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 once I got out of, when I was, I think about it's major transition in my stupidity. Like, you know, I, everyone thought, I wasn't that stupid. Well, I was basically everyone thought I was faking, I like stuff and I was faking wanting to be, it's always what it'd be a scientist. So five, six, seven years, I'll be a scientist, take things apart and everyone's like, Yeah, this guy wants to be a scientist, but he's an idiot. And so, so everyone was really confused. I think at first that I wasn't smarter than I, you know, it's claiming to be. And then I just basically didn't do well in the attest and I went down and down and down and down and down and then, um, and I was kind of like, this is really embarrassing. I really like, maths and everyone says, I can't do it. I really like physics and chemistry and all that science and people say, you can't read and write. And so I found myself in a learning difficult class at the end of primary school and the beginning of secondary school in the UK secondary school is like 11, 12 years old. And I remember being put in the remedial class and the remedial class was basically full of were two types 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 was a bit of a rebel. I refused to read what I was told to read. And I found it difficult to read individual words in the way they were told. But anyway, I got caught one day teaching someone else to read. And they said, OK, then we don't understand this. I, I know always know what to be a scientist, but didn't really know what that meant. And I realized you have to get university and I thought I could 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 exam should be entered into, you're not, you're, you're just going to get C, D or E. You can't even get A, B or C, right? This is the UK G's D or C's. And I was like, Oh, shit. And I said, can you just put me into the high exam? I said, no, no, you're going to fail. There's no chance. So my father, I didn't intervene 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 have we paid? So they said, well, okay, so you didn't actually have to pay, pay if I failed. So I took the exams and passed them, unfortunately. I didn't get the top grades, but I got into A-levels. But then that also kind of limited what I could do at A-levels. I wasn't allowed to do A-level maths. because I had such a bad math grade from my GCSE, I only had a C. But I wouldn't let me go into the ABC for masks because of some kind of coursework requirement back then. So the top grade I could have got was a C, C new E. So I got a C, and then let me do kind of AS level maths, which is this half intermediate, but get to go university. But in the I like chemistry, I had a good chemistry teacher, so in the end I got to university to chemistry.

I have no idea other than. I was really, I really like not understanding stuff. For me, when I not understand something, I didn't understand. I feel like I don't understand anything. But now, back then, I was so, I remember when I was like, I don't know, I tried to build a laser when I was like eight. I thought, how hard could it be? And I basically, I was going to build a CO2 laser and I was like, right, I think I need some partially coated mirrors and need some carbon dioxide and I need a high voltage. So I kind of, and I was like, I didn't have a, and I was so stupid, right, I was kind of so embarrassed. I had to make enough CO2, I actually set fire and try to filter the flame.

Just to crack something off CO2 and I was like completely, completely failed and I've been, 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 and so, you know, So I remember being super curious and being determined to find answers. And so the kind of, when people do a give advice about this, why are asked advice about this? I don't really have that much advice other than don't give up. And one of the things I try to do as a chemistry professor in my group is I don't, I hire people that I think that, you know, I'm kind of home. If there's persistent enough, Who am I to deny them to chance? Because people gave me a chance and I was able to do stuff.

Essentially. I love being around smart people and I love confusing smart people. And when I'm confusing smart people, not by stealing their wallet 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.

And as long as they're not telling you just a complete idiot, and they give you different reasons. And I mean, I'm, you know, if ever, it's like with assembly theory, and people said, oh, it's wrong. And I was like, why? And they're like, 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 at that and the other. So I think 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 have some faith that I always wanted to have a new idea. And 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 could 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 your equations incorrect for this or your method is wrong. And then so why try and do is get enough criticism from people to then triangulate and go back. And I've been very fortunate in my life that I've got great colleagues, great collaborators, funders, mentors and people that will take the time to say, you're wrong because And then what I 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. But I'm not criticizing you as a person. I'm just criticizing the idea and trying to make it better and say, well, what about this? And sometimes I'm kind of, my filters are kind of, uh, you know, truncated in some ways. I'm just like, that's wrong. That's wrong. That's wrong. That's wrong. What to do there? Some people like, oh my God, you just told me, you destroyed my life's work. I'm like, relax. No, I'm just like, let's make it better. And I think that we don't do that enough because we're, you know, we, we're, we're, we're either personally critical, which isn't helpful. Or we don't give any criticism at all because we're too scared.

I'm sure I make mistakes on that. I argue lots with lots. I mean, I argue lots with Sarah and she's kind of shocked. I've argued with Yashir in the past and he's like, you're just making Yashir barking and you're just making that up. I'm like, no, no, not quite. But kind of. You know, I had a big argument with Sarah about time. She's like, no, time doesn't exist. No, no, 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. Necessity had us to abandon the fact that time is eternal to actually really fundamentally question how the universe produces commentary or novelty.

So I think assembly theory is fine in this time right now, but I think it helps us understand that something interesting is going on. So there's, and I'm really inspired by a guy called Nick Gisn. I'm going to butcher his argument, but I love his argument a lot. So I hope he forgives me if he hears about it. But basically, If you want free will, time has to be fundamental. And if you want time to be fundamental, you have to give up on Apostolic 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 Brawa said no, you can't all numbers of finite. So it kind of like with, so let's go back to step, because I was like, people are going to say, 70 theories seems to explain that comment or large commentorial space allows you to produce things like life and technology. And that large commentorial space is so big. is not even accessible to a Sean Carroll David Deutsch multiverse. The physicist saying that all of the universe already exists in time is probably, probably, that's strong work, not correct. that we are 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 its mathematical universe. He says, you know, the universe is kind of like a block universe. And I apologize to Max if I'm getting it wrong, but people think you can just move. You have the stat. You have the initial conditions. And you can run the universe right to the end and go backwards and forwards in that universe. That is not correct.

Yeah.

Yes, and 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. Is 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.

I think what you're saying is not. Impossible. Impossible. So here's why I'll make a quick, really quick argument. And this argument isn't mine.

Yeah, so I'll give my view, which kind of resonates with his, but basically it's very simple, actually, it would say that free will, that your ability to design and do an experiment is exercising free will. So he used that full process. Well, 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 is something really interesting. And he very much inspired me, but I think that Sarah Walker said that inspired me as well, that these will converge is that I think that the universe in the universe is very big, huge, but actually The place is largest in the universe right now. The largest place in the universe is Earth.

Because we have this commentorial 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 by logical selection just to be clear by logical evolution and then you have multi-cellularity. then animals and abstraction and we're in 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 could naturally arise anywhere and the further that distance goes in time and there's kind of it's just it's gigantic

I agree, and I would say, I'll say again, that the earth is the most gigantic thing we know in the universe, common authority. We know. We know. Now, 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 is associated with life is that I think the commentorial space associated to these planets is so different. We are never going to, our causal cones are never going to overlap or not easily. And this is a thing that makes me sad about alien life. Why we have to create alien life in the lab is 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 architectures.

Yeah, 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.

I, I truly don't know, but I, it's an excuse for me to ask for people to give me money to make a planet simulator. Yeah, right. If I can make with a different I'm just like another shameless like give me money.

It's like, you know, I'll be the first and I did my, my, my, my, my Rick, my Rick garage has run out of room, you know, yeah. No, um,

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 to look in the universe. So here's a thing. Here's my dream. My dream is that by creating life in the lab, and based upon constraints, we understand. There's like, for Venus type life or Earth type life or something, again, do I have 2.0? Screw it. Let's do I have 2.0? And I have 2.0 has a different genetic alphabet, fine, it's fine, different protein alphabet, fine, have cells in the evolution of that stuff. We will then be at a 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 chains where, but another tell us to go to other planets. that we are in that zone, we are most likely to conventorally overlap with, right? So because you know, we 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, not common goal or off, AIT type structure, but evolutionary structure, given by Assembly Theory, and we start to, but I would say that because I'm a shameless assembly theorist.

That's it. I hope that as we build, as we build abstractions, The main, I mean, 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 we will overlap there, even though we have completely different chemistry, literally completely different chemistry, that we will be at a past information from one another. But it's not a given. And I have to kind of try and divorce hope and emotion away from what I can logically justify.

But this 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. He flicked the Voyager program and pale blue dot. So I'd look how big the universe is. I was done at Illinois Rancid. Look at the Voyager program that came from the planet Earth that came from Luca. Look at how big Earth is.

It produced that. Yeah. And that I think is like completely amazing. And then that should allow people and everything. But well, probably we should try and get um, causal chains offer thunder mars onto the moon wherever. Well, it's human life or Martian life that we create, it doesn't matter. Um, but I think, um, this commentorial space tells us something very important about the universe. Um, and, and that I realized in the assembly theory that the universe is too big to contain itself. And I think this is and I'll coming back and I want to I want to kind of change your mind about time because I'm I'm guessing that your time is just a court. Yeah, so I'm I'm going to change.

Yeah, I'm going to change one of those. I'm going to change my mind in real time at least attempt.

But you can just add, you can just add, I don't know, time wants to it, right?

Or raise it a bit. 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 principle and Newtonian mechanics is this. If I give you the coordinates of your of an object's 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. However, you cannot specify these coordinates to infinite precision. Now everyone's saying, you know, oh, this is kind of like, you know, the kale serial argument. No, no, it's deeper than that. Here's a problem with numbers. This is how this is where Hilbert and Brower fell out. To 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. There's 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 you do? So in principle, if a finite object cannot be specified to infinite precision, in principle, the initial conditions don't apply. Well, how do you know against or how do you store it infinitely long number in a finite size?

Well, let's take the object. Let's say the object is a golf ball. Golf ball is a few centimeters in diameter. We can work out how many atoms are on the golf ball. And let's say we can store numbers down to atomic dislocations. So we can work out how many atoms are on the golf ball. And we can store the coordinates in that golf ball down to that number. But beyond that, we can't. Let's make the golf ball smaller. And this is where I think that we think that we get randomness in quantum mechanics and some people say you can't get randomness quantum mechanics deterministic. But 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 could say, was it true or false? You really know. But this is the fact we are unable to predict the future with the precision, is not evidence of lack of knowledge. It's evidence that the universe is generating new things.

Statistically, for that, but sure, I can say statistically what's going to happen, but then what they do happen, and then you keep nesting it together, You can't, I mean, go almost back to look at, look at, look at, look at, let's think about entropy in the universe. So how do you, how do we, how do we understand entropy change? Well, we could do the look at or process. We can use the algorithm hypothesis. We can also have the counterfactuals where we have all the different states and we can even put that in the multiverse. Right? 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 in the future. The real numbers are real. They're just observables.

Let me out. Do you believe or do you accept you have free will?

So then you are then you have to believe that time is fundamental.

Well, no, that we can logically follow us because if you don't have free will, so like, if you're in a universe that has no time, the universe is deterministic. If it's deterministic, then you have no free will.

No, I logically follows. No, no, I don't disagree. I'm not saying any, it's deep and it's important. All I'm saying, and it's the difference to, it's actually different what I've said before, is that if you don't require platenistic mathematics, and accepts 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 conditions, specify everything, to a mismatch in creative time. And I hope we'll do experiments. I think it's really important to, I would love to do an experiment that proves 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, a good mathematical background, and say, oh, hey, 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. The Boltzmann brain makes me super kind of like, you know, everyone's having a free lunch. It's like saying, it's like, let's break all the laws of physics. So a Boltzmann brain is this idea that in a long enough universe, a brain will just emerge in the universe's conscious. Without, and that neglects the causal chain of evolution that required to produce that brain. And this is where the computational argument really falls down because of computations, because they say, I can calculate probably if a Boltzmann brain. And I can, and they'll give you a probability, but I can calculate probably if a Boltzmann brain, zero.

Yeah, it's like when we start falling ourselves with numbers, then we can't actually measure and we can't ever conceive of. I think it doesn't give us a good explanation. And I've become, I want to explain why life is in the universe. I think life is actually novelty minor. I mean, life basically minds novelty almost from the future and makes it actualizes in the present.

I'm I'm really struggling around them this because I had a really good argument with Yashabakh about randomness. And he says, said, randomness doesn't give you free. Well, that's insane, because you'd just be random. But I think, and I think he's right at that level. Yeah. But I don't think we, I don't think he is right on another level. And it's not about randomness. It's about, it's about constrained, I've got the sound blinks. Constrained, I'm making this up as I go, I'm so making this up. Constrained opportunity. So what I mean is like, so you have to have, so that the novelty, what is novelty? You know, this is what I think is the funny thing. You ever want to discuss AI? Why I think everyone's kind of gone AI mad is that they misunderstanding novelty. But let's think about novelty. Just 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. It's always with precedent. 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 tie. I mean, of course I'm wrong, but how wrong? And I think that life opens up that commentorial space in the way that our current laws of physics, or the way 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 is correct, but it's really beautiful. But the David Deutsche's conception of the multiverse is kind of like given. But I think that the problem with wave particle duality in quantum mechanics is not about the multiverse. It's about understanding how to determine the past it's why 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're we're debating this for a long time now about how we how do we reconcile novelty to determinism in determinism it's okay just to clarify you both you and Sarah think the universe is not deterministic Uh, I'm, I won't speak for Sarah, but I roughly can't. I, I think that the universe, I, I think the universe is deterministic looking back in the, back in the past. Right. But under term and going future, going forward in the future. So I'm kind of having my cake and eat it. Yeah. Yeah. This is because I fundamentally don't understand randomness, right? As Yasha told me or other people told me. But if I adopt a new view now, which um, 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 deterministic, a universe that has deterministically looking rules? There's non-determined going in the future. Is this breakdown in precision in the initial conditions? And we have to just stop using initial conditions and start looking at trajectories and how the commentorial space behaves in expanding universe in time and space and assembly theory helps us quantify the transition to biology on biology appears to be a novel in mind because it's making crazy stuff you know and that we are unique to earth right that there are objects on earth that are unique to earth that will not be found anywhere else because you can do the commentorial math

So what I'm kind of meaning is because the future is bigger than the present in a deterministic universe. How would you go from the How do the how do the states go for one to another? I mean, there's a mismatch, right? Yeah. 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 might help us explain that. And I think as why I'm so determined to try and crack the the non-life to life transition looking at networks and molecules and that might help us think about it the mechanism. But certainly the future is bigger than the past in in my conception of the universe and some conception of the universe and by the way that's not obvious right that's was just kind of the future being bigger than the past.

Yeah. Yeah, yeah.

I think so. I think, but I think it's entirely Because look, we have the second law. And right now, I mean, we don't need the second law if the future's bigger than the past. It falls naturally.

So why we retrofitting all these, these sticking past is onto our reality to hold onto a timeless universe.

But it's not really exciting.

Yeah, it's kind of crazy, but obvious.

But the nice thing is you can, so the reason why Assembly theory turned me onto that was that you let's just start in the present and look at all the complex molecules and go backwards in time and understand how evolutionary processes go get gave rise to them. It's not at all obvious the taxol, 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 always unique to earth. There's no tax oil swearing the universe. And tax oil was not decided by the initial conditions. It was decided by this kind of, this interplay between the, so the past simply is embedded in the present. It gives some features, but why the past doesn't map to the future, one to one is because the universe is too big to contain itself, that gives space for creativity, novelty, and on some things which are unpredictable.

I think that this falls into the brauer, Hilbert trap. So how do you get a cellular time to produce a 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, like it's fascinating to me that for Pi, there is a formula where you can go to the million decimal place of Pi and read out the number without having to go there. But there are some numbers where you can't do that, you have to just crank through. Whether it's all frameyone computation where you reduce the ability or some other thing, it 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?

No, because the complexity on earth has a copy number and a assembly index associated with that, that CA is just a number running.

Well, it does in the human where we're looking at humans producing different rules, but then it's nested on selection. So those CAs are produced by selection. I mean, the CA is such a fascinating pseudo-complex E-generator. What I would love to do is understand quantify the degree of surprise in the 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, got it. CAs are mining novelty in the future by iteration, right? And you're like, oh, that's great. That's great. You didn't predict it. Some rules you can predict 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.

Absolutely.

You need three things, you need the initial conditions, you need the rules, and you need time iteration to mine it out without the coordinate, you can't get it out.

And you can't predict it from initial conditions. Yeah. If you could, then it'd be fine.

I think it's a, yeah, you have to have the resource. Yeah, because time is a fundamental resource and, 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, it's round up here at your time fundamentals. You should be as well. If you believe in free will, the only conclusion is there is time and fundamental. Otherwise, you cannot have free will. It logically follows.

looking back was in time and that's correct universities and everything else is is kind of leap it requires a leap I mean 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 because it helps explain this so the way I say if you take that's interesting why well let's let's just um My favorite one is because I'm the AI dooms as a driving me mad. We don't have any intelligence yet. I call AI autonomous informatics just to make people grumpy.

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 neuroscience is making great advances. But I think that we have no idea about AI. So I am a technological, I guess, optimist. I believe we should do everything. The whole regulation of AI is non-sensical. I mean, why would you regulate Excel, other than the fact that Clipy should come back and I love Excel 97, because we can play, you know, we can do the flight simulator. I'm sorry, Excel. Yeah, if you're not played the flight, it's simulator in 97.

What does that look like? It's like wireframe, very, very basic, but basically I think it's x0, y0, shift and it opens up and you can play the fight simulator. Oh, well, well, it is using Excel Excel 97. Okay. I resurrected at the other day and saw Clippy again for the first time in a long time.

I'm very frustrated by the way that we're AI-duming right now and people are bestowing some kind of magic. Now let's go back a bit. So you said, are we far away from Asia? Yes, I do not think we're going to get to Asia anytime soon. I'll see no evidence of it. And the AI-dumes in our area is non-sensical and extreme. And the reason why I think it's non-sensical, but it's not non-s... And I don't think there isn't things we should do and be very worried about, right? I mean, there are things we will need to worry about right now, what AI doing, whether it's fake data, fake users, right? I want authentic people or authentic data. I don't want everything that be faked and I think it's a really big problem and I'm 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 can't think of. Why is this? I'll take a very simple series of logical arguments. And this is that the AI dooms have not had the correct, and this has not had the correct, they do not have the correct epistemiology. They 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-dume AI. We can work out the probability of a asteroid hitting the planet. Why? Because it's happened before. We know the mechanism. We know that there's a gravity well, or that space time is banned and stuff falls in. We don't know the probability of AGI because we have no mechanism. So let me give you another one. I'm really worried about AGI. What's AG? AG is anti-gravity. One day we could wake up and anti-gravity is discovered. We're all going to die. The atmosphere is 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. I don't understand the current Um, reason for these, 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 got the optimists say AI is going to cure a soul and AI is going to kill a soul. What's the reality? What 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?

No, not not plus I think I don't know. I was seeing on Twitter today various things, but I think you're caskies at 95%.

I think. Well, I thought I think it's got Aaronson. I was quite surprised. I saw this online, so it could be wrong. So sorry if it's wrong. It says 2%. But the thing is, if someone said there's a 2% chance you can die going into the lift. Would you go into the lift? In the elevator for the elevator.

So I would say anyone higher than two percent. I mean, like, I mean, I think there's a zero percent chance of AGI do zero.

And you don't find that convincing. I think this is, 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, watching all the huts does online with a prompt engineering and all this stuff, When I talk to a typical AI compute scientist, they keep talking about the AI is having some kind of decision making ability. That is a category error. There's decision-making ability comes from human beings. We have no understanding of how humans make decision. We've just been discussing free will for last half an hour, right? We don't even know what that is. So the intention, I totally agree with you, people who intend to do bad things can do bad things and we should not let that risk go. That's totally here and now. I do not want that to happen and I'm happy to be regulated to make sure that systems I generate, whether they're like computer systems or You know, I'm working on a new project called cammackin'er.

We're done. Yeah, yeah, which is basically A, yeah.

And I only know one way to embody intelligence, that's in chemistry and human brains. So category R number one is agents that they have agency. category R 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 No reason to expect that we are going to make systems that are more intelligent. More capable, you know, when people play chess computers, they don't expect to win now, right? They just, 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 does the first happen? Eric Drexler, nanotechnology, 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 the self-replicating nanobots. You 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, no, sorry, the only functioning nanomolecular technology we know produced by evolution. There. So let's go forward to AEGI. What is AEGI? We don't know, it's super, it can do this or humans can't think. I would argue the only AGI is that exists in the universe produced by evolution. And sure, we may be our make-up working memory better. We might be able to do more things. Human brain is the most compact computing unit in the universe. Uses 20 watts. It's a really limited volume. It's not like a chat GPT cluster, which has to have thousands of watts, a model that's generated and 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? Well, I think it's kind of, they're making leaps that they're trapped in a virtual reality that isn't reality.

I think that that's right that you unintended consequences we have to think about and I'm that I fully 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 but hey let's talk about it because more I'll give myself a qualification yeah we're both qualified and sentient say thing yeah so there's much as anyone else I think the paper clips scenario is just a 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 come and did. For paper-mit clip manufacturing to really happen, I mean do the math. It's not going to happen, there's not enough energy, there's not enough resource, where there's all going to come from. I think that what happens in evolution is really Why is a killer virus not killed out all of not killed all life on earth? What happens is, sure, super killer viruses that kill the ribosome have emerged. You know what happens? They nuke a small space because they can't propagate. They will die. So there's this interplay between evolution and propagation, right? And death.

I think non-sensical. Okay. I think that just wouldn't, again, it wouldn't work. It was too deadly. It would just kill the radius and not replicate it.

I mean, I don't, I, so many more hands.

I think 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 by weapons have been made, and 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, right? And sure, it would be possible for a bad actor to engineer something bad, but the damage would be, we would see it coming, and we would be able to do something about it. Now, I guess what I'm trying to say is 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 Yan Laku, and I think we could put out a very good point about trying to regulate jet engines before we've even invented 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 this all dying. Yeah. When basically we need to actually really focus on, now let's say there's some back to the earnest. All right, let's say you're the Kalski is being 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 all going to be happy forever after. Yeah.

I understand that and I 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 so what's happening right now is there seems to be So let me, let's say, having some people saying AI doom 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 were really had existential threat. Almost as bad as now with AI doom, they were really worried, right? There was some great, they were not great, there were some horrific documentaries, I think there's one called Fred's that was generated in the UK, which was like, there was terrible, it was like so scary. And I think that The correct thing to do is obviously get rid of nuclear weapons, but let's think about unintended consequences. We've got rid of all the sulfur particles in the atmosphere, right? Or the or the syrup. And what's happening in the last couple years is global warming is accelerated because we've cleaned up the atmosphere too much. So, sure. I mean, the same thing if you get rid of a nuclear opportunity. 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. This sounds ridiculous, just a second hang on. But if we could all agree on the AI, do we just woke up? Yeah, yeah, yeah, that's statement. But I really don't like politicians who are basically just looking at loot local sampling, but if you could say globally, look, here's some game theory here. There's how what is the minimum number of nuclear weapons we need to just distribute around the world to everybody? to basically reduce war to zero.

But I don't think anyone will use them. Because 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 theorists 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 there's reduced number but not for rid of them because we'll have too much conventional warfare. So then what is the minimum number of nuclear weapons we can just reach around to remove human's hurting each other? is something we should stop doing. It's in, it's not out with our conceptual capability, but right now, what about the nations, 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 every human will go up faster. I am an optimist and I believe humanity is going to get better and better and better that we're going to eliminate more problems.

But we get, we just give you the nuclear nukes like population, right? We give what we do is we, but anyway, let's just go there. So if a small nation with a couple of nukes uses one because they're a bit bored or annoyed, they're likely that they are going to be pummeled out of existence immediately is 100%. And yet, they've only, they've only nuked one of the C. I know this is crazy, and I apologize for it.

I can predict a future where we take all nuclear material when we burn it for energy, right, as well 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.

Yeah. I don't know, I just made it up. No, it's interesting.

I think they're still in Argentina and they do in Somalia and they're doing a lot of these places where no I I think this is a great idea I'm a strong advocate now for so what we come up with burning burning all the nuclear material to have energy and before we do that because mad is good mutually assured destruction is very powerful let's take it into the metaverse and then get people to kind of subscribe to that. And if they actually nuke each other, even for fun in the metaverse, there are dire consequences.

No, they're happy. They have a job for another 20 years, right?

Yeah. Yeah. Yeah. Yeah. We got, I'm in believe ready. Cool employment.

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, senses. Once you can start to see things coming toward you, And you can remember the past and interrogate the present and imagine the future. You can do something amazing, right? So, and I think only in recent years did humans become cheering complete, right? Yeah.

Right, and we'll go and so that cheering completeness kind of gave us another kick-up. But our ability to process that information as produced in a wet brain. And I think that we are not getting going. We do not have the correct hardware architectures to have the domain flexibility and the ability to integrate information. I think intelligence also comes at a massive compromise of data. Right now we're obsessing about getting more and more data, more and more processing, more and more tricks to get dopamine hits. So we're going to, when we look back on this, going, oh yeah, that was really cool, because when I've chat, I've chatGPT, it made me 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, um, you know, as I said earlier about my nephew, you know, I just went from Bill to Billy and he went whole rightly, Roy. Like, how did he make that leap? They were able to basically, without any training. I extended his name, he went gay and that he doesn't like, he wants me to go bill. He went back and said, you like to be called Lee, I'm going to call you Lee Roy. 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 cheering complete. on our own. I don't, although AI is a built and cheering complete things, they're thinking is not cheering complete, in that they are not able to build universal explanations. And that lack of universal explanation means that they're just inductivists and activism doesn't get you anywhere, not it's just basically a party trick. It's like, you know, I like the, I think it's in the fabric a reality from David Deutsch where basically, you know, the farmer is feeding the chicken every day and the chickens getting fat and happy and the chickens like I'm really happy. Every time the farmer comes in and feeds me and then one day the farmer comes in and doesn't instead of feeding the chicken just rings its neck. you know, and that's kind of and had to check and had an alternative understanding of why the farmer was feeding it.

Oh, I've been pressed. I'm impressed. Increasingly so. But we're mining the past. Yes. And what the human brain appears to be, I do is mine the future.

I can show on the back of a piece of paper what that's impossible. And it's like the problem is that, and again, this domain experts kind of bullshitting each other. the term generative. Yes. Right. Average person. Oh, it's generous. No, no, no. If look, if I take the numbers between zero and one thousand and I train a model to pick out the prime numbers by giving all the prime numbers between zero and a thousand, he doesn't know what prime number is. Occasionally, if I can get a bit, it will start to guess. It never will produce anything out with the dataset because you're mind the past. The thing that I'm getting to is, I think that actually current machine learning technologies might actually help reveal why time is fundamental. It's like, I don't even say him, 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, um, so I think, so let's think about what the live language models are doing. We have the, we have the, we have all the internet as we know, yeah, you know, language, but also they're doing something else. We're having human beings correcting it all the time. Those models are being corrected, um, steered, corrected. modified tweaks. Yeah, but it'd be cheating.

Well, let me put it humans in the loop. Sorry to interrupt.

I don't think I think, again, we can show that on the piece of paper, that sure. I think that you have to have, so this is the failure in epistemology. I'm glad I even can say that word. Let me know what it means, right? I said it multiple times. I know. It's like three times now.

Thanks. So, but I think the, so what is reasoning? So coming back to the chemical brain, if I could basically, if I could show that in a, because I mean, I'm never going to make an intelligence in a, in a, in a, in a, because if we don't have brain cells, they don't have Giles cells, they don't have neurons. But if I can make, if I can take a major, a gel, and engineer the gel to have it be a hybrid hardware for reprogramming, which I think I know how to do. I will be at a process a lot more information and train 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, if human beings have had to become true and complete. And so I guess the question to give back at you, and it's 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 in explanations, inspiration comes from out, and then you then test that, and then you see that going towards a truth. And human beings are very good at doing that in the transition between philosophy, mathematics, physics, and natural sciences, where, and I think that we can see that. where I get confused is why people misappropriate the term artificial intelligence to say, hey, there's something else going on here because I think you and I both agree machine learning's really good. It's only getting better. We're going to get happier with the outcome. But why would you ever think the model is thinking or reasoning? Reasoning requires intention. And the intention, if the model isn't reasoning, the intentions come from the prompter and the intention has come from the person who programmed it to do it.

But those initial conditions came from someone starting it. Yes. And that calls little chain in there. So that intention comes from the outside. I think that there is something in that causal chain of intention that's super important. I don't disagree. We're going to get to AGI. It's a matter of when and what hardware. I think we're not going to do it in this hardware. And I think we're unnecessarily fetishizing really cool outputs and dopamine hits. Because obviously that's what people want to sell us.

I 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 Super Intelligence Generate can mine level even the future that I didn't see and it's training set in the past, I would agree that something really interesting is coming on. I'll say that again, if the intelligent system be a human being, a chatbot, something else, is able to produce something truly novel that we, I could not predict, even having followed it trail from the past. They're not going to be sold.

I think they are in the training set. I think everything it produces comes from a training set. There might be inter, there's a difference between inter, but novelty and interpolation. We do not understand where these leaps come from yet. That is what intelligence is. I would argue, those leaps And some people say, no, it's actually just what will happen if you just do cross domain training and all that stuff. And that may be true. And I may be completely wrong. But right now, the human mind is able to my 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 use chat GPT for a few weeks. Well, this is cool. And then it took me two, I had to, I will, what happened? Is it took me too much time to correct it? Then it got really good. And now they've done something to it. There's not actually that good. Yeah. Right.

I think that this, this is the thing that makes me most excited about these technologies, is they can help me demonstrate to you that time is fundamental. The unit future is bigger than the present, which is why we are human beings are quite good at generating novelty because we have to expand our data set. and to cope with unexpected things in our environment. Our environment froze them all out. Again, we have to survive in that environment. I mean, I never say never. I would be very interested in how we can get cross-domain training cheaply in chemical systems, because I'm a chemist and the only thing I know of is human brain, but maybe that's just me being boring, predictable, and not novel.

Yeah. I mean, this is one that goes my team. I try and do things that are non-obvious, but non-obvious in certain areas. And one of the things I was always asking about in chemistry, people like to represent molecules as graphs. And it's quite difficult. It's really hard. When 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 differentiable. Could I do something that was continuity differentiable? And I was like, well, molecules are actually made up of electron density. So I got thinking, say, well, okay, could there be a way where we could just basically take a database of readily solved electron density is for millions of molecules. So we took the electron density for millions of molecules and just trained the model to learn what electron density is. And so what we built was a system that you literally could give it a, let's say you could take a protein that has a particular active site, or, you know, a cup of the certain hole in it, you pour noise into it. And with a GPT, you turn the noise into that redundancy. And then, in this case, it hallucinates like all of them do. The hallucinations are good because it means I don't have to train on such a large number, such a huge dataset, because 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 data set. But what you've literally done is a quantum mechanical calculation we 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 densities is. So then you give it an unknown pocket. You pour in noise and you say, right, produce me electron density. It produces the electron density that doesn't look ridiculous. And what we did in this case is we produce the electron density that maximizes the electrostatic potentials to the stickiness. But minimizes what we call the steric hindrance. So the overlap so it's repulsive. So you know, make the perfect fit. And then we then use the kind of kind of kind of like a chat GPT type thing to turn that electron density into what's called a smile. A smile string is a way of representing a molecule and letters. And then we can then just generate some and then the other thing is then we bung that into the computer and then just makes it.

We've got the conveys that you just do chemistry. 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, the hallucinations are really great in this case, because in the case of a large language 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, but it thinks you're doing probabilistically. The problem on these urgency models is it's very expensive to solve a shredding equation, going up to many heavy atoms and large molecules. And so we wondered if we trained the system on up to nine heavy atoms, whether it would go beyond nine. And it did. It started generic molecules of 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. And then what we were able to do here is, and this is a really good point where I was trying to say earlier, that we were able to generate new molecules. from their known data set that would bind to the host. So a new guest would bind. Were these truly novel? Not really, because they were constrained by the host. Were they new to us? Yes. So I do understand, I can see that machine learning systems, artificial intelligence systems can generate new entities, but how novel are they? It remains to be seen.

That's what a lot of people say, like, you know, so the way to really get to genuine novelty and the assembly theory shows you the way is to have different causal chains overlap. And this really 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 a more different their histories the more novelty they generate in time going forward. And so it could be that genuine novelty is basically about mixed mix it up a little and the human brain is able to mix it up a little and all that stimulus comes from the environment. But all I think I'm saying is the universe is deterministic going back in time, non-deterministic going forward in time because the 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 generate more and more novelty. And that's how it works.

But 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.

Yeah. For this, you want to know? Yeah. Is I think that a lot of it, 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 futures. So openly like guys, met a guy's and all that. Well, 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, oh, yeah, we should do this because and it could cover up for the fact that we have got some problems with, you know, teenagers and Instagram and Snapchat and, you know, all this stuff. And maybe they're just overreacting now. Yeah. It's like, oh, yeah, sorry. We made the bubonic plate and gave it to you all and you all dying and, oh, yeah. But look at this over here. It's even worse.

Yeah, I agree, but what I worry about right now is like, I'm really, I do care about the ethics of what we're doing and then one of the reasons why I'm so open about the things we're trying to do in the lab, make life, look at intelligence, all this is so people say, what are the consequences of this? And then you say, what are the consequences of not doing it? And I think that what worries me right now in the present is lack of authenticate users and authenticate data and human users. Yeah, human users.

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 describe sentience and legal rights to a chatbot that makes you feel less lonely.

Yes. The chatbot's not what right now, using the technology we use is not going to be sentience.

I was God. Yeah, I don't know what God is. I mean, so God exists in our mind, created by selection. So human beings have created the concept of God in the same way that human beings have created the concept of superintelligence.

I think the universe, there is a create 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's some people I know that angry atheists say that religious people are stupid. I don't think that's the case. I have faith in some things, because I don't, I mean, when I was a kid, I kept like, I need to know what the charge of electronics is like, I can't measure the charge of electronics. I was just gave up and had faith, okay, you know, resistors worked. So when it comes to, I want to know why the universe is growing in the future 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 life better. I would love to continue that tradition.

Yeah. I think that. So I think that.

Well, I think selection. I think selection is the force. Selection is the force in the universe. It creates novelty.

Yeah, I think persistence of objects that could decay into nothing through operations that maintain that structure. I mean, think about it. It's amazing that things exist at all, that we're just not a big commentorial mess. Yes.

Yeah. I mean, that's think maybe the universe is actually But in the present, the things, everything that can exist in the present does exist.

I think the university's might, so the university started super small, the past was deterministic, there wasn't much going on. They were able to mine, mine, mine, mine, mine. And so the process, I mean, is somehow generating universities basically, I'm trying to put this into place.

No, I didn't say that. Sorry, there's free will. I think I think I'm saying that three will My curse at the boundary between the past and the future, the past and the future.

Everything that is so, everything that's possible to exist at this, so no, really, there's a lot of loaded words there.

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.

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.

And it's an amazing force. Because you're imagining it, this is the most important thing that we don't understand is our imaginations can actually change the future in a tangible way, which is what the initial conditions and physics cannot predict. Like your imagination has a causal consequence in the future.

It breaks the laws of physics as we know them right now.

if we then go back to initial conditions and that is simply not possible that can happen. But if we go into a universe where we accept that there is a finite ability to represent numbers and you have round it, we're not rounding errors, you have some that the sum what happens, the durability to make decisions imagine and do stuff is that that interface between the certain and the uncertain. It's not as Yasha was saying to me randomness goes and you just 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, or that choice is you interacting with a future in the present.

The universe. The fact it seems to be very undecided, very open, and 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 chase, you know, um, Deheta is going to be over at some point. No, I, for me, I don't, so I, 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. His ideas have been 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.

It would be quite boring because I mean, I mean, I mean, I mean, I mean, I mean, I mean, I mean, if it's a faithful representation of what I've done in my life, that's great. That's 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.

I mean, within some constraints, I've got, you know, you might, I can predict some things about you. You can predict some things about me. We can't predict everything. Everything. And it's because we can't predict everything is why we're exciting to come back and discuss and see it. So yeah, I'm I'm I'm I'm I'm kind of I'm happy that it'll be interesting that some things that I've done can be captured, but I'm pretty sure that my Angle one mining level teeth in the future will not be captured.

I think life is a selection produces life and life affects universe and universes with life in them are materially physically fundamentally different and universes about life and that's super interesting and I have no beginnings of understanding I think maybe this is like in a thousand years I'll be a new discipline in the humans we have of course this is how it works right and in retrospect there will be obviously I think it's 70 theories, obviously. That's why a lot of people got angry, right? They were like, oh my god, this is such nonsense. You know, like, oh, you know, actually is not quite. But the writing's really bad.

It's the pleasure to always like thanks for having me on.