Lex Fridman Podcast
#404 – Lee Cronin: Controversial Nature Paper on Evolution of Life and Universe
Sat, 09 Dec 2023
Lee Cronin is a chemist at University of Glasgow. Please support this podcast by checking out our sponsors: - NetSuite: http://netsuite.com/lex to get free product tour - BetterHelp: https://betterhelp.com/lex to get 10% off - Shopify: https://shopify.com/lex to get $1 per month trial - Eight Sleep: https://www.eightsleep.com/lex to get special savings - AG1: https://drinkag1.com/lex to get 1 month supply of fish oil Transcript: https://lexfridman.com/lee-cronin-3-transcript EPISODE LINKS: Lee's Twitter: https://twitter.com/leecronin Lee's Website: https://www.chem.gla.ac.uk/cronin/ Nature Paper: https://www.nature.com/articles/s41586-023-06600-9 Chemify's Website: https://chemify.io PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ YouTube Full Episodes: https://youtube.com/lexfridman YouTube Clips: https://youtube.com/lexclips SUPPORT & CONNECT: - Check out the sponsors above, it's the best way to support this podcast - Support on Patreon: https://www.patreon.com/lexfridman - Twitter: https://twitter.com/lexfridman - Instagram: https://www.instagram.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/lexfridman - Medium: https://medium.com/@lexfridman OUTLINE: Here's the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time. (00:00) - Introduction (09:37) - Assembly theory paper (30:06) - Assembly equation (43:19) - Discovering alien life (1:01:38) - Evolution of life on Earth (1:09:34) - Response to criticism (1:27:12) - Kolmogorov complexity (1:39:02) - Nature review process (1:59:56) - Time and free will (2:06:21) - Communication with aliens (2:28:19) - Cellular automata (2:32:48) - AGI (2:49:36) - Nuclear weapons (2:55:22) - Chem Machina (3:08:16) - GPT for electron density (3:17:46) - God
The following is a conversation with Lee Cronin, his third time on this podcast. He is a chemist from University of Glasgow, who is one of the most fascinating, brilliant, and fun to talk to scientists I've ever had the pleasure of getting to know. And now a quick few second mention of each sponsor. Check them out in the description. It's the best way to support this podcast.
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So we talk about the origin of life in the universe defined more generally, complexity, the emergence of complexity that forms life, the origin of life on Earth and the evolution of life as being part of the same system that integrates physics and chemistry and biology, all that kind of stuff. But ideas, ideas as organisms. brought to life.
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And now, dear friends, here's Lee Cronin. So your big assembly theory paper was published in Nature. Congratulations. Thanks. It created, I think it's fair to say, a lot of controversy, but also a lot of interesting discussion. So maybe I can try to summarize assembly theory and you tell me if I'm wrong. Go for it.
So assembly theory says that if we look at any object in the universe, any object, that we can quantify how complex it is by trying to find the number of steps it took to create it, and also we can determine if it was built by a process akin to evolution by looking at how many copies of the object there are.
Yeah, that's spot on.
Spot on. I was not expecting that. Okay, so let's go through definitions. So there's a central equation I'd love to talk about, but definition-wise, what is an object?
Yeah, an object. So if I'm going to try to be as meticulous as possible, objects need to be finite and they need to be decomposable into subunits. All human-made artifacts are objects. Is a planet an object? Probably yes, if you scale out. So an object is finite and countable and decomposable.
um i suppose mathematically but yeah i still i still wake up some days and go to think to myself what is an object because it's it's it's a non-trivial um question persists over time i'm quoting from the paper here an object that's finite is distinguishable i'm sure that's a weird adjective distinguishable
We've had so many people offering to rewrite the paper after it came out, you wouldn't believe it's so funny.
Persists over time and is breakable such that the set of constraints to construct it from elementary building blocks is quantifiable. Such that the set of constraints to construct it from elementary building blocks is quantifiable. The history is in the objects. It's kind of cool, right? So, okay. So what defines the object is its history or memory, whichever is the sexier word.
I'm happy with both depending on the day.
Okay. So the set of steps it took to create the object. So there's a sense in which every object in the universe has a history.
Yep.
and that is part of the thing that is used to describe its complexity, how complicated it is. Okay, what is an assembly index?
So the assembly index, if you're to take the object apart and be super lazy about it or minimal, 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. And I only worked out why a few weeks ago, which is kind of funny. Because I was just like, no, this is sacrosanct. I don't know why. It will come to me one day. And then when I was pushed by a bunch of mathematicians, we came up with the correct physical explanation, which I can get to.
But it's the minimum. And it's really important. It's the minimum. And the reason I knew the minimum was right is because we could measure it. So almost before this paper came out, We've published papers explaining how you can measure the assembly index of molecules.
Okay, so that's not so trivial to figure out. So when you look at an object, we can say a molecule, we can say object more generally. To figure out the minimum number of steps it takes to create that object, That doesn't seem like a trivial thing to do.
So with molecules, it's not trivial, but it is possible because what you can do, and because I'm a chemist, so I'm kind of like, I see the lens of the world for just chemistry. I break the molecule part, break bonds. And if you take a molecule and you break it all apart, you have a bunch of atoms.
And then you say, okay, I'm going to then 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 structure.
lego architecture but then if you maybe take you know um a couple of blocks and put them together in a certain way maybe there have a their 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 then make a square triangle and keep going and you remember those motifs on the chain so you can then leap from the
start with all the Lego blocks or atoms just laid out in front of you and say, right, I'll take you, you, you, connect and do the least amount of work. So it's really like the smallest steps you can take on the graph to make the object. And so for molecules, it came relatively intuitively. And then we started to apply it to language. We've even started to apply it to mathematical theorems.
I'm so well out of my depth, but it looks like you can take minimum set of axioms and then start to build up kind of mathematical architectures in the same way. And then the shortest path to get there is something interesting that I don't yet understand.
So what's the computational complexity of figuring out the shortest path with molecules, with language, with mathematical theorems? It seems like once you have the fully constructed Lego castle, or whatever your favorite LEGO world is, figuring out how to get there from the basic building blocks, is that an NP-hard problem? It's a hard problem.
It's a hard problem, but actually, if you look at it, so the best way to look at it, let's take a molecule. So if the molecule has... um, 13 bonds. First of all, take 13 copies of the molecule and just cut all the bonds. So take cut 12 bonds and then you just put them in order. Yeah. And then that's how it works. So, and you keep looking for symmetry and re or, or copies.
So you can then shorten it as you go down. And that becomes commentorily quite hard. Um, for some natural product molecules, um,
um it becomes very hard it's not impossible but we're looking at the bounds on that at the moment but as the object gets bigger it becomes really hard and but that's the bad news but the good news is there are shortcuts and we might even be able to physically measure the complexity without computationally calculating it which is kind of insane well how would you do that
Well, in the case of molecule, so if you shine light on a molecule, let's take an infrared, the molecule has each of the bonds absorbs the infrared differently in what we call the fingerprint region. And so it's a bit like, and because it's quantized as well, you have all these discrete kind of absorbences.
And my intuition after we realized we could cut molecules up in mass spec, that was the first go at this.
We did it with using infrared, and the infrared gave 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 for a molecule that we can calculate mathematically.
Okay, so these are all methods of mass spectrometry, mass spec. You scan a molecule, it gives you data in the form of a mass spectrum, and you're saying that the data correlates to the assembly index.
Yeah.
So how generalizable is that shortcut, first of all, to chemistry, and second of all, beyond that? Because that seems like a nice hack, and you're extremely knowledgeable about various aspects of chemistry, so you can say, okay, it kind of correlates. But the whole idea behind assembly theory paper, and perhaps why it's so controversial, is that it reaches bigger.
It reaches for the bigger general theory of objects in the universe.
Yeah, I'd say so. I'd agree. So I've started an assembly theory of emoticons with my lab, believe it or not. So we take emojis, pixelate them, and work out the assembly index for the emoji. And then work out how many emojis you can make on the path of emojis. So there's the Uber emoji from which all other emojis emerge. So you can then take a photograph, and by looking at the shortest path...
by reproducing the pixels to make the image you want, you can measure that. So then you start to be able to take spatial data. Now there's some problems there. What is then the definition of the object? How many pixels? How do you break it down? And so we're just learning all this right now.
So how would you begin to compute the assembly index of a graphical, like a set of pixels on a 2D plane that form a thing?
So you would, first of all, determine the resolution. So then what is your X, Y, and what is 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 would basically then... do exactly the same thing we would do for cutting the bonds.
You'd cut bits out of the emoji and look at the – you'd have a bag of pixels, and you would then add those pixels together to make the overall emoji.
Wait a minute. But, like, first of all, not every pixel is – I mean, this is at the core sort of machine learning and computer vision. Not every pixel is that important. And there's macro features, there's micro features, and all that kind of stuff. Exactly. The eyes appear in a lot of them. The smile appears in a lot of them.
So in the same way in chemistry we assume the bond is fundamental, what we do in there here is we assume the resolution at the scale at which we do it is fundamental. And we're just working that out. And 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 is 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 wandering a bit here, but it's kind of worth wondering, I think in 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 when 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 scales in this combinatorial universe.
Yeah. Can you explain each one of them?
Yep, so the assembly universe is like anything goes. It's just combinatorial kind of explosion in everything. So that's the biggest one? That's the biggest one. It's massive.
Assembly universe, assembly possible, assembly contingent, assembly observed. And on the y-axis is assembly steps in time.
Yeah.
And on the x-axis, as the thing expands through time, more and more unique objects appear.
So, yeah, so assembly universe, everything goes. Yep. Assembly possible, laws of physics come in, in this case in chemistry bonds. In assembly, so that means... Those are actually constraints, I guess. Yes. And they're the only constraints. They're the constraints of the base. So the way to look at it, you've got all your atoms, they're quantized, you can just bung them together.
So then you can become a kind of... So in the way in computer science speak, I suppose the assembly universe is just like no laws of physics. Things can fly through mountains beyond the speed of light. In the assembly possible, you have to apply the laws of physics, but... you can get access to all the motifs instantaneously with no effort. So 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 have somehow built a system that allows you to select that path rather than other paths. And then the final thing is, 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.
Wait a minute. So when you say the universe has to construct the system that does the work, is that like the environment that allows for selection?
Yeah. That's the thing that does the selection. You could think about it in terms of a von Neumann constructor versus a selection, a ribosome, a Tesla plant assembling Teslas. The difference between the assembly universe in Tesla land and the Tesla factory is Tesla Everyone says, no, Tesla's are just easy. They just spring out. You know how to make them all.
The Tesla factory, you have to put things in sequence and out comes a Tesla.
So you're talking about the factory.
Yes, this is really nice. Super important point is that when I talk about the universe having a memory or there's some magic, it's not that. It's that 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 um so it's not kind of just making everything yeah but lee what's the factory that made the factory
So first of all, you assume the laws of physics has just sprung to existence at the beginning. Those are constraints. But what makes the factory the environment that does the selection?
This is the question. Well, it's the first interesting question that I want to answer out of four. I think the factory emerges in the interplay between the environment and the objects that are being built. And here, let me, I'll have a go at explaining to you the shortest path. So why is the shortest path important?
Imagine you've got, I'm going to have to go chemistry for a moment and then abstract it. So imagine you've got, a given environment that you have a budget of atoms you're just flinging together and the objective of those atoms that have been flung together in say molecule A have to make they decompose so molecules decompose over time so the molecules decompose
in this environment, in this magic environment, have to not die, but they do die. They have a half-life. So the only way the molecules can get through that environment out the other side, let's pretend the environment is a box, you can go in and out without dying, and there's just an infinite supply of atoms coming, or, well, a large supply,
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 molecule takes 10 steps and it's using a finite set of atoms. Now, let's say another molecule, smart-ass molecule we'll call it, comes in and can survive in that environment. and can copy itself, but it only needs five steps.
The molecule that only needs five steps, because both molecules 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's just like a kind of, it seems to be like some kind of conservation law.
So one of the intuitions you have is the propagation of motifs in time will be done by the things that can construct themselves in the shortest path. So like, you can assume that most of the objects in the universe are built in the shortest, in the most efficient way. So... Big leap I just took there.
Yeah. 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, an individual 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 a compromise. Right. So when you see 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. And this is still very hand-wavy.
I maybe have no leg to stand on, but we think we're getting somewhere with that.
And there's probably some parallelization.
Yeah.
Right? So this is all, this is not sequential. The building is... I guess when you're talking about complex objects, you don't have to work sequentially. You can work in parallel. You can get your friends together.
Yeah. And the thing we're working on right now is how to understand these parallel processes. Now there's a new thing we've introduced called assembly depth. And assembly depth can be lower than the assembly index for a molecule. when they're cooperating together because exactly this parallel processing is going on.
And my team have been working this out in the last few weeks because we're looking at what compromises does nature need to make when it's making molecules in a cell? And I wonder if, you know, I may be like, well, I'm always leaping out of my competence. But in economics, I'm just wondering if you could apply this in economic processes.
It seems like capitalism is very good at finding shortest path.
you know every time and there are ludicrous things that happen because actually the cost function has been minimized and so i keep seeing parallels everywhere where there are complex nested systems where if you give it enough time and you introduce a bit of heterogeneity the system readjusts and finds a new shortest path but the shortest path isn't fixed on just one molecule now it's in the actual
existence of the object over time and that object could be a city it could be a cell it could be a factory but i think we're going way beyond molecules and my competence probably should go back to molecules but hey all right before we get too far let's talk about the assembly equation okay how should we do this now let me just even read that part of the paper
We define assembly as the total amount of selection necessary to produce an ensemble of observed objects, quantified using equation one. The equation basically has A on one side, which is the assembly of the ensemble, and then a sum... from one to n, where n is the total number of unique objects.
And then there is a few variables in there that include the assembly index, the copy number, which we'll talk about. That's an interesting, I don't remember you talking about that. That's an interesting addition and I think a powerful one. It has to do with what? That you can create pretty complex objects randomly.
And in order to know that they're not random, that there's a factory involved, you need to see a bunch of them. That's the intuition there. It's an interesting intuition. And then some normalization. What else is it?
And minus one, just to make sure that more than one object. One object could be a one-off and random. And then you have more than one identical object. That's interesting.
When there's two of a thing.
Two of a thing is super important, especially if the assembly index is high. So we could say several questions here.
One, let's talk about selection. What is this term selection? What is this term evolution that we're referring to? Which aspect of Darwinian evolution are we referring to that's interesting here?
So, yeah, so this is probably what, you know, the paper, we should talk about the paper for a second. The paper did, what it did is it kind of annoyed, um, we didn't know. I mean, it got attention and obviously angry people, the angry people were annoyed. There's angry people in the world. That's good. So what happened is the evolutionary biologists got angry.
We were not expecting that because we thought evolutionary biologists would be cool. I knew that some, not many, computational complexity people would get angry because I'd kind of been poking them and maybe I deserved it. But I was trying to poke them in a productive way. And then the physicists kind of got grumpy because the initial conditions tell everything.
The prebiotic chemist got slightly grumpy because there's not enough chemistry in there. And then finally, when the creationist said it wasn't creationist enough, I was like, I've done my job.
You say in the physics, they say, because you're basically saying that physics is not enough to tell the story of how biology emerges.
I think so.
And then they said a few physics is the beginning and the end of the story.
Yeah. So what happened is the reason why people put the phone down on the core of their paper, if you view reading the paper like a phone call, they got to the abstract. Yep. And in the abstract... The first sentence is pretty strong.
The first two sentences caused everybody... Scientists have grappled with reconciling biological evolution with the immutable laws of the universe defined by physics.
True, right? There's nothing wrong with that statement. Totally true.
Yeah. These laws underpin life's origin, evolution, and the development of human culture and technology, yet they do not predict the emergence of these phenomena. Wow. First of all, we should say the title of the paper, this paper was accepted and published in Nature. The title is Assembly Theory Explains and Quantifies Selection and Evolution. Very humble title.
And the entirety of the paper, I think, presents interesting ideas but reaches high.
I am not... I would do it all again. This paper was actually on the preprint server for over a year.
You regret nothing.
Yeah, I think, yeah. I don't regret anything.
You and Frank Sinatra did it your way.
What I love about being a scientist is kind of sometimes... Because I'm a bit dim. I'm like... And I don't understand what people are telling me. I want to get to the point. This paper says, hey, laws of physics are really cool. The universe is great. But... they don't really, it's not intuitive that you just run the standard model and get life out.
I think most physicists might go, yeah, there's this, you know, it's not just, we can't just go back and say that's what happened because physics can't explain the origin of life yet. That doesn't mean it won't or can't. Okay. Just to be clear, sorry, intelligent designers, we are going to get there. Second point, we say that evolution works, but we don't know how evolution works.
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 evolutions and then that might have made it even more crystal clear but i didn't think that biology evolutionary biology should be so bold to claim ownership of selection and evolution
And secondly, a lot of evolutionary biologists seem to dismiss the origin of life questions and 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 chemists are in the middle going, but hang on.
and this paper kind of says hey there is an interesting um disconnect between physics and biology and that's at the point at which memories get made in chemistry through bonds and hey let's look at this close and see if we can quantify it so yeah i mean i never expected the paper to to to kind of get that much interest and still i mean it's only been published just over a month ago now
So just to link on the selection, what is the broader sense of what selection means?
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.
Mm hmm.
So if I was going to kind of bolster the definition of an object, so if something can form and persist for a long period of time under an existing environment that could destroy other, and I'm going to use anthropomorphic terms, I apologize, weaker objects or less robust objects, then the environment could have selected that.
So good chemistry examples, if you took some carbon and you made a chain of carbon atoms, whereas if you took some, I don't know, some carbon, nitrogen and oxygen and made change from those, you start to get different reactions and rearrangements. So a chain of carbon atoms might be more resistant to falling apart under acidic or basic conditions.
versus another set of molecules so survives in that environment so the acid pond the molecule the molecule the resistant molecule can get through and and then then that molecule goes into another environment so that environment now maybe being an acid pond is a basic pond or maybe it's an oxidizing pond and so if you've got carbon and it goes an oxidizing pond maybe the carbon starts to oxidize and break apart so you go through all these kind of
Obstacle courses, if you like, given by reality. So selection is the ability happens when an object survives in the environment for some time. But, and this is the thing that's super interesting.
subtle the object has to be continually being destroyed and made by process so it's not just about the process the object now it's about the process and time that makes it because a rock could just stand on the mountainside for four billion years and nothing happened to it 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 proto factory, the environment. So really to answer your question, what the factory is, the factory is the environment, but it's not very autonomous. It's not very redundant. There's lots of things that could go wrong.
So once you get high enough up the hierarchy of networks of interactions, something needs to happen that needs to be compressed into a smaller volume and made resistant and robust. Because in biology, selection and evolution is robust, that you have error correction built in, that there's good ways of basically making sure propagation goes on.
So really, the difference between inorganic abiotic selection and evolution, and evolution and stuff in biology, is robustness. The ability to survive in lots of different environments. Whereas Our poor little inorganic soul, molecule, whatever, just dies in lots of different environments.
So there's something super special that happens from the inorganic molecule in the environment that kills it to where you've got evolution and cells can survive everywhere.
How special is that? How do you know those kinds of evolution factors are everywhere in the universe?
I don't, and I'm excited because I think selection isn't special at all. I think what is special is the history of the environments on Earth that gave rise to the first cell that now has taken all those environments and is now more autonomous. And I would like to think that this paper...
could be very wrong but i don't think it's very wrong it means certainly wrong but it's less wrong than some other ideas i know right and if this allow 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 process that's giving us
giving us high copy number objects that also are highly complex. But that doesn't look like life as we know it. And we use that and say, 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 would call it in biology, super advanced selection.
And even, I mean, you could use the assembly equation to look for technology and God forbid, 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 thought experiment I could do.
You have a little Petri dish, and on that Petri dish you put some simple food. So the assembly index of all the sugars and everything is quite low. And you put a single cell of E. coli cell. And then you say, I'm going to measure the assembly, the amount of assembly in the box. So it's quite low, but...
The rate of change of assembly, DADT, will go vum sigmoidal as it eats all the food, and the number of E. coli 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 E. coli's stopped... I mean, dye is probably a strong word.
They stop respiring because all the food is gone. But suddenly the amount of assembly in the box has gone up gigantically because of that one E. 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, an environment. You know, we try and kill the molecules.
And really, that's the main kind of idea for the entire paper.
Yeah, and see if you can measure the changes in the assembly index throughout the whole system. Yeah. Okay, what about if I show up to a new planet? We'll go to Mars or some other planet from a different solar system. How do we use assembly index there to discover alien life?
In very simply, actually, if we, let's say we'll go to Mars with a mass spectrometer with a sufficiently high resolution. So what you have to be able to do, so good thing about mass spec is that you can select the molecule from the mass. And then if it's high enough resolution, you can be more and more sure that you're just seeing identical copies.
You can count them and then you fragment them and you count the number of fragments and look at the molecular weight. And the higher the molecular weight, And the higher the number of the fragments, the higher the assembly index. So if you go to Mars and you take a mass spec or high enough resolution, and you can find molecules, and I'll give you 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. Now, you would say, oh, well, maybe the geological process. I would argue very vehemently that that is not the case. But we can say, look, if you don't like the cutoff on Earth, go up higher, 30, 100, right?
Because there's going to be a point where you'll find a molecule with so many different parts, the chances of you getting a molecule that has 100 different parts is... And finding a million identical copies, you know, that's just impossible. That could never happen in an infinite set of universes.
Can you just linger on this copy number thing? A million different copies. What do you mean by copies and why is the number of copies important?
Yeah, that was so interesting. And I... Always understood the copy number was really important, but I never explained it properly for ages. And I kept having this, it goes back to this, if I give you a, I don't know, a really complicated molecule, and I say it's complicated, you could say, hey, that's really complicated, but is it just really random?
And so I realized that ultimate randomness and ultimate complexity are indistinguishable. Until you can see a structure in the randomness. So you can see copies.
So copies implies structure.
Yeah. The factory.
I mean, there's a deep, profound thing in there. Because if you just have a random process, you're going to get a lot of complex, beautiful, sophisticated things. What makes them... Complex in the way we think life is complex or, yeah, something like a factory that's operating under a selection process, there should be copies. Is there, like, some looseness about copies?
Like, what does it mean for two objects to be equal?
it's it's all to do with the 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're all familiar with a molecule and molecules you can hold you know on your hand and lots of them identical copies a molecule is actually a super important thing in chemistry to say look you can have a mole of a molecule so an avogadro's 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 indistinguishable. 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. Let's prove 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 take another one out. If you observe it using technique, you 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 and rotational states. They're moving all the time. So with this respect, identical molecules have identical bonding.
In this case, we don't even talk about chirality because we don't have a chirality detector. So two identical molecules in one conception assembly theory basically considers both hands as being the same. But of course, they're not. They're different. As soon as you have a chiral distinguisher detect the left and the right hand, they become different.
And so it's to do with the detection system that you have and the resolution.
So I wonder if there's an art and science to which detection system is used when you show up to a new planet.
Yeah, yeah, yeah.
So you're talking about chemistry a lot today. We have kind of standardized detection systems, right, of how to compare molecules. So when you start to talk about emojis and language and mathematical theorems and things I don't know, more sophisticated things at a different scale, at a smaller scale than molecules, at a larger scale than molecules, like word detection.
If we look at the difference between you and me, Lex and Lee, are we the same? Are we different?
Sure, I mean, of course we're different close up, but if you zoom out a little bit, we'll morphologically look the same. You know, height and characteristics, hair length, stuff like that.
Well, also like the species.
Yeah, yeah, yeah.
And also there's a sense why we're both from Earth.
Yeah, I agree. I mean, this is the power of assembly theory in that regard. So the way to look at it, if you have a box of objects, if they're all indistinguishable, then using your technique, what you then do is you then look at the assembly index. Now, if the assembly index of them is really low, and they're all indistinguishable, then it's telling you that you have to go to another resolution.
So that would be, you know, it's kind of a sliding scale. It's kind of nice. Got it.
So those two kind of are at tension with each other. Yeah. The number of copies and the assembly index.
Yeah.
That's really, really interesting. So, okay. So you show up to a new planet, you'll be doing what?
I would do mass spec.
On a sample of what? Like, first of all, like how big of a scoop do you take? Did you just take a scoop? Like what? So we're looking for primitive life.
I would, I would look, yeah. So if you're just going to Mars or Titan or Enceladus or somewhere, so a number of ways of doing it. So you could take a large scoop or you'd go for the atmosphere and detect stuff. So, and you can make a light, um, a life meter, right? So, um, well,
One of Sarah's colleagues at ASU, Paul Davis, 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 found the alien we've found we found the alien elon musk smoking a joint in the bottom of the cave on mars or elon himself whatever right you say okay found it so what you can do is the mass spectrometer um
you could just look for things in the gas phase, or you go on the surface, drill down, because you want to find molecules that are... You've either got to find the source living system, because the problem with just looking for complexity is it gets burnt away.
So in a harsh environment on, say, on the 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 soil that's billions of years old.
Then I would put in some solvent, water, alcohol or something, or take a scoop, make it volatile, put it into the mass spectrometer and just try and detect high complexity, high abundant molecules. And if you get them, hey presto, you can have evidence of life. Wouldn't that then be great if you could say, okay, we've found evidence of life.
Now we want to keep the life meter, keep searching for more and more complexity until you actually find living cells. You can get those new living cells and then you could bring them back to Earth or you could try and sequence them. You could see that they have different DNA and proteins. Go along the gradient of the light.
meter how would you build a life meter let's say we're together starting a new company launching a life mass spectrometer would be the first way of doing it just no no but that's that's uh that's one of the major components of it but i'm talking about like i would what if it's a device we got it and branding logo we're gonna talk all right that's later but what's the input what's the like how do you get to the um a metered output
So I would take a life, so my life meter, our life meter, there you go. Thank you. Yeah, you're welcome. Would have both infrared and mass spec. So it would have two ports so it could shine a 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 and
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 mass spectrometer, into electrostatic trap, and you'd weigh the molecules and fragment them. Alternatively, you'd shine infrared light on them. You'd count the number of bands.
But you'd have to, in that case, do some separation because you want to separate. And so in mass spec, it's really nice and convenient because you can separate electrostatically. But you need to have that. Can you do it in real time? Yeah, pretty much. Pretty much, yeah. So let's go all the way back. Okay, we're really going to get this. Let's go. Lex and Lee. No, no, Lex and Lee.
It's a good ring to it.
All right. So you have a vacuum chamber. You have a little nose. The nose would have a packing material. So you would take your sample, add it onto the nose, add a solvent or a gas. It would then be sucked up the nose. And that would be separated using what we call chromatography. And then as each band comes off the nose, we would then do mass spec and infrared.
And in the case of the infrared, count the number of bands. In the case of mass spec, count the number of fragments and weigh it. And then the further up in molecular weight range for the mass spec and the number of bands, you go up and up and up from the dead, interesting, interesting, over the threshold, oh my gosh, Earth life.
And then right up to batshit crazy, this is definitely 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 problematical is that for many years, decades...
What people have done, and I can't blame them, is rather they've been obsessing about small biomarkers that we find on Earth, amino acids, like single amino acids or evidence of small molecules and these things, and looking for those, 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 and abundance is evidence of selection. That's how our universal life meter will work.
Complexity and abundance is evidence of selection. Okay, so let's apply our life meter to Earth. So if we were just to apply assembly index measurements to Earth, what kind of stuff are we going to get? What's impressive about some of the complexity on Earth?
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, no, it ain't going to work. And I was just like, because the chemists were saying, of course there are complicated molecules out there you can detect that just form randomly. I was like, really?
That's like, that was like, you know, it's a bit like a... I don't know, someone saying, of course, Darwin's textbook was just written randomly by some monkeys and a typewriter. Just for me, it was like, really? And I've pushed a lot on the chemists now, and I think most of them are on board, but not totally.
I really had some big arguments, but the copy number caught there, because I think I confused the chemists by saying one-off, and then when I made clear about the copy number, I think that made it a little bit easier. Just to clarify...
Chemists might say that, of course, out there outside of Earth, there's complex molecules. Yes. Okay. And then you're saying, wait a minute, that's like saying, of course, there's aliens out there.
Yeah, exactly that. Okay. Exactly.
But you're saying, you clarify that that's actually a very interesting question, and we should be looking for complex molecules of which the copy number is two or greater. Right.
Yeah, exactly. So on Earth, coming back to Earth, what we did is we took a whole bunch of samples and we were running prebiotic chemistry experiments in the lab. We took various inorganic minerals and extracted them. Look at the volatile because there's a special way of treating minerals and polymers in assembly theory. In our life machine, we're looking at molecules. We don't care about polymers.
because they're not volatile, you can't hold them. If you can't ascertain that they're identical, then it's very difficult for you to work out if there's undergone selection or they're just a random mess. Same with some minerals, but we can come back to that. So basically what you do, we got a whole load of samples, inorganic ones,
We got a load of, we got Scotch whiskey and also took Ardberg, which is one of my favorite whiskeys, which is very peaty. And another whiskey is like, so the way that in Scotland, in Islay, which is a little island, the Scotch, the whiskey is let to mature in barrels. And it's said that the complex molecules in the peat find their way through into the whiskey.
And that's what gives it this intense brown color and really complex flavor. It's literally molecular complexity that does that. And so, you know, vodka is the complete opposite. It's just pure, right?
The better the whiskey, the higher the assembly index.
The higher the assembly index, the better the whiskey. I really love deep, peaty Scottish whiskeys. Near my house, there is one of the lowland distilleries called Glengoyne. It's still beautiful whiskey, but not as complex. So for fun, I took some Glengoyne whiskey in our bag and put them into the mass spec and measured the assembly index. I also got E. coli.
So the way we do it, take the E. coli, break the cell apart, take it all apart, and also got some beer. And people were ridiculing us, saying, oh, beer is evidence of complexity. One of the computational complexity people was just throwing... Yeah, 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. What he didn't realize is that it's not beer per se. It is taking the yeast extract, taking the extract, breaking the cells, extracting the molecules, and just looking at the profile of the molecules to see if there's anything over the threshold. And we also put in a really complex molecule, taxol.
So he 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're going to get this to work. And they really, you know, they gave us some super complex samples. And they gave us two fossils, one that was a million years old and one was at 10,000 years old. Something from Antarctica, seabed.
They gave us a Murchison 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, counted. And in this case, implicit in the measurement was in mass spec, you only detect peaks when you've got more than, let's say, 10,000 identical molecules.
So the copy number's already baked in, but wasn't quantified, which is super important there. This was in the first paper, because I was like, it's abundant, of course. And when you then took it all out, we found that the biological samples...
gave you molecules that had an assembly index greater than 15 and all the abiotic samples were less than 15 and then we took the NASA samples and we looked at the ones that were more than 15 and less than 15 and we gave them back to NASA and they're like, oh gosh, yep, dead, living, dead, living. You got it. Mm-hmm. And that's what we found on Earth. That's a success. Yeah. Oh, yeah.
Resounding success.
Can you just go back to the beer and the E. coli? So what's the assembly index on those?
So what you were able to do is like the assembly index of, we found high assembly index molecules originating from the beer sample and the E. coli sample. So I mean, I didn't know which one was higher. We wouldn't really do any detail there because now we are doing that because one of the things we've done, it's a secret, but I can tell you. I think it's a secret.
Nobody's listening.
Well, is that we've just mapped the tree of life using assembly theory, because everyone said that you can't do it in biology. And what we're able to do is, so I think there's three ways, well, two ways of doing tree of life, well, three ways, actually.
Yeah, what's the tree of life?
So the tree of life is basically tracing back the history of life on Earth, all the different species going back, who evolved from what, and it all goes all the way back to the first kind of life forms, and they branch off. And you have plant kingdom, the animal kingdom, the fungi kingdom, and different branches all the way up.
And the way this was classically done, and I'm no evolutionary biologist. Evolution biologists tell me every day, at least 10 times. I want to be one, though. I kind of like biology. It's kind of cool. Yeah, it's very cool. But basically, what Darwin and Mendeleev and all these people do is just they draw pictures, right? And they taxa.
They were able to draw pictures and say, oh, these look like common classes.
Yeah.
Then...
They're artists, really. They're just, you know.
But they were able to find out a lot, right, in looking at verbrates, inverbrates, Cameron explosion, all this stuff. And then came the genomic revolution, and suddenly everyone used gene sequencing. And Craig Venter is a good example. I think he's gone around the world in his 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 archaeology, like measure the samples and form some inference. What we did is we were able to fingerprint we took a load of random samples from all of biology and we use mass spectrometry.
And what we did now is not just look for individual molecules, but we looked for coexisting molecules where they had to look at their joint assembly space and where we were able to cut them apart and undergo recursion in the mass spec and infer some relationships. And we were able to recapitulate the tree of life using mass spectroscopy, no sequencing and no drawing.
All right, can you try to say that again with a little more detail? So recreating, what does it take to recreate the tree of life? What does the reverse engineering process look like here?
So what you do is you take an unknown sample, you pung it into the mass spec. Because this comes from what you're asking, like, what do you see in E. coli? And so in E. coli, you don't just see, it's not that the most sophisticated cells on Earth make the most sophisticated molecules. It is the coexistence of lots of complex molecules above a threshold.
And so what we realize is you could fingerprint different life forms. So fungi make really complicated molecules. Why? Because they can't move. They have to make everything on site. Whereas some animals are lazy. They can just go eat the fungi. They don't need to make very much.
And so what you do is you look at the... So you take, I don't know, the fingerprint, maybe the top number of high molecular weight molecules you find in the sample. You fragment them to get their assembly indices. And then what you can do is you can infer common origins of molecules. You can do a kind of molecular...
when the reverse engineering of the assembly space, you can infer common roots and look at what's called the joint assembly space. But let's translate that into the experiment. Take a sample, bung it in the mass spec, take the top, say, 10 molecules, fragment them, And that gives you one fingerprint. Then you do it for another sample, you get another fingerprint.
Now the question is you say, hey, are these samples the same or different? And that's what we've been able to do. And by basically looking at the assembly space that these molecules create. Without any knowledge of assembly theory, you are unable to do it. With a knowledge of assembly theory, you can reconstruct the tree.
How does knowing if they're the same or different give you the tree?
let's go to two leaves on different branches on the tree, right? What you can do by counting the number of differences, you can estimate how far away their origin was. And that's all we do. And it just works. But when we realized you could even use assembly theory to recapitulate the tree of life with no gene sequencing, we were like,
So this is looking at samples that exist today in the world. What about things that no longer exist? I mean, the tree contains information about the past. Some of it is gone.
Yeah, absolutely. I would love to get old fossil samples and apply assembly theory mass spec and see if we can find new forms of life that are no longer amenable to gene sequencing because the DNA is all gone. DNA and RNA is quite unstable. But some of the more complex molecules might be there and might give you a hint of something new.
Or wouldn't it be great if you find a sample that's worth really persevering and doing the proper extraction to PCR and so on and then sequence it and then put it together.
So when a thing dies, you can still get some information about its complexity.
Yeah, and it appears that you can do some dating. Now, there are really good techniques. There's radiocarbon dating. There is longer dating, going looking at radioactive minerals and so on. And you can also, in bone... you can look at what happens after something dies. You get what's called racemization, where the chirality in the polymers basically changes and you get decomposition.
The deviation from the pure enantiomer to the mixture you can have a time it gives you a time time scale on it half-life so you can date wh