The Physics Reason AI Works When It Shouldn’t - #568

The same mathematics that explains why a fridge magnet sticks to your refrigerator also explains why neural networks work when they have no right to. His group did the calculation. Nobody else had. Subscribe if you want science with evidence, not speculation. Goldenfeld is a Professor of Physics at UC San Diego, a Fellow of the Royal Society, and a Member of the National Academy of Sciences who spent 36 years at the University of Illinois applying condensed matter physics to problems everyone else had given up on: why the genetic code is optimal, why early life evolved impossibly fast, and why AI works despite being overparameterized beyond anything classical statistics can explain. The thread connecting all three is one idea: that what emerges from many things together is qualitatively different from the sum of its parts. That idea explains magnetism, AI, the origin of the genetic code, and why life may be inevitable wherever the laws of physics apply. He also argues that what is happening to science right now is not a disagreement about facts but a fracture in how people decide what is true, and that is a more dangerous problem. What you’ll hear: -Why the same phase transition that explains magnetism also explains why AI works at all -Why Francis Crick concluded life must have come from outer space and what Goldenfeld found instead -What horizontal gene transfer has to do with how libraries work -Why Goldenfeld thinks Enceladus is a better bet for life than Europa -The purpose of life, stated as a thermodynamics problem -Why “different is more” is more useful than “more is different” “The impact you make is the ratio of what you do divided by what everybody else does. Minimize the denominator.” — Nigel Goldenfeld CHAPTERS 00:00 AI shouldn't work. It does. 00:56 What is a phase transition? 03:10 What the renormalization group does 08:54 Ising gave up. Wrong dimension. 13:32 Nigel almost met Ising. 40 minutes away. 26:38 AI is the best example of more is different 33:52 Bardeen won two Nobels. The transistor looked like chewing gum. 37:24 The three mysteries Crick couldn't solve 46:20 The genetic code can't evolve. And yet it did. 49:00 How early life evolved like a library 57:06 The purpose of life as a physics problem 01:00:04 Life is physics, not chemistry 01:05:56 Anti-science age. Not because of opinions. 01:13:00 20 seconds with your 20-year-old self 01:17:14 Different is more Get the transcript, fascinating bonus content, and my Monday M. A. G. I. C. Message: https://briankeating.com/yt Have a .edu email and live in the USA? You automatically win a meteorite: https://BrianKeating.com/edu Subscribe: https://www.youtube.com/DrBrianKeating?sub_confirmation=1 Support Into the Impossible on Patreon, get my weekly M. A. G. I. C. Message, unfiltered bonus content, and live monthly Office Hours with me: https://www.patreon.com/drbriankeating Join this channel for perks, monthly Office Hours, and your name in the Member Roster at the end of every episode: https://www.youtube.com/channel/UCmXH_moPhfkqCk6S3b9RWuw/join Featured Guest: Nigel Goldenfeld website: https://guava.physics.ucsd.edu/~nigel/ Lectures on Phase Transitions and the Renormalization Group: https://www.amazon.com/dp/0201554097?lv=shuf&channelId=500&plpRedirect=mhFallbackNigel Goldenfeld on Twitter/X: https://x.com/NigelGoldenfeld My books: Losing the Nobel Prize (memoir): http://amzn.to/2sa5UpA Think Like a Nobel Prize Winner: https://a.co/d/03ezQFu Focus Like a Nobel Prize Winner: https://a.co/d/hi50U9U Galileo’s Dialogue (first-ever audiobook): https://a.co/d/iZPi9Un Twitter/X: https://x.com/BrianKeating Substack: https://briankeating.substack.com Blog: https://briankeating.com/blog Audio-only: https://briankeating.com/podcast #intotheimpossible #briankeating #NigelGoldenfeld #physics #AI #originoflife #condensedmatterphysics #podcast Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  And you're way, way into that regime where you're just fitting noise and the whole thing shouldn't work. It obviously shouldn't, and yet it does. Francis Crick said, look, there's no way that life got to this level of complexity in such a short period of time. It must have come from outer space. The genetic code is optimal in the sense of minimizing errors. If you wanted to know what is the purpose of life, the purpose of life is to help planets come into equilibrium. So a phase transition, you know, is like, for example, what happens to a piece of metal? When I cool it below a certain temperature and I want to know, can I use it to stick? The pictures of my kids' holiday pictures on the door of my refrigerator?

• 0:41Speaker 00

  And the answer is yes, if it's magnetic, it'll stick with a piece of metal holding the picture up. And if it's not magnetic, it won't stick. And if you take that piece of metal that works as a magnet, fridge magnet? And you heat it up, it will stop becoming a magnet. And that's, that's called a phase transition, as you know, and maybe some of your listeners know or viewers know. The interesting question you might ask is, as I get closer and closer to the temperature where the magnetization disappears? How does the magnetization disappear? Does it, it disappears gradually in fact? And if you ask how much magnetization there is, the answer is it goes like the

• 1:23Speaker 00

  square root of the difference between the temperature you're at and the critical temperature where the magnetization fully goes to zero. At least that's what you would expect. And that's what very generic, very persuasive, simple theoretical arguments that anybody can understand. I can explain it to my class in literally, you know, 20 seconds, that's what you would predict. When you do the experiment, you find that it doesn't go like the square root of the critical temperature minus the temperature. It goes like the Tc minus T to a power like 0.3265136, some weird, weird number like that. And you might say, well, it's just a, you know, a more accurate number.

• 2:05Speaker 00

  The problem is that there's no known way, or there was no known way to account for the fact that the number is not a half. It, I mean, it's like to prove it's a half, all I need to know is that magnets can be either magnetized north or magnetized south. And that's basically it. It's an argument that is so compelling, it can't possibly be wrong. And yet, in the decades from the 1940s up to the middle 1960s, it was discovered that it was wrong. And, and it wasn't just only the magnetization, there were other thermodynamic properties like heat capacity and things like this, which I won't go into, which also have a similar unaccountable behavior.

• 2:49Speaker 00

  And it was the fact that these numbers, which are themselves not particularly important. It was the fact that you couldn't even explain in principle why they are not these simple numbers like a half and so on. And that was the reason for the puzzle. And, and the explanation is a truly mind-boggling explanation. But just, just tell you the outlines of the story. This phenomenon was addressed by Leo Kadenoff, Ben Widdon, eventually Ken Wilson. And, and they invented this process of looking at a physical system on different scales of energy.

• 3:28Speaker 00

  So, you know, you could look at matter at the scale of this room where you could hear the sound waves, you can see light bouncing off the surfaces. On the other hand, if you want to go and see that there are atoms and see that there are quarks and things like this, you need to build, you know, a machine that's, you know, put in a tunnel 70 miles long under the Swiss Alps in order to be able to see things like that. So what you can see depends on what energy you look at it at and what time scale and what length scale you look at it at. And the same thing turns out to be true of the laws of physics themselves. And Leo Kadenoff was the first person who, who realized that. And Ken Wilson turned it into a mathematical tool, which was called the renormalization group. In fact, it's not even a group. You ask whether it's a group. It's actually a semi-group.

• 4:13Speaker 00

  And the idea was this, take a physical system and then just say, well, you know, I've got magnetic dipole moments, they're really spins of electrons, but we'll just call them magnetic dipole moments. They're in this bit of the sample, we'll just lump them together into one effective dipole moment. Because, you know, in this patch over here, you know, 80% of them are pointing up, 20% are pointing down. So we'll just say, okay, it's basically just a spin pointing up. And so you sort of block things up in that way. And then, once you've done that once, you can do it again and again and again, and you keep on doing, and you keep on doing it. And, and then you ask, what happens when you take that process to the infinite limit? And, and it's called a group, it's really a semi-group because you can lump the spins together

• 4:59Speaker 00

  and then make these bigger and bigger spins, this coarse graining as physicists call it, but you can't go backwards. If you know the configuration of the very large scale and you say, well, what was the actual microscopic configuration of the electric dipole moment, the electron dipole moment? There's no unique answer to that. You know, the one that we had 80% up, 20% down, if it had been 75% up, 25% down, it would have still ended up being as, regarded as a spin just pointing up. And so there's no unique answer, you can't go backwards. And that is why it's so profound. Because when you start looking at the laws of physics and you say, actually what we're doing, when we're doing this, we're actually looking at the laws of physics. And I can tell you why it's the laws of physics in a minute.

• 5:41Speaker 00

  Then if you know what the laws are microscopically and you start saying, if I know what happens at the scale of atoms, can I work out, you know, what happens to my crystal or, or fluid or something like that? Well, I can do this process and coarse grain like that, but I can't go backwards. If I can't go backwards, then you say to yourself, wait, I'm a physicist, all I can see around me is the natural world. There's nothing in this room that, at least if I live in the 19th century, would let me know that atoms exist and things inside the atoms and so on and so forth.

• 6:15Brian Keating?

  Drive Boltzmann crazy, eh?

• 6:16Speaker 00

  Well, it drove, it drove Boltzmann to suicide. It's not just that. There isn't a way in principle, so let's suppose you're trying to work out, you know, theories of the standard model, as people were doing in the, in the 60s and 70s. Well, you can write down all sorts of non-Abelian gauge theories that you like, and they all sound very interesting. You have no way to know which one of them is right because they will all give you the same standard electricity and magnetism that we use in everyday life. And so the renormalization group, this non-uniqueness of going down in scale and going up in scale, that's the thing that makes high-energy physics, fundamental physics if you like, hard.

• 6:56Speaker 00

  And, and it's important in condensed matter physics because you say, well, I'm going to start at a level of description, which is I'm going to take, you know, atoms for granted, then work out what are the properties of matter. And so you can go in the way where there's only one way to do it. And that's, that's why condensed matter physics is so successful. The other thing I would say is that this facet of the normalization group is what enables us to do physics in the first place. So think about it this way, suppose you're a chemist, okay? And you're, you're trying to understand organic chemistry, chemical reactions, biochemistry or something. Let's suppose, you know, somebody knocks on the door and says, hey, we've got some really disturbing news.

• 7:37Speaker 00

  Somebody's just measured the radiative corrections to the mass of the top quark and they're 20% different than what we thought. Does that mean all our chemistry is wrong? Well, the answer is no, because all of that was just lumped into one constant in the theory, just like we were taking the spins and lumping them together into one effective spin. And that, that constant is the mass of the proton, the mass of the hydrogen atom, whatever. So a chemist is not worried about that. They, we know that the microphysics can be lumped into effective descriptions at a larger scale. All the QCD and superstrings and whatever, all ends up just giving you the mass of the proton or spin of the proton or whatever. Because we don't have to worry about that, you can do chemistry.

• 8:22Speaker 00

  You can say, I don't worry about what the world is really made of. I just start with my level of description that I'm comfortable with, atoms, and then I proceed from that. And so without that, if that didn't happen, then we wouldn't have been able to do science.

• 8:38Brian Keating?

  I want to get back to reversibility and, and maybe even touch upon the origin of time, perhaps in the context of temperature. But before I get there, why didn't Ising realize this, you know, 40 years before Wilson and then Kadenoff and, and so on?

• 8:53Speaker 00

  There's a model called the Ising-Lenz model. Lenz was Ising's advisor. And, and Lenz decided it would be nice to make a simple mathematical model of a magnet. So this was in the, in like 1925, 1926, I think. So they, they didn't really know all the microphysics. So they said, well, let's just say that we have, you know, magnetic dipole moments. And we'll just say that in appropriate units, they can either point up or point down and spin up, spin down. And that model is, has just two variables, they can be, spin can be plus or minus one, and that's it. And then you take a lattice of all of those things, and then here's the extra ingredient. So a magnetic dipole, of course, interacts with an external magnetic field. If you apply an external magnetic field to a dipole, it will orient with the external field.

• 9:39Speaker 00

  But there's another field, which is the fact that the, the electric dipoles exert a field on each other, on their neighbors. And so this was one of the first models where you explicitly had a cooperative Phenomenon built in, in other words, what, whether this spin points up or not, depends on not only whether there's an external magnetic field, but whether its neighbors are pointing up. If its neighbors are also pointing up, it's got a much higher likelihood of pointing up. If its neighbors are pointing down, it will likely point down. And so that's why this has been, you know, it's a famous model. You know, you can model social behavior with it. You can model the production of pistachio nuts in California orchards using it.

• 10:21Brian Keating?

  As we often do, yeah.

• 10:22Speaker 00

  So that's what the model is. And it, and it really is the, the drosophila of, of theoretical.

• 10:28Brian Keating?

  The elegance.

• 10:29Speaker 00

  Of matter physics. What did Ising do? Well, this is a fantastic, fantastic story of, of, of failure and missed opportunity. So they said, well, let's just simplify the problem. Let's just, instead of having, you know, a three dimensional material, which is what matter really is, we'll just say, we'll just do these spins in one dimension. And, and so then, and then it's possible to, even if the problem is nonlinear in a, in a complicated way, you can solve it exactly. And when Ising did that, he found that it didn't have a phase transition. This phase transition of the magnet, the fridge magnet that, that below a certain temperature will stick to the refrigerator door and above that it won't. It didn't, it didn't work in this calculation.

• 11:13Speaker 00

  He didn't see that at all. And so they gave up. They just said, well, this, this model is a useless model. Okay. Now, there's a reason, there's, it's a very interesting thing. What they didn't know was that the behavior of matter strongly depends on dimension.

• 11:29Brian Keating?

  Hmm.

• 11:30Speaker 00

  And that, that's not obvious. And it wa, it wasn't known at that time. Now we know it, in fact, we now we use dimension as a, as a variable, which we treat as a continuous variable and, and do perturbation theory in, in dimension and things like this. And then Lasson Zaga figured out in nineteen forty-four, how to solve the two dimensional Ising model exactly. And, and I think it's on a par with Einstein's theory of relativity, general theory of relativity as one of the most fantastic examples of theoretical physics I, I know of. It is, it is a masterpiece and it inspired many things, including string theory and all sorts of things like, I, I, I, there's, there's so much to be said about that. Okay. So, so then we knew that there was a phase transition

• 12:15Speaker 00

  and it didn't behave the way that you would have guessed, the simple square root theory that we talked about. And, and eventually we, we discovered that, um, well, it's not as a community. We discovered that be able to solve the collective behavior of matter exactly is a fool's errand. It's much better to have an approximation method that is guaranteed to work on any problem rather than say something like the two dimensional Ising model, which Onzaga solved by absolutely brilliant mathematics. His solution worked, but if you apply an external magnetic field, it all goes away. It doesn't work. And if you try to do it in three dimensions, nobody knows how to do that.

• 12:58Speaker 00

  So, so these special cases are special for certain reasons, just like integral systems, soliton equations in differential equation theory. If you can solve it exactly, it means there's something special about it. And there, and there was, and it's now understood. And the renormalization group, why it's taught and why it's so important in graduate physics is, well, we, uh, we need to know how to solve any, any problem in condensed matter physics, whatever, and I've seen many other fields of science. We now know we can solve them systematically to any order you like, any accuracy you like, using renormalization theory. Before I came here to UCSD, I spent thirty-six years at the University of Illinois at Bang and Champagne. And one day I discovered, I don't remember how, that Ising was teaching at a university,

• 13:42Speaker 00

  a college, a teaching college in Peoria, about forty minutes away from the university where they were. And I thought, holy cow. And so I wrote to him, I, I, because apparently he didn't really understand that, that his name is, i- i- is a revolutionary, is attached to a revolutionary model in, in, in physics. And, um, so I wrote to him and unfortunately I was a few weeks too late. I could have, you know, I, I'd been there already maybe fifteen years when this happened. I cursed myself I didn't do it earlier, but I did, but I did talk to his son and, and, and, and exchanged some correspondence with his son and, and explained to him various things about his fa, his father's work.

• 14:24Brian Keating?

  That's, that's unbelievable. It's like Aronoff is, works at Chapman University, you know, which is less than an hour from here and he's still alive and many, including me, consider him, you know, worthy of a Nobel Prize for, for his work and inspired my late, great mentor, Jim Simons and C N Yang.

• 14:40Speaker 00

  Yeah.

• 14:41Brian Keating?

  Just incredible. Lectures on phase transitions and the renormalization group. And it's written by you and it's got this lovely cover and it's got your description. Take us through this cover, the title, Frontiers in Physics and, uh, and this beautiful cover art.

• 14:54Speaker 00

  Well, the, the cover art is, is a deliberate British understatement. And when you see a cover like that, you think to yourself, oh, I'm about to walk through a garden full of a millions of beautiful flowers, strange butterflies and wonderful, uh, unexpected sights. And that's actually true because one of my colleagues at the University of Illinois, after the book came out, he wasn't in this field, wrote to me and described the book in exactly those terms. And the reason is because this book is, it's still used, widely used as a graduate text in advanced statistical mechanics. And I wrote the book because I thought I had something unique and new

• 15:38Speaker 00

  to say about the renormalization group, which other people hadn't noticed. There's things in it that you won't find in any other textbook in, in, in this topic, including the fact that the renormalization group has nothing at all to do with statistical mechanics. And the first exercise in the, in the book, as you may remember, I, I don't remember exactly which order. I think one of them might be, the first problem might be to prove Pythagoras is there am using dimensional analysis. And the second one is to work out the yield of the Trinity test of the atomic bomb based on just the data from the motion of the shock wave uh, from the photographs that were published in Life magazine.

• 16:17Brian Keating?

  And famously Fermi did the same thing. He just sprinkled some, uh.

• 16:20Speaker 00

  He, he, he sprinkled bits of paper and, um, and, um, Taylor, G I Taylor actually did the calculation. That, that's in the, in the book. And he actually got into trouble because he did this calculation, reported the results in the newspapers and, and it was classified information.

• 16:39Brian Keating?

  Yes.

• 16:39Speaker 00

  And, uh, so, you know, it's, uh, uh, there's lots of things in this, in this book that are very unusual and those things have stood the test of time and have actually grown since then in, in importance and significance. And, and another thing that's interesting about this book is that it's about a very obscure and arcane problem. And if you want, we can get into it. Uh, renormalization group, the problem of critical exponents in second order phase transitions. But it turned out that this problem completely upended our view of what physics is, what we're doing when we do physics and the nature of scientific explanation.

• 17:18Brian Keating?

  I want to take one more detour, you know, before we get too deep into the weeds. And, and that's this thing that you mentioned before, which is had to do with reversibility. And the fact that there are, there's no injection, bijection, I guess you'd say, between final state and the initial state. There are many initial states that can produce a given final state. Uh, so it's not invertible essentially.

• 17:37Speaker 00

  Right. I would say, you said, we're not talking about states. We're talking about that the variable is not time, the variable is scale.

• 17:45Brian Keating?

  Scale.

• 17:45Speaker 00

  And that was the thing that Kadenoff realized, that, that, that, that the way, the energy scale at which you look at a system is the important thing. And so, so I will often talk about the importance of levels of description. Now, it's a very important problem. For example, if you're a biological physicist, as, as, as I, as I am, you might say, well, what is the right level of description to describe a biological system? Should I describe every atom in the biomolecules that are inside a cell and then inside the cells and inside the tissues and so on? Or should I try to make a more coarse grain description? And this is not an easy question to answer because it depends, what is the question you're trying to understand?

• 18:28Speaker 00

  If you're trying to understand how does some particular molecule bind to some particular protein or something like this, you, you definitely need to understand the atomic level of description, the binding and, and things like this. If you're trying to understand why is it that inside a eukaryotic cell, we now know just in the last fifteen years or so, that in fact, the biomolecules phase separate from the rest of the, of, of the cell and form a membraneless compartment inside which, God knows what happened. We were still trying to understand the function of these things. So you have the, the sort of phase separation processes. We understand those at a very different level of description. It has nothing to do specifically with the atoms and molecules

• 19:12Speaker 00

  and the specific sequences of the RNA and things like that. It's a general property. Also, so you have to, so depending on what question you're trying to understand, different levels of description are important. And, and this tension is very prevalent in biology because it, it's, it's not obvious what is the right level. It's not as simple as saying, well, I'm a chemist, so I'm just going to assume or everything, all the microscopic, high energy physics, standard model, standard model, particle physics stuff is just absorbed into the mass of the proton. We don't know that you can, when and where you can do that.

• 19:45Brian Keating?

  Where the balance, yeah.

• 19:46Speaker 00

  In, in some things complex as biology.

• 19:48Brian Keating?

  Interesting. You start your lectures and UCSD statistical mechanics. I, I can't tell if they're graduate or undergraduate because I'm.

• 19:55Speaker 00

  They're graduates.

• 19:55Brian Keating?

  They're graduates, so.

• 19:56Speaker 00

  Have you seen all YouTube?

• 19:57Brian Keating?

  I do watch them on YouTube with Chopin Lover. Is that your channel name?

• 20:01Speaker 00

  Chopin Junkie.

• 20:02Brian Keating?

  But you start the lectures, you use this famous, you know, phrase, which I've always felt, I hate to say it, Nigel, and I know he's a hero of yours, but Philip Anderson's The Amore is different.

• 20:11Speaker 00

  Yeah.

• 20:11Brian Keating?

  I always felt that was kind of simplistic, but, but maybe I'm wrong, I'm just a, you know, dull-headed experimental cosmologist. So tell me, what is the significance? Is there anything really significant about, I mean, of course, like where does a sand grain start to become a sand pile? Where, where do you, you know, so tell me, what does it mean to you? Why is he a hero? Why, why do you start with that in that, in that?

• 20:31Speaker 00

  Well, I understand hero, okay, many things. He won the Nobel Prize for his work on sorted electrons. But there's no field of condensed matter physics, which was left untouched by his intellect. So, so, so in condensed matter physics, he is a giant and is in the same way that Einstein, Hawking, others.

• 20:49Brian Keating?

  Bohr.

• 20:50Speaker 00

  And, uh, well, I'd say more than Bohr, actually. The more is different. The article was immensely influential. First of all, he really was the first person, I mean, there's, there's technical ways in which more is different is important.

• 21:02Brian Keating?

  Yeah.

• 21:02Speaker 00

  For example, you can't have phase transitions unless you have, you take the sort of, the thermodynamic limit. Uh, and, uh, but it's not just that when you have phase transitions, it's just that you can have previously unanticipated, complex behaviors that you would never have otherwise expected based on looking at the thing that stuff is made of. So again, let's go back to our fridge magnets, okay? You've got your, your electric, your electrons and the material, and they have magnitude dipole moments. You would have, unless you did a particular calculation, you would never know that this thing could be used to stick your kids' drawings on the door of your refrigerator. Okay, it's, it's a, it's a cooperative effect.

• 21:46Speaker 00

  It is a conspiracy of the atoms. And I actually do an experiment, which we, we can do right here, okay?

• 21:53Brian Keating?

  If you wait.

• 21:53Speaker 00

  I do this.

• 21:55Brian Keating?

  Why wouldn't I?

• 21:55Speaker 00

  Well, so the experiment is this, okay? So there's the ceiling up there.

• 21:59Brian Keating?

  Yeah.

• 22:00Speaker 00

  Okay, and we're going to move the ceiling.

• 22:02Brian Keating?

  Yeah.

• 22:03Speaker 00

  Okay, and we're going to do it like this. Take a finger.

• 22:05Brian Keating?

  Yeah.

• 22:05Speaker 00

  To this finger.

• 22:06Brian Keating?

  Yeah.

• 22:07Speaker 00

  Okay, and push.

• 22:08Brian Keating?

  Okay, well, my, my ego made a little do it.

• 22:11Speaker 00

  Come on, come on, flowing. Put some effort into it.

• 22:13Brian Keating?

  But this is a gas, not a solid.

• 22:15Speaker 00

  It's a gas, not a solid, so we didn't move it.

• 22:18Brian Keating?

  Right.

• 22:18Speaker 00

  The thing is this, the Hamiltonian, the formula for the energy.

• 22:23Brian Keating?

  Yeah.

• 22:23Speaker 00

  Of the gas is exactly the same as the formula for the Hamiltonian of the solid. They're no different. And yet, when I

• 22:34Speaker 00

  take this and I, I push my water bottle, you know, my, my fingers don't go through. All the atoms in this conspire.

• 22:42Brian Keating?

  Does that really true, Nigel? I mean, at some level, just to be Vanderwall's versus Hook's law.

• 22:48Speaker 00

  No, no, no, it's really true. And, and the, and, and the, and this is why it's important. Because when we're talking about emergence, I remember like I said, we're talking about new laws of physics.

• 22:58Brian Keating?

  Yeah.

• 22:58Speaker 00

  When you have a solid, there are new laws of physics. The, the atoms have decided that they're not just going to sit at particular sites in a checkerboard lattice that somebody has conveniently read out for them. They've actually conspired that they're going to keep their relative separations the same. And because of that, they minimize their free energy by doing that. This is a statistical mechanical description of what is happening. That means that you now have new excitations, which are, first of all, you have the rigidity, the stiffness, the emergent rigidity of a solid, as measured by the Young's modulus and things like this. And you have the ability to transmit sound waves and, and, and other waves as well, of course.

• 23:41Speaker 00

  So at the level of description of the material, you now have new laws of physics. And, and the only thing that's changed is the temperature. You've, you haven't changed the interactions between the atoms. You have changed the correlations. And that's the important thing, but it's a statistical property and it's not one that you can see just looking at two atoms, sorry, just looking at two. You have to, you have to look at the whole ensemble. So that was a thing that, that Anderson was very interested in and understood it's the depth of its significance more than other people.

• 24:17Brian Keating?

  Hmm.

• 24:17Speaker 00

  And, and later, you know, he wrote that essay in nineteen seventy-two. In nineteen eighty-five or so, when I came to the University of Illinois, the first project I did was with my cousin, Paul Goldbart, who's, who's also a very well-known theoretical physicist, and will next year be the president of the American Physical Society.

• 24:37Brian Keating?

  Oh, wow.

• 24:38Speaker 00

  And, uh, and we worked on this, this question of why rubber is solid. So everybody knows that rubber is stretchy and can expand and stuff, but, but that's not the right question. It, it's stretchy, but, and you know, the piece of, you know, with this, this cable here is can bend and deform and stretch, but it's still solid. The first question you should be asking is not why is rubber elastic? But why is it solid in the first place? Because you have a bunch of polymer molecules, they are stapled together by cross links, just like having a bucket of, of, of worms, or a bucket of worms, all flapping around in a thermal equilibrium. You go in and do an experiment that you'd never get an IRB to do, even though a worm doesn't have a backbone, which is staple the worms together in random.

• 25:22Speaker 00

  And then you find that the thing is not just connected, like a fishing net, which would just be floppy, but it's actually rigid.

• 25:29Brian Keating?

  Yes.

• 25:29Speaker 00

  And like a gel. And, and then, you know, you can tap it and it will wobble and it has sound waves and things like that. And those are all emergent phenomena. It's very complicated to calculate them because the whole thing, the polymer chains are going at random, the cross links are at random, everything is, is random. It's a very hard technical problem, but it's, it's an example of this more is different. And, and the point about more is different and the point about emergence that everybody misses is that when you talk about emergence, something emerges, what is it? And the answer is, it is a particular type of rigidity, which, which is a generalized rigidity, as Anderson called it, which basically technically comes from a certain type of response function

• 26:13Speaker 00

  of how does the system respond to perturbations when, when you poke it? And, and that was the lesson of that. And it wasn't really understood in those terms. And, and once you understand in those terms, then you can, that lays the groundwork for applying it to more complicated materials and more complicated systems. If I may, I'd like to give you another example of more. Okay, so the most stunning example of more is different is something that all of you know, all of you viewers know and, and use, and that is AI. Okay, when you ask how, as I do, how is it possible for AI to even work in the first place?

• 26:56Brian Keating?

  Right.

• 26:56Speaker 00

  Okay, let's, let's think about this. So the first thing you would say is, let's suppose I've got a time series of, of data points, you know, whatever it might be, stock prices, who, who knows? And you say, well, I want to make a model of that. So the first thing you do is you take your data and you say, I'm going to make a model. It's just a straight line goes through some of those data points, but it doesn't go through all of them. The data points, you know, wiggle and twist and turn. And, uh, and so the straight line, if you ask, does it fit all the data? Of course it doesn't. If you ask, does it make good predictions? The answer is, well, you know, not, not really, because it's, it's too simple a model. So then you might say, look, I've got, you know, fifty data points here that I'm training my AI on.

• 27:37Speaker 00

  You know, why don't I just use a hundredth order polynomial, a much more complicated equation? That equation will fit every single data point that you want to train the AI on.

• 27:47Brian Keating?

  Every single point.

• 27:48Speaker 00

  Every single, a hundredth order, I've got fifty data points, I've got a hundredth order polynomial.

• 27:52Brian Keating?

  And how are you embedding?

• 27:53Speaker 00

  Well, I can, I can find a way to, I can find, you know, a lot of data, but I can find a way to make it fit through every single data point, so there'll be no error in the way that it fits the data. So this, this thing is going to be really great at making predictions in the future. Except it's not. And it's not because I've fitted the data, but I've also fitted the noise.

• 28:13Brian Keating?

  Hmm.

• 28:13Speaker 00

  And so if you make predictions, they're basically contaminated by the noise. So then you would say, well, okay, so if I have a large error, well, I only have a, a linear fit. That's not going to do very well fitting a complicated data set. I've got a very complicated formula, that's also not going to fit very well because it's fitted the noise. Somewhere in between those extremes, there should be a sweet spot where the two things balance out. And that should be the place where you should, you know, try to make your, your, your model. That's what AI should do. And, and that, that was the conventional thinking, okay? And so you say that theater, except that's not what happens. In fact, we have, when we fit our data with modern AI, we are fitting it far more than a hundred parameters.

• 28:58Speaker 00

  We're fitting with the, you know, a trillion parameters, right?

• 29:01Brian Keating?

  Yeah.

• 29:02Speaker 00

  Yes, and you're way, way into that regime where you're just fitting noise and the whole thing shouldn't work.

• 29:08Brian Keating?

  Mm-hmm.

• 29:09Speaker 00

  That's a mystery. How is it that having such a, such a huge number of, of parameters can work in principle? Obviously, it obviously shouldn't, and yet it does. And, and that's a problem that, that we have, we have a solved, at least for a very, a simple, a simple sort of mantra of your model of how AI works, with a student here, Chan Lee.

• 29:30Brian Keating?

  Oh.

• 29:30Speaker 00

  But the answer is that there's a phase transition in the statistical physics of the learning process. And that phase transition has a rigidity, the generalized rigidity, just like the rigidity of Mura Masor, which nobody knew was there because they, they didn't do the calculation that we did. And so we could understand the transition, we could understand.

• 29:52Brian Keating?

  Does it have critical exponents? Does it have redonization?

• 29:54Speaker 00

  It has critical exponents, it has data collapse, all the phenomena that you'll find in my book. And, and the phase transition turns out to be very similar to the superconducting phase transition.

• 30:04Brian Keating?

  Ah, I was.

• 30:05Speaker 00

  And, and, um, and there's a lot that can be said about that, if you want to talk some more about that. But my point is, this is an example of more is different. Okay, it's not just that whether you have more things and so you can fit more things. There's act, it's different is the important thing, not the more.

• 30:21Brian Keating?

  But eventually.

• 30:22Speaker 00

  Different means that there is a, a, it's qualitatively different, not just, well, there's a slightly different number. You know, and it's that phase transition, the qualitative difference, that means that a material or a stochastic computer algorithm, say stochastic gradient descent that is used to train AI, has new behavior when you go beyond a certain point. And that's, that's the thing that why, you know, I think more is different is so important. But because, because it's, it's not just. Yeah, having more, having more money i- is better than having no money. Yes, I could buy a slightly better car.

• 31:06Speaker 00

  There's a quality to difference that comes when you, when you have a, and that's, that's the message of, of Anderson's article.

• 31:13Brian Keating?

  But here's when I push back with, first back to you and Anderson. Here's some ice. If I told you this is ice that I collected at the South Pole, Antarctica. He's like, no, it's not, it's water, right? And if I had more, and actually this was chock full, I filled it up to the very brim. And then it melted and now it's this, right? So I'm going to phase transition from the South Pole to San Diego, right? Now, if I keep putting more and more ice in there, more should be different, right? Nigel, that's what Anderson's telling me. But if I keep doing it, it's just, it's just going to be more of the same. So there's, there seems to be, yes, I agree, more is different. There's a water molecule. It's not like this liquid in here. But when there, if I doubled the amount of, if I added more and more and more, it doesn't behave quantitatively different from this, right? So at what point does the more start to be the same?

• 31:53Speaker 00

  It does.

• 31:53Brian Keating?

  I mean, when it becomes a black hole, at what point?

• 31:55Speaker 00

  No, no, it, it, it is different. So, so the amount of water and ice that you have in there, if you measure that, you've mentioned the critical exponent, like say you have a heat capacity. It's a first order phase transition, so you don't have critical exponent. But let's suppose we're talking about, say, the magnetic transition. So yes, you would find that as you, that there's a temperature where the, the, say, the divergence of the heat capacity, which you will see in an infinite system, it'll literally go to infinity. When it's a finite size system, it won't diverge. It will start going up and then eventually it'll, it'll smoothly, smoothly go over. And, and that's important because you, you literally see that in, say, granular superconductors.

• 32:37Speaker 00

  And if you, if you look at a machine learning, at a neural network, in the ideal case, where you have an infinite number of neurons and infinite numbers of data sets and some appropriately taken asymptotic limit, you can make a very sharp mathematical theory for that. And only in that case, mathematically, do you literally have the ability to say there's a phase transition and non-analystic behavior and so on. If you, on the other hand, make the, the system be finite, then the computer scientists would call this ridge reg- ridge regression or regularization. Then in fact, this infinity goes away and the behavior i- is different. There isn't, there isn't a transition. You won't be able to see that if you put more and more ice in there.

• 33:19Speaker 00

  If you're doing this with a magnet or you're doing it with a superconductor, you can do the experiment and you literally can see that only when I go to infinity, do I see the sharp phase transition. But, you know, I only describe it in my book. If you get to within, you know, 10 to the minus 12 degrees of the critical temperature, then you will start to see the fact that you, there, you don't have an infinite number of atoms in your, in your water bottle.

• 33:43Brian Keating?

  I want to talk about a man you mentioned in your course as well. And you mentioned with great glee that the only man to win two Nobel Prizes in physics was a condensed matter physicist. John Bardine. Often here it's said that if it wasn't for the laws of quantum mechanics, we wouldn't have had the transistor. And I always have a little bit of problem with that because if you look at the first transistor that they built, you know, Shockley, it was, it was.

• 34:04Speaker 00

  Unfortunately, he didn't build it. He was, he was, he just poached in the photographs.

• 34:07Brian Keating?

  Right.

• 34:10Speaker 00

  In the famous photographs, he, he's sitting down as if he built the thing.

• 34:13Brian Keating?

  It looks like a piece of.

• 34:15Speaker 00

  A coat hanger. And Britain was just standing around, like, why, why, why are we here? Why is he there?

• 34:23Speaker 00

  That actually was the reason why Bardine, Bardine left and went to Illinois. Yeah. He was so, he just couldn't get on the shock.

• 34:30Brian Keating?

  Yeah, Shock, well, Shockley was a very, very troubling character. I've talked about it. The question is, you look at it, it's a piece of chewing gum. There's a coat hanger, there's a rock in the middle of it, right? It's, it's very unlikely that you'd say, hmm, this is the solution of a short linear equation with Fermi levels. And, and do you believe that, that we look into the laws? Because the reason I'm asking is people say, when we have a theory of everything, Nigel, they'll be able to look into it. And just like they did with quantum mechanics, instead of making transistors, we'll make warp drives and, and gravitational impellers and, and multiverse, you know, teleportation devices. Well, what do you make of this? First of all, is that historically accurate? And you're, you've seen a lot of these people, you, you interacted with the, with the Titans, you are one of the Titans. But, but tell me, Nigel, do we look into the laws of physics to get the technology on the screen that you talk about in your course?

• 35:16Brian Keating?

  Is that really what happens or do we describe it later on? Os facto by these laws that we discovered.

• 35:21Speaker 00

  So just the fact that the first transistor was, was a big lumpy thing. I mean, I mean, we said before that there's, that everything in this room is, is classical. But, but you knew that I didn't really mean that. I mean, look at the, look at the flowers there. They have color. The only reason that they have color is because of quantum mechanics.

• 35:38Brian Keating?

  Well, these are made of plastic, but, but anyway, if they were real.

• 35:41Speaker 00

  Oh, in that case.

• 35:42Brian Keating?

  You gave up, you gave, you blew my secret.

• 35:46Speaker 00

  I'm a real biologist, right? I can't even tell.

• 35:48Brian Keating?

  We're going to get the biology.

• 35:49Speaker 00

  A plastic flower from a real one.

• 35:51Brian Keating?

  But you're saying.

• 35:52Speaker 00

  So yes, it was a macroscopic object, just like your iPad is.

• 35:55Brian Keating?

  Yes.

• 35:55Speaker 00

  But it's, it's operating due to laws of, of quantum mechanics. And so, yeah, semiconductor electronics. It's not like, before we understood semiconductor electronics, we could, we could build iPads. We could, and this, this thing didn't exist 15 years ago. In fact, we didn't even know enough about the liquid crystal displays, let alone the, the electronics to go into it and so on, so.

• 36:16Brian Keating?

  I want to give you a quote from a countryman of yours of some renown, who said, I'm very poorly today and very stupid. And I hate everybody and I hate everything. I'm going to write a little book for Murray on orchids. And today I hate them worse than everything and I hate species as well. Oh my God, how do I hate species? Do you know who that was? That, that British gentleman of some renown, whose father told me, or whose father said about him, you care nothing except for shooting dogs and rat catching and you will be a disgrace to yourself and to all your family. Who was that said about?

• 36:50Speaker 00

  Darwin.

• 36:51Brian Keating?

  Darwin. So this man, you know, loved life. He created these ideas and he was, he was, he's such a fascinating character. It's reputed, and okay, you're going to disabuse me of this again, I'm a poor experimental cosmologist, Nigel, that you have seen and you were part of the group or team perhaps, that is really working to maybe state the limitations of Darwin or the, the restrictions on selection. So let's talk about why is selection, why is biology? You talk about your paper with.

• 37:22Speaker 00

  Woos, is it Woos?

• 37:23Brian Keating?

  Cow Woos.

• 37:23Speaker 00

  Moos. Life is physics.

• 37:25Brian Keating?

  Life is physics.

• 37:25Speaker 00

  Yes.

• 37:26Brian Keating?

  Is that right? I mean, besides your blunder about this little.

• 37:29Speaker 00

  Well, it could be worse. I mean, I could have said that spherical thing if there was a cow.

• 37:33Brian Keating?

  What relevance does physics have in biology? You, you make the point in your course, again, everyone should watch your course because it's so enjoyable and easy. It's graduate level course, but let's be honest, you could take it as a freshman if you're energized and you're willing to do the work. You may not get the highest grade, but, but you, you talk about how easy physicists have it compared to sociologists and what you call, and what has been called the dismal science of economics. I just had Alvin Roth, who won the Nobel Prize in Economics a few years back, talking about repugnant markets. It sure seems, you know, easier to do that than to do cosmology and trying to figure out what happened, you know, 10 to the minus 32nd seconds after the big bang. So tell me, anyway, what does physics have to do with biology? And what role do you play in perhaps overthrowing this, this irascible, you know, kind of self-loathing man named Darwin?

• 38:17Speaker 00

  So a lot of people did interpret our work as being against Darwin.

• 38:23Brian Keating?

  Yeah.

• 38:23Speaker 00

  But that's completely wrong.

• 38:24Brian Keating?

  Okay, same.

• 38:25Speaker 00

  Okay. The whole idea of, well, yeah, I'd say it's Darwin and Alfred Russell Wallace. Wallace really was the first person who, you know, wrote the paper that was presented at the Lincoln Society. And, and Darwin added his things to it and so on. And the, the correspondence between them is, is very interesting and revealing. But let me just say what, what, what, what people mistakenly are referring to. So i- the usual picture of evolution, that people who are not necessarily deeply into biology think about is this. They say, well, you've got your genes and then you transmit your genes to your children. They transmit their genes to their, to your grandchildren and so on and so forth. And the genes propagate like that. And that is indeed what, what happens.

• 39:10Speaker 00

  But there's a very fundamental problem. I mean, I'm going to talk about what it is that we actually did. And then we'll talk about whether it's against Darwin or not. Which is, which is just to be crystal clear about. So, so then you might ask the following questions. Francis Crick, who's another one of my compatriots. So you might ask yourself the following question. Could the genetic code evolve? All right, so let's think, what is the genetic code? So just to review some very simple biology, you have proteins that do lots of stuff in your, in your body. The proteins are made out of amino acid. How do you know which amino acid to put into which protein? So then you read your, your genome and you, and you read sequences of nucleotide bases,

• 39:54Speaker 00

  which will say U C A N G, those are sort of abbreviations for their names. And then you read those and then you read them in triplets. And then you, you take each of those triplets and if you get U U U, you get phenylalanine. And that's the amino acid that you then put at that position in the protein that the ribosome is building in every cell of your body. And the map that tells you, take triplets of nucleotides and convert them into.

• 40:21Speaker 00

  One of the amino acids of life, the twenty amino acids of life, that's called the genetic code.

• 40:26Brian Keating?

  Yeah.

• 40:26Speaker 00

  So it's not your genome.

• 40:27Brian Keating?

  Hmm.

• 40:27Speaker 00

  People always say the genome is your genetic code, that's not true. So the question is, well, where did that map come from? There's a very interesting feature about this map. It's called the genetic code. Uh, you can write it on a T-shirt. It's a many-to-one code, because you've got your alphabet of four letters, words of three, uh, three letters as well. So I've got four times, four times four, so sixty-four possible amino acids I can get. But in fact, I, we only use twenty.

• 40:56Brian Keating?

  Hmm.

• 40:57Speaker 00

  So then I'd say, well, why, why, why twenty? Actually, Francis Crick had an answer to that, which I'll, which I can tell you if you like. So there's obviously redundancy in this code. So then you ask, well, when did this code, when was it developed? So you go back and you do molecular, what's called molecular phylogeny, there's ways, Karl Woz was the first person to develop, to look at molecular sequences and then, you know, find what they were descended from and therefore you can work out the evolutionary history of.

• 41:22Brian Keating?

  The last universal common ancestor.

• 41:25Speaker 00

  That's right, he gets the, the last universal common ancestor where.

• 41:28Brian Keating?

  So he coined that, or did he coin archaea?

• 41:30Speaker 00

  He discovered archaea.

• 41:32Brian Keating?

  He discovered archaea.

• 41:33Speaker 00

  Right, so he, so he started doing this, thinking that there's prokaryotes, new karyotes, and then one day he discovered that these things that are prokaryotes, they're not prokaryotes. There's, there's something else in there, what the heck is this? Okay? And, and, and, and that was a methanogen that he'd, he'd, and, you know, Woz was doing these experiments, the very dangerous radioactive experiments, he was doing them virtually alone for ten years, everybody thought he was off his rocker, and his goal was to simply find a way to map out the evolutionary history of life on Earth, and he discovered a whole new domain of life that people just looked at on the microscope and say, oh, this is a very blobby thing, it must be a bacterium. Turns out, have completely different evolutionary history from, from that. And in fact, we are descended from the archaea, we, we now know. He was doing this.

• 42:16Speaker 00

  And, and as you say, once you start building these trees, you manage to discover that, uh, that you can build them all the way back to about three point eight billion years ago, and that's the last universal common ancestor of life on Earth. And there's various converging evidences that give you that number three point eight billion, and some people say it's even earlier, maybe four billion years ago, um, here's the interesting thing, how old is the Earth?

• 42:40Brian Keating?

  Well, I wanna take a segue, because I forgot to give you your gift. I'm talking about magnets, here's a magnet.

• 42:45Speaker 00

  Okay.

• 42:45Brian Keating?

  And here's a magnet with some gifts on it for you. So these are pre-Earth meteorites, these are discovered in Argentina, those are yours to keep as a guest.

• 42:53Speaker 00

  Thank you.

• 42:54Brian Keating?

  On the Into the Impossible podcast. So the Earth is about four point two, four point three billion years old, these are four point three five billion years old. So they're quite a bit older, but, uh, they date from the pre-super, the supernova that blew up, which by the way, was the mechanism by which was discovered by more countrymen of yours, one of whom occupied this office, Jeff Burbidge.

• 43:11Speaker 00

  Yeah.

• 43:12Brian Keating?

  And his wife Margaret. So I have Margaret's place, these are her photographic plates from Palomar.

• 43:16Speaker 00

  Oh, wow.

• 43:16Brian Keating?

  So we have a lot of, uh, things to come. But yeah, so the Earth is, is older than that, but not by much. I mean, life began very early.

• 43:22Speaker 00

  That's right, that's right. So whether it's four point three, or some, you'll say four point five, something like that, i- i- it's, as you say, it's very close. And so the thing is this, we know, because we can do molecular phylogeny back to that last universal common ancestor, that essentially the architecture of the modern cell was already in place, three point eight billion years or so ago.

• 43:43Brian Keating?

  Yeah.

• 43:43Speaker 00

  So you say, so wait a minute, you're telling me that life went from nothing, four point five, whatever, really, three, plus or minus, billion years ago, of which half that time the Earth was completely uninhabitable, this had, you know, and then by three point eight billion years, you've, you've, you've developed the machinery for replication and.

• 44:04Brian Keating?

  For our first ancestor, yeah.

• 44:05Speaker 00

  Yes, uh, for all, all of that, and somebody, you know, looking at the organisms around about that time, you would see very little, relatively little, in, in the sense of the global architecture of the cell, different from, different from now. And so the question is, how is it possible for life to have evolved so quickly?

• 44:24Brian Keating?

  Yeah.

• 44:24Speaker 00

  So that's the first question. And Francis Crick was very perplexed by that. Second question, second question, why is there only one genetic code?

• 44:31Brian Keating?

  Yeah.

• 44:32Speaker 00

  Okay? The, uh, we call it the canonical genetic code, and there's minor variations, mainly to do with stop codons, but it's basically the same genetic code. Then there's a third one, which you, you, you probably knew that there was only one canonical genetic code for all life on Earth, but the other thing you may not know is that the, the genetic code that we actually have is optimal in the sense that it minimizes errors of translation.

• 44:57Brian Keating?

  Hmm.

• 44:57Speaker 00

  So let's suppose, let's suppose we were in the world of intelligent design, I'm being deliberately provocative here. So you say, okay, Brian, okay, you're a smart guy, you know lots of things, design for me a good genetic code. And you would say, well, if I'm gonna design a good genetic code, I know there can be lots of errors in reading and.

• 45:15Brian Keating?

  Yeah, there's some redundancies, sixty-four minus twenty.

• 45:17Speaker 00

  So, well, not just the redundancy, but I should make a code, so that if you get the wrong amino acid, I should make it so that the amino acid I do get is, in some appropriate biochemical way, which has to be defined, is a decent approximation to the one that I should have got. So it doesn't do too much damage, so that the protein has in it a, the wrong amino acid, but it can still fold and do the thing that the protein is supposed to do. And if you could create such a genetic code, you would say, well, that's gonna be really, really good. That would be the one that I, as intelligent designer, would, would choose. Okay? So the, and the genetic code, when you, when you, when you analyze it, you can do this

• 46:00Speaker 00

  calculation, there's many different ways you can do it, every, every time you do it, you get the, the same qualitative answer. The genetic code is optimal in the sense of minimizing errors.

• 46:11Brian Keating?

  Hmm.

• 46:12Speaker 00

  Okay? It's fantastic. Okay, so those are three facts. How on earth could all of those things have happened? Now Francis Crick was very perplexed about this. Francis Crick said, look, there's no way that life could have, it, it got to this level of complexity in such a short period of time, it must have come from outer space. So he, eventually he, he embraced the panspermia idea, which are called, then just pushes the problem off to another ground.

• 46:35Brian Keating?

  And say, origin of life on Earth is solved, but not the origin of life in.

• 46:38Speaker 00

  Exactly, exactly. But in fact, there's more to the problem than that, there's, there's, there's these other two facts that I've talked about. Francis Crick was also very perturbed, because, as he argued in nineteen sixty-eight, the genetic code can't possibly be something that evolves. Right? Because, think about it this way, suppose it does evolve, so think about this, think about we're doing, we're doing this experiment, okay? Um, I'm communicating you, to you in code, okay? And I write down my coded message, and you get the coded message, you use a code book to, to, you know, translate the message. So that, that works fine. Let's suppose halfway along, we're, and us doing this, and we're in, you know, separate continents or something like this, I, you literally decide I'm gonna use a different code.

• 47:22Brian Keating?

  Hmm.

• 47:22Speaker 00

  Okay? Suddenly all my messages are gonna stop making sense, you won't be able to, you won't be able to interpret them. So the code book is the genetic code, it literally is, tells you how to translate from the message that is in the DNA and the mRNA into the protein that you're ultimately going to produce. And so obviously, if you evolve the code, which means change it mid-stream, then it won't, then there's a whole, then you'll start getting the wrong proteins, and then everything will die out.

• 47:50Brian Keating?

  Hmm.

• 47:50Speaker 00

  Okay? So, so it can't evolve. What we did in the, in this paper was we figured out how to solve all of these three problems. We figured out why the genetic code is unique, why it is optimal, and why it evolved so quickly. And, and in fact, that it really did, uh, evolve. Obviously, that factors it's optimal, which, which Francis Crick didn't know, the fact that it's optimal, uh, either you think that it was intelligently designed, or it evolved under selection.

• 48:18Brian Keating?

  So in what sense is this a canonical criti- critique of Darwin? I mean, why, why do people even say that? I'm not saying, I believe that.

• 48:23Speaker 00

  I'll, I'll tell you why.

• 48:24Brian Keating?

  On the lace.

• 48:25Speaker 00

  It, it isn't. I'll tell you why. Because what we discovered was that indeed, these things would not have happened if you had just, were you just using the vertical evolution that we talked about at the beginning? You give your genes to your children, they give their genes to their grandchildren, to your grandchildren, and so forth. If that was the process operative at the dawn of life, it wouldn't have happened this way.

• 48:48Brian Keating?

  Hmm.

• 48:49Speaker 00

  But, in fact, what happened was horizontal gene transfer. Mainly that genes can be transferred between organisms that are not related. For example, let's suppose we could do this, okay? So let's suppose you decide that you want to learn, you know, ramification group theory from my book. So you could slog through my book and go to my classes and so on. But wouldn't it be easier if I could just pop out the gene that enables you to do Feynman diagrams and four minus epsilon dimensions? Let's suppose there were a gene for that, which of course there isn't. And I just give you the DNA and you just take that DNA, put it into a DNA. Well, some big, great, I know how to solve the, you know, I can solve Feynman diagrams and four minus epsilon dimensions. Whoopie, I can compute pretty close. Okay, it doesn't happen like that for us.

• 49:33Speaker 00

  But it does happen in the world of microbes. That's how antibiotic resistance, for example, is transmitted so rapidly. And the reason it happens so rapidly is because when you're transmitting genes in this particular way, you're using a network effect. I can distribute my genes, not just to you and not just to my one or two children. I can, I've got two children, exactly, not one or two. You can distribute them to hundreds, a thousand. That's, that's how libraries work. Libraries do this. It's a Lamarckian mode of evolution, but it's not, it's still evolution. In other words, only the books that are actually good end up in the library. Only the right physics books, the physics books will tell you the actual right physics.

• 50:16Speaker 00

  The storybooks that are actually really entertaining, you know.

• 50:19Brian Keating?

  Yeah.

• 50:20Speaker 00

  So you have a network process, a horizontal gene transfer process, which is different from your traditional view of how genes are transmitted vertically.

• 50:28Brian Keating?

  I have to interrupt, sorry to interrupt, but I'm sorry, I have to. It seems to me you're like taking a PowerPoint file on a modern, you know, SSD drive and then putting it into a Windows 95 computer from 1995 and somehow it's working. Like, how is that even possible? You just get gibberish, you'd get, you know, these glyphs and how is that even possible?

• 50:47Speaker 00

  So you have to ask what happens at the dawn of life. At the dawn of life, the genotype phenotype distinction had not yet really been, been clear. The organisms were very porous. They underwent endosymbiosis. That means that they would absorb one another. And then the stuff inside that, hey, I can take all the stuff. And we know that that's where our mitochondria come from. That's where chloroplasts come from, in the plastic flound and things like this. So life did that and life transmits, exchanged genes in that way. And today organisms do this. I mean, if you sequence the Drosophila genome, the fruit fly genome, okay? The Ising model, bowels you love.

• 51:28Brian Keating?

  If you will, like Harvard is the UCSD of East Coast.

• 51:31Speaker 00

  You will find in it the genome of Wolbachia. It is a, it is a parasite, a microbe, a bacterial parasite of Drosophila. And it has inserted its whole genome, actually multiple times, into the Drosophila gene. And there's many, there's many other examples of, of horizontal gene transfer. If you look at the phylogeny of, of, of flower implants, angiosperms, very, very complicated. It's not like a family tree. It's a network. And what we discovered was that the, the early life evolved through this, through a network effect, which was called that state of life, the progenote. I don't know why, but he did.

• 52:13Speaker 00

  And, and then there was a phase transition to an era of vertically dominated evolution. And when we're talking about what is evolving, we're tracking the genes, specifically the genes that code for the architecture of the cell, the fundamental cellular processes, such as translation, replication and so on. So, so that's how we define species today. And so today we build the tree of life, but there's nothing mandatory that says it should be a tree. And in fact, prior to the last universal common ancestor, it was a network. And as it was a network, it evolves faster. But it is still doing Darwinian evolution or Wallace Darwinian evolution. It is still survival of the fittest or all of that. You know, however you interpret that, it's a complex argument in and of itself.

• 52:57Speaker 00

  But basically it's fundamentally, we're not saying anything different about. We're just talking about what is called the mode of evolution.

• 53:05Brian Keating?

  One question about the network, does it exhibit things like Reshame's law? But the network law, the scaling goes geometric and it's, the reason that it's so, it's so facund is because of this network dynamics that, you know, lately we've learned about with social graphs. But, but in fact, we can understand it maybe how, how successful it is via network theory rather than, you know, just pure genes.

• 53:30Speaker 00

  Yes, I haven't personally done a network analysis of what, what kind of network you get from this specific process. I mean, I think the more interesting thing is that there is a network effect. And the thing that Crick had missed and other people had missed was that, was that, um, I can explain by a kind of analogy. Let's suppose that I, I drive over to your house and the wheel comes off my Toyota Corolla while I'm there. And say, well, that's too bad. And you say, well, you know, I've got a Tesla in my garage here. I don't know if you have, whatever you have, you know, but you just take the wheel off that. Well, obviously that's not going to work, okay? But let's suppose we were doing that, say, 120 years ago, right? It was the dawn of the age of automobiles.

• 54:12Speaker 00

  So I, I drive over to your house with my jalopy whose top speed is like 20 miles an hour or something like this. And the wheel comes off and it's broken and so on. And you say, well, look, I've got a bicycle.

• 54:22Brian Keating?

  My Model T.

• 54:23Speaker 00

  A bicycle, to take the wheel off my bicycle and stick it on. So I just goes out, take the screwdriver out and screw it on and I'm good to go. And, and you can do that because the, the, the very early primitive forms of, of, of an automobile are very, you know, you could just swap things in and out. The technology is not very advanced. It's not six, six precision and things like this. In the early days of, of living systems, they were very simple. And so they could tolerate ambiguity in the proteins that they use. As they became more and more complex, then, you know, you really had to have just the right protein to fold in just the right way to be able to make the thing that goes into your neurons or something like this.

• 55:03Speaker 00

  And so what we realized was that you can build a dynamical systems model of the co-evolution of the complexity of the organisms along with the evolution of the genetic code. And so you find that then through this network effect, it evolves very rapidly and eventually gets to the point where it shuts off the network effect and then transitions to the vertical era of evolution we're in right now.

• 55:30Brian Keating?

  So does that make you more or less sanguine? You know, getting back to Fermi's question to our late great colleague, Herbie York. You know, where are they? Where are the aliens? Are you more, I mean, knowing this level of, you know, kind of punctuated equilibrium? You also quote Gould and the fact that, you know, we don't actually have that many more genes or, you know, anything productive compared to a worm.

• 55:51Speaker 00

  No, that's pretty much the same. And if you, if you really wanted to punch a hole in more is different, you would say, well, that can't be true because the same amount of genes is the same. But it's, as Gould wrote in his year 2000, whatever it was, New York Times op-ed piece, um, there's many more interactions between the units than you, than you have in C. elegans. C. elegans are so simple that we know every single.

• 56:19Brian Keating?

  Right.

• 56:21Speaker 00

  Every new one is mapped.

• 56:22Brian Keating?

  Yeah.

• 56:23Speaker 00

  It's not the case for us.

• 56:24Brian Keating?

  Yeah, exactly. Right, if we, if we spray C. elegans throughout, you know, on the planet Mars, you know, it's different than spraying koala bears on there. Where does this leave us in Trump?

• 56:32Speaker 00

  Tardigrades.

• 56:33Brian Keating?

  Well, they're already there. I mean, there's human poop on Mars right now. I guarantee it because the astronauts are spraying out, you know, they vent it out to the, to, to space and then eventually gets to, you know, I have a piece of the moon here. You know, this, this is a meteorite from the moon. So stuff is striking and we're.

• 56:47Speaker 00

  I think it's on the moon.

• 56:48Brian Keating?

  Yeah, exactly. So I'm sure they're on Mars. But, but tell me, Nigel, does this make you more or less sanguine about life elsewhere in the universe? Forget about, forgetting or pausing for now the, the concern, the, the origin of life, you know, generally, but just origin of life in specifically on other solar systems, in other solar systems.

• 57:04Speaker 00

  I tend to believe that, that life is the inevitable consequence of the laws of physics and which we understand imperfectly. And I, and I say physics, not chemistry, because I don't think that life is restricted to particular chemistries.

• 57:20Brian Keating?

  It could be silicon based or it could be a different genome.

• 57:23Speaker 00

  Well, I have a question for you about that, which would you be the ideal person to, to, to, to answer? I do think that, that it is, it is a, a physical process. And I can even say a little bit more about why I think that. I would say that if you wanted to know what, what is the purpose of life? What is the meaning of life? If you like, what is the purpose of life? The purpose of life is to help planets come into equilibrium. How I say, so think about a planet, a planet after it's formed is has a huge variety of chemical potential redox gradients in its environment. And those gradients will eventually relax and homogenize as they should from second law, from dynamics and all sorts of other good reasons. And that's then that happens.

• 58:07Speaker 00

  And what what life does is life uses information to find new pathways to short circuit, if you will, those chemical potential gradients and use the energy to power life. And that's how ecosystems work. Ecosystems compete with abiotic processes to literally take chemical potential differences and use the flow of energy in them to make living things. And and and those living things are powered by those chemical potential gradients. So life uses the information just in the way that I was saying with the horizontal gene transfer, that that's one very fast way of searching a space and and finding new ways to solve the problems that emerge, the organizational problems that emerge.

• 58:52Speaker 00

  And we know that that happened. By the way, there's lots of supporting evidence for our horizontal gene transfer theory. And there's a recent paper that just came out in the Journal of Astrobiology, which which is sort of reviews, not one that I wrote with with other people. And but it's you looking back on that. And there's even other data which supports this theory. But the point is, that's what living systems do. And there's nothing special about doing it on Earth as opposed to Enceladus, which would be my favorite place, you know, where I used to direct a NASA Astrobiology Institute.

• 59:25Brian Keating?

  Right.

• 59:25Speaker 00

  And I tried very hard before NASA disbanded the whole NAI program sadly, to persuade anybody who would listen that the place we should go with not Europa, we should listen to, we should listen to 2001, the space of the sea and give Europa a miss. Go to Enceladus, because maybe you got a much better chance. And we already know from the Cassini mission that, you know, you can sample already the water that's there. And it actually looks like alkaline hydrothermal vents. So there's all sorts of interesting astrobiology that could be.

• 59:56Brian Keating?

  That sounds amazing, because it seems to me it's closer to answering Schrödinger's question than Fermi's question, let alone that.

• 1:00:01Speaker 00

  Yeah, it is. Carl Bosse and I wrote a review article called Life is Physics. And and and the reason we wrote it like that is the following. First of all, Schrödinger wrote this book called What is Life, which of course everybody is inspired by. And then the other reason is that when I, when I go to astrobiology conferences, you know, the first day, somebody will stand up and say, well, life is chemistry. But I don't agree any more than I think that a computer is, you know, if you ask me what a computer was in Victorian England, I'd say, well, it's Babbage's machines built out of cog wheels and springs and levers. And you sort of turn things like this and it will compute.

• 1:00:38Brian Keating?

  And then loveless.

• 1:00:39Speaker 00

  And then you, that's right, exactly. Yeah, he's a loveless. And then you go and ask, you know, an engineer trying to figure out how to design hydrogen bombs at the Institute for Advanced Study in the 1950s. And he'll say, well, it's John von Neumann's building it in that shed over there. It's lots of thermionic valves and relays. And that's what a computer is. And now you ask.

• 1:00:59Brian Keating?

  Catherine Johnson.

• 1:01:01Speaker 00

  You ask me, you know, 20 years ago, you or anybody would say, well, it's my iPad, it's my my Windows, my MacBook or my my Windows computer. And or somebody today, what is my phone or my glasses or something, you know? You know, there's a difference between the substrate in which something is made and, you know, what it, what it, what it actually is. And so when we think about trying to understand the fundamentals of living systems, of course, if you want to know how to make somebody better because they're ill for some disease, well, you better understand something about biochemistry for sure. But if you want to understand, you know, why is there life in the universe? Why does the phenomenon of life even exist? That is a fantastically profound and interesting question.

• 1:01:45Speaker 00

  And we don't, truthfully speaking, I don't feel that we know the answer to it. I think we make, we make steps towards the answer. But I think the answer is it is a physical process. It it it can be realized in certain types of atoms and so on. But, you know, here's a question for you. Could life exist three minutes after the Big Bang?

• 1:02:03Brian Keating?

  Depends what you call life. I think the universe did transfer through a period of time when water was liquid. The CMB was once at 300 Kelvin, right? So there's no, you know, that wasn't, you know, very that soon after the Big Bang. I mean, I think in terms of atoms forming in 380,000 years. Right. So it's like very, very implausibly, but perhaps as Deutsch says, you know, if it doesn't violate the laws of physics, perhaps.

• 1:02:24Speaker 00

  So let me tell you a science fiction story. Okay. It's not, it's not meant to be real. It's meant to be a thought experiment, which is meant to raise your consciousness. Okay. So I'm going to make the the the following claim, which I am saying, this is not a scientific statement, it's a thought experiment. Okay. That you have at that early stage of the universe, we're way above the the physics that applies to the standard model of particle physics as we know it now. And you've got some, I don't know, non-Abelian gauge fields or some god knows what gauge group or some strings or something like that. And they have non-Abelian flux tubes that go between whatever the quark-like excitations of this thing. And those things are non-Abelian, so they can wrap around, they can store information, just like we want to use non-Abelian anyons to make build quantum computers and store

• 1:03:09Speaker 00

  information. And so you could store information in this way. And then you could have, you know, the chemistry of these objects. And so you could imagine you could build self organized objects that are built out of, you know, non-Abelian flux tubes. The thing is that they're on a scale of like 10 to the minus 20 meters and an energy scale of, you know, 10 to 100 GeV or something like that. And they last for 10 to the minus.

• 1:03:31Brian Keating?

  Planck time.

• 1:03:32Speaker 00

  Planck time or something like that. But but you could imagine that. And you could imagine those, those beings sitting around in in in the, in the non-Abelian gauge theory bar, drinking beer and saying, you know, what, do you think life could exist? You know, I don't know, for 13, 13, 14 billion years after the Big Bang. And they'd say, oh, come on, don't be so stupid. I mean, they'd have to be absolutely enormous. The scales would be enormous. And the time scales, don't even ask me about the time scales, they'd be just huge. And and by the energy scales would be pathetic, you know, what a loser, you know? Completely ridiculous suggestion, of course not, you know?

• 1:04:14Speaker 00

  So I think it says that, you know, when you think about what is the the physics of life, the processes that are involved in creating the phenomenon of life, you know, they're on a sort of logarithmic scale of energy and time and space and complexity and so on and so forth. And when we talk about life, we usually mean life like us. But if you want to ask about life that's not like us, well, why not? And I certainly think that you're going to find microbial life long before you find.

• 1:04:42Brian Keating?

  Dolphins with iPhones.

• 1:04:43Speaker 00

  Dolphins with iPhones.

• 1:04:44Brian Keating?

  Yeah. You are kind of the embodiment of the more is different to me. I mean, I'm sure the listeners can can determine for themselves the vast, you know, kind of depth and breadth that Nigel engages in. But you're also a citizen scientist in the kind of tradition of our late great colleagues like Herb York and Roger Revelle and and many others throughout, throughout history and throughout different continents that you've, that you've lived on and you've experienced this. But now, you know, I get the sense, you know, for someone as cheerful as you are, I consider you a very optimistic pessimist. And and you're seeing things and you and I have spoken offline about the kind of precariousness of the age that we live in. I want to ask you first of all, is it our fault? You know, Katalin Karakow, co-inventor of the COVID vaccine, sat in that chair.

• 1:05:29Brian Keating?

  And she told me that, you know, we, we sort of have this inflated view of scientists. And actually, we're quite egotistical. And, you know, she went through kind of the the negative side of academia. You know, how much of it are scientists to blame ourselves? I don't want to make it sound like we are even a very large fraction of the blame. But you hear nowadays, and we're talking now, Fauci's going in front of Rand Paul, and there's this big theatrics, I think it's all or nothing burger, I don't think anything's going to happen. But I do feel like we're living in an anti-science age, but not because of the reason that everyone has their truth. I don't care what you believe. I don't care what you do, you know, in your private life. But if we have different epistemologies, that's very dangerous, right? If you and I have different ways of discovering what is true and characterizing what is true.

• 1:06:13Brian Keating?

  Like, you may believe that 9/11 was an inside job and that fire doesn't melt steel and whatever. And I may believe that, no, no, no, actually, it didn't have to melt. You know, so we have different, at least we have the same epistemology. We're using science in some way. I'm not saying that those people aren't crackpots. But Nigel, are we living in in an age that's not like post-truth? It's just, it's relative truth. It's renormalized truth, where you can believe whatever you want, Nigel, and I'm going to believe that, you know, that there's some nefarious conspiracy and I have different ways of getting to my truth. What do you make of this age? And who's to blame? And what can we do? Sorry to wrap three questions in one, but what's going on here?

• 1:06:48Speaker 00

  I would say that the, you know, I've been very outspoken and active in trying to defend science in the United States over the last year and a half or so.

• 1:07:00Brian Keating?

  I would say longer, just to give you, just to give credit, where I don't think people realize the role that you played in the 2020 COVID, you know, kind of pandemic and bring quantitative. I mean, you were really at the forefront of being data-driven and predictive using a lot of your models, which we didn't have time to talk about today, but we'll do a part two. And I think that's remarkable. So I don't want to say the last year. I don't want to say it's just Trump. I do think that there are other factors at bay, but you know, he certainly plays a role that's unique now.

• 1:07:26Speaker 00

  Yes, but I think that's the, that's the, that's the biggest step that I'd like to talk about. You know, most of my activity has been really to defend the public interest because I do feel that what is happening to science, is happening to science, is, is not being done in a good faith. As I am a member of the National Academy of Sciences, for the world society and so on, I, I feel that it is the job of scientists to speak out and to try to work with Congress, in the case of the United States and so on, in order to make sure that they have the best interests, the best information. And that's how the National Academy of Sciences was founded by Lincoln in 1863 during the Civil

• 1:08:07Speaker 00

  War. And so all the work I've been doing, you know, has been work that the, the Academy itself could not do on its own for various reasons, which I won't go into, but is now becoming actually in, in, in the way, in the way that it possibly can, much more visible in, in, in the, in the public eye. So much so that, that Donald Trump has literally is, is being posted on social media about, you know, defunding the National Academy of Sciences.

• 1:08:35Brian Keating?

  Believefully, yeah.

• 1:08:36Speaker 00

  Believefully, just after the World Cup or during the World Cup. So I, I won't say too much about what, what, why I've been, I've been doing, but I want to talk about why I think it's important. And the reason is this, it's not that I feel, well, I want my money. I want my lab. I want the money coming in that supports the research. That's not the important thing. The reason we do science is because it is in the public interest. If people like me, I'm actually, you know, working on cancer at the moment, trying to understand how cancer works. I'm very excited about some work that we've done. We wrote a $11 million grant proposal to NIH from here, which will probably never get funded. But the reason is important.

• 1:09:16Brian Keating?

  Jay Panachariah is the director, is a friend, and he's sat in that chair too? So maybe we can talk.

• 1:09:20Speaker 00

  Well, yeah, but the, the, but the, the point is, it's not a question of, is, is my, is my personal hobby funded? The question is, we're doing this for the public good. All the technology that we have, you know, that we hold in our hands, our silicon security blankets and, and, and the medicines that, that will help us live longer and all those things, came from the scientific process. And, and, and I believe, as many do, that this is in peril at the present time in, in this country. And it is our, it is our duty and it's the duty of people who engage the public, like, like yourself, to, you know,

• 1:10:00Speaker 00

  make those things crystal clear to people so that people understand what is, what is, what is happening, who stands to benefit from this, and why is it not in the public interest? Is the scientific system perfect? No, no system is. If, if you, scientists are being attacked in the, in the media. If you ask, if you poll people and ask who are the most trustworthy people, politicians are right at the bottom, scientists and teachers are right at the top. You shouldn't be weaponizing the inevitable flaws in a system like peer review. Is it, is it, is peer review broken? Is it really true that we've stopped innovating in science, which I think is complete nonsense? But that's, but that's the rationale that's

• 1:10:43Speaker 00

  being used by Michael Kratzios in particular, the, the director of the Office of Science and Technology Policy in the White House, for saying, we need to take science away from the universities, put it more into industry and so on, towards.

• 1:10:54Brian Keating?

  Or charge it benefits of individual scientists. Right. Yeah.

• 1:10:57Speaker 00

  But one of which makes any sense.

• 1:10:59Brian Keating?

  Or benefit AI. AI is science now, according to all the David Saxes and the advisors to the president. And it's very troubling.

• 1:11:07Speaker 00

  So what is alarming is that these are interesting discussions, but they're not being held in isolation and by disinterested parties arguing in, in good faith. And I think that's, that, that to me is, is a problem more than someone who, you know, had difficulty getting tenure and then it ends, ends, ends up.

• 1:11:25Brian Keating?

  With an ax to grab.

• 1:11:26Speaker 00

  Winning a Nobel, winning a Nobel Prize and so on. Yes, we, we, we know that there's examples like that. And I've been, I was actually very lucky spending the first half of my career, the first 36 years at the University of Illinois, where I was essentially working on the lunatic fringe end of condensed matter physics. But people like twice Nobel Prize winner, physicist, John Bardine, said, okay, I, you know, I support what you're doing. He gave you the encouragement and, you know, yes, go ahead and do this. You know, I was working on high temperature superconductivity and I had a, a view on it that was completely not shared by anybody else in the community for five or six years until eventually we

• 1:12:06Speaker 00

  could prove that it was correct, meaning the D wave, as a D wave nature of the superconductivity. John Bardine was the first person who says, that is, that is wonderful. And he was, he gave me moral support and, and told people, we should follow this. So, so I, I, I do know what it's like to be an outsider.

• 1:12:27Brian Keating?

  Yeah.

• 1:12:27Speaker 00

  But I've been very lucky that I've been able to do enough things that are sort mainstream, as it were, that even though I don't stay in my lane, I've been supported. And, and it's not true of everybody. I think if I'd been at another university, we wouldn't be sitting here talking about my career. It would have been very different.

• 1:12:45Brian Keating?

  I think, I think you're absolutely right. And, and to use, you know, a phrase from the namesake generator of this podcast and the namesake generator of the word podcast in general, Arthur C. Clarke, he said, any sufficiently advanced technology is indistinguishable from magic. I want to ask you two questions, kind of as we close, that are prompted by him. And, and that's the first one. What, what is sort of the most magical? I mean, we talked about so many marvelous things today. And literally we've scratched the surface. I feel like you and I could talk for hours and hopefully we'll get another chance. You're the second condensed matter physicist from UCSD Physics Department after Jorge Harris to come on, and he's been a two-time guest, so you have to be a multiple time guest. Can't let Jorge have all the fun. But Nigel, tell me, what is the most magical? If you could put something on a monolith and launch it into space for four billion years, what would

• 1:13:28Brian Keating?

  it be? What would encapsulate, as Feynman said, the, the most information in the fewest lines of, of text or code?

• 1:13:34Speaker 00

  Well, Feynman's answer to that was that atoms exist. And I guess my answer would be more or less different. Because it's not enough just to say that atoms exist.

• 1:13:42Brian Keating?

  Very good.

• 1:13:43Speaker 00

  Everything that we've talked about are emergent properties of different levels of description and so on. And I would say, you describe me as a condensed matter physicist, and that's where my intellectual roots are, but I work in, you know, astrobiology and evolutionary and food mechanics and all sorts of other things. But I think it's the recognition that there are emergent phenomena, which I think is, is not a philosophically obvious thing. And if you don't know that, then many things in the universe are far more perplexing than they would seem to be. So I'll give you an example. Humans try to figure out how the world works. And so we, we came up with one answer, oh, there must be a God that makes

• 1:14:23Speaker 00

  everything do the things that it does. I'm a, a, a, a practicing Jewish atheist. Okay? And I don't believe in God, but I do think that you, you see in, you know, what, what you see in society and in the world around you, phenomena that are seemingly inexplicable, the, the hidden hand, as Adam Smith called it, about, about economics. But you see the same thing in all aspects of, of human life. And you might say, well, that's really God. I'd say, well, it's, it's an emergent aspect of, of things. And, and I think this sort of motif really is more or less different as you brought up. That really does have

• 1:15:03Speaker 00

  many, many ramifications beyond the most trivial ones. So that's, I think that would be, that would be my answer.

• 1:15:11Brian Keating?

  That would be that. Okay. Anybody who's sophisticated, you have to be able to read it, whether you know it.

• 1:15:16Speaker 00

  That's right.

• 1:15:17Brian Keating?

  And so if you couldn't see his monolith.

• 1:15:18Speaker 00

  But if you know, the assassination, send it off into.

• 1:15:20Brian Keating?

  To get two monoliths. That's even more exciting. Arthur C. Clarke said, the only way of knowing the limits of the possible is to go beyond them into the impossible. That's the namesake of this podcast, the giver of the podcast. If you had 20 seconds with a 20-year-old Nigel Goldenfeld, what would you tell him? What would you tell him to give him the courage to do what you've done, which is to be a remarkable scientist, but a citizen scientist as well?

• 1:15:40Speaker 00

  I would just say that you can do this. I don't think it's true that you have to be a genius to do good science. It might help and it may not help. It's not obvious that it does. It depends on how you approach things. You know, Einstein, who I think was, could have won seven Nobel Prize, I can listen for you. I don't know that he was smarter than anybody else, but I think he had a better algorithm and a better approach. And so I think the, the, you know, the question I always ask myself, and I ask other people this, I ask other scientists I meet, how do you choose the problems you work on? What is the way you decide what to work on and what not to work on? And so I think that's, that's what I would.

• 1:16:18Brian Keating?

  It's a matter of taste. Yeah.

• 1:16:19Speaker 00

  It's not a matter of taste. I, I don't agree with that. It's a matter of how you can make the biggest impact and increase the likelihood of making discoveries. If I could, yeah, more than 20 seconds, I would say it's like this. The impact you make is the ratio of what you do divided by what everybody else does. And the usual algorithm that people have is, well, I'll try to maximize the numerator, you know, but that's limited by things like, you know, how much funding you have, which university you're in, what facilities you have, how, how smart you are, or, you know, your family circumstances, a million other things. But the better strategy is to minimize the denominator. Don't work on something. I don't work on anything if I think that if I didn't do it, somebody else would do it three weeks later.

• 1:17:00Brian Keating?

  Right. You said, yeah. You only work on, that's my philosophy of writing books. I only write books that only I could write.

• 1:17:05Speaker 00

  That's right. When I talk to students, they, I, I often try to give, when they ask me for advice, I, I tell them this, you know, do, do something different. It's, it's not that more is different, it's that different is more.

• 1:17:17Brian Keating?

  That's beautiful. That's, we decided the, the title of this episode. Nigel Goldenfeld, so proud and happy to have you as a colleague. And I have a question about the Ising model applied to cosmology, which I'm going to run by you on the blackboard outside. But Nigel, thank you so much for joining us.

• 1:17:31Speaker 00

  Thank you very much for your interesting questions and for having me on your show.

• 1:17:34Brian Keating?

  Hopefully this will be part one of many, of more, many more. Thank you.