Winter Olympics Deep Dive: Ice Physics, Performance Pressure, and Climate Change (EP. 26)

It's been 200 years, and we still don't know why ice is slippery. We're getting close, but, you know, it's... What? Yeah, it's kind of crazy. We have to lock in for this next story because it's about the neuroscience of choking under pressure. That's right. Which, in this Winter Olympics, we have seen in real time. The future of the Winter Olympics is not looking good, okay? Climate change is coming, and the Winter Olympics specifically are very much at risk. Hello, Internet. This is your captain speaking, Lester Nare, joined as always by my co-host and our resident PhD, Krishna Chowdhury. For those watching, if you could not already tell, this week we're going to be doing a deep dive on the Winter Olympics as we've donned our ski gear appropriately. This week we're going to cover three scientific areas. We have a physics story, a neuroscience story, and also a climate change story, along with some other random thoughts. We're going to start off with a story about ice being slippery. Yeah. In the Winter Olympics, every sport depends on ice being slippery, but the science and physics specifically behind it is actually non-trivial. Yep. We'll follow that up with a neuroscience story around the idea of choking, right? Obviously, the stakes are high, especially at the Olympics. And there is really good neuroscience around why do people choke when the stakes are so high? We'll wrap up with our climate change story and a couple of other interesting tidbits as it relates to our deep dive on the Winter Olympics. You are going to learn stuff today because we're going to break down the science from its fundamentals because this is from First Principles. my friend we are donned and prepared for our winter olympics deep dive yes my first question for you is what event because i know what you're good at and so what events are you going to trial for yeah i think the event that um i compete in is the full send the full send the full send event which is um you're at the top with your skis and then you just french fry the whole way down no pizza no pizza you just french fry and then you end up getting dragged out on one of those ski patrol um sleds yeah who can do that the fastest with the least amount of actual injury i compete in it all the time. It's great. Mammoth knows all about it. This is so good. So we're going to go ahead and get started with our physics story of the day. Yeah. And the physics story is starting out with this idea of ice being slippery. Why is ice slippery? It turns out it's apparently not such a simple problem. And scientists have apparently been working on this for 200 years, but we still don't have a foolproof answer yeah so let's kind of talk because there's so many events in the winter olympics that deal with ice yeah and they're all dependent on the central physical fact right that ice is slippery yes right and it's been a 200 year old question it's pretty incredible the slipperiness of ice versus the friction on other solids right this is a great example that we saw in minnesota our local Gestapo agents named Ice slipped on ice. This is not a political statement because this is not a political show. We are not a political show. I just think it's funny that Ice slipped on ice. I just think that's funny. I don't think that's weird to bring up in a science podcast. We're talking about the slipperiness of ice. Yeah, we're talking about the slippery slope of ice, but I'm talking about the physics. I'm not talking about the extrajudicial powers of our federal police. No, no, no, no, no. I'm talking about the physics. So don't you dare come after me in the comments. Actually, please do. I want to see what you'll come up with. But in any case, that's the central question that I want to answer today. And, in fact, I'm not going to answer it because the research is still ongoing, which is quite incredible. It's such a simple question, right? Like, why is ice slippery? It's relevant to stuff like glaciology, like glaciers moving off continents into the oceans and then raising our sea levels. It's relevant for transportation. You don't want to slip on ice. And obviously it's relevant for winter sports. The standard explanations are pretty bad. They seem satisfying from like a high school physics level. Oh, okay. There's a layer of water and then the water makes it slippery. But when you just go a little bit deeper, it doesn't make any sense. And it's actually quite interesting. So let's go to the 200-year-old question, right? 200 years ago, there was this guy, Michael Faraday. He is the greatest of all time in terms of experimental physicists. You can come at me in the comments again. This guy is the GOAT, okay? He's also actually the founder of scientific communication. It wasn't Carl Sagan. People think that Carl Sagan was this first guy. No, Michael Faraday used to have Christmas lectures at the Royal Institution where he would demonstrate electricity and magnetism for the common public. And there are these very famous, you know, outreach events that happened in the 1800s in London. So, you know, this guy's an OG and I love everything about him. And one of the many things that he did, he did, you know, electricity and magnetism is what he's really famous for. But he actually did experiments all over the place. And he's the first to observe something called regulation, which is this idea that there's a permanent liquid-like layer of water around every ice block. And people sort of took that observation and said, oh, that's why ice is slippery, because there's a little bit of water on top, right? I just want to make a quick note that we are not talking about the system that puts a Premier League team in England. Is that called regulation? It's called relegation. Oh, relegation. Yeah, I've heard that. I've heard that. My cousins are really into Arsenal, and they're like, oh, they're going to get – So, for example, used in a sentence, Tottenham Hotspur is potentially in the relegation zone. Oh, are they really? Yes. However – Did they have a terrible season, so they're going to go down? Yeah, they're potentially going to go down. How do you feel about that? You're a Chelsea fan. I am ecstatic about it. Right, yeah, okay, that's what I thought. I'm ecstatic about it. It's happened again. It's happened again. Tottenham Hotspur, it's happened again. Okay. But we're talking about regulation. Regulation, which just to be clear here. Yeah, that's the liquid layer of water on top of ice. And this liquid layer can be nanometers thick. It can be only like a few molecules to tens or hundreds of molecules. Right. And for the longest time, Michael Faraday did some experiments that showed that this is true. And for the longest time, it was like, oh, like those water molecules are what's causing the slipperiness. When we started getting into some deep thermodynamics, the Thompson brothers, the most famous of whom is Lord Kelvin. And he started looking at the statistical mechanics of what happens at this interface between ice and liquid water. Liquid water is very interesting because just water in general is very interesting. It's one of these unique compounds. Because of the geometry of the molecule, it increases in volume when you freeze it. This is very strange. This is why ice floats. Ice is less dense than liquid water. The solid phase of water is less dense than the liquid phase, which is why ice floats. This has everything to do with the geometry of the water molecule, the fact that it's 104 degrees between these two bonds of oxygen, hydrogen, oxygen, hydrogen. And for the longest time, that's been kind of the dominant explanation is because the volume increases. Suppose now I were to press down on ice. right if i stand on ice with skates or something like that i'm pressing down i'm increasing the pressure and what physics wants to do at all times is resist change and so when i press and i compress the volume it's going to undo the freezing part and become liquid does that make sense like like when water freezes it expands i'm pushing in so i'm going to make it unfreeze i'm going to make the the water sort of come back as liquid instead of being in the solid form and that's the i mean i've heard this explanation even from fineman there's a really famous interview with fineman where um a guy asks him you know why how do magnets work and he goes on this random tangent stream of consciousness about what do you mean why does it work and the interview is like i don't know it's a simple question why do magnets work and he's like well you know suppose there were an alien around and i said grandma slipped on the ice how far deep would i have to go into the explanation to tell him what i mean and then he talks about oh well grandma slipped on the ice because ice is one of these unique compounds that is slippery when you stand on it because of the pressure and all this stuff and he even cited this thing right but let's let's just like try to hone in on this explanation the explanation is i squish the ice the ice becomes water okay that works for negative temperatures like negative two degrees celsius negative three degrees celsius okay when you're getting to something like negative 20 degrees celsius to negative 30 degrees celsius i can still skate on that ice but this explanation won't work because i'm so cold no matter how much I press, the physics at that scale, the statistical mechanics of this bulk body, it's not going to let the water come out. The idea being when temperatures are colder, simply applying pressure from your ice skate onto the ice is no longer going to change that surface layer from its solid state to its liquid state. And so you actually got it right there, the surface layer. there's some different physics happening at the surface layer and we can't count on the big equations that we use in statistical mechanics for example the main one is the classius claperon equation and that's the one that gives us this phase diagram we can't actually use that in this scenario and what we need to do is think about what is actually happening at the surface level it can't be pressure because of what i just told you right it's not enough to explain the slipperiness of ice at really, really cold temperatures at negative 20, negative 30 degrees Celsius. So in 1939, Bowden and Hughes came up with an explanation. They said that actually there's heat generated by friction and that heat is what causes melting. Okay. So now we've got a good way to get a layer of water in between whatever I'm standing on. Let's say skates. Let's use skates for this whole example. I'm standing on skates between my skates and the ice. there's going to be a tiny liquid of water because layer of water because i'm going to move with the skates that's going to cause friction and the friction is going to cause heating and that heating is going to cause some melting and i'm going to get a layer of water what it makes me think about is when you know you were in kindergarten or first grade you're running around and you're in the classroom and the classroom had a rug and somehow you ended up sliding on your knees like harry mcguire after scoring yeah a header and you get rug burn and it would feel hot Yes. Because your knees were moving on the surface. That was friction and it was heat and the heat burned my flesh. Yeah. But similarly, the. But also, if you were to measure the temperature of the carpet. Yeah. It would be a tiny bit warmer. It would be warmer. Yeah. And so the point is, you know, this contact between the bottom of the skate and the top of the ice layer. We understand intuitively as just regular people. Yeah. That when we rub our hands together or we slide our knees on rugs, there's heat there. There's heat there. And that's the entry point potentially for what they're trying to say here. Yep, yep, exactly. Bowden and Hughes. Yes, that was Bowden and Hughes in 1939 out of the Royal Society. Okay, that's all fine, except the lubricant in this case is still liquid water. Yes? Yeah. In between the two contact surfaces, right? There's ice, there's my skates that are metal, and the lubricant in between is liquid water. And that's what you're saying is what's causing slipperiness, right? liquid water is a terrible lubricant okay because it has very low viscosity and that's kind of the point the reason why life works the reason why water can go up the phylum and xylem of plants is because it's very low viscosity so the leaf when the leaf pulls on some water it'll go all the way up to the roots and that force will get relegated right that makes So it's actually a feature of water that is very low viscosity. Yes. But that's not going to work in this case because whenever we want to lubricate metal on metal, for example, we use oil. Yes. Right? Like car oil and things like that. Those things have very high viscosity. The point of high viscosity is if I have a contact between two pieces, I don't want the liquid in between to give way. Right? I want there to be a film in between such that there's no metal-on-metal contact, or in this case, solid-on-solid contact. You need high viscosity such that the liquid actually resists that tension. The pressure. The pressure, yeah. Liquid water is not going to do that. Got it. Liquid water is just going to get the hell out of the way. And so the thickness of that film, if you were to actually, the hydrodynamic thickness of that film is going to be nanometers or less compared to something like a highly viscous substance like oil. That's why we use oil in our engines and not water. If we used water, the engine parts would be rubbing up against each other. It would not be a good time. Right? So that's the central discrepancy now. We're at 1939. Yes. We figured out why there's liquid water. Yes. but we haven't quite figured out how the liquid water becomes this lubricant it really shouldn't right because because what we're saying is just by the skate blade in our analogy contacting the ice on its own based on what we know it should not create that nanometer scale layer of water yeah yeah like how does that happen yeah like if it's a nanometer scale no if we do that if we do the physics yes the the the scale should be nanometers it should be nanometers but it needs to be a lot thicker nanometers is like you know tens of atoms i see one nanometer is 10 hydrogen atoms that's not enough to like to keep me from contacting the ice right you know what i mean yes so so that's the idea how do we get a how do we get a a layer of water and and we get that layer of water to be more viscous than bulk liquid water understood okay and that's where there was this beautiful paper in 2019 in the physical review x by canale and other authors nanoreology of interfacial water during ice gliding this is a paper that tried to understand why the water was slimy between my skate and my ice okay is slimy a technical term yes i believe slimy is viscosity is anything above whatever oil is i don't actually know what the numbers uh or the units for viscosity are that's something i should look up later but but the point it is meant to be a technical description yes it's meant to be it's much more slimy than normal water normal water is not slimy yes right i can just like get rid of it it'll evaporate away slimy stuff doesn't evaporate it's viscous it's sticky things like that okay and and we need that okay so the key challenge is that this film between the ice and where the water is sitting between my blade is an ephemeral film. It only exists during this dynamic act of sliding. Let's get into some of the chemistry behind what ice is and how that layer works. So you've got a solid layer. The solid layer is very high molecular order. You've got nice water molecules that are stuck in a crystal form, regularly spaced, characteristic of solids, right? So all of these water molecules are sort of interacting with each other, but they make this hexagonal lattice. The layer in between my ice and my skate is going to be the pseudo liquid layer where there's going to be a lot of molecular disorder, right? Because if you go down, the order is really high. And if you go up, it's fully liquid. There's going to be some transition where the water molecules are behaving in a very unique way, right? That's what this paper was trying to solve. What is the chemistry and the physical properties of that interfacial layer of water molecules? Where there is a high disorder. Yes, where there's high disorder. And can that actually tell us something about why the viscosity is so high, right? And what they use is something called an atomic force microscope, but with a tuning fork. So an atomic force microscope is this incredible technology. This is one of the technologies that I thought should win the Nobel Prize this year. that I called. Didn't get it, but I think it's coming. The AFM is an amazing tool. It's effectively a cantilever. So you've got a little pointy thingy that's pointed downwards, right? And if I've got a sample with molecular level irregularities, like I'm talking tens of nanometers to less, when I bring this thing up, it's going to move up and down, right? Because the literal atoms on my surface are going to resist the cantilever. And if I have a laser that's shining on the cantilever, and then it's on a detector as the as the cantilever moves the laser on that detector is going to move right and then i'm going to be able to sense these tiny surface level atomic irregularities and that's what the atomic force microscope is doing it's it's been revolutionizing surface chemistry studies like all over the place from biology to chemistry everything right i think if i remember correctly the way we analogized it was it's like the when you have a record player yes exactly and it's reading a record but just with a laser for precision yeah on the readings yeah but just and the records are at atomic atomic scale versus whatever records are currently but just as a visual analogy for folks that that's kind of the reference yeah that's exactly right and with the atomic force microscope the problem is you're only going to read this sort of x y or sorry the z displacement right the up and down displacement what we want to know with ice because we're sliding is we got it we got to get this right so what they what they they made a tuning fork autonomic force microscope a tuning fork is is if if you're a musician you know these like two prongs of metal that will vibrate at a specific frequency so if you want an a the the size of these prongs tells you that it's only going to vibrate at an a and so when you bounce it it's going to be like and it's only going to be out of this really clean tone they took a tuning fork microscope and they attached it sorry they made they took a tuning fork and they attached it to an atomic force microscope they attached that to a bead that would interface with the ice so the bead is kind of like my skates yes i have a tuning fork on top yes okay that tuning fork is going to vibrate sideways yes and that sideways vibration is really tapped in to whatever resonant frequency that tuning fork is at right if i've tuned that tuning fork to an a it's only really going to vibrate at an a right right yes and the up and down can be the atomic force part i see but the sideways part can be my tuning fork vibrating at a very specific frequency yes okay so now i can get both the up and down motion yes and the side to side motion and i get two resonance modes in this case i've got a tangential mode which is my stroke and that's that's the you know going parallel to the lubrication layer yes so i can i can characterize the little thin film of water that's created how is it responding this way and how is it responding this way yes independently so so what we've done now uh with this uh afm plus tuning fork is we've added an additional variable layer that we can measure before we were measuring in one dimension yeah we were just doing okay what's the height of this thing right but now it's like what's the mechanical response this way and so now we have two different dimensions of measurement that can be appropriately and robustly measured independently of each other which means we can better characterize what's happening because we have more data and information exactly yeah we have data in all three dimensions and we also have data in time. That's going to be huge, right? Because with the tuning fork, I can make it resonate at a certain frequency, and I can tell what the response is of my material, right? So there's going to be two things, and this comes from, you know, if there's any electrical engineers out there, they must have heard of this concept of impedance, which is the idea. It's kind of like a resistance, but for AC circuits, for the alternating circuits. Because when you have direct current, the current goes through, the resistance sort of just like stops the current from happening. And then the output voltage is going to be a little bit lower because you've lost a bunch of energy inside that resistor. When you're doing alternating current and you put a resistor in there, the output is going to be another alternating current. But there's going to be a phase shift. There's going to be a time delay because the resistor is not only reducing the amount of energy. It's also causing a time delay. And that's actually what they see with this water. This water has mechanical impedance. So there's an elastic property, which makes it sort of dissipate energy. But there's also this viscous dissipative component that is creating dissipation. So if I were to poke the tuning fork and the tuning fork is going in this way, my response is going to have a delay. And that delay tells us a lot about the viscosity of that layer. And it turns out that layer is highly viscous. It's not the viscosity of normal water. And so this is the first indicator of the slimy water that we talked about earlier. On its face, water is not very viscous, which allows it to, in the tree example, float up because it's not introducing new friction. Yeah, it's very slippery. It's very slippery, which means it can move around very easily. in order for skating ice skating to work in the way we think about it at a minimum the top layer of the big body of ice needs to be extremely viscous exactly uh meaning not slippery mean being able to being able to catch on to basically grab on to the blade yeah as it's moving on top of the surface and this is the first indication that where we can measure and see that oh actually that top layer is highly, highly viscous. And if you were to now calculate how thick would the film, the film be? Yes. It's now a hundred to 500 nanometers. It's not just a couple. Yeah. It's like two orders of magnitude above what we thought it should be before. And so now that layer is enough. Right. To, to, to lubricate this contact between my blade and the ice. Right. And this was, this was in 2019. It was, it was, I thought it was a really cool experiment, just the way that they constructed an AFM, which is pretty established now, but they attached it to this tuning fork to get that XY displacement as well. I just want to briefly note, this is a very interesting point about how when tools are built, AFM, CRISPR, et cetera, et cetera, tools are, let's say, platforms, however you want to categorize it. They're not in a finite state of completion. No. Right. You can add your aftermarket attachments on top of it for different use cases and this is a perfect example of taking afm and having a little additional attachment on there that allows you to see stuff a little bit differently that's very cool yeah yeah yeah it's it's very cool and and the other thing that they could tell from this new technology is like not only why is it viscous they could also tell that the reason why that thing was viscous is because there's tiny little ice crystals in that layer of water that's causing the viscosity to go up interesting right and that's what makes sense so now when it comes to like you know why do we why do we put wax on our on our coating like when we do skis and stuff like that i mean at the olympics everyone's waxing their skis right and the reason why you want to wax your skis is because they're hydrophobic they they don't like water on it right and that's actually enhancing this viscous property of that layer which is which is kind of cool it's like kind of it's making that more scientifically justified before it was just like an observation like if i wax like it just works yes and people had hand wavy ideas right but now we're really getting into the physics of it it's very very cool okay um it hasn't stopped there because that was done at you know very very low temperatures now how do we bridge the gap right because this is clearly happening at all all temperature scales and that kind of theory only really works for this very specific temperature ah that's interesting so it's not done so we're not done it's not universally true it just goes back to our there's a difference between what happens at negative three degrees versus negative 30 and so the afm tuning fork solution yeah and that how the slimy water layer was being created is true at uh very low temperature at very low temperature yeah not like the negative two negative three that we see in winter sports right right but it's a clue at least yes as to as to why that part works it's like it's like the game clue where we found the candelier in the kitchen uh and has some fingerprints on it but we've not yet done the exactly analysis yeah yeah exactly and then in 2024 there was another paper hong and others in nature what they did was atomic scale visualization using cryogenic afm so now they upped their afm game and they were doing atomic scale resolution all the way down to like angstrom level wow okay and what they found was there this thing called pre which initiates a kind of defective boundary because the ice is not going to be a clean hexagonal lattice right there's going to be defects where like there's this domain and then it's like kind of interacting with this other domain of hexagons but it's the hexagons don't like completely line up and what what that does is where those things don't line up you get this atomic defect that compounds to create that layer got it of like weird water okay so that was in 2024 2025 there was another paper with Attila and Mousser they proposed something called cold self-lubrication at very low temperature so now they're going to negative 40 degrees and they're trying to say that there's some mechanical shear stress so when you have a lattice the shear is like how much you like sort of warp it this way like contort it and when you have that shear stress that creates a disordered amorphous solid like layer that then becomes this viscous lubricant between our stuff so as you can see like it's it's still a very ongoing field of research 2025 was that last paper 2024 was the paper right after 2019 was this afm paper which was kind of like the really initial like an initial the initial clue that has let us down a like a path yeah to a solution it's just six years ago yeah yeah and and people are still investigating it i mean it's got an incredible importance for our society right if we just talk about climate modeling and climate change which we're going to get to later on in the in the episode um if water is a hundred times higher viscosity right in between interfaces of ice and other solids then that completely changes the current models about how glaciers slide off continents oh interesting right yeah yeah because before we had this number yeah and we're like trying to model okay the glaciers are going this is the friction yeah but now we've got a completely different number and the number is two orders of magnitude different about 100 times different so now the the sliding rate is going to change it's going to get a lot higher just to be clear your your note about the difference is we initially talked about how the assumption was it's you know two to three nanometers or a couple of nanometers yeah is the slimy water layer that enables the ability to skate yeah quote unquote yeah we've now with afm tuning fork and follow-on uh research have identified that that's in the hundreds of nanometers yeah yeah what we've clearly done the the layer depends on how much pressure you're putting right like if there's a human body weight on a bit of tiny skate i mean there's a lot of pressure on that tiny little like you know millimeter thick blade but with a glacier glacier is like like kilometers thick worth of right worth of stuff so there's going to be a lot more pressure so the the layer is going to scale that way what we've done is confirmed that viscosity is a lot higher yes and that viscosity number is what we're going to put into our models right because now because the viscosity is a lot higher it's a variable when we look at large-scale glacier glaciology it's a variable in a larger equation that has meaningful impact yes on modeling yes yes and one of the one of the things that you can think about is like these shear thinning events that happen all of a sudden that lead to a catastrophic flow and acceleration. There's this glacier called the Thwaitis Glacier. I think that's how you pronounce it. In Antarctica. This single glacier contributes to 4% of the global sea level rise. It's massive. It's the size of states in America. And it is moving extremely fast. Something like 2 kilometers per year. That's really fast for a glacier. The surface of the glacier is moving on the underlying landmass. And you know, In this century, it's projected to raise the sea levels by several centimeters. If the whole thing went, which I think people are projecting it's going to go in the next three centuries, that's two feet of ocean level rise from a single glacier. It's crazy. It's crazy, right? And now with these new models, it's like maybe this is even faster. Right, right, right, right. It's crazy. Yeah, right. This is actually an interesting note on how what seems to be a totally unrelated issue with the question, the entry question of why is ice slippery? Yeah, yeah. Has all of the second, third and fourth order consequences on things like how do we model sea level rise based off of glacial ice evaporation, etc. Yeah, yeah. Which makes sense when we talk through it. Yeah. But it's not, you don't immediately make the connection. Yeah, you don't – I mean you could be like, oh, it's such a – why do we care? Well, in science, there's always other consequences that deal with these fundamentals, right? Fundamentally, why are water molecules so weird has so many consequences. So I thought that was like pretty exciting because it is such a simple question. It's been 200 years that we've been asking it. All of our best scientists have worked on it. And, you know, we're still the closer you look, the more interesting things are. This is this is so. And I think what's so fascinating about this is the Winter Olympics have been going on now for I think it's 25 years is what they were saying on the broadcast. It's like relatively new as compared to the Olympics. It's been around for a very long time. I think it's it's been around longer. No, 25 years. So we can we can do a look the way that NBC is. No, 1924 was the first one in Chamonix. Chamonix, sorry. So they must be talking about the like in the way that Premier League talks about the Premier League era versus. Yeah, yeah, yeah. Yeah, yeah, yeah, exactly. Legit or not legit, whatever, what have you. It is still fascinating to me that we don't understand the fundamentals of this thing that we have a massive global event going on that's been around for 100 years. Yeah, an industry. An industry, billion dollar industry. And we actually don't know why it works. Just straight up, why is I slippery? For some of the key events. Great physics story to start off with. We're going to move now into the rundown, where we're going to, again, with the rundown, we can't cover every story every week. There's so much breaking and frontier research science happening. We do our best to cover the stories that we're most interested in and can cover. but the rundown gives us an opportunity to share what else is happening in the world of science at a slightly higher level. Before we jump in, I do want to talk about a couple of housekeeping notes. For those who are listening to the pod, whether that's on Spotify as audio only, on Apple Podcasts as audio only, we are a video podcast. This is funny. People say, well, if you have a video, aren't you a show? We're not syndicated on an actual network or streaming platform. So in my view, definitionally, we are not a show, but we are a video podcast. And so many of the things we talk about on the show, we accompany with a lot of visuals. I think in every episode, we almost have 40 to 60 overlays that we display. 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We're excited to grow and expand the show, and your support will do a lot to enable us to do so, including some of our on-site episodes, one of which we've already shot, and we are in the edit process for, which we are super excited about. Now, with all of that housekeeping out of the way, let's go to our first story of the rundown. And this one is about AI doing physics. So Sam Altman, unclear if he's a human or a non-human, non-human intelligence himself, but Sam Altman and OpenAR are claiming that ChatGPT is now doing research-grade high-energy physics research. What is your take on this recent OpenAI story, which I think was in tandem with a couple of other institutions, maybe namely MIT, if I'm remembering correctly? Yeah, it's a pretty interesting story, and it's a pretty big claim. I first heard about it on their Twitter. The idea is in particle physics, we are worried about calculating something called the scattering cross-section of stuff, okay? Imagine you're at the LHC or any collider. Large Hadron Collider. That's the Large Hadron Collider in CERN. Right. You've got jets of particles that are interacting with each other, and then they have a certain energy, and then you've got a bunch of detectors around. And what the particles are going to do is, because they're at such high energy, there's going to be interactions of different fields at this quantum level. There's going to be a Higgs boson coming. There's going to be electrons, protons, like all sorts of random stuff happening and then they're going to scatter off right and then different particles are going to scatter off and we're going to collect all that data in our detectors from that collision right what we want to do is calculate what the scattering amplitude and the probability is going to be in each of these directions right because the point is after the collision these things are scattering in all kinds of all kinds of different directions directions depending on whatever physics right is going on at the point right and so fundamentally in particle physics all these guys are doing is calculating these scattering cross sections okay because that tells us intimately how the fields interact with each other right how does the electron interact with quarks how do quarks interact with each other and in this case they're wondering how do gluons interact with each other gluons are the mediators of the strong nuclear force we went over this in a previous episode but just to briefly reiterate the strong nuclear force is what keeps the nucleus together. Okay. Nucleus is full of protons, which are all positively charged. According to electromagnetism, they don't want to sit right next to each other. They want to blow apart. But the strong nuclear force between the quarks inside of these protons is what's gluing the nucleus together inside of an atom. And that glue comes from gluons, which are the mediating force between all of these quarks. That's how the quarks kind of talk to each other. Now, gluons can interact with themselves. A gluon here can interact with another gluon here. And the focus of this particular paper is about how those gluons interact. There's a certain type of diagram. We use Feynman diagrams, which is this sort of tool. It's a mathematical tool, really, but also a visual tool that Feynman came up with that helps us understand how these fields interact with each other, with like virtual particles, a gluon interacting with another gluon and so on and so forth. And usually when we calculate these scattering cross sections, we want to figure out all the different ways that a gluon can interact with other gluons and so on and so forth. There's a particular way that they interact, which we thought would never happen. Because if you were to calculate through the whole integrals of all of the Feynman diagrams, this tree level diagram, which had no loops, the answer came out to be zero, Meaning the amplitude was zero, which means the probability that this particular process happens is zero. That's what it was thought. So the math was saying that there's an outcome that should not happen. That should never happen. And we feel very confident about the math. And so the math was like, this is solid. This has been proved true in other use cases. And so we should safely assume that in this use case where n equals zero, that nothing will happen. Yeah, yeah, exactly. Right? The amplitude should be zero. The probability should be zero. Then about a year ago, the authors of the study from IAS Princeton, Cambridge, Harvard, they decided that actually it might not be totally the case. OK, they went all the way up to N equals six, which is six gluons interacting with one another. And they tried to write out by hand the formula for how probable this outcome would be. it's a ridiculously bad formula in terms of just like for a human being to write out all the combinatoric possibilities of this gluon going here and going there what's the probability of this and keeping track of all those integrals they do it by hand all the way up to n equals six okay but what they what they're getting an inkling of is maybe this is not zero this answer is not all going to cancel out okay so that's when they employed chat gpt chat gpt took those expressions simplified it and then conjectured a simple formula that was a general case for all n not just n equals all the way up to six but n equals seven you just plug in a number you get the thing out and then very this was kind of interesting then an internal open ai model spent 12 hours reasoning behind this thing came up with the formula on its own and came up with the proof for that formula that was then corroborated by the authors the proof was verified and it was correct so let me make sure i'm getting this right so they initially fed this thing to chachi bt and it created a simple a simple formula yeah simplified way of doing a simple calculator to do the math yeah for n equals any number anything it figured out some sort of patterns yes within like n equals one two three four five six and maybe figured out a pattern that was going on and it was like actually it's in physics we do this all the time it's called an ansatz It's our best guess for what do you think the general formula should look like? So it created its own version of this simplified expression. It's a simplified formula. And then they fed it to an internal OpenAI model that had a bunch of scaffolding that's specific to scientific research stuff. It let it run for 12 hours. And this is like an important note. Like, you know, the state of the art. There was a different model that let it run for 12 hours. Correct. I do want to be. This is not like 5.2. Right. They had an internal model that ran for 12 hours. And so just conceptually for context here, because I think this is interesting, you can take these base models and then what they call they put scaffolding around it, which is this technical term to mean these additional weights and processes that are hyper specific to a particular task or use case. So this is not just you could go into ChatGPT today and you could then get this result. Yeah. But the underlying model intelligence is being amplified with this sort of bespoke use case. Anyway, they let it run for 12 hours. Yeah. And I think this is important because a year ago you could not have long-running agent-based autonomous processes. and just actually recently in the same time period as this is coming out, now the maximum time last year, the maximum time was about three hours, a couple hours. Just about a week ago, the max running time, this was for a Claude Opus 4.6, was two weeks straight, and it built a C compiler of 100,000 lines of code from scratch that worked with no human intervention. So I just, I wanted, yeah, yeah, yeah, I heard about this. That was crazy. It's really these being able to run these things for longer enables stuff like this. So they ran it for 12 hours and then it came up with a proof, which then meant the human scientists could then go through that proof and verify and validate that it's true. Yep. Yeah. And it was true. And it was true. So it is quite fascinating. Right. And I think it is a big deal. Yes. OK. From from where I'm standing, I think it is a big deal. But there are caveats. OK, there are nuances because I want to understand what is actually happening. I do hate these black boxes. Yes. But, you know, we're in the age of A.I. black boxes. Is it actually understanding stuff or my hypothesis is, well, let's go through. Is it actually understanding stuff? Is 5.2 understanding something? Friend of the show, he's going to be in the acknowledgement section. Alan Southworth, he sent me a screenshot of something that he asked, ChatGPT. um and that's in the next photo i want i want you to show that okay so he asked chat gbd 5.2 okay i want to wash my car and the car washes 50 meters from my house do you think i should walk there or do you think i should drive there you should drive there because it's your car yeah right okay chat gbd answers at 50 meters you are officially in the put on sandals and stroll territory right because it's in all of its LLM knowledge it's like oh 50 meters you can walk because there's probably so many blog posts out there about when is it okay to walk and why to not you know use gasoline and all this other stuff what's hilarious about that is at the end of the whole thing you know chat gpd always asks a follow-up question because open ai wants you to keep engaging the follow-up question is so are you going to get a full detail or so it knows that you're doing the car wash the whole time yes but in the middle it's like you should walk and then at the end it asks are you going to do a full detail or like what are you getting about your car yes yes do you understand and the point being it means it doesn't actually have an understanding of the question and the variables inside the question because for any you could ask a five-year-old that question and they'd be like you should drive the car because you need the car to wash right they've associated some type of meaning behind the task that you're trying to do and accomplish which is get my car washed and the mode of transportation you would need to get there you would have to take your mode of transportation because the task is related to that mode of transportation that's chat gpt 5.2 that's not able to actually make that connection i actually would be curious is it does he have be curious if he had thinking on or off interesting okay because you can't have reasoning on or off with 5.2 oh okay i'm not saying that it would have made a difference right but no that's a valid question i think it is because that's the argument that those on the inside are making it's like oh when you just use the base models without reasoning yeah this additional layer to basically in theory check for this kind of stuff yeah then yes you will get these quote unquote hallucinations but the argument is oh reasoning with 5.2 and opens 4.6 covers most of these use cases i'm not saying that's true that is the argument thing that is the argument so alan it would be good to know if you use thinking on or off yeah because if thinking is on it really does i think expose a huge with even within the reasoning pathway it is really not actually understanding yeah and from there i wanted to ask like okay like how if it's not understanding how is it able to do this physics right right right um i have a hypothesis i don't know if it's correct and you know perhaps someone can tell me i'm wrong my hypothesis is that you know chachipati in all of its wisdom and all of its research in pre-training found a piece of mathematics that was very similar to this physics problem, right? It's reducing a bunch of integrals that are sequential and all of these processes, and it's trying to find some, like, generalized formula. Perhaps in all of its reading of the world's mathematical literature, it saw and made a connection to someone else who had done something similar to find a general use case, right? Pulled that bit from its latent space and then injected it here. I'm wondering if that's what happened. And that would make sense given the structure that we are currently told is what these large language models are framed as because your point, what you're saying is there is a pattern that the model found in other – in mathematics applied to another use case that for whatever reason we as humans have not yet made the connection to. And the model has made the connection. Maybe the physicists who are working on this are just not aware of like some fringe mathematical aspect. And so perhaps it made that pattern recognition, right? regardless i think this does show the utility of these large language models to do frontier theoretical research now right right one of the things i know we've spent a long time on this story but i think this is such an i think it was cool this is really cool and i think it's very important because this is like a zero or one phase state change kind of issue either these models are not able to discover new science or they are yeah and the difference between a world in which they are not and in which they are are is an order of magnitude in terms of the implications yeah yeah yeah so it's it's something that we should cover and you know i'm not quite um convinced that they can do really new science right but they can fill in gaps yes and i think that's what they're doing here yes right yeah and even that is itself a very good thing i want to remind people that chat gpt which is the first like consumer version of the modern era of lms came out three years ago yeah and so i think keeping the time scale of progress in mind is very important yeah uh you don't even graduate college in three years yeah and we've gone from it can do absolutely jack to getting to the fringes of some of these fundamental science concepts, I think it's very unwise to underestimate this. I get that there's a whole variety of social, economic, political implications that are all very important to talk about. That is 100% true. But saying this is a stochastic parrot that can't do anything of real value I think is a gross underestimation of what is currently happening. Yeah, yeah. And we need to, like, as a society, start grappling with the true potential of this technology and how we're going to get around it. Because if it doesn't get there, great. Yeah. But if it does get there, we don't want to be getting there with our pants down. Yeah, exactly. Great first story. Again, potential watershed moment as this moves into scientific discovery. We've talked about several previous episodes where AI is already having other tangential impacts within Breakthrough and Frontier Science Research. Yeah. A long story number one will be quicker for the stories. Story number two that we have here. This is out of the Universita D'Aglia Studi di Napoli, Federico II in Napoli, Italy, and the universities in Berlin in a paper in Scientific Reports. This is about feline behavior. A new study has shown that a cat's purr reveals much more about its individual identity than a meow, a cat's meow. Yeah, so a meow is different from a purr is the point. You know, cats were domesticated probably like 10,000 years ago in the Middle East. And what they found using 27 different cats and the vocalizations of all these different cats is the cats do not meow to each other. The meow of the cat has specifically evolved to interact with their humans. Oh, wow. Okay, that's the point of the story. The purr is actually something that is like very unique to a cat. So one cat's purr is going to be just a foundationally different sound signature than another cat's purr. But the meows have a very high variance. And the meows are basically used to interact with human beings. Cats only meow at each other when they're like in a fight, effectively. Otherwise, they're like communicating like, hey, this is me using a purr. And what they did was they also compared the vocalization of these 27 domesticated cats with the cats in the wild. Okay. Again, that's what they found. The meows are more variable, but the purrs are actually much more related to these wild cats. So the purr has kind of been around since domestication and before domestication around 10,000 years ago in the Middle East. But the meow has actively evolved to communicate with human beings. Like, I need more food. I want to go outside. I hate you. I don't know what cats are like, but I think that's what's going on in their head. So we've identified that a cat's purr is like their fingerprint, the idea that every individual's fingerprint is different. But the meow is the way for them to interface with the meat suits that are human beings. Yes. That they get to boss around as they like to. Another follow-up to our Lion Roar story that we did last week in the rundown. A lot of great animal science stories. We're now going to talk about immunology and the debate of nature versus nurture. As scientists discover how life experiences rewrite the immune system, it's like we have a molecular diary of our past. past. Yeah, this is an incredible story out of the Salk Institute in La Jolla, California, right outside of UC San Diego. It answers this question of variability, which is something that is very familiar to us having gone through the COVID pandemic Some people got completely wrecked by COVID when they got it Other people were fine you know even with the vaccine on both ends right Even if you control for those who are vaccinated and not the variability between responses from one individual to the other is extremely different OK, and this particular paper is trying to answer that question. Why is stuff so different? They focus on something called the epigenome. The epigenome is how the DNA gets expressed. Everybody has the same DNA effectively, but like how each DNA strand, how the genes in that DNA get expressed is part of the epigenome. And that's a very dynamic thing that can change as we age and as we have life experiences. The genetic patterns can be changed through two ways. Either it's a genetic thing, right? Like there's part of our epigenetics where the cells pick which genes to express and which genes to not based on the genetics themselves. And then there's another one where our life experiences actually change genetic expression, right? And those competing factors are very much in play when it comes to immune cells because immune cells have to learn throughout the experience of an individual, right? I get some disease. My immune cell has to now remember what that disease looked like mechanistically so that we don't get that disease in the future. Right. So immune cells are this really great lab to try and figure out what are these competing effects like. OK, what they focused on was something called differentially methylated regions. Basically, you've got your DNA strand, your body, your cells put tags on the DNA with these things called methyl groups. OK, and that sort of gives them a distinction between, hey, this is a methylated piece of DNA. This is not a methylated piece of DNA. So structurally, from a molecular level, they can tell two bits of DNA apart. OK, what they looked for is how these differentially methylated regions were tied to things like genetics and life experiences. And what they found was there's actually two different types of markers in our genetics. OK, the part that's more genetic is actually particularly in long lived immune cells like the T cells and the B cells. These are the ones that have memory of our past immune attacks and things like that. And all of these methylated regions are found in the stable regions of our genome. On the other hand, if you have things like, you know, the killer T cells, these are the ones that are rapid response. Those are the ones that have this methylated region in more flexible regulatory regions. OK, so you've got these two different effects. And so what this kind of cell specific database can tell you is new insight into how immune responses form. And also later on, we can do, you know, future treatments that are tailored to each person's unique biology. right because their particular immune system is going to respond in a different way to somebody else based on their past treatment so if we can read the epigenome we can then forecast how is someone going to respond to a certain treatment how is their immune system going to respond that's the idea this is very fascinating the the the concept here being there are uh you know our genome has both these like genetically uh inherited from long the long history of evolution that then formulate into these long-lived T cells and B cells, which kind of makes sense. It's like, oh, these are things that for millennia, for generations have been helpful. So we can kind of memorialize it in our long-term memory. And then there's this sort of epigenetic layer, which is more about the lived experience of the individual or its most recent predecessors impact the killer T cells and these sort of aspects that might need to be more reactive to real-time changes in the environment. And so the point – And we're able to now in the molecules see the difference. See the difference, how they're tagged between coming from this long history versus a short history. And again, I mean this goes to the importance of like genetic diversity in clinical trials as an example, which is a space that my mom works in because you will have different responses based not only on someone's African versus African-American, but even if they're both black, the epigenetic layer of the experiences are going to be fundamentally different between those who are part of the African slave trade versus Africans who are not, just as a use case example. And so these kind of details are important because it – especially if someone is black, like the medical system and us being able to get treatment is a very complex issue. Yeah. Because just like photos and film was initially created for only white people, right? I didn't know that. There's fundamental things about the way that film, like actual film works because of light. If you think about how light bounces off of white people's skin versus dark people's skin. So until we got later into digital, it was never really made for black people. Medicine kind of has a similar issue where a lot of the genetic profiles have been or the way in which we've operated is for a particular group set. And I think as we continue to do this type of research, it will allow us to expand the efficacy of medicine across a larger swath of genetic profiles. So fascinating story again there on talking about immunology, which has been an issue. We've talked a subject. We've talked about quite a bit on the pod. we're going to move on to origin of life yeah for our last rundown story or second to last sorry second to last i want to do i want to do five this time okay okay okay uh so for our second to last which is going to be this um scientist finding genes that existed before life on earth what does that even what does that mean yeah that doesn't that doesn't mean anything to me right right genes before life what are you talking about is exactly what i thought when i was when i was reading this i mean because like it's like life is genes right so how does it before yeah yeah yeah so here's what's going on there might be some genes that are in nearly every single organism today that were duplicated before life shared a common ancestor okay okay because let's think about all of life on earth right it came from a single common ancestor that's what we think Yes. Because we all have DNA and there's all these different markers. Right. Now, that single common ancestor. There must have been stuff before the common ancestor that were building blocks to make that last common ancestor. Right. Right. And these guys are saying they have a way now to find genes that were there before that last common ancestor was even alive. Fascinating. Like the building blocks of that last common ancestor. It's pretty insane. So when we think about the lost common ancestor, right, these are cells that already had membranes. They've got an inside and an outside, and they've got DNA to store genetic information, right, to store some information for self-replication. Now, these are essential traits, and they've already been established. So what happened before that, and how can we tell? Well, they look for something called paralogs, okay? Paralogs are groups of related genes that appear multiple times within a single genome. A good example is for us hemoglobin. We have eight copies of hemoglobin in our DNA. And that hemoglobin came about about 800 million years ago. That's the thing. That's the protein that carries oxygen in our blood. We've got eight different copies. All of us have eight different copies. A lot of mammals have eight different copies. The fact that all of us have that means that hemoglobin is a really old, old protein. Okay? So the idea is if there's repeated copying and extra versions of this gene, then the copying must have happened way early because all of us have that. Right? So now let's look for universal paralogs, which are genes that are repeated, like they have this repeated tendency and these copies across everyone. bacteria, us, fungi, literally everyone. What they're looking for is gene families that appear at least two times in at least two copies in the genomes across life. And so to be clear, you're saying hemoglobin, there's eight copies. Eight copies, but it only happened 800 million years ago. Right. Like bacteria don't have hemoglobin. Right. And so we're looking for things that have multiple copies like hemoglobin, but hemoglobin we only see in humans and mammals yeah and so we're saying what else has these n number of multiple copies but in other everywhere yeah yeah but literally everywhere that's the other thing okay yeah it's got to be literally everywhere because then you can make the argument it happened way back even before the universal ancestor right yes and they found a few And all of these genes have to do with two things, either building proteins or managing the membrane, how to get in and out of the membrane. And that kind of makes sense. We've talked about this. You've brought this up several times about the membrane. And it's like, how did that happen? How did that happen? It turns out these cell membranes and managing transport across the cell membrane is something that might have happened even before our last common ancestor. just in like random molecular processes and like proteins at a molecular level not even a cell right trying to self-replicate right but like molecules yes trying to get across yes and if a molecule got across it had an advantage to like do more of itself right um and i think that's that's really fascinating what they could also do is reconstruct the protein and produce this ancient ancestral protein that could then go across molecules. It's molecular Jurassic Park. Yes, yes. And what's crazy is that molecule that's billions of years old now, it can traverse the same membranes that we have. So that old use case, it can still do it. It's like we've found, we've like reburned a CD copy of Now That's What I Call Music Volume 4, and we're on Now That's What I Call Music Volume 200. But it's like we found the old, and it got the same intro, and it plays in the same player. That's kind of a rough analogy, but that's actually, I thought that was really crazy. This is very cool, because again, what this means is we can continue to log and continue to look for these paralogs across everything that would allow us to identify these ancestors before the currently accepted universal common ancestor in terms of traversing the path of evolution from single cell to multicellular organisms. Unbelievable. This is out of Oberlin College, MIT. I misstated MIT earlier. This was the MIT story. And our Midwest companions, UW-Madison, in cell genomics. we're going to move to our last rundown story which is about astrophysics and exoplanets uh which you know astronomers have discovered a solar system that should not be possible four planets orbiting a red dwarf yep uh 116 light years away from earth yeah so what is happening here and why should this solar system not be possible right so we used to think that every solar system should kind of look like ours for very good reasons. The way it looks like ours is the inner planets are rocky. The outer planets are gas giants, right? That makes sense because when solar systems form, the star is going to be very volatile. So it's going to, the radiation from that proto star is going to basically shoo away all of these lighter elements like helium and hydrogen and ice and things like that. The rocky elements like iron and other nickel, that's going to stick around the star and create rocky planets. And then the outside is going to be gas giants. That's how our solar system is. The physics makes sense. Yes. They have found an inside out solar system. This solar system goes rocky, gas giant, gas giant, rocky. Oh. And that really doesn't make sense. Yeah, that doesn't make any sense. Okay. Just from the physics argument that I gave you. Yes. Right. And they're trying to figure out what the hell is going on. Right. Okay. This rocky planet that's on the outside is 1.7 times the mass of the earth. It's what astronomers would call a super Earth. They tried to figure out like ways that it could have formed. Like suppose maybe it was a gas giant, but then the atmosphere got ripped apart. Right. And so now we're seeing it as a rocky planet. They did a bunch of simulations. Didn't work. So what they think is happening is that this outer rocky planet actually just formed later in the history. Because suppose the inner planets formed early. So you got the rocky planet on the inside. You got two gas giants. Those gas giants have hoarded all of the gas. And now when this outside one formed, there was no gas around to really like nucleate on the outside. Right. And which is why it's now rocky. So the idea, the hypothesis here is that there was the difference is because of a time delay, a formation time. Yes, a formation. They started forming at different times. And by the time that fourth planet started forming after the rocky gas giant, gas giant, all of the materials to make it a gas giant were not available. And so it became a rocky. Exactly. Rocky planet. Yeah. This is a good one out of University of Warwick. Yeah. University of Michigan Ann Arbor, plus several others in science. Yeah. We went long on the rundown today, but we love this stuff. So sometimes we get sometimes we get. Yeah, sometimes we get a little carried away. We'll try to keep it tighter, but we know you all like the details, and so we will always go with the details. But we are now moving back to our theme of the week, which is the Winter Olympics. We talked about why is ice slippery first. We are now moving on to our second main story, which is going to be a neuroscience story. Yes. And this story is about choking under pressure. Not literal pressure like in our first story. No. And not literal choking. And not literal choking. But the figure of speech, what happens in sports all the time, there's a sequence. You've done it a thousand times. You've got a down pat. You train for four years. And then when it comes down to the moment, you just can't lock in. Yeah. And there's actually really good neuroscience basis for these. Yes. And I wanted to talk about this because of the recent events that have happened in Cortina and Milan. This Winter Olympics, there was a man named Ilya Malinan. He was purported as the quad god. This is a Scientific American article talking about the physics of how he can pull off these impossible jumps. He's a two-time reigning world champion. pre-event odds before he went for the free skate portion the individual free skate portion negative 10 000 which is implying a probability of 99 at gold that tells me two things one this guy is incredibly good and everyone is thinking he's going to get gold and two the bookkeepers have really terrible models okay because how do you not include the variability of the Olympics. The Olympics is like no other event in sports, especially for these types of sports. There's the world championships. Okay, he's a two-time world champion. The Olympics is different. I don't watch the world championships. People who are into ice skating will watch the world championships. But everybody is watching the Olympics, right? I think I just saw this chart the other day where the Winter Olympics is like the number five most watched sporting event. only behind the Cricket World Cup, the Summer Olympics, and the World Cup, and one other event that's escaping me. But it is, and it's in the billion, like it's a massive, it's like 10x the Super Bowl. Like it's very, very watched. Yes, exactly. He was the quad god. He was going to get gold, 99% chance. He gets on the ice and he completely chokes. Okay. He was going to make this quad axle, which was going to be the first time anyone's ever done it in a competition. Everyone was looking forward to it. This was crazy. I was watching it live, dude. He goes for his first jump, which is the quad flip. Does it very well. The commentators say it's an effortless start. The next one is going to be this quad axle. And the commentators say if he's going to go for the quad axle, it's going to be this next one. I think he goes for it. In the middle of the jump, he abandons it. He only does one turn. And from there, it just unravels. Like mentally, he just like completely collapsed. Yep. Yep. Okay. Yep. And I just thought that was so fascinating because this is a guy who's done that routine probably thousands of times. He's prepared for it. Right. And the Olympic ice is just different. Right. It's still water. It's still H2O. But there's something that is different about that moment that just completely the house of cars just completely collapsed. And it's not a physics issue. No. Like we talked about earlier. No. It is a pretend it's a neuroscience. It's a neuroscience issue. And afterwards, he said, it's the Olympics. And I think people only realize the pressure and the nerves that actually happen when you're on the ice. Right. And it was something that just overwhelmed me. And I felt like I had no control. This is a quote from Ilya. and from there i wanted to talk about sort of what that means what is going on in an athlete's brain when something like that happens and before we jump in i just want to be clear here um especially as someone who is a former athlete at high level this is not meant to be disparaging to ilia uh no sports is extremely difficult yeah and the stakes are very high there's a lot of money involved it is just the topic that is it's there for us to discuss and i think it's interesting there's an interesting science angle here and so we're trying to like understand the neuroscience of this this is not about oh my god i can't believe he failed or didn't fail no yeah no we're gonna we're gonna be talking smack but it's gonna be later and it's not gonna be about don't you worry this is an olympics podcast but you know ilia is very young and he's gonna be fine so he's gonna be back in the next olympics and you know one of the things that we're gonna uncover about the neuroscience of choking is the more experience you have the better these pathways get to prevent you from doing that that's why lebron is still like incredible right at like just shooting yes even under pressure right yes so let's get into some of the theoretical frameworks before we dive into the neuroscience okay there's several theories behind why this happens one is called the distraction theory what it says is basically working memory which is like your memory of like events that are happening now and what you need to do you know in a while that has a finite capacity and it's flooded with task irrelevant stressors like there's fear about failing there's the crowd there's the cameras on you um and so you get this sort of loss of goal-directed control of attention OK, that's the distraction theory. Then there's the explicit monitoring theory, which is actually the opposite, which says that, OK, athletes actually consciously control some automated practice skill. And if you overthink. That's when it hurts you. OK, if you if you start consciously thinking about what you're trying to do, that's actually what's bad. And then there's another one, which is this over arousal or over motivation theory. And that's the idea that there's actually an optimal amount of arousal when it comes to doing difficult and easy tasks. And if you want to do difficult tasks, you should be aroused less than if you're doing easy tasks, which is kind of incredible to think about. When you're doing an easy task, you want to be more in it. But when you're doing a really hard task, it's kind of better to be a little bit out of it. Yeah, yeah, yeah. It's kind of probably what people describe as that flow state. Exactly. It's the flow state versus the intense attentional control that you're putting on something, right? Right. And so in the context of these theories, I wanted to talk about the brain regions. The main brain regions we're going to talk about is the prefrontal cortex, the motor cortex, and the amygdala. The prefrontal cortex is this sort of advanced mammalian part of our cortex right up here. This is something that is very big in humans. It's also there in primates. It's not so much there in lower order mammals. Okay? This is where you have executive control, working memory. You delegate micromechanics to the other subcortical structures. So this is kind of like our control center in some sense. I mean, I remember there was this guy. He's still there, Professor Bujaki at NYU. He hates when people say this. He used to call it the prefrontal cortex, the trash can of the brain. Because whenever someone was like, oh, this, this is probably the prefrontal cortex. But the reason is because it's such a highly evolved part of our brain that it seems that a lot of these higher functions are happening here. Right? If that makes sense. Yep. So there was an experiment that was done about the prefrontal cortex and how the prefrontal cortex functionally disconnects with the other cortices during high stress. There's a pretty incredible paper called Out of Control Diminished Prefrontal Activity Coincides with Impaired Motor Performance. Here's what it was doing, okay? They use fMRI data, and they have this bimanual visual motor tasks where people, like human beings, are playing snake, okay? And every once in a while, whenever they get the snake game right, they get like $10. Every once in a while, they'll get a jackpot of like $50. And they want to see how the participants do. They actually performed less on the jackpot tasks. It's the same game. But when there's this pressure of, oh, I could just win like 50 bucks instead of 10, the performance dropped. And then when they look at the prefrontal cortex and the motor cortex connectivity during these jackpot trials, it was inversely related to choking susceptibility, meaning the less it was connected, the more you were going to choke. OK, so there's literally a connectivity issue between your prefrontal cortex and your motor cortex. The motor cortex is the thing that's actually doing the gameplay. And when that connection goes down, you're likely to choke more. Now, the question is, why is this connection going down? Right. Right. Right. During these high stress scenarios. So the initial intuitive thought process is, okay, the high stress scenario is what is directly correlated to the decreased connection between the prefrontal cortex and the motor cortex. Yeah. Theoretically. Theoretically, right. But in neuroscience, we always want something more mechanistic. Right. Right. Right. At least I do. So now let's go to this next paper that this was from Smulder and other authors in 2024. This was a neuron, a neural basis of choking under pressure. And what a title. Yeah. Here's what they did. They use you. They they use 96 channel Utah arrays in Reus macaques. So macaques have a prefrontal cortex kind of like we do. This was in the motor cortex and in another brain region called PMD. And they had the similar behavioral paradigm of choking under pressure. Basically, there were these jackpot scenarios where the monkey knew that if it succeeded, it was going to get a really high reward. And again, the same thing happens. You get this increase in performance, but when you get an incredibly high reward anticipation, your performance decreases. So what we're looking at here is three charts of monkey E, P, and R with six sessions, nine sessions, and 12 sessions. And on the Y-axis is success rate, and on the X-axis is sort of jackpot size, going from small going to large. And you can basically see this like top of a trapezoid where we have at small to medium. There's an increase. There's a huge increase. And then medium to large, it kind of maintains that higher level success rate. And you see a very drastic decrease in performance when you move from large to jackpot across all these session lengths and all of these different subjects. Exactly. And so regardless of number of repeats, et cetera, et cetera, there's a clear decrease in performance efficacy when the jackpot gets sufficiently high. Yeah. And the jackpot is way higher than the large. Right. Is the other big thing. It's like small, medium, large are like successively higher. But jackpot is like an actual jackpot. And that's kind of what the Olympics are. Right. In some sense. Right. Like the stress is so high. And that gold medal that's like sitting there could be yours. Yes. It's incredible, right? And so how do we manage that? And so, okay, we saw the behavioral paradigm, which is the same as we have in humans. The trick is now we want to find a neural paradigm, something in the neurons themselves that correlates to that behavioral paradigm. Because then we found a neural signature for what is happening, right? They use something called dimensionality reduction. This is something that we've been through in neuroscience. The idea is your brain lives in a very high dimensional subspace, right? If you're listening to 10,000 neurons, that's 10,000 different dimensions in your mathematical subspace of where your brain is. Your brain doesn't actually live in that subspace. That's just how we're describing it. There might be lower dimensions that we can move along that tell us something about, oh, how much does the brain care about reward in this scenario? how much does the brain care about the target getting to the target and getting that reward in this scenario right we can decompose the brain activity into independent metrics and see what happens so what they found was in the reward axis there was an axis that like basically correlated with reward okay so when it was jackpot it was really high there were a bunch of neurons that were firing when it was a jackpot and that was like those neurons care about it's like kind of telling the rest of the brain, hey, there's going to be a jackpot. Like, we've got to lock in. Then there another one which is the target preparation axis This is the dimension within the target plane that is critical to the reach which is part of the task Like how far am I going to reach for the macaques to get this reward, right? And that target axis has the same behavior as what we saw in behavior, meaning for low reward, I'm not that high on the target axis. But as I go to jackpot reward, again, I come back. OK, so these neurons, these specific neurons that care about the target axis, the geometry of the brain has changed to where this target axis is actually the thing that is causing that choking under pressure. The point being there is now a neurological signature that maps onto the behavioral experimental data around this idea of there being sort of this diminishing as the jackpot gets sufficiently high in task completion. Exactly, exactly. And now we can actually think about a mechanism, right? And what they came up with is something called the expansion then collapse mechanism. Here's the idea, okay? For small reward, I'm influenced by reward a lot, okay? But as I move in this trajectory, there's some optimal space that I want my brain to be in, okay? There's like an optimal location in all of my neurons, in all of my neural space that I want to be in, okay? But when I get this massive motivational signal from the jackpot trials, what that's going to do is put my system into overdrive. And it's going to push my system away from this optimal setting. Yep. Right? Yes. So where now my neural states abruptly like collapse on top of each other. Yep. And I can't actually discern between like what to do when I have the task in front of me. Because like all of my neurons are in overdrive. I've got stress neurons coming in. I've got like the future planning neurons coming in of like, oh, what am I going to do when I get, you know, like what's going to happen in the future all of the past mistakes that i've done that stuff's coming in the memory is coming in all of the stress is like trying to like get into this flight or fight response and it's putting your brain into overdrive and then you get a physical failure because now you can no longer actually do the task as well as you once could just just i want to bring up this chart again which is this uh neural bias why do animals choke and we're looking at an X, Y, and Z axis. Neuron 1 is, let's say, X. Neuron 2 is Y. Neuron N is Z. And we sort of see the influence of the reward, small, large, and jackpot, like in a 2D image meant to represent its 3D positioning on this X, Y, and Z axis. And the point is sort of saying the large, the little circle with the dots around it. That's the optimal. That's your target region where you want to be at. That's where you want to be. Because that's where all the balance of all of the inputs and everything is just right for you to execute. Yeah. And what we're sort of saying here is the introduction of a jackpot reward moves you beyond that optimal positioning. Because there's so much other stimulus coming in. Coming in and going on, which sort of it makes sense because if you just think about athletes, right? Yeah. Some of the athletes in every sport who we mention as being the GOAT, when you look at them playing, almost if you talk about people like Messi, Wayne Gretzky, Usain Bolt, et cetera, visually when you're looking at them with the human eye test, it almost appears as if they are totally unperturbed, disturbed, unfazed by anything going on around them. And it's like they're floating. People always describe Michael Phelps. They're like, they are operating at a plane that is different than anybody else. Yeah, because they've somehow disconnected that input drive that's coming in. And I think that comes a lot with experience. Yes. Right. Which is fair. Which is fair. Like, when it's your first time at the Olympics, like Ilya's, mate, like, I don't know what that's like. That's got to be insane. It's got to be crazy. You've been working. You've been dreaming about this moment for the past, like, God knows how many years. He's probably started ice skating very, very young, since he could walk probably. And then you think about the gold medal opportunity. Everyone is there. The NBC is calling you the quad god. There's so much hype, 99% on Polymarket. That's got to be so much pressure. I would love to see the same group do research on Lamine Yamal because this kid is 19 now, and he's dominating grown men. in every level of competition in soccer, football, globally. And it doesn't make any sense. And there has to be something upstairs that is blocking going to the jackpot space in the gradient descent. How is he with free kicks and penalties? He's unbelievable. Because that's sort of where I would expect choking to happen, right? Because that's an individual kind of thing. With team sports, I don't – Fair. I wonder if we can take these things. Fair. No, no, that's fair. Because it's a little bit different. Yeah. It's a little bit Tiger Woods. Because also Ilya in the team event, although that was a free skate that he did individual and he crushed it. So that's a good point. Over 200. No, that's a good point. But then when it came to his individual, which was only a few days later, he followed the same procedure. That's a very good point. You know, I only bring it up because he's young. Yeah. And like as a counter thesis to the experience point. but you you correct team sports and individual sports very different context yeah yeah yeah exactly and um i just want to end with you know ilia now he's he i mean he's like beside himself and one one of the articles was just about you know it's kind of the point that winning olympic gold isn't supposed to be easy and i don't know who thought it was a 99 because with sports at the highest level anything can happen yep you know yeah and um one of the things he added was i just felt like all the traumatic moments of my life really just started flooding in my head and there was just too many negative thoughts that just flooded in there and i just did not handle it this is a quote from him afterwards which is i mean it's incredible that such a young man has the vocabulary and mental fortitude after such a traumatic event to even speak to the press i think I would like give the middle finger and just like leave. Yeah. But, you know, I think he's going to be back. I have seen him do the, I've seen like videos of him practicing that quad, like axle thing, and it's like incredible. And it's also when he's doing it in the practice, it looks effortless. It looks effortless. Which is crazy. Yeah. Because it's so ridiculous. Yeah. It's so ridiculous how many turns. He's like four and a half turns landing backwards. It's crazy. On that thin millimeter blade with the hundred nanometers of flimby water. It's like, it's crazy. Yeah. So he'll probably be back. But I just took that opportunity as a quick deep dive into neuroscience because I always love that stuff. No, it's fascinating. Again, I think, you know, sports, as we move into the era of infinite social media and infinite content and TV and movies are sort of losing their luster of all of us watching them for the first time at the same time, binging and all this stuff. sports as a medium and the importance of sports as being a connective tissue that's real time it's the only appointment uh media left yeah you gotta you gotta be there when it happens uh both in person or digital yep and it is you know we see these kind of situations this this was not meant to focus on it happens in all sports no all of the time why is it that zion williamson in the nba was one of the most lauded NBA draft recruits that everyone was super excited for him to be the next big thing in the NBA. Totally flopped. But now Cooper Flagg, 19-year-old, comes in, same kind of pathway, people. He's absolutely dominant. And it's very interesting to see this play out across different sports and across different contexts. Yep. We are going to wrap up the day with our sort of final main section, which is a little bit of a potpourri. Yeah, it's a hodgepodge. It's a little miscellaneous. There will be a climate science aspect to this, but we're going to cover a lot of different areas. I think you did have some other random thoughts about the Olympics given our Olympics focus here. So why don't we start with some of this potpourri that you got for us? Yeah, so the first thing I want to talk about is climate change. It is real, and it's going to hurt Winter Olympics a lot more than Summer Olympics, as you can imagine, right? With the earth warming, the first Olympic Winter Games were held in Shamanics, France, in 1924. All 16 events took place outdoors. Look at these fine gentlemen in suits. Like they're ready to, you know, I think this is the skate race, the 1,000-meter skating race. the athletes relied on natural snow for all the ski runs and the freezing temperatures on the ice rings now we get to 2022 in beijing all artificial snow yes not a single snowflake there was made by like the actual weather it was all artificial snow in 2022 okay and in a recent study scientists have looked at the past 19 venues on the winter olympics to see how each one might hold up given the climate scenarios that we can forecast into the future. They found that by mid-century, four of the former host cities, including Shamanix, Sochi, Grenoble, and somewhere in Germany, Garmisch, Partenkirchen. That's pretty good. Yeah, Germany can do. That was pretty good. Those would no longer be able to host reliably given the climate that we're coming in, even under the best case scenario that's actually okay and if we do the current fossil fuel rate of burning then places like squaw valley and vancouver are also not going to be able to do it right this is getting pretty bad yeah and especially when we have something like the paralympics which happened you know a month or two after the real olympics snow making requirement is going to keep on increasing because we're going to have to keep making snow in March and the amount of snow that we'll have to make is going to increase all the way from zero to now like 80% if you want to do it in Eastern Europe and things like that. Right. I mean, we're already seeing this. I talked about this, but at Big Bear. Yeah. They have the only thing, the only reason you can ski on three or four of the runs right now is because of artificial snow. Period. And, you know, we think that, okay, maybe this can be fixed by snowmaking, right? Maybe we just artificially make all the snow that we ever need. That's not even going to work either because even snowmaking works at an ideal temperature, right? You need to be lower than the dew point, which is when the snow that you're putting out is not going to condense into water droplets. Right. And so you've got to be below negative 2 degrees Celsius, 28 degrees Fahrenheit, I mean, depending on the pressure and the humidity. But usually that's about the temperature. Now, that's really bad because we've covered a story on this podcast before. About how the world mountains are warming up faster than the plains. Yes. Because hot air rises and so on and so forth. So we have that little tidbit that the mountains are actually warming up. Yes. So all of these factors are combining to make it really, really quite problematic to do Winter Olympics in the same places that we used to be able to do. Right. People are suggesting that they can do something called snow farming, which is a new thing. I don't know if you've heard about this. I don't even know this is possible. Yeah. Okay, you get a bunch of snow, and you pile it up with massive piles of sawdust, tarps, and wood chips, and that retains 60 to 75 percent of the snow. Interesting. I need to look into how the physics of that works because, like, over the summer, you're telling me it doesn't melt? Yeah, I'm not. That one. That's crazy, but it's, like, working. It, like, works, and people are doing it. If you guys want us to cover the snow farming story, let us know in the comments. Yeah. Because I am also. That doesn't make any sense. That doesn't make any sense. Like you put sawdust, shouldn't it be warmer under the sawdust? I don't know. In any case, I'm just saying that, like, you know, people are going to have to come up with interesting strategies now to keep the Winter Olympics going. I will say I do find sometimes a little bit frustrating where the answer to the problem is always, oh, we'll just find a way to innovate our way out of the problem. No. Without actually giving a specific answer. Yeah. Like you can't just be hand wavy about it. No. Like how? How? Yeah. Like, okay. Yeah, we'll just – but no. Like, why does that actually work? Yeah, like fundamentally, the physics wise, you can't just make snow. Right. That still depends on weather. Right. And so anyway. All right. The next thing I want to talk about was curling. Yes. Curling is an amazing sport. The most electrifying sport in the Olympics. Yes. And all of the curling stones come from a single island. Wait, really? Which is crazy. Oh, OK. There's two places. There's a little island in Scotland called Alissa Craig. I think that's this one. Yeah. And then there's the Treffer granite quarry in Wales. Okay. All of the curling stones come from this island. Each stone is 40 pounds. And the reason why is because somehow these places have very specific types of granite. Okay. In a curling stone, there's two surfaces. There's the part that comes into contact with the ice, which is the running band. Yes. And then there's a part that comes into contact with other stones and, like, knocks them over. Yes. And that's the striking band. And you need two different types of physics for each of them. Okay. Okay. The running band, which is the thing that's on the ice, needs to be smooth. Yep. Right? Because you don't want like grainy texture there because it's going to be moving along the ice and you want it to be as slippery as possible. Low friction. Low friction, exactly. The striking band, that striking surface, you actually want a more granular structure in that granite. Because as it hits one another, if it's a really nice crystal, there's going to be cracks. Right? So what you want is the two different things, the two different parts of the stone to have different sort of chemistry. Yes. Because they have two different functional areas where they're relevant. Yeah. One for making sure it gets down the ice quickly and sufficiently. Yeah. and the other to make sure when it contacts other stones it does so in the most. And it's like a really nice elastic collision that we read about in physics textbooks. Momentum is conserved. There's no like nothing lost to heat and things like that, right? Okay, so somehow there's only two places where there's these good stones. I am convinced this is a racket. It's a racket. Like a racket. There's no way, dude. But look, okay, so people tried to make an effort in Canada in the 1950s. They tried to use the very black igneous rock called an orthocyte to make these. And then those things just started chipping way too quickly. Like the stones would get damaged. And speaking of the Canadians, they are now cheating in the Winter Olympics. I don't know if you guys saw this. Typical. But, dude, this guy, so, you know, you're only allowed to grab the handle and then let it go before that line. This guy was grabbing the handle, letting it go, and then pushing it with his finger. And then when the Swedes called him out, he, like, literally started yelling at them and told them to F off. And then the Swedish NBC, these guys are the OGs, they placed their own camera. Because the Olympic cameras are placed, like, here and behind. So the guys could have gotten away with that. The initial comment of the initial complaint was prior to the video. Yeah, because this is a known thing that this Canadian dude does. OK. And so the Swedish guys for the Canada versus Sweden match. Yes. The Swedish NBC, their television. Yes. Put a specific camera at that spot and caught this guy red red handed. He did it again against the Swiss. And I think now he's facing penalties. after all that bluster the judges were just like not doing anything yeah yeah because they were like well i don't know if he did it or not well now it's like we got a specific camera that's showing that he did it i guess it must be the case that no one was dumb enough to do it which is why there's no like goal line technology for this currently yeah but it seems obviously true to me that like if that's the rule yeah and there's an advantage you can get from breaking that rule because you you give an initial momentum yeah and then a tiny a tiny nudge will like yeah Because the target is meters away. Yes. So even a tiny bit of nudge in that angle is going to cause a huge deflection later on, right? It's not nothing. Very, very, very sad. Look, we're trying to continue to establish and repair our North American relationships with the Canadians. There are several things to be upset at us about, but we are now upset at you guys about this cheating. That's BS. Let's not – remember, as Bad Bunny said, it's America, and it listed everybody. Yeah, yeah, yeah. So we've got to be on the same page here. No cheating in the Olympics. Yeah, yeah, yeah. I want to beat Sweden as much as anyone. We're on the same team on this one, okay? Okay, and the next thing about cheating, I don't know if you saw this. No, I did not. This is a family-friendly podcast. And so when I say these words, I am using the biological terminology. This is penis gate. Okay. Okay, ski jumping penis gate. allegedly some competitive ski jumpers may have artificially enlarged their crotch area by injecting their genitals with engorging chemicals or stuffing their underwear to make a bigger bulge i'm not kidding what is the what is the athletic advantage of this okay so that's exactly like because that's a lot like what injecting stuff down there what mate what are you doing okay so Here's the idea, right? Ski jumpers, ski jumpers, they get laser, whatchamacallit? Hair removal? No, no, no. It's like they get laser, their body gets laser scanned. Okay. And then the suit that they put on has to be exactly fitting to their body. Oh, it's like Frozone's, where is my super suit? Yes, it's exactly that, okay? And the reason for that is their sport has everything to do with aerodynamics. Okay? So here's how the physics of that works, right? You go down this giant ski hill, and I think we've got a visual for it. Yes. This is 4-13. Yes. We go down the giant ski hill, right? During that downhill, you want to reduce drag as much as possible to get as much velocity. Yes. Now when you lift off, you want to increase the amount of drag because that is going to increase the amount of lift. No way, dude. Right? and and what these guys are saying is that if i have a slightly bigger like area that is going to increase my lift and so it's going to make me go farther and that's why they're injecting stuff down there dude this is so insane what is going on the surface area of the bulge increases your lift yeah you're going to get you a farther distance yeah this is a ski jumping thing where they go up and they're just like yeah and then they do like a v so that they can yeah and and they have to hold this position but like just a i guess a few inches down there look a few a few inches has never been more impactful right right it's a gold medal versus not medaling don't try this at home no not at all this is for the olympics the olympics what are you guys doing Not for your at-home Olympics. There's no medals in that sport. It's a losing game. Yeah, dude. Anyways, that was my last story. That was sort of my stream of consciousness. Of all the things I was researching, this is the V. And you see, like, if you make the crotch area just a tiny bit bigger, maybe you get, like, two more meters over the other guy. I don't know what the judicial system is for sports. I think it's CAS, the central something for sports. Yeah. I think you're going to have to look at this issue. Yeah. this is ridiculous guys that's uh i mean okay look i think steroids are is more reasonable than whatever this is yeah let's not let's not do that yeah um that's i'm gonna keep it pg and i'm gonna leave it there yeah yeah yeah exactly this is a family-friendly show yeah but this is a real thing that's a real thing it's happening it's happening i think you guys should know about it because i was alarmed that that is that is quite yeah that is quite uh curious and this also speaks to again the what we talked about earlier the stakes as it relates to these high level events like the olympics where the stakes are that high that people will literally physically do anything to their bodies to win um it's never worth it uh no it's never worth it we want to keep human sports human no robotic olympics when they start don't support them um so we have gotten to the conclusion yes of our fantastic winter olympics episode i am starting to get some beads of sweat on my nose here because we are in la we are in la and although it's not that cold although it is raining it is not snowing yeah and so these ski jackets are are quite warm quite warm but we we We did a lot of fun stories today. Again, science is all around us. We talked about the physics of slippery ice. We talked about the neuroscience of choking. We looked at how climate science, climate change, anthropogenic climate change is going to impact the ability to have future Winter Olympics. So if you have kids right now that you're trying to get on the U.S. Olympic team for the 2042 speed skate or I guess any of these outdoor related events, it's going to be relevant to you living vicariously through that future Olympic child. And our rundown was super fun today. We had a ton of good stories. The AI doing physics thing I think is a – No, that's an interesting one. I think let's not sleep on this issue. I understand, again, I have similar feelings about where the money is coming from for all these billionaire frontier models, why it's bad to replace all human labor with LLMs and software, AI and robots. And also, we have no plan for distribution. And yes, there are some cases where hype is happening. But this is happening, and it is moving very, very, very quickly. And if the last time you tried any of these things was the free version of ChatGPT, even six weeks ago, even two weeks ago, where the frontier is, is exponentially better than it was two to six weeks ago. It is unbelievable, and I just really encourage people to remove their prior biases about AI, not because we're saying it's amazing and brilliant and all this stuff, but because we're saying it's growing at a rate that no other phase shift in technology in our lived lifetime has changed. And the implications of that are so enormous, it's like hard to really articulate. And it is not just we're software engineers and everyone else is going to be fine. Yeah. I just this is something I'm just going to keep beating the drum on because I think it's very important. But we had other great stories today. We talked another animal behavior study story on on cats, meows versus purrs. We did immunology talking about us discovering how we rewrite the immune system and the epigenetic versus long, long form genetics that informs that the origin of life. beyond our common ancestor that's a really fantastic one and then the astrophysics and exoplanet stories about us discovering a solar system that should not be possible i mean where else everybody can you get the absolute best breakdown of breaking and frontier science across physics chemistry biology all the stuff in between it's only here at ffp the fundamentally flawed podcast yeah which is a funny name that we got out of one of the little thingies we use but it is from first principles we are so grateful for our audience last two things comment yes what should it be thoughts now what are your thoughts on uh the controversies that we yes encountered whether it's the canada or the ski jump yes crotch or the gate the next gate uh This is a free form one. Some of you guys have had some really good comments, so we really appreciate you. Again, if you love the show, if you've gotten to this point in the show, if this is not your first episode, you're one of the key members of our community. We appreciate you listening to the pod. We have now opened up our donations flow. This is going to be hugely helpful for us to be able to continue to produce and expand the team and ability for us to do more shows with more content all the time with the pod. So any support we can get from you all is really appreciated. And I will also mention we are building out our community portal, which is going to have some exciting features. We have a sign-up form on the homepage at ffppod.com. So sign up for email updates if you are interested in donating. Go to ffppod.com backslash donate. You can find us on all of the socials, X, Instagram, Facebook, LinkedIn, Blue Sky, any ones I forgot to mention. The main full-form video podcast is on Spotify, Apple Podcasts, YouTube. We're also on Overcast, iHeartRadio. Effectively, anywhere you can listen or watch stuff, you will find us. If you watch our clips, our clips will not be in context of the almost two-hour episode that we did today. And so, yes, you might have a clever comment that is true in the context of the clip, but it is untrue in the context of the full episode. So we appreciate the feedback. But so you know, we always email all of the authors of the papers we cover to get their feedback and provide corrections from them. And if we don't get corrections from them, then the clip gets to live on in perpetuity with no corrections. I am your host, Lester Nare, joined as always by my co-host and our resident Ph.D., Krishna Chowdhury, with another wonderful deep dive here on the Winter Olympics. We will see you all next week. Because this is from First Principles. Thank you.