From Princeton to the Nobel Prizes — How FFP Started + 2025 Nobel Recap

0:00Konichi Wagwan internet this is your captain speaking Lester Narre joined as always by my co-host and our resident PhD Krishna Chowdery this is from first principles also known as FFP pod we are joining you here in our post Nobel Prize week episode unbelievable week super interesting we did three days in a row we put out the full episode the engagement has been unbelievable clearly people liked our sort ESPN style coverage. >> Waking up at 2:30 was worth it. >> Um, super interesting stuff. We're going to do a follow-up this episode. But before we start,

0:40>> uh, one of the questions that kept coming up in a lot of the comments as more and more people started watching the show was, "Who are you guys?" >> Um, which is a fair question given we just started the podcast. >> Our first episode was July 31st of 2025. >> Yep. >> So, we're only a couple of months in. >> Yep. and we thought it would be a good time to kind of talk about our origin story, uh, which is not dissimilar from many other podcasts, but it all starts at one place we talk about a lot on the podcast, which is Princeton. Uh, we both sort of were at Princeton at the same time, became best friends. Um, and at that time you were in one of the most illustrious programs on the planet.

1:21>> Yeah. >> In the Princeton physics program. >> Yes. >> And >> boy, that was a doozy, wasn't it? So we we met sophomore year. >> Yeah. >> Which was 2011. So we've been friends for about 14 years now. >> Um our wives are very close at this point. >> Uh which is another interesting variable. But at the time >> um you know I played soccer and I was moving from economics to program 2 which was Shirley Tilman's pet project for creating a arts program at the school. >> Right. >> And you were busy doing the hard sciences. >> Yeah. I was pretty set on physics right when I got there. I remember asking you one day, uh, oh, like you know, physics, like, oh, was that hard? And you were like, mate, me, you have no idea. Yeah.

2:06Program started with like 20 200 freshmen being like, I'm going to be a physics major. And then slowly it just ended up being like the 20 of us being like, bro, this saved me. >> This is ridiculous. So, we have a long friendship and a long history. And a lot of the times even back in the day you know I would always come to you about you know one of the interesting overlaps in both of our lives is that we both come from immigrant families. Yes. >> Uh Indian and Zimbabwin >> both of whom have two parents that are heavily involved in the sciences. >> That's right. Yeah. >> Uh between the two of us we have three PhD parents. >> Yeah. >> Uh we have uh physics, botany, parasettology and clinical trials as the

2:48sort of verticals that our parents work in. Mhm. >> And so I think part of the initial like substance of why this show works is we both grew up in science-based households >> Yeah. >> that were very academic focused in terms of us. >> Exactly. And like the the stories that I would hear growing up about like the heroes right would for me would be like scientists >> 100%. You know, my dad would tell me stories about fine men and Einstein and Chandra Shakhar, you know, and so instead of sports, we got I got at least a lot of just science heroes to look up to. >> I mean, it's very similar in Zim culture

3:29where you know your path out. A lot of times people don't know a lot about Zimbabwe. The number one thing most people know about Zimbabwe is we had a trillion dollar note because of hyperinflation >> uh in like the 2000 2000 or 2001. Um, but one thing that's not well known is we have an incredible academic infrastructure >> in the country. And when you grow up, >> you're you're built to be in the sciences, >> be a doctor, >> be in mathematics. Uh, cuz that was your way to sort of salvate. That was your way out of poverty. And I same in India. I was going to say it's very similar. >> Education was your lottery ticket. >> Exactly. Yeah. >> Um, and so we have this sort of shared background both family and college-wise.

4:10Uh, you know, there's an LA connection as well. >> That's right. >> Uh, B, you born here. Me moving here after college. >> I wasn't born here. >> Not born. >> Yeah. I I was born in India, but I did grow. This is the most I've grown up in. This is the place most grown up in. >> Most the most normal home. >> Yeah. >> And what's interesting is I remember when I was trying to decide >> between New York, San Francisco, and LA. >> Mhm. >> Which is the classic three choices that you have >> Yeah. >> after school. >> Yeah. Um, I really wanted to come to LA and you were so you were just like, "Yeah mate." >> Yeah, LA is the place to be. >> LA is the best. We both ended up back here.

4:51>> Yeah. >> Um, a little bit of different paths. >> Um, I went straight to the private sector. I've worked in sort of entertainment and tech for the last 10 years, which is kind of where I've acquired a lot of the equipment that now enables this podcast. It's been sort of 10 years of working uh in influencer marketing and gaming and and now running a tech company. You stayed in academia. >> Yeah. >> For a little bit. >> Yeah. Went to UCLA for graduate school. Um got my PhD there. Ended up first at in the physics department of course. And um you know at Princeton I got really interested in the emerging field of biological physics which is the idea of

5:34trying to figure out how life even like exists >> in a in a world where physics is king. >> Right. >> Right. In a world where um where the second law of thermodynamics is an axiom where everything needs to go to soup and everything needs entropy needs to increase and everything needs to be uniform and at equilibrium. We are clearly like highly non-equilibrium beings that are just creating podcasts and not just us but like plants, bacteria, all of these little things are hacking physics at a fundamental level to stay alive. And that was always so fascinating to me >> that you know >> in a world where um the second law of

6:14thermodynamics is an axiom you can have so much stuff that is just like visibly breaking that rule somehow but it's not you know it's definitely not breaking the rule but it's very clever in how it >> circumnavigates that rule you know >> and I I thought that was awesome. So at Princeton I did some research in like theoretical physics of DNA confinement like polymer physics how DNA bends and curves and stuff like that and um protein aggregation in stuff like Alzheimer's where these amoid proteins like aggregate in a neuron. So what are the statistics of that? And then finally for my senior thesis I did a little bit on um this thing called the omitted

6:56stimulus response which is a a way in which the retina in your eye literally acts like a little microcircuit controller that sends compressed data to your brain in a very cool way. So that that's where I got really into neural computation, >> right? >> Of like how does a neural network that is biological and running at 300 Kelvin in this hot and soupy environment able to compute stuff. And so that's where I got into that. And then when I came to UCLA, I did my PhD in neuroscience and physics, but it was in the physics department. And most of my most of my scientific inquiry was physics-based, although the experiments were biological because they had to do with like real,

7:38you know, neurons in real brains. But it was it was a really cool synthesis of like the two fields. Um, got my PhD in physics at UCLA, did a posttock and now I'm working as a scientist in the private sector. I think while you were one of some of your work, correct me if I'm wrong, while you were at UCLA did get public some sort of press coverage. Oh, yeah. As being pretty pretty important. >> Yeah. Yeah. That was that was cool. I my first like first author paper came out of Nature Communications and a lot of the press really really took it up. Um, you know, as the press do, there are some things I was like, that's not quite right. But hey, I'm happy you're you're

8:19talking about it. >> Yeah. Um, you got some international coverage, too. That was really cool. There was like a paper uh a news article in Iran. There was a news article in Japan. So, that it was pretty cool to see like, you know, people responding to my work. >> So, how do we get from this soup of backgrounds to deciding to do a to deciding to do a science podcast? >> It's not our first rodeo. Um, you know, in my work, I've previously done solo podcasts that were more focused in the tech space. uh given that I have a production background uh again all of the technical implementation of lights, cameras switchers editing

9:00distribution. Yeah, >> that was kind of the learning curve there around. Uh, we had actually, you know, one of the things I'd always pushed on was even early on back when we were at Princeton, I was like, I I think I think you have the gift of gab around science communication that has potential, you know, and we tried it with the dark m dark dark matters podcasts uh right around when co started. And I think in part the inspiration was the clear lack of like sort of uh the public health communication during that time period was maybe let's say lacking. >> Yeah. >> And severely >> and there was not really an

9:40understanding of the basics around a lot of the things related to vaccines, the immune system. We'll actually touch on the immune system in this episode a little bit. And so a little bit of the inspiration to try it then was that >> it just didn't work at the time for a number of reasons. Then we tried again uh earlier uh LA like last year you doing a solo me running production >> and you know it just there wasn't the >> it just the magic dust >> the magic dust wasn't wasn't there and then I finally decided let me come out from behind the camera. I I had actually done a little bit of a UAP unidentified anomalous phenomenon >> uh content creation and podcast over the last two years.

10:21>> Yeah. where >> and in that process you set up this >> the studio as a part of that and found success there and it kind of figured out I think the the way in which we need to structure a show. So I came back and was like let's let's try again. >> Yeah, let's do it. >> And that's how we got to where we are today with from first principles. And so just a little bit of background on you know where we're coming from. And ultimately we've built this show with sort of two component ideas. One is it's it's meant to be a love letter to the scientific community, academics, researchers, uh especially who give us the incredible life we have today where every device, every convenience that we take for granted is the result of some

11:03researcher toiling away years ago. >> Uh and ultimately that getting into industrial production and then into end consumer products. Um, and I think the the second reason, and this is more of my reason, is when I look around and I'm looking for content to consume, I'm like, why is there not an ESPN for science? Uh, like why isn't there something that is doing the same kind of analysis and promotion and hyping around the thing that makes all of our lives so much better? >> Yeah. And so this combination of love letter to the scientific community and building the ESPN for science is a lot of the like thesis and theory of the case for for why we've built the pod. And with all of that being said, one

11:44other question that came up um was uh how did you guys get sponsored by uh a a beverage company if you're if you're so new? So many of you probably have seen the shows presented by Standard Model Beverages which has been conveniently placed uh for those who are listening uh if you watch on the video it's always in the podcast uh as the drink of choice. >> That's right. >> And what is the what is the history behind standard model beverages? So standard model beverages also has um a history in science. Um it was started by me and a friend of mine Cameron Bravo. He was a PhD friend from

12:25UCLA. He worked in particle physics at CERN, experimental particle physics. Um, and he got really good at making drinks. >> Oh my god. I remember your bachelor party was the it was incred the brew he made was incredible. I remember talking like are you going to do something with this? >> Yeah, exactly. At the bachelor party was when we started thinking like, hey, maybe we could like do this. And then after my wedding, he he brought more beer. And then it was a hit there. And then we were like, you know, let's just let's make a let's make a sciencecentric company, a beverage company that celebrates science and scientists and the experimental method of how we create these things cuz he's he's a man of science as well. And he he uses the scientific method to to get the best sort of ingredients and the best

13:05flavors. Um and so we called it the standard model beverage company after the standard model of particle physics. um which we're huge fans of and maybe we'll get into in some of the later episodes. Um it's right now we make non-alcoholic soda from agave sugars and on the back of every can you'll find a featured scientist that you can learn about. So this one has Galileo Galile. It'll tell you all about his life and the science that he's known for. Other cans have other scientists. So it's really again just as this show is a love letter to scientists and science this drinks company is a love letter to science and scientists even you can go on our website and learn about the

13:47quantum mechanics behind our logo which is a visual depiction of the Durac equation which is the equation for an electron or any relativistic particle and and and it gives you a prediction of matter and antimatter the antimatter being the hole in a sea again something that we can go into in later episodes because that's one of the greatest achievements of theoretical physics is to l literally predict antimatter based on the fact that a square root can be positive and negative, right? Um and and that's what that's what sort of so all of our artwork, all of our branding is around this love for science. And check us out. Our website should be on the links.

14:28Um we're working towards our alcohol license from the ABC Office of California. And pretty soon we'll we'll be offering more. >> And I think what's so funny is if you listen to this podcast, you'll be one of the few people that understands the secret of the logo that goes on the front of the screen. >> Exactly. Yeah. >> And and shout out to Snapple Facts. Uh which if you grew up in the '9s and drank Snapple inspiration, >> um you turned the cap and there's a little fun fact on the underneath and that was a little bit of inspiration for >> featuring a science scientist on every can. And so with all of that procedural nonsense out of the way, we can get back to regularly scheduled programming. Also, not industry plants, by the way.

15:09>> We are not industry plants. >> That would make my finances a lot easier to manage. >> Yeah. Yeah. This is all self-funded. >> It's just it's just the two of us. We don't have like a team. >> There's no production crew. Everything is done, processed, edited, produced, output just by the two of us. So all the support that you guys give us is really really meaningful as we try to again grow this into a network and again build that ESPN for science which in the times we live in today is more important than ever. >> Yeah. >> And with that we will now pivot into our quick Nobel uh recap. >> Yeah. >> Uh so we last week we did coverage of all of the three science Nobells

15:51>> chemistry uh medicine, chemistry, and physics. >> Yep. And we want to do a quick followup on a couple of the discoveries starting with the medicine follow-up on non-immune roles in regulatory tea cells uh or T-regs. Yeah. >> And so we'll start with that quick recap now. >> Yeah. It's um you know the the 2025 Nobel Prize was given to three individuals Shimon Shakaguchi, Fred Ramdell, and Mary Bronc. Um Shiman Shakaguchi was at the University of Osaka in Japan and Fred Ramstell and Mary Bruncow were um two individuals at private research companies in Washington in America. They were given for basically discovering T-regs which are

16:33regulatory TE-C cells. This is the it it's a cartoon that the Nobel Prize committee came up with. It's got a alien I guess inside of a police ship and the police ship is the T-reg which is the T- cell that is a regulatory T- cell and inside the alien has a cap on and the cap says FOX P3 because the FOX P3 is the gene that sort of creates and regulates the T-reg itself and and and makes the T-reg different from all the other TE-C cells in our body. Um, and just as a quick review for what these T-Rexs do, right? Their basic role is to

17:14act as the police of the police. The police being our greater immune system that targets viruses, targets antigens, targets other human cells that have been affected by a virus or an antigen and are now falling apart. So TE-C cells are normally involved with identifying those guys and then gearing them up for greater immune like therapy, greater immune attack from macrofasages, from all these other kinds of things that come in. And once the T- cell has identified that bad cell, the other guys come in and sort of take care of

17:54business, right? But every once in a while, the T- cell is going to is going to identify one of your own as a bad cell because all it is is a lock and key method. And sometimes the locks and the keys don't work like they're supposed to. And so what these regulatory T- cells do is they inhibit that immune response, right? And that's what these three individuals showed. Shakaguchi was the guy who found T-regs and and showed that they were completely different from normal T-reg T-reg cells. I mean from normal tea cells. And then Fred Ramdell and Mary Broncow found the FOX P3 genome that actually makes these T-regs what they are. So it was both the discovery of the function of this special class of tea cells in

18:36addition to understanding how they are actually created >> at a genomic level >> at at the genomic level. It's both both aspects. >> Yeah. And and that's why there were there were three that got the Nobel Prize, right? Um but since then it's been you know 40 years of research since this all all of this has been happening and now we figured out that T-Rex aren't just about controlling immunity, right? They can also directly influence non-immune tissue function in a in a way that previously we hadn't really seen immune cells do. Okay. So, one of the things in in in today's topic, there's so many different ways that T-regs are are doing this where they're doing this non-immune function, but um the thing

19:17that we'll focus on today was discovered in 2013 and it shows that T-regs are really involved in muscle repair repair and regeneration. We've got a um that's the that's the paper that came out of Harvard Medical School by um Berserine and others in Nature Medicine in 2013. They're the ones who found a population of T-Rex in damaged muscle cell tissue that can actually promote repair of those muscles. Okay? And the way it works is in photo 4 you go these T-Rex they actually sit in your muscles so they're tissue resident instead of sort of circulating in the blood. A lot of

19:58times we think of immune cells as just circulating in the bloodstream right and they go and they find stuff to take care of. These are tissue resident tea cells T-regs that are found in our muscle tissue. And what they do is they modulate the action of stem cells. Stem cells are the cells that don't really have an identity yet, but they lead to progenitor cells that lead to some kind of tissue cell. So in this case, they would become muscle progenitor cells that would then become new muscle cells and repair and damage the the tissue there. Does that make sense? Yeah. And they and these kinds of of um stem cells are found all over. They're found in our bone marrow. They're found in our

20:38muscles. They're found in our hair follicles. And that's actually the other thing that I wanted to highlight that's kind of cool is another um this was pretty recent. Another way that these T- cell T-regs are are doing stuff that's outside of the immune system is they become on-site repair formin for like stem cells in our hair follicles. So they they promote hair growth in our hair follicles by actually influencing the stem cells that are in there that are called hair follicle stem cells. And those stem cells promote the growth of hair in those hair follicles. Right? So without the T-regs actually like

21:18mediating that interaction, you're not going to get >> hair growth. >> Hair growth in those hair follicles. >> So we can thank the cellular military police for our wonderful lock. >> Yeah. do a bunch of side jobs too, right? Where where they're like just maintaining >> a lot of the tissue resident stem cells for doing whatever job that they're doing. >> So they get deployed into uh local cities across your body to maintain order. >> Yeah, there it is. There it is. Don't listen let's not let's not get too triggering. Um but in this was um this was work that was done by UC Santa San Francisco and this was a paper in cell in 2023 that um showed that T-Rex can

22:01actually help hair follicle regeneration. They use something called the notch signaling pathway which is just another it's it's it's one of these other lock and key methods >> signaling pathways where the T- cell locks and keys into a stem cell and then the stem cell is like oh okay I need to start doing whatever I need to do. This is fascinating. So not only the Nobel discovery was around the like the existence of this specific TE-C cell type and its genomic origins >> and then now since those early discoveries we've now begun to understand that >> these regulatory tea cells these T-regs >> have multiple functions

22:42>> uh they're not just in the the highway of the bloodstream >> they can be in the tissue cells and actually facilitate other aspect other processes that are independent of the immune response which is its primary responsibility. >> Exactly. Yeah. And that's how they were discovered. But now it turns out they've got a much larger role in our body. Right. So it's it really shows why something like that deserves the Nobel Prize. Like discovering this whole new class that is actually doing so much more >> than just um an autoimmune response >> sort of yeah like curtailing the autoimmune response. Now it's doing all sorts of stuff. The other thing that's interesting and this goes back to kind of what you always talk about with biology as compared to physics where it's like that here like there's a lot of complexity still that we are

23:22continuing to better understand >> uh in terms of biological systems. >> Yeah. >> Um and there's complexity there. >> There's complexity at every level. It's insane. biology is is somehow this like hodge podge stack of cards that is just like staying alive cuz everyone is is making sure the cards don't you know >> fall right at every level >> at the molecular level at the cellular level at the organism level then you can go into like ecosystems and there's population dynamics it's it's an incredible like hierarchy of of being >> it's very cool >> the combinatorial problem set there

24:04is >> one to behold. >> And and so that was again the the medicine >> Nobel from last week. If you haven't watched last week's episodes, we have both individual stories for each of the individual awards as well as a collective episode with all of them. So you can zoom in to the subject you care about or zoom out and listen to them all. They're all fascinating. Um and then so day two, which was Tuesday, >> was was physics. Mhm. >> Uh this one was for macroscopic quantum tunneling. >> Yep. >> I I will note uh you know there was some commentary about the use of the word macroscopic. >> Yeah. >> And understandably in this context

24:45>> it is macroscopic but in our everyday lived life. When we say macroscopic we don't mean laptop macroscopic. >> Um it's still quite quite small. >> This thing is still quite small. Yes. But it's still at the nano micro scale. >> But it's still meaningfully different than where we were before. >> Yeah. It's still 10^ the 9, you know, 1 billion things quantum tunneling. That's not a joke, right? Um it was given to John Clark, uh Michelle Dev Ray and John Martinez for their discovery of macroscopic quantum tunneling. It was a experiment that they had done in the 1980s at Berkeley. John Clark was the principal investigator at Berkeley. Uh Michelle Devy was a posttock in his lab and John Martinez was a PhD student in

25:27his lab. I will be remiss to say we also call it Cal on this podcast. >> Yeah. But guys Berkeley is fine but for the sake of the international audience we will refer to it as Berkeley. >> Yeah. Yeah. We I mean in I think in science I've almost never heard it called Cal. Okay. I'm sorry. I've been around circles in in science. >> It's called Berkeley. Okay. >> Go Bears in athletics. Cal in science we you know we'll stay with >> I don't think anyone from Berkeley is pressed about it honestly. Okay. Anyways >> let us know in the comments. >> Yeah let us know. Um, and in any case, like what they did was they showed that you could build and customize this kind

26:08of artificial atom in some sense, right? That that even though it was 10 to the 9 different things that were doing this quantum tunneling, all of them collectively are obeying the Schroinger equation. And so one could use this as a substrate to simulate things that do quantum mechanics, for example, atoms. And this is the central idea behind a quantum computer, right? It was actually first hypothesized by Richard Fineman, one of our favorite physicists in a 1981 talk. The talk became a 1982 paper in the International Journal of theoretical Physics. And the the paper was titled Simulating Physics um with quantum

26:49systems right? It's an incredible paper that's so forwardinking and it's something very much in the style of Fineman. He he builds it from first principles and he asks like okay what if I want to um simulate a quantum system >> right >> okay what would that take and here's the math that he does he says suppose I have an interacting system of n quantum particles okay and I want to simulate all of that can I do this with a classical computer pretty soon it gets way way out of hand okay and here's why consider are just two

27:29quantum particles that can be in two states. Okay? Um they can be in a zero or a one, right? In a classical computer, well, you would just have one thing be the first state and one thing be the second state. And then you can decide whether it's a zero or a one and you have four bits, right? But you can just keep track of each of the bits and as you grow the number of bits like it just grows linearly in terms of how much stuff you need to you need to save. You need to store n bits that's n different transistors that are storing a zero or one. If you want to start doing quantum systems now combinatorically it goes insane right because just let's imagine

28:12two quantum systems right like two electrons that are spin up or spin down you actually have to keep track of four different complex numbers okay each complex number is actually two numbers one how much how much of the how much of the number is on the real axis how much of the number is on the imaginary axis and what you have to do is you have to keep track of the spin up spin down. You have to keep track of the spin down, spin down, and then spin up, spin down, spin down, spin up. Right? That's four different complex numbers that you got to keep track of. So that's eight different things. With three, now I got to keep track of all eight of these spin >> systems, right? And with n, it becomes 2 to the n. two to the n different numbers

28:54that I got to keep track of to really fully characterize a quantum system because each of these each of these individual spin states are themselves distinct. And so I need a number for each of these distinct spin states. And so pretty much what ends up happening is if you if you scale with the number of bits, the amount of stuff that you can store in a classical computer becomes linear, but the amount of stuff you can store in a quantum computer be becomes exponential. Right? because a quantum computer by design is storing all of the little values for each of the superposition of these states. So it was a very simple simple argument that Fineman made and he did this back of the envelope calculation. He's like, well,

29:35if you need two to the n numbers to keep track of a quantum state that has n things, each of those things having two states, then you know, with um if you want just like 40 interacting particles with two states, that's 2 to the 40. And one real quick trick to convert 2 to the something into 10 something is to know that 2 10 is 1024, which is about 10 3. So 2 becomes about 10 12. That's a trillion. That's a trillion bits that you need in your RAM, >> not in your hard disk. You need in your RAM because you're >> you're messing with all of those numbers, right? In a >> in terms of computation. This isn't data

30:17that's being stored on a permanent basis. This is stuff in the middle of your computation that you're using to then calculate the new state and the new state and the new state. So that's a that's a terabyte of stuff in your RAM, >> right? Which is already a lot. A terabyte of RAM is is is quite a I wish I had a terabyte of RAM on the computer we have to render the stuff. Yeah. Yeah. It would be it would take that that's that's reaching at the level of like supercomputers, right? But 40 different things is not really what we're even talking about. We're trying to do like 200 200 or 400 cubits, right? Because in in mo like for a protein for example, a pro a protein will have like on the order of 100 to 400 atoms that many interacting quantum states, right? For

30:57each of the little configurations that the electrons can do. And already at like 2 to the 200 you're getting to 10 the 66. >> That's an insane number >> which is which is an insane number because there's only about 10 the 80 atoms in the universe right so like what each atom in your universe is now you know like you can't make transistors. >> Yeah it's not feasible. >> Yeah it's not feasible anymore. So that was the main impetus and it was sort of introduced by Fineman in in the 1980s to start thinking about what if what if we wanted to do quantum simulations. We would really need a quantum computer in order to do it. >> Classical systems don't have basically the the horsepower the to be able to

31:40sustain as you get to more complex >> Yeah. >> systems. >> Exactly. And so we need we need a computer that's made out of quantum bits, right? And this is where these superconducting circuits that won the Nobel Prize, they sort of became a leading platform because the the superconducting circuit itself can now have these quantum behaviors. And so you can use that as your two-state system that encodes a zero and a one. And that's what sort of I want to get into is just a little bit of background. We can't cover all of it because that's going to be an episode in itself that maybe we can do. But I just wanted to give you a little bit of uh uh a starter on why um superconducting cubits became

32:21like this sort of ubiquitous method of making a quantum computer. >> And this is the Josephson's junction circuit. >> Yeah. Yeah. This is this Yeah. This is exactly the the Josephson junction stuff that we talked about on the episode that became a cubit in itself. So a good primer if you haven't already watched our Nobel Prize episode on physics would be to watch that because we go into very good detail from first principles about like what is >> yeah a Joseph junction uh which is important to understand like >> why this fundamentally is a workable solution to the problem. >> Exactly. Yeah. Yeah. But we'll we'll give you a tiny primer here. Um we'll start with just an LC circuit. Okay. An

33:01LC circuit is something that I think anyone who's taken an undergrad physics class, the second semester you go into AC circuits, um, which is analog circuits. And an LC circuit is very simple. There's a capacitor and there's an inductor. A capacitor is a is a configuration of metals basically that lets you store charge. And an inductor is like a coil of stuff that lets you create magnetic fields and you can charge it up and you can decharge the magnetic field. it becomes um a little battery in some sense. Okay? And if you hook up a capacitor to an inductor and you charge up the capacitor and then you turn on the switch, what's going to end

33:43up happening is the the the capacitor is going to discharge because it's storing a bunch of charge, but then the circuit is going to be like, "Oh, there's a way for me to for me for the charge to rebalance." As it as it rebalances, that's going to create a current in my loop. That current is going to turn on and then create a a a magnetic field in my inductor which is going to become like a kind of battery that's going to reverse the circuit and the circuit is going to go the other way and then it's going to go one way and then it's going to go the other way and this charging and discharging of the capacitor and the charging and discharging of the inductor becomes a sort of simple harmonic oscillator. This is ubiquitous in physics. We love simple harmonic oscillators. Okay? Because everything is

34:24a pendulum in some sense, right? everything is around some energy minima and you and it oscillates as it goes from one part to the other part of that energy minima and that's what an LC circuit becomes. It becomes a simple harmonic oscillator. Now you take anything at the classical level in this case an LC circuit which is a simple harmonic oscillator and you cool it down. First of all, this circuit is going to become superconducting, meaning that there's going to be no resistance, which means this guy, this circuit is just going to keep going. There's no jewel heating involved. And so, it's not going to lose any energy. So, this thing can keep going as an oscillation, right? And

35:07um in anyone who's taken first semester um quantum mechanics usually goes through the Griffith's quantum mechanics test textbook. And this is the cartoon they have. They show Schroinger's cat going up and down a ladder. And all the ladders, the rungs of the ladders are equally spaced. And what this guy is doing is going up and down the energy states of a quantum harmonic oscillator. In a classical harmonic oscillator, you can um in a classical harmonic oscillator, my pendulum can be in any state, right? It can go up and and if I push the pendulum more, it'll have a higher amplitude. This is like you want to swing, right? You can have arbitrarily low amount of energy. You can just sit on the swing stationary with no swinging

35:49or you can have a little bit. If you push a little bit more, you can have a little bit more. Um, in a quantum harmonic oscillator though, quantum mechanics takes over and there are discrete energy levels where the quantum harmonic oscillator will have a certain frequency or it'll have a little bit more frequency or it'll have a little bit more frequency and each of those frequencies of oscillation is tied to a energy just by har omega. Right? And the key with a with a quantum harmonic oscillator is the rungs of that ladder are equally spaced. >> Mhm. Now, this is cool for a quantum harmonic oscillator. It becomes a problem if we want to make a quantum computer out of it >> because what we want are just two

36:30states. And we want to be able to reliably go between one state and the other. But imagine if the energy difference between 0 and one is the same as the energy difference between one and two. When I'm poking it and this thing is at the one, it could go to two. We don't want that. We want it to be >> fixed within 0 and one. >> And so what we do is we add a Josephson junction to our superconducting circuit. And what that does is so on the left we've got a perfect parabola. That's our omega omega x squ which is a perfect parabola. That's our simple harmonic oscillator. Okay. That's like hooks law you know um a spring and a mass on a

37:12spring. The energy of that thing is 1/2 kx^ squ. Similarly, if you have a parabola, then you get a perfect pendulum. That's what we don't want. So, when we add a Josephson's junction to our LC circuit, then what ends up happening is you add a cosine term >> Mhm. >> to that parabola. And that cosine is very much like a parabola on in the bottom, right? If you if you zoom in close to its minima, it's going to be like a parabola, but it's going to add a little bit of wiggle on the outside. And that's what's called an anharmonicity, which means we've gone from a harmonic simple harmonic oscillator to a anharmonic oscillator that has a tiny bit of a difference in that parabola.

37:54And what that does is now our ladders, it's still a it's still a ladder, but the rungs of the ladder are no longer equally spaced in energy. And so what I can do is now tune my poking, >> right? so that it only um resonates to that 01 transition and it doesn't resonate with anything else. And so I can reliably now control whether it's in a zero and a one and I can switch it from a zero to a one. And that's where this Josephson's injunction comes in. Okay, it adds that little cosine magic that turns my perfect quantum harmonic oscillator into into something that I can manage as a two-state system >> which is which is required in order to make a quantum computer operate in the

38:36way in which we needed to to get like tangible like to have it operational. >> Yeah, we want a two-state system at all times for a quantum we want to I mean we like bits, >> right? And um and a lot of the simplest logic you can do is with a bit a two-state system. Um this was first actually implemented at Tokyo by um Nakamura and his colleagues in a nature paper in 1999. And that's what sort of started the field of superconducting cubits and it's come a long way right and now um one of the one of the papers that I wanted to highlight was the big paper in 2019 by the Google team um John Martinez was um involved in the hardware leadership and they published in nature

39:19in October 2019 with an experiment titled quantum supremacy using a programmable superconducting processor. This was a very big deal. They're claiming quantum supremacy. Quantum supremacy is the idea that we have done something now with a quantum computer that cannot be done with a classical computer no matter how long you wait. >> Okay. Not no matter how long they said something like um the age of the like a million years. Okay. Something crazy. And they were like we did this in 200 seconds. That would have taken a million years to do. The point is in a classical system it would be so far beyond the

40:00life cycle of of humans that it's irrelevant they could do it in a million years. >> Yeah. Yeah. It's like it it's something that we could not do. >> Okay. Um now what they did was they designed a random quantum circuit sampling task. And this is where their claim met some scrutiny. Okay? because the task that they're saying they did that a classical computer couldn't do was itself a quantum task in some sense. So, so you're maybe you're gearing the problem for the hardware that you have and that's not completely out of precedent but you can understand if their competitors were like you know

40:40doesn't count. >> Yeah. Yeah. it doesn't count. But in any case, they said that this is a like you know the the the burden of proof is I've done something that a classical computer can't do. Right. Quantum simulation is another thing that Fineman came up with that is obviously by design something a classical computer can't do. Yes. >> Right. So it's not it's not that like weird for me. >> Um they've got a 53 cubit computer. Okay. 54 physical physical cubits. that's um in a in a sort of nice chess board pattern. Each of the cubits talks to four of its neighbors using a a coupler and it's all in a 2D grid. Their

41:23chip was called the Syncamore chip. It's 54 physical cubits. Tiny tiny chip that's inside of a giant dilution refrigerator like those chandelier stuffs that we were talking about. It's got to be cooled down to where these things can be superconducting and they can do all of those things. And their claim was that this quantum device could sample i.e. it could like produce these bitst strings from a quantum distribution from a probability distribution that was inherently quantum and in 200 seconds they could produce enough bitst strings to totally characterize this probability distribution. Okay. And they estimated that a classical supercomput like this

42:03is a big supercomputer would require 10,000 years to do the same. Okay. And they did some cross entropy benchmarking to show like for smaller number of cubits that this would work and how that thing would scale. Okay. And so that was their main thing. They were like look we did this in 200 seconds. This would require 10,000 years on a supercomput a million years on a normal computer like blah blah blah. Okay. um it's it's sort of outperforming these classical algorithms, right? IBM claps back because IBM is the other big um competitor in the field of superconducting circuits. So shortly after the Google announcement, they published this blog post that um you

42:46know eh it's not it's not it's not that hard. Their their first thing was like 10,000 years. We we and they they they made a better classical simulation. They they outlined a better way to do that classical simulation that would take 2.5 days, not 10,000 years. >> So they kind of they kind of undercut they were like, well, >> yeah. Yeah. It's like it's like, well, you didn't use the latest sort of classical algorithm to benchmark how good your quantum computer was. you know, 2.5 days is still not 200 seconds, which is what Google did, right? But it's not also not 10,000 years. So, they were saying, you know, you shouldn't say quantum supremacy, you should say quantum advantage at this point. Yeah. It's like they're I mean, they're

43:27they're pressed because like this is a big deal still, right? And and if you think about just also just economically from the business context, IBM has been struggling >> uh to survive both uh in chips uh in in its in its clientele base in terms of being dominated. They are being pressed by Google, by Nvidia, by AMD in all avenues of their business. So just from a period, >> they made a big push in the quantum >> place you know >> and so they had to say something. >> Yeah, they had to. Yeah. And I mean the the other things that they did talk about is like the the paper itself is quite self agrandizing like the 2019 paper in nature says quantum processors

44:07have thus reached the reg regime of quantum supremacy. We expect that their computational power will continue to grow at a double exponential rate. I mean that's that's you know that's that's a lot that's saying a lot that maybe you shouldn't say in a scientific paper and maybe the press should say that right but so there's there's still ongoing scrutiny. There's some papers that say that they've improved the quantum the classical simulation algorithms to increase that to decrease that gap even further. Um there's philosophical critiques about like well should should we really say supremacy and all this other kind of stuff. So it's still an ongoing debate and meanwhile the the

44:49field of quantum computing just like forges forward you know with these superconducting circuits. It's going to be very exciting. I think the the implications of you know stepping back from some of the corporate intrigence the the implications are that we now have computing systems that have a capability set to simulate massively complex concepts environments um at a degree that we don't have the capability for in classical systems >> and there are a variety of use cases that you can imagine a lot of times people talk about, oh, it's going to break encryption because you can just, you know, brute force hack blah blah.

45:29That's like the lowhanging fruit of implications, but you can imagine, >> you know, simulating biological systems. >> That's what I'm most excited about, right? It's like it the the breaking encryption is like fine, I guess, from a national security point of view or whatever. But for me, it's like doing quantum simulation, the the dream that Fineman had originally, right, of like now imagine you you've got a new idea for a material. It's incredibly hard to simulate the physics of a material now because of this problem of exponential blowup. Well, now what if we could just you know put in we know where the positions of all the electrons are. We can create this molecular Hamiltonian that tells you how the physics of that molecule is

46:11going to work and then we put that into a computer and we try to see things like okay what is the what is the base energy? What is the conductivity of this thing? Imagine finding a room temperature superconductor by just hypothesizing all of the different materials that it could be, putting it into the quantum computer and having it tell us, hey, is this thing superconducting or not? >> There's huge implications in material science, in drug discovery, >> um in personalized healthcare med like you can it's it's hard to like make a list. >> Yeah. >> You know, it is it is as fundamental as you know, vacuum tubes giving us computing for the first time. It's as fundamental as the move to mobile, as the internet. It just in terms of you can only

46:53it's hard to even imagine >> Yeah. all the things that we can do we could do with it. Um because it's it's a sort of an infinite canvas of opportunity. Um it's I always find the quantum space so fascinating. >> Yeah. And then um I guess the last one we did was chemistry. >> Yes. The last follow-up was for for chemistry. This was on uh metal organic frameworks and the you know it was our third day >> of waking up at 2:30 in the morning >> but it was equally as interesting >> uh and it was one that I had the least amount of basis >> for understanding. I think someone made an interesting comment that was like chemistry never gets the love that it deserves for how like important and

47:35crazy the stuff we do in it is. So we're making sure that uh shout out to all the chemists out there that chemistry gets most important sort of Nobel prizes have come in chemistry. >> Chemistry, right? >> We're we're going to make sure you guys get your just desserts here. And so, yes. So, chemistry was our our last uh uh prize that we covered last week. >> Yes. This was for metal organic frameworks. It was given to um Susum Kitagawa at Kyoto, Richard Robson at Melbourne, and Omar Yagi at Berkeley. Omar Yagi is someone that I called. >> Yes. >> I I totally predicted that. >> And next year, we're going to do a a more a more crazy prediction show. We're going to try to get uh some some partnerships with uh I don't know, maybe we'll do uh what is it uh Poly Market

48:15and maybe we'll get uh Kalshi uh one of the prediction markets out there. >> Yeah, that'll be hilarious. Um but Omar Yagi specifically, we're going to focus on some of his follow-ups. Um he made5, which was the really big deal, metal organic framework, right? This thing had a single gram, had several football fields worth of surface area. And we got a lot of questions in the comments actually about like what does that even mean for a molecule to have surface area? And this was something that I sort of had an idea what they were talking about, but I wanted to dig deeper. So, you know, my my initial inclination was

48:55that they're basically talking about how much area is available for interactions at a molecular level, right? Um, when we think about absorption of molecules, this is a 2D surface interacting with molecules and absorbing it and making it stick, right? instead of absorption with a B which is a 3D way of absorbing molecules. So at a 2D level, how much surface area is available for interaction with other chemistry? That's the idea. And the analogy you can use is like a parking garage, right? It's a single building, but it has an insane amount of surface area. It's packing

49:37like five or six parking lots into a single 3D structure. And so you can park a bunch of cars there, right? And in this case, we're calculating the surface area. We're using how much surface area is available available for parking other chemical stuff. Okay. One of the ways that they do this to calculate the actual surface area is by using liquid nitrogen and nitrogen gas absorption. So here what they do is they they they take your sample and they and they cool it down with liquid nitrogen so that it's super cold and then they run nitrogen gas over it and they see how much nitrogen gas is gone from the sample and

50:18gone into the sample. And from that you get this curve where on the x-axis you vary the amount of nitrogen that you're putting in that you're exposing that maf to and on the y-axis you get okay how much nitrogen gas volume-wise was absorbed by this by this compound and then you can fit something called the browner emtt teller equation the bet equation which then calculates how much volume has been absorbed to create a monollayer a single layer of of N2 on this thing right >> which would it be the equivalent of a single level of the parking garage. >> Yeah, exactly. It's like a single It's the amount of stuff. Exactly. And then and then the more pressure you put in,

50:58the more molecules are going to get absorbed. And then from this, you can figure out, okay, what is the constant amount of surface area that is needed to show this dynamics of how much is being absor absorbed. And that's where you get in get get this, you know, 3,000 square meters per gram per gram, >> like several football fields per gram is because the amount of stuff that this one g of thing is absorbing, the amount of nitrogen that this thing is absorbing would be equivalent of if I had a football field of nitrogen absorbing area and that's how much nitrogen was absorbed. And and so part of the idea here is like, you know, we've maxim

51:41we've m we've engineered the space of the parking garage to be maximally efficient for the number of cars that can park >> at any given level at any given time. So you can imagine a parking garage with double wide spaces. >> Yeah. And we've created the minimal amount of space for any individual molecule car to be able to park to maximize the amount of cars that can be parked at each level. >> Yeah, exactly. And sometimes maybe you do want the double wide spaces. So then there's that do that only work for larger, >> right? >> Like for CO2, right? CO2 is slightly larger than N2, but you want to absorb that and not the N2. So then there's

52:21other ways of doing it. Exactly. It's tunable. The the the space of the parking garage is tunable. It's it's very cool. And the other question that we were getting a lot and this is something that I was also interested in is, you know, how do you make these things in a lab, >> right? >> How how do how do you make these things? And I was briefly in um a chemistry lab at UCLA when I was doing rotations um from one lab to the other to figure out what I want to do my PhD physics in. This was a lab that um was actively doing cryeleron microscopy to find um you know the structures of giant proteins. And in that my adviser at the

53:01time um she said you know chemistry is a lot like cooking okay in that there's only there's there's a few techniques that you have and you have to be extremely good at figuring out which techniques you want to do and the order in which you want to put them in order to actually make your chemistry happen. But it is really like cooking because you've got standard tools, right? You've got heat. You can heat up stuff. You can cool down stuff. Um, you can mix stuff together and you can stir stuff together. Every once in a while you have like fancy techniques like if you want to do creme brulee or whatever that thing is with like a blowtorrch, right? And you're like, you know, every once in a while or like you want to electrically shock stuff for some reason. Um, but

53:43most of most of it is basically mixing, heating, letting it sit, all of the techniques that we use in the kitchen to make a really good meal, right? And that's what's happening in chemistry like in the lab. That's that's what you have. And so MOFS are created by this process called solvothermal synthesis. Okay? Effectively, what you're doing is you're mixing together metal salts. think like n uh zinc nitrate um you've got copper um zirconium and and and chlorine together. You mix that in with your organic linker which is the linker between the things that makes that cube happen and these can be like caroxilates organic organic molecules. You've got

54:26some kind of solvent usually that's DMF which is dimethyl form formide. This is pretty toxic um solvent. You can also now there's techniques that are using ethanol or water and then what you do is you mix them up you heat them in a sealed vessel for at you know 250° C. You can heat them up for hours to days in these vessels that are like teflon lined autoclaves. Autoclaves are like ways to to make high pressure high temperature reactions happen and then you can cool them slowly. The idea is to cool them very slowly so that that promotes the crystalline growth. Right? As you cool the the chemicals are now going to start

55:07forming in this energetically favorable way where the organic linkers are going to find the metal and then the metal are going to find more organic linkers and you're going to grow this MOF out of a out of a tiny seedling of stuff. It it's the mix has the prerequisites such that when you apply heat and then apply cooling, the end result is what is planned for based on the amount of heat applied, the period of time the heat is applied, the amount of cooling that's applied, the period of time that the cooling is applied. So, it's going to fall into place >> um based on just the mix, how it's mixed, the the proportions of each component part and that sort of healing heating and cooling cycle. >> Exactly. And that that's why I'm telling you it's like a lot like cooking, right?

55:49Because like if the bread is like underproved, if if people watch the great baking show, which which I love. Um you know, if the bread is underproved or overproved, it becomes like stodgy and and whatever. And you know, so so everything has to go perfect for all of this to happen, right? And and so it really is like a a cooking thing. And after all of that's done, now you've got these crystals. And what you have to do is now wash out the solvent. And then you have a naked mof, right? And you get these crystals which they kind of look like this under the microscope. They're tiny tiny amounts, you know, grams at a time. The the real challenge now is scaling this

56:29thing industrially. >> I I remember one comment saying like, well, can you produce it in at industrial scale? >> Yeah. Yeah. And it's it's difficult. There's a lot of difficulty here. First of all, the DMF, which is a common solvent that's used, this thing is toxic and it's expensive. So we'd rather use stuff like ethanol or water. The yield is pretty small. We're getting like, you know, grams of stuff at a time. And if you scale up, then you can imagine the crystals are less good because the environment is not completely uniform. The bigger the vessel, there's going to have you're going to have like edge effects, right? Where the edge temperature is different from the central temperature. The pressures are different. Um, you know, and removing that solvent is pretty hard at larger and larger scales

57:11because what you have to do is basically vacuum pump all of that stuff out. And, you know, producing a big enough vacuum pump for the for industrial scale is pretty hard. I did find a company, there's several companies, but there's one company I wanted to highlight, Novaf. They're a company out of Switzerland. We're not sponsored by them or anything, okay? But it's it's a cool company that I found. They they made 300 kg of their NOFF and that 300 kg has 240 km squared of surface area which is like the size of cities, >> right? >> And they're using this for carbon capture in factories, right? But they they've they've they on their website they talk about the challenges that comes with trying to scale these up at

57:52industrial level and some of the techniques that they're using to go through and and actually mitigate those those things. So what's interesting is the the the concept of metal or like like most of the Nobels the discoveries have been made quite some time ago. >> Yeah. >> And you know with uh metal organic frameworks we're at a place now where they've been experimentally proven. There's a variety of different methodologies that have kind of been identified. >> Yeah. There's been the also the the rule book on how to make stuff, right? The cookbook is now pretty well established. And so now the challenge is is going from making a meal for me, you >> the spouses >> to like McDonald's

58:33>> to McDonald's. >> How do you how do you make this man, you know, enterprise industrial grade volume, size, scale, uh which again is non-trivial but is is the tail end of this sort of fundamental research to end consumer product cycle. >> Yeah. Exactly. Exactly. Um and it really shows how science benefits us as a society, right? It's like the process is always fundamental science needs to happen first to show the base case. It's possible and it's worth it. Once you have that then you go into okay how do I industrial scale this thing? How do I make it better? How do I

59:14make it cheaper? Blah blah blah blah blah. You know this is an important context in understanding like how the public and private sector work in terms of innovation. A lot of times, especially in the modern tech era, innovation is framed as the private sector is the only location in which innovation can arise because in the public sector there's too much bureaucracy and all this other stuff. And the the challenge with that viewpoint is so much of the innovation, big eye innovation that gets talked about >> has a basis that was publicly funded for fundamental research that dictates it. There are some exceptions to this rule where the private sector will look at an area and it'll usually it'll be a

59:56founder company where the founder has super voting shares to be able to dictate what happens and it doesn't matter and they have a conviction about something and then they'll go and do that fundamental research. they'll acquire all we've seen this particularly for example in AI which again is still based on decades of fundamental >> research every every even every private company that is doing this fundamental research they're standing on the shoulders of giants right and those giants are always funded by public institutions and by our taxpayer dollars >> because there's not a profit incentive no for the private sector to do fundamental research where they can't tie it to quarterly earning or

1:00:38shareholder value in a time cycle that is reasonable for the sort of stock market system that we have today. >> If we look at AI, right? Like John Hopfield in the 1980s working on neural networks was NSF funded. Everybody thought he was just like doing some weird bioysics like stuff. Okay. Like you made you made an ing model out of the brain. Cool. And then you know Jeffrey Hinton saying that guys um neural networks are the future and everybody else was going for the algorithmic AI. He's the one who was like no let's just make it bigger and bigger and with back prop it's going to work. No one believed him but he got funding because some people were like it

1:01:19might work let's let's give him some funding for it. And now we have all of AI, right? The the the PhD students of Jeffrey Hinton that went and started open AI and all this stuff, they were supported by grants >> from taxpayer dollars. >> And now it's a multi-t trillion dollar global industry. That is >> Neurolink. The PhD students that started Neurolink were supported by grants from the American government >> 100%. >> Right. like there's no there's no world where this isn't happening because of funding from our taxpayer dollars. And this is one thing that I really feel really strongly about is like when I pay taxes, I want it to go for this kind of stuff. One of the things that has

1:02:00created this strategic advantage for the US where we have been a dominant global power driven not only by our military but by our technology. Both of which Mhm. >> are fundamentally where they are because of our investment in fundamental science research. >> We would not have dominance in air and sea with the Navy and the Air Force. We would not have dominance where all of the biggest technology companies on the planet >> Yeah. are here >> are here. We would not have that without um >> the early investments in these arenas that were perceived as not being commercially viable at the time.

1:02:40>> Yeah. Yeah. Yeah. Exactly. It's like it doesn't make any sense to me because this used to be this used to be a bipartisan thing. >> That's what's so interesting. >> This used to be a very bipartisan thing. We're going to be the best when it comes to science. Okay. George Bush funded um the NASA's re going to Mars and stuff like that. Um there's so many so many things that have happened now especially with the current administration that is just like totally totally bankrupting us when it comes to our supremacy in in in the sciences. And it's really really rather unfortunate. >> And we have sort of photo seven here which is um

1:03:22>> you know we're leading in Nobel prizes. >> Yeah. Our universities are at the top. >> But the current administration is just running scientists out of our country >> which is like another problem which is like if you look at the Nobel prizes from the US >> Yeah. >> even this year >> and who and who they are. >> Yeah. >> And how they got to be Americans. >> Yeah. Omar Yagi he was um an immigrant from Jordan. Palestinian refugee came in, embraced this country, was supported by the DOE, was supported by the NSF, did an NSF posttock fellowship at Harvard. And the NSF posttock fellowship is now completely gutted. The NSF posttock fellowship used to be this

1:04:03thing that would take graduate students that were stars and put them at these top institutions to do posttock research and gear them up for becoming top faculty members at our leading institutions. And now that thing is gutted. You know what's funny is the only reason that I am able to be in the US is you know my dad did his posttock at Harvard and was funded >> he not only got in through a newly created visa program that was specific to Zimbabwe >> okay >> right and it was the first round and he won the lottery the first round he similarly got to be able to do that's how he got to McGill where he did grad school and then he got to do the Harvard posttock because of a similarly

1:04:44>> uh federally funded grant program around posttock research. Um and like you know he's been in science and nature published multiple times has multiple patents that are acrewing value to yeah >> multiple American companies. You know he's been a director of biology at a biotech that's sold for >> millions of dollars and like all of that value creation is because of these systems that existed. >> Yeah. I mean same for my dad. My dad came on a um N I think it was the NOA fellowship or an NSF fellowship. We first came to Huntsville, Alabama from India. We stayed there for 2 years. He was working at the Marshall Space Flight Center for NASA and then he got a tenure

1:05:24track position here in LA and that's how he moved here. But even throughout his position as a professor here in LA, he's gotten funding from the NSF and now all of that is going down. It's just really really quite insane to me that this is happening at a countrywide scale. And it's not something that I think we should take lightly because, you know, Germany I I I hate to bring up Germany as an example, but it really is such a great example because before the 1920s and 1930s, Germany won almost every Nobel Prize in chemistry, in biology, and and then afterwards, they haven't won a lot. It took them a while to crawl

1:06:05back and we're seeing that happening with American institutions. The UC system has a hiring freeze, >> right? >> Um JPL has let go of 500 of their staff, >> right? And that's just right around the corner from us here. >> I mean, it's just it's just nuts, dude. Like, it it's going to take us I I fear that it's going to take us decades to to come back from this. And I think I think you know we should really be thinking about this as as a nation about like what is important to us. Like if American exceptionalism is important to us, which it should be, it's certainly important to me. Like you know, I got my American citizenship and I love the fact

1:06:47that America is exceptional at a lot of things, right? And it's perhaps more so than any other profession, I think scientists understand what that means. >> Yep. >> To have American exceptionalism, right? We have the greatest research infrastructure in the world and we shouldn't be so casually letting that go. >> 100 100%. I mean, and it it's one of those things that takes a long time to see transpire and it's why ringing the alarm sooner rather than later matters because the Nobel prizes that went out last week were for discoveries from decades ago. >> And so there's like an inertia, >> right, to seeing it show up in the

1:07:28system. Yeah. Yeah. >> And so just >> Yeah. We don't want to be in the 2050s now and then all the Nobel prizes are being won by countries outside of the US. There's several stories of scientists now leaving the US because of what's happening, right? Other countries are salivating >> at the opportunity >> at the opportunity to just poach all of our scientists. And this is happening now in real time. This is something that needs to stop. >> It's it's this is an important subject we have covered before. >> Yeah. But I really Yeah, I think the the recent Nobel prizes like really made me think about it, right? Because you know, Omar, like we're also doing this whole anti-immigration thing, which I totally

1:08:08get, right? Like with the illegal immigration and all that. Like there's there's arguments to be made there, but I'm I think both sides of the aisle should agree that curating exceptional international talent is something that America should be doing. It's what we've been doing for hundreds of years. >> Yeah. And it we've done it through multiple world wars. >> Yeah. We've done it since the 1800s. Andrew Carnegie was a was a immigrant and look what he did for our nation, right? All Albert Einstein was an immigrant. Enrico Farmy was an immigrant. Like, oh, come on, guys. Tesla was an immigrant. If you look at most of the top uh companies in the S&P 500 um if you

1:08:52look at fang most of these you know Facebook, Amazon, Netflix, Google etc etc the Nvidia the biggest companies that the US has right now the majority of them are founded >> by immigrants. >> Yeah. Yeah. And I mean even this year's Nobel prizes, right? Four out of the six Americans are immigrants. You've got actually no sorry three out of the six. John Clark, he's an immigrant from the UK, did his PhD at Cambridge and then came here to Berkeley. Michelle Deere did his PhD at Paris Sud came here to Berkeley. We've got Omar Yagi obviously um from Jordan came here. So

1:09:35it's worked guys. Even if you look at our math olympiad team. >> Yeah. >> It's uh I think it's 100% Chinese. >> Yeah. No, there's there's an Indian guy and there's an American guy. There's a US guy, like a white guy. That's fair. >> Yeah. But I mean, I love that, dude. >> Like I love the fact that like >> our country curates talent from all over the world and we just we just create the A team. Yes. >> Right. >> Yes. >> I I absolutely love that >> and we should continue to do so. Yeah. >> Um so >> we're getting the plus ones, right? It's our scoreboard, >> right? 100 100%. Uh this is this is an important issue. Uh we need to continue to fund fundamental science in the United States. Uh we need to continue to bring the best and brightest from the

1:10:15world here >> to continue to facilitate the life and the lifestyle that we have facilitated and also give the gift of what we create to the rest of the world. Uh we have the infrastructure to do so. We have the sort of cultural dynamics to do so. irrationally confident >> uh and >> and it works >> and it works >> and it works. We are irrationally confident and we just do it and we just do it and we we and if it doesn't work we try again and we try again because we're so confident that it's going to work, you know, and that's how we get stuff like uh MOF5 that has a football field size

1:10:57surface area in a gram or everybody else was like what are you talking about? and he's like, "No, this thing literally has a football field in a >> It's been a really fascinating two weeks with the Nobel prizes." Um, we want to thank all of you who are listening, whether it's on >> YouTube, Spotify, Apple Podcast, Tik Tok, Instagram, X, Facebook. Um, you guys really are powering the show. Yeah. >> Um, continue to send over questions. Uh, we'll try to touch on them as much as possible. We may introduce a listener question section. >> Yeah, we might >> um in future episodes. Uh but this is uh

1:11:37this is one of the most important subjects to all of our lives. >> Uh our everyday lives, our family, our careers, and everything. And we're going to try to continue to do it justice by covering it from first principles. I am your host Lester Nar joined as always by my co-host and our resident PhD Krishna Chowdery. This is from first principles. We'll see y'all next week. [Music]