Endgame with Gita Wirjawan - Michael Levitt - The Interdisciplinarian Nobelist: AI Changes Science Forever

Episode Date: August 8, 2024

Nobel Laureate Michael Levitt delves into the transformative potential of AI and its role in evolving global knowledge. Professor Levitt shares his unique journey through the world of molecular biology, highlighting key moments of serendipity and the importance of multidisciplinary research. Additionally, he offers a detailed analysis of the COVID-19 pandemic, emphasizing socio-economic factors and the critical need for diversity in science. #Endgame #GitaWirjawan #MichaelLevitt About Luminary: Michael Levitt is a Nobel Laureate in Chemistry and a distinguished professor of structural biology at Stanford University. Renowned for pioneering work in computational biology and molecular dynamics, Levitt's groundbreaking research has reshaped our understanding of protein structures. His career is marked by serendipitous events and interdisciplinary collaborations, making him a leading figure in the scientific community. About the Host: Gita Wirjawan is an Indonesian entrepreneur, educator, and Honorary Professor of Politics and International Relations at the School of Politics and International Relations, University of Nottingham. He is also a visiting scholar at The Shorenstein Asia-Pacific Research Center (APARC) at Stanford University (2022—2024) and a fellow at Harvard Kennedy School's Belfer Center for Science and International Affairs. Episode Notes: https://sgpp.me/eps193notes Earn a Master of Public Policy degree and be Indonesia's future narrator. More info: [e-mail] https://admissions.sgpp.ac.id https://wa.me/628111522504 Visit and Subscribe:‪ @SGPPIndonesia‬ | @Endgame_Clips‬

Biological intelligence is not us. We did not create biology. And therefore, it's an alien form of intelligence from which we can learn a great deal. AI has just hacked the operating system of human civilization. So if you look at the lesson of evolution, the great strength where the future survival of humanity is that diversity.

My name is Michael Levitt. I'm a professor at Stanford Medical School in structural biology. biology was an association also in computer science. Professor Michael Levitt, recipient of the 2013 Nobel Prize in Chemistry. He was interdisciplinary before it was fancy to be interdisciplinary, and he was interdisciplinary because the work and the vision that he had required that he master disciplines, from physics to chemistry, to biology, to computer science. My natural tendency in life has always been to treat life as a buffet. Take what you like and don't complain about what you don't like.

And by that way, you can always find good everywhere. We don't know the future. However smart we think we are, we don't know the future. Just retain the curiosity of a five-year-old. And I think that if we can do that for young people, we will greatly improve the potential of the future. Hi, friends and fellows, welcome to this special series of conversations involving personalities coming from a number of campuses, including Stanford University. The purpose of the series is really to unleash thought-provoking ideas that I think would be of tremendous value to you. I want to thank you for your support so far, and welcome to the special series. Hi, today we're honored to have Professor Michael Levitt, who is a professor of structural biology at Stanford University.

And Michael is also a Nobel laureate. He won the Nobel Prize in Chemistry in 2013. Michael, thank you so much. Thank you so much for having me. It's a real pleasure to be here. Michael, you were born in Pretoria, grew up in South Africa, went over to the UK, and then went over to Israel, and now you're at Stanford.

You've been here since 1987. What made you? And how did you get curious about signs? What would it take to win a Nobel? Firstly, the very simple answer is good luck. And many, many people are deserving a Nobel Prize, and it depends on what they're interested in, what they want to focus on, and so on.

So I think becoming a Nobel laureate is an unpredictable process. On the other hand, and we can say more about this later, the consequences of becoming are much more deterministic. I think I was just a very curious kid, a mother who actually lived until 107. She passed away a year and a half ago who didn't have, she was forced to leave school young, but she had a brother who went to university in South Africa,

poor family so they couldn't afford to educate her. She was a third child and who did very, very well in science. And I think she felt that I was her firstborn, that educating me was really important. well, they never made me feel that way. And my childhood in South Africa was filled with being a kid. Right. And playing around and having friends

and probably being way more interested in girls and dancing and things like I at the age of 12 than I was in science. And then again, there were... I see that my whole life is full of unintended consequences of various effects. and something that really got me going was coming home at night when I was 15 at 4 a.m. having been playing snooker with my friends. My friends at school were always the least good students because they were most fun.

I did fine. I was not the best student in the class, but I was probably in the top five, but I didn't put a lot of effort into it. And my mother basically said, look, you know, firstly, I've been really worried because South Africa is a dangerous place. and you know you I didn't have a cell phone or anything you didn't let me know and I was staying up all time so clearly you aren't interested enough in school why don't you just skip school and I was now at this point two years before the end of school schooling in South Africa is actually a relatively low level it's way lower than the schooling in Britain so basically we were just coming up to the summer

holidays, which are winter here. And she basically said, look, you should skip, you should try to finalize your matriculation in the next three months and then go to university, and then we can see what you're going to do. And I kind of was intrigued by this. She put a lot of money, and she didn't have much money. She'd been recently divorced in private lessons. And the trouble was, is the matriculation isn't math and physics.

It's also English and Afrikaans and Latin. in history, subjects that I wasn't particularly good in. But I had the private lessons. I managed to pass, essentially passing the exam, which was like the backup exam for matriculation, most people took it before the summer. But if they failed, they had a second chance. She then got me accepted into Pretoria University, which was actually an Afrikaan-speaking university in Pretoria.

They wouldn't accept me at Fitz University because I was too young. Right. basically went there for a year. And then as a reward, she said, why don't you go and visit London? I'd never been out of the country, so I flew to London by myself, stayed with my uncle and aunt who were both very, very good scientists. And that's sort of, I decided not to go back to South Africa, and that was the start of everything.

This was at King's College. I went to King's College. At a relatively young age, though. I was 17 when I went in. Okay. thing was that being at university in South Africa for a year was equivalent to one year of A-levels in South Africa, in England. So basically, I had to go to a technical college to get my A-levels, got them. And then another lucky circumstance was that in January, so in South Africa, they

hadn't been television. And I saw television and was totally addicted to it. And I remember this is a television about this size, black and yellow. because there wasn't really any white in those days. And by pure chance, a Nobel laureate John Kendrew, who'd won the Nobel Prize at the end of 1962, had a television program that came on in January, 1964. And of course, there's only one channel, so I watched it.

It was called The Throat of Life. And it was basically a beautiful introduction to molecular biology at actually a pretty high level. And I saw this and I said, wow. that's what I want to do. Now, in England, if you have A-levels, you can't go to Oxford or Cambridge. You have to do an extra year of S-levels.

But King's College had been implicated in the whole DNA story. So I thought this is a college, which is in London. I love London. It's a great place to be. I'll go to King's College for my BEST degree in physics, not chemistry, not biology, because physics is easy. I mean, physics is principles and mathematics. Chemistry is all this learning, and biology is even more learning.

And that was it. it. So that sort of got me going. So it really was a number, and there were other lucky circumstances. At the end of my best degree, I had done well, and I wanted to do a PhD with Kendrew who'd given this program, and I wrote to me and he said, no. But then I was again very lucky because my best friends at university were business school people. And they said, you know, in business, if somebody says, no, you don't just say, okay, you come back with a counteroff. So my counteroffer was, if I can't come this year, I can come next year. A pretty trivial counteroffer changed everything. They'd never had, you know, in science you'd never had a counteroffer like that. So they said,

well, why don't you come and see us? I went to see them and I met all these really great scientists, people like Francis Crick and Max Proust, all these Nobel laureates who were giants in the field, because Cambridge had really reinvented or invented molecular biology. But then, after seeing me, they said, well, we enjoyed you. We'll tell you. We'll tell you. in the year's time, whether we'll accept you for a year, which means I now have a gap year. So then again, my business school friend said, you haven't gained anything. I mean, you still don't know what you're going to do with your year. So I did something I think was very difficult for me. I got the courage to drive up to Cambridge and announce, without an appointment,

hung around on the corridor, and happened to see Max Perrutz, who was the leader of the place, an amazing man who has a Nobel Prize, but his real claim to fame is he is the best social engineer I have ever met. He had empathy. That was amazing. Caught him in the corridor, shaking saying, shaking, I was scared, talk to him. But basically shaking saying, look, my finals are coming up. The uncertainty of my life is worrying me. Can we talk?

Went into the room and he basically said, look, I'm the co-leader of this place with John Kendrew. John isn't here today. I'll let you know on Monday. And then I had the good sense just to say, well, thank you very much and beat a retreat. By Monday I had been accepted, but on one condition, John Kendrew said he wouldn't take me that year.

I had to go to Israel for a year. And I never really understood why somebody who was not Jewish would send me to Israel until I discovered that during the Second World War, he was in the British Air, in the RAF. And he had known Chaim Weizmann, the president of Israel's son, who was a pilot, who actually was killed in a plane accident. And then had met other Israelis and actually wanted to come to Israel. But he didn't do that.

Instead, he was on the scientific advisory board of the Weissman Institute. And he knew that there was somebody there who would be very important for me. Now, again, all of this is unknown to me. I didn't want to go there. I said, oh, this is backwater. So who wants to go to Israel? I want to go to Tokyo. I want to go to Boston.

This was 67, right? 67. After the war. The war then happened. But it was no... Then he said, look, you're going to go to Israel. Not only that, he basically bribed me to go to Israel in the sense that they'd just set up a... The Royal Society had set up an exchange program with the Israeli Academy to exchange post-doctoral fellows.

But he said, look, this year, you know, there was a war in Israel. we have no candidates, I will get you a post... Remember, I've just finished my BAS degree. I'm not a postdoc. We will get you a postdoctoral fellowship to go to Israel. And this was like three times more money than I'd ever had in a year. But I went and there I met the people

who essentially results in the Nobel Prize. So basically there's a very tight connection between playing snooker as a child and getting the Nobel Prize, which you would never have predicted. You were costing quite a number of Nobel laureates. Did you ever think that you would someday win? Not really.

At that time in the 60s or? Well, I mean, I didn't even expect it 40 years later. You know, I was working in computation. Right. In 1970, right? Right. And really, even before 67. So I was really pioneering what later became computational biology.

But computers in biology were not, weren't seen as a natural fit. Although if you think about it, biology is complicated. Computers are great for complexity. It was there. But basically, I think I just, you know, maybe in a different time, I would have been a hacker, you know, breaking into bank accounts and things like that. Could still be. No, I'm too old for that.

But instead, I really loved computers, and computers were actually very important for crystallography. So what I did besides molecular dynamics was actually do a lot of things in crystallography. and I was very lucky because when I went to Cambridge the year later, I really felt that I had my PhD in the back, because I had a few papers. So I was able to look around and do other things. I was like a freelancing first-year PhD student. I worked with Crick, Frances Crick, I worked with Aaron Klug and Max Perruth.

I have papers with all of them. But it was an amazing situation, and they were not in computing. There was almost nobody in computing, but they were really starting to see. So, for example, DNA sequencing is a big, big deal. I was actually asked to work on the very first bit of DNA that had been sequenced, which was from a phage called Phyx, maybe it was RNA. And when the person came to me, I said, no, no, I'm not really interested in DNA. I'm going to keep on working on proteins.

This is in 1985. So I was really lucky because Cambridge was absolute ground zero for this field. in the end, from this one laboratory, about 300 people, they ended up getting 28 Nobel Prizes of people who either were working there or had got their Nobel Prize winning idea there. And I knew these people. And I was very, very lucky. But again, another bit of luck.

I mean, my whole life, but I think any of us who've succeeded, you look back. Right. And you all think about luck. And I think luck is very important. I think you have to be very important. open. But another thing that happened to me, which was again amazingly lucky, so when I was in Israel for that one year, I actually got married. And my wife passed away 50 years later, Rena, but we had a long marriage. But her best friend, who I also knew when I was in Israel, was a young lady who was hitchhiking

in Israel in 1968. And by chance, Francis Crick had come to Israel to visit, and they picked her up. And he already won the Nobel right? He had run a Nobel Prize and he was super famous with a friend of his and they were hitchhiking around Israel. And this woman, Shlmette, decided to go with them and she picked them up. And then she stayed with them for their tour. And at the end she said, you know, my best friend has just moved to Cambridge. Would you give her these books?

And now I'm in Cambridge. I'm a beginning PhD student and suddenly I get a call from Crick saying, I have books for you. Wanted to come over? So these things are enormously important and serendipitous. But now that I am part of the Nobel group, if you like, I meet many Nobel priorities. And there's even another one who Snooker played a big role in his life, a man called Rich Roberts. So these stories, and they will all talk about the serendipity.

They will all talk about how often they failed. Failure is a very important. I mean, you know, people think. Yeah. People don't talk about that that much. Anyway, enough on that. So that's a long answer to your short question. But it's quite amazing how you could be so divergent.

You can move from one dimension to another. I mean, you studied physics. You tinkered with biology. Then you won the Nobel in chemistry. You played snooker. And I'm now very interested in epidemiology. I think they actually are connected. I believe that the disciplines are of,

official. I think one reason where we have disciplines is a very simple reason. You're in chemistry at Stanford, and you want to hire junior faculty. Now, what you want that junior faculty do is be a great researcher, but you also want them to teach chemistry 101. And you want somebody to teach chemistry 101 who took chemistry 101. So this is a, I mean, so very few physicists would have taking chemistry 101. So you end up reinforcing

the silos. Stanford actually made a huge effort to dismantle the silos with the bioX program

and X means bio, we don't know what it should be. It's like an unknown in an equation. Not biophysics,

not biochemistry, not biomathematics, not biomputing, by anything you like. And this program has been really important

at breaking down the silos in Israel. People are in the same building. I remember when the building, I've been in that building since the very beginning. And there aren't any departmental offices in the building, but there are people probably from 30 different faculties in the building, ethics, whatever. And this has now been replicated in the engineering center. So a lot of people have replicated this idea. And I think that the silos, which existed for teaching reasons, are breaking down.

I mean, in some ways, the best person to give Chemistry 101 is a recording and an online class that was recorded by the best teacher ever. And this is going to happen more and more. I agree. So I think that Stanford is well positioned, but again, somewhat because of serendipity. Yeah. You came up with the term molecular dynamics. You were critical at some point about how that...

was unable to basically help refine protein. Is there, is there a hope that that's going to happen? You know, the refining, so molecular dynamics is how proteins, if you think about a static structure of a protein, which you can make a sculpture of or whatever, proteins are not like that. Proteins are in continual movement. And this is just simply a consequence of room temperature.

We live at room temperature. If proteins weren't moving, we would be dead. So the fact is that we actually live at an elevated temperature to make our proteins move faster and our chemical reactions to go faster. So one of the reasons why warm-blooded creatures were evolved was to optimize the way the proteins were working. So a moving protein is a real protein.

I think my skepticism came from the fact that a lot of this movement is just incidental movement. But I think that it's been very, very valuable in that it's... much, much better to look at a moving model of a protein than a static model. And now in the computer we can make movies of moving models. And then experimentalists who know their structure intimately, you can say, oh, wow, I didn't realize those pieces come together. They're actually far apart, but they can sometimes come together. And this leads to new experimental work.

I think that computers now have undoubtedly had a massive role in biology. I feel fortunate that what we were recognized for was the first real use of biology and computers. And there will be more of this. I think that biology is... Talk about that. You used a metaphor of your Volvo. How it's changed in size, capacity, speed and all that. This was a metaphor that I used. Again, there were three people involved in my Nobel Prize, a senior investigative from Harvard, a person whose program, I had been when I went to Israel in 1967.

Ariya Varshali, so the senior person was Martin Carpolis, Ariavarshal and me. And Ariavarshal had been a postdoc with Martin Carpalis, but had not left with a very good impression. And he had felt that Carpola's had not furthered his career like he should. Carpus is a very smart man, but like a lot of faculty tends to think about himself more than the people.

he's looking for. Most of his past members are not really happy with him. So Ariavarshal, let me knowing, went to the people running the rebel thing. And normally what would happen is, is that one of the three people would give the after-den-the-speech, but it's the oldest person out of order. So he basically said, look, I don't want to give the often in the speech, but I also don't want purpose to give the speech. So suddenly, without, I was it. And I knew this quite a long time before, and you have two minutes, and it's a big deal because there are maybe 1,200 people in the hall, the king, other laureates, etc. And you get up on a little podium and give a speech. So the first thing I decided was that I would try to give the speech in Swedish

to start with. And I don't speak Swedish. So I had a Swedish postdoc in my lab. I said, look, this is my, I actually wrote the speech in English, including the vulva pot that we'll come to. and I said, you know, I want you to take this opening sentence and translate it to Swedish. It was actually a hard sentence. But the gist of it was, you know, your majesty, you know, your excellencies, ladies and gentlemen, I start my talk in Swedish to show that I can still learn something 45 years after finishing the work that brought me here. And then I said the same thing in English. And, you know, the king was smiling like crazy.

I then went on to say how much I liked Sweden. Sweden is a very special country. But I was actually saying how much I liked Sweden for its alcohol. And this was, you know, I think the whole Nobel thing is a mixture. The Swedes have a very interesting sense of humor. They also have a drink called carbonated vodka. And if you think about vodka, if you think about flat Coca-Cola, it is totally unpalatable.

you make it sparkling and it's very drinkable. So sparkling vodka is really drinkable. But of course, the bubbles put the alcohol in your brain very quickly. So, you know, I'm not going to make any comparisons. But anyway, I kind of liked it. But then I went on to tell the story about the Volvo, basically saying that the work we had done had been massively propelled forwards by computers.

And then I actually, I think what had actually happened was, you know, you hear about the Nobel Prize in October, and then you get all the local fuss, and sometime after the announcement, the San Jose Mercury News, the local paper had asked me, how much have computers changed? And this is a time when you feel you aren't thinking anymore, all you're doing is answering stupid reporters questions. And the smart thing to have done would have been to say, look, Moore's Law, Wikipedia, goodbye. But instead I actually thought about it. And what I discovered is that computers have increased dramatically in four different areas. They've become much smaller, they've become much foster, they've become much cheaper,

and they have much greater capacity. So I thought of a story saying that if motor cars had progressed the same way in these last, it was probably maybe 45 years or something like that, then we would see a Volvo, for Swedish reasons, costing a dollar. It would be able to carry 50,000 people in comfort, would go, I don't know, 2 million kilometers an hour or something like that, and be able to park in a shoe box. Now, this was funny and everyone liked it, and it's true.

But what's interesting is that each of those factors, have improved by about 10,000. It's 10,000 times smaller, 10,000 times foster, which is interesting to me. I mean, why should they all have improved by 10,000? Probably because the answer is, that's the product. And in fact, this is now 10 years out of date. I'm sure for you that now, you would,

I mean, computers have changed so dramatically in the last 10 years that you're able to make it instead of a factor of 1,000, I mean, 10,000, maybe a factor of 100,000. But it is interesting, And, you know, when you think about it, everything is interesting. And I think what I think I'm normal, but I think everyone should be like this. Just retain the curiosity of a five-year-old. And I think that if we can do that for young people, we will greatly improve the potential

of humankind. Extending on this, how do you see the role of AI in being able to simulate? late. The way you've been doing it the last 40, 50 years. Everything I've been doing has been

AI of one kind to another. Right. The, the machine learning, right? Machine learning, you know,

at least squares is machine learning. Right. And we've seen this dramatic change from punch cards and six hours to wait for your

program to run. So an iPhone that is more powerful than all the computers in the world were 50 years ago. And I think

machine learning for me was an incredible through. I mean the large language models. I remember vividly my first encounter with chat GPT3.5, which was on a beach in Israel. We, Shoshan... In 2020? End of November, actually, beginning of December 1st, 2022. Okay.

Basically, my wife, Shoshan, is a curator of Chinese art, but she also taught in Beijing for five years. and she was actually teaching Hebrew and some of her students have moved to Israel and she's in touch with them and one of her students Chinese girl

who married an Israeli and we were on the beach so we tried to see them for social reasons we were on the beach having lunch together and her husband said you know have you heard of Chad GBT

and I said I heard of it but you know what is it so he said well just try it and then Shoshan was scheduled to have an exhibition of a Chinese artists on December 24th, three weeks later.

And she basically said, you know, she wrote in, please write a curatorial speech for an exhibition by Chang Kichung in Israel. And out comes a great speech. So then in those days, it was very easy to say, we'll try again. Outcomes a different great speech. So this was like, wow, I've got to get it. So I got it immediately. And initially, asking it questions in retrospect that were very naive.

You know, write three lines of Fortran. And now every time I'm still continue, you know, now I've been using it nonstop. I have my history. I think I have 10,000 sessions. I'm an enormous number of sessions with it, all of which is kept. And I use it all the time. I mean, right now, how do you think that will impact? Enormously.

the impact is a really enormous. Initially, people were very scared about being an existential threat, and I said there are many insubstantial threats like unknown meteorites, primarily nuclear war is still a serious existential threat. I think human's stupidity is generally more of an existential threat than humans being smarter, and AI has the potential to make us all smarter. I see this happening globally through smartphones, and initially smartphones will become much smarter. I really were seeing that when you do a Google search, it starts with an AI summary, which you can take or not take. I felt that most of the criticisms, in fact, what I did in a narcissistic way, narcissism is really gets you motivated. If you read about me, at least at that time, online, I am, you know, renan for having been completely wrong about COVID, except I was right.

But there was a lot of antagonism to this. So actually, my first sessions where GPT was saying, well, tell me about Michael Levin and COVID. It actually wrote nice things. And I kept on saying, well, tell me again, tell me again. At one point, I had two Nobel Prize as one from COVID. At one point, I lost my Nobel Prize. But I got this whole spectrum. Basically, gee, this machine has read the Internet.

It's probably giving an unbiased opinion. And this is pretty good. So I saved them all. And then I started to use it for programming and was completely blown. away. Everything I've tried. I mean, you know, even recently I was asked to give an abstract for a lecture. And they'd asked for the lecture as a PDF file. So I thought, you know, I'd lost my computer. I was concerned about catching up on my taxes and writing NH reports and meeting people at Stanford, having interviews like this. I didn't want to write an abstract. So I uploaded this PDF file,

which was, I think, nine megabytes, into GPD, and said, please write an abstract. And he wrote an abstract. I said, this is incredible. I would never have any more to, just by looking at my slides. And looking at the text,

and my slides actually are all bilingual. I make a point of always having my, in whatever language I'm lecturing, in China, all my slides have Chinese. And when I gave a talk in Korea, they all had Korean. These are translations done by GPT, which is an incredible translator.

And I was blown away. And then I said, well, this is a bit too long. they wanted 300 words, please shorten it. And it's there. Another recent moment was, we were on a train from Shanghai to Beijing. My wife was going to talk to an art curator.

And I said to, you know, we can now upload photographs. Give me one of the photographs of this work of this artist. And I'll ask, Chachyp. What do you think about it. And this artist during COVID had spent his time sort of locked down, but photographing a nursery that had trees and rocks and they would load them and of course construction was the thing that was really favored during COVID

it continued like there was no tomorrow so it was because the roads were empty it was easy to do it and there are pictures of trees and rocks hanging in the air on the crane and that's when he photographed them and then being put onto a truck to be delivered somewhere so the exhibition are all these trees hanging in the air And ChachyPT, I hope said, this is unbelievable. He, you know, it recognizes that this is isolation, that it's dislocation. The trees had their roots in like a net.

It's masking. And she said, this is incredible. So, you know, every time of my encounters, we've asked it personal advice, medical advice, legal advice. And in every case, the answer has not, you know, it's been like having a smart friend. It doesn't mean it's always right. And if you don't like it, you can come back and say, well, please, let's discuss it. I've asked it about books where I've had a viewpoint that was a little bit unconventional. I would say, in this book, didn't you think this was all about censorship rather than this?

And initially he would say no, and then I would say, let's discuss it. And he would say, you know, I actually see your point. So I think it's been an amazing friend, smart, but I don't think it's infallible. I don't think I've met a human being who's infallible and I'm not particularly disturbed by false information I guess maybe as a scientist I'm used to things being wrong as an anecdote I always would tell my group

you know everything you do I'm going to check but don't feel that I'm unsure about you but my basic viewpoint is that each of you have been hired by my biggest enemies to destroy my reputation you know you're smart enough to be able to size up as to whether or not this is correct. But how about those that are not as smart as you?

Firstly, it's no less wrong than any of the social media. It's no more wrong than any of those places. I think anyone who believes the Google searchers being the only answer is making the mistake. I actually think people, I think the average person is way smarter than their leaders make them out to be. If we look at, you know, COVID, there was a lot of panic about it. But now even the doctors are joking about the boosters and people on taking them. And, you know, and no one is particularly worried.

When I had my pneumonia, they said, we were going to check you for flu, but we're always going to check you for COVID and RSV. I said, fine. I don't mind being checked. I like numbers. But it wasn't like, you know, did you have your booster? And I said, I had COVID three months ago. That's fine.

So I think that people are much, much smaller. I think leaders can basically harness the resentment of certain groups of people, which is the understandable resentment of certain groups of people. And basically, while not offering them more, offered to damage the group to whom they resentful. I'm going to get to COVID later, but two more questions on AI, right? Yeah.

Do you get, or don't you get the sense that it's not being pushed forth in an adequately multidisciplinary manner? In terms of the hypnosis? I think it is. I think, you know, for example, one thing I did really, really early on was subscribe to all the user groups on AI

and get all the developments. Yeah. And look at all the changes. It's now boring and no longer. But firstly, the number of people who were vehemently against. it has gone away. You know, we're talking about how it's going to be weaponized during this election.

We don't need AI to weaponize things. I think that I have been reading more recently than the normal, and I read a very nice historical fiction novel by a writer called Neil Stevenson called the Baroque cycle. It's actually 4,500 pages, but it didn't make my phone any heavier. Maybe it did make it slightly heavier. I don't really even know. But I read the whole thing.

It was basically about the period from about 1650 to 1720. It was basically Newton's life. And the kinds of things that were going on there was posters being put out about people, you know, false posters and false things and people being arrested falsely. And the kinds of injustices, I mean, in England at that time, the kinds of injustices that were going on were horrendous. Slavery was still fine. So I think it made me realize that fake news

has been with us for a very, very long time. One of the main uses of the printing press and Gutenberg was for fake news. I have a very wide perspective because we're also spending significant time in China, which is a different viewpoint. And we're actually living in these places,

which is very different from being a visitor. But then I went back and read about, thanks to GPT, it's great for teaching you history. I asked about, you know, printing had been used in China for a long period. It hadn't caused any time. disruption. China is very, very good at maintaining stability. Europe is very bad at maintaining stability. And I think there's a natural trade-off between innovation and stability. And maybe it's a good thing

that the world, unfortunately, has these periods of, you know, the United States has been probably more unstable in the last 10 years than for quite a long time. And that led to the AI breakthrough. So I think it's good. Is that likely to stifle? creativity? I think stability stifles creativity. And, you know, the real question is, is an important one. I feel I'm actually very interested

in governance. And I actually believe that nobody has a monopoly on the right governance scheme. But not only that, no one has yet discovered the right governance scheme. We have, and I think, I think it's kind of interesting that we have examples of Singapore, Sweden, small countries.

We have big countries. And, you know, my natural tendency in life has always been to treat life as a buffet. Take what you like and don't complain about what you don't like. Just, you know, so gee, the chicken at this dinner has been really good. The fact that the steak was terrible is irrelevant. I didn't, you know, not a big deal. And by that way, you can always find good everywhere. And I think that every system I've seen has good and bad things.

And I think, but I do actually believe that we will find a optimum scheme. I think it's difficult. And I think there's the traditional issues. There's, you know, globalism versus localism. I think that the degree of inequality is an important parameter control. I mean, capitalism is a great driving force, but uncontrolled capitalism leads to a lot of injustice. Yeah. We're seeing a lot of that now.

We're seeing a lot of the United States. I call it the elitization of the economic order. Yeah. And I think that this is a bad thing. And I think, unfortunately, I don't think that there are checks and balances that will hold it. I think in some ways, you know, the founding fathers did a great job with the U.S. Constitution. but I think it's freeing. And what worries me is the level of poverty and inequality in the United States.

The United States has been a beacon of innovation, at least for 100 years, probably for more. And I think this is something we don't want to lose. You know, you saw the Internet as the democratizer of information, right? But it didn't lead up to commensurate democratization of ideas. is an economic capital. I don't know. I think that if you ask, I think a lot of people,

the capital is a problem. Those who have it hold onto it very well. And certainly the rich have become richer. Right. I think the poor haven't actually become poorer. The inequalities increased. Yeah. But I think the number of people

who are above the poverty line has increased greatly in the last 20 years. No doubt about that. And the number of kids who are dying in childbirth has gone down. I think the number of women who are being abused has gone down. And I think a lot of this, I think the democratizing effect really comes through the phone. The smartphone has been so widely accepted.

I was just reading a book right now, written by a book called Yoga, written by a French author, Emmanuel Carrier. And actually, it's not about yoga. It's about all sorts of things. And right now he's writing about refugees on the Greek islands. and he said these kids have nothing, but they have their phones. And their phones are all their memories, the means of communication.

I don't think we appreciate how incredibly democratizing a smart thing. Such an enabler. It's a massive enabler. Maybe it's also a source of TikTok and silly things, but I actually think that the kids who are going to benefit from it, you know, know a good YouTube channel from TikTok.

I think it's actually think, Overall, I'm super in favor. I have 12 grandchildren, between myself and my wife, of ages between 7 and 21, and they have been very exposed to these things. And I think overall they're fine. You know, I think that, and again, because they have different parents, they're different regimes in their household about how open the internet it is, how close it is, what restrictions they are.

But I see them finding things that are quite amazing. history explained in cartoon figures and then being able to tell me all about you know Hannibal's wars my eight-year-old grandson made a joke which was a little bit of color but he basically said I'm a painter I failed at school

I'm now a dictator who am I and you know and I know I want to be a dictator and I thought that was interesting I mean, he thought it was very funny. His parents thought it was funny. I think we talked about it. But I think, you know, I see basically there are, the wonderful thing about humanity is how diverse we are.

And this diversity can be brought together. I think one of the great things about a university like Stanford, it's embracing diversity. It's a diverse school because it has quite a strong Republican center, the Hoover Center, where Condoleezza Rice and George Schulz and you've got the FSI. And the FSI. And the FSI. And then you still have other things.

I wish they were more talking to each other. But at least here on campus, you have them. And I'm super proud. You know, when I got involved in COVID, I had a lot of interactions with Hoover. I want to take this one more question before we get to COVID, but put this in the context of the biological evolution. We started out as bacteria about a billion years ago. A really important realization. So basically...

Where are we going? Okay. That's a great question. Final slide in my talks. But first, I would say there are several sources of intelligence on Earth, humans. Right. Machines. So we have H.I.

A.I. But if you really think about it from the point of view of molecular biology, we have B-I. And biological intelligence is the big one. It invented the molecules that made life possible. It invented the schemes of evolution. It invented all sorts of amazing things. And when you see these things, you know, it's all about self-assembly. So basically, a protein is a...

a machine that is about as big as the thickness of a wire in the best microcircuits we can print, five nanometers. And this machine can do really important things in a size like that, but most importantly, the machine assembles itself. And all of biology, if you think about it, an egg and a sperm, from there, it's all done by itself. There's no one outside saying, well, no, gee, you know, the woman doesn't say, gee, your arm is on wrong, we're going to put it right. and everything we make is made in a factory from outside. So we still have a future ahead of us of self-assembly. I'm sure we'll get there.

Chemists are getting more and more informed by biology. So in the same way, we can learn about material science from biology. The basic fundamental unit in AI is neural network. It's based on a model of a nerve cell from 1943. Basically, you have multiple inputs, summing them, waiting, putting them out. That is the fundamental calculation behind all AI, and it's based on a model that came from neurology. So everything is informed by biology.

So one of the most important things in biology is evolution, because basically it has led ultimately to us. I should also say that when I talk about biological intelligence, I tell people, you know, this could be created by God in four days or in a longer period depending on neural religion, what's important is that biological intelligence is not us. We did not create biology. And therefore, it's an alien form of intelligence from which we can learn a great deal. So if you look at the lesson of evolution, people have often talked about it being survived with a fittest. And that actually is true for bacteria, because bacteria, you know, a daddy

bacteria just copies itself and makes 100 sons coming from the daddy bacteria. I deliberately use a male analog here. But this didn't get biology. I mean, bacteria, you don't see them, unless maybe plaque on your teeth, but you don't actually see bacteria. They're too small. Bacteria started evolving three billion years ago quite a soon time, you know, after the original of the earth. So it was fairly easy. But they basically didn't reach, anything they gave diversity to the earth. Then about a billion years ago, we invented eukaryote cells.

These are cells like yeast that still look like bacteria. But they have one big difference. They have sex. Gender. Non-clonal. Non-clonal. They have mother and father. And in all organisms,

most species have one mother and one father. Some species have multiple gender. I think they're mushrooms that actually have more more than one, more than two, more male, female, and so on. But the simplest have male and female, as do we. And again, evolution, which by this time had quite evolved mechanisms of copying genes and things like this, decided to actually give a random half of the genes from the mother and a random half of the genes from the father. What would have stopped the cloning? I think, well, I think this evolved independently. It was just, cloning is still going on.

Now, bacteria are still cloning. So things are still there. But once nature invented sex, it led to this massive proliferation of diversity. Think of any life you can see, whether it's a bird or a leaf or grass or a fungus or human beings or chimpanzees or anything, all comes from that one idea to have gender. It led to massive diversity. So in some ways, if you ask for bacteria, it is survival of the fittest. Because you give your, you know, daddy gives all his genes to his. Successful daddy gives all his genes to his kids.

As soon as that we started with gender, we basically give half our genes from our mother, half from father. We could have developed a mechanism to give the best genes from the father, best genes from the mother. Why didn't we do it? It's a very simple reason. It's the same reason that a good banker is diversified. we don't know the future. However smart we think we are, we don't know the future.

And for this reason, if you care about, and what DNA really cares about is the long-term survival of the species, the species being those individuals who can exchange genes. And the long-term survival of human beings depends on the diversity.

It even goes further. You can say, well, okay, once we had one cell, why did we have to get advanced? Why did we have to go and develop creatures that can walk? Trees were very successful. Why did we have to be able to move around? Why did we develop brains?

And the reason is that our behavior is way more complicated than the behavior of a tree. Human beings have way more complicated behavior as we've become culturally smarter. Our behavior is much more complicated. So in some sense, as this diversity, we have both diversity of species, diversity of our DNA, but we also have diversity of behavior. So in some senses, the great strength for the future survival of humanity is that diversity. And this actually I like, because it's making a social statement. It's basically saying that equality, you know, you have to really care about the weak genes.

They may be weak now, but there are circumstances you could imagine. Nature wants them. Nature doesn't want one group to take over and therefore worrying about everybody is the best way to ensure the future survival of humanity and it's not because gee, it's not nice to live

when there's homeless on the street it's because those homeless guys could have genes that we really, really need we don't need them now, maybe right now we need banker's genes but we want everything and I think I find us a very comforting thought because

I actually do think that what we are in life is a question of pure luck. I probably most likely should be dead. If you think about how lucky you are to exist, remember you had to exist, your father had to exist, your mother had to exist, and you go back and back and back. And if any of the forbearers had not had children, you wouldn't exist. So it's a massively lucky event. and you could equally well have been somebody who died in childbirth. I mean, no one, you know, it's random who your consciousness is in.

And I think this is something which I find really comforting. It's almost like, you know, we have to be equal for survival. It's not to be, oh, it's socially important or whatever. It's not because certain groups were underprivileged. But basically everybody brings something different. And I actually hope that this democratization, of the internet will increase how diverse people are getting together. And again, I think one thing I really like about Stanford is how it's embraced diversity

besides these various programs. There's the Knight-Hannisie graduate program, which basically tries to get the best students everywhere in the world. And they make an effort to recruit them. They make an effort. Now, obviously, this can improve. There are countries that are not who have not been on the radar enough. But we want those people because they're different.

We don't want them because they're the same. And another thing that I also noticed about science. So again, I was talking before about the BioX program, which celebrated 25 years yesterday. And when this program first started, and it was a very complicated issue. But one of the things was they would just have weekly meetings of random people in the medical school,

actually run by somebody. David Bottsy and who was there then went back to Princeton, but a very, and basically, after a while, we said, okay, we've heard what everyone's doing. Let's do something different. So the idea was, is that random pairs of scientists would decide to give a talk as if they were proposing something, this would happen. So basically, there were various random pairs. I paired up with somebody who was working on defects of walking. and bloodity defects, and he was doing computer modeling of how we walk. And I said, well, I do computer modeling how molecules move, and you do computer modeling,

have human boom. Let's do something together. And we did. The biggest problem initially was that he had a PC, and I had a Macintosh computer, so we're giving our presentation. But we give this presentation. And then, a few years later, a large donation was received from Jim Clark for the Clark Center. and they raised additional money

and part of the money was for seed grants in multidisciplinary ideas. So we put this forward. It led to massive NIH grants in the end. It led to a whole discipline. It became really important. Somebody thing called simbios which is sim biology at different levels.

And I actually think that there should be a grant mechanism like this where you basically say, for example, you know, my interests are such but I would love to work with them with you. And initially the challenge would be, well, what are we going to work on? Where is the area? And that's the most exciting time.

It's kind of cool, actually. We would be finding a vocabulary. We would be finding something. But once we had that, the great thing would be is that suddenly, this is like mother and father. Coming together very diversely. Our project is a child. But the child is immediately informed by your knowledge, your cultural, your cultural baggage or whatever you've got,

mine, it's not just the genes, it's everything we know, goes into that, we would be able to apply methods from both fields, and I think this would lead to a massive outburst of new ideas. I really would love to find somebody who is interested in continuing this. I might push. I'm interested in lots of things and sometimes finding the time, but I think this is something which would be truly amazing, And it's not, you know, you could almost argue,

and what this program did in the BioS Center there, the seed grant was $20,000, maybe $50,000, which is, but it was unrestricted funds. And unrestricted funds are really important. Because, for example, you can have Friday afternoon parties with unrestricted funds. So, you know, $100 goes a long, long way. You don't want to use NIH funds for things like that.

So these funds suddenly become really important. And I think could still be used enormously. I think this is something which has a potential, because we still have silos in funding. People are trying to get it, but the idea of taking people don't, until you've seen it, you don't appreciate how rich it can be. And to this, you know, one other thing I wanted to mention, I love numbers

of all kinds, and one of the things that I've done is actually study Nobel laureates. I started actually studying NIH as a big granting body. And actually at the time of the Nobel Prize, I was studying, are they giving out the money fairly? And I discovered that basically there was a bias against young people. But the bias, basically, what had happened in the 30 years or whatever of NIH's existence, the people who were, the median age of the people who were in NIH had grown by 20.

years. That's because there hadn't been a World War, baby boomers had come in and so on. But as a result, the median age of the first grantee had increased by 20 years. Why? And people were talking about 40 years than you're 20. But the real reason was, is that a 40-year-old is quite good at evaluating a 20-year-old. But when you're 60, you've completely lost that connection. And we saw that the curves were completely the funding profile. The funding profile completely matched the age profile of the group. So we published this. And then I got interested in prizes.

And one of the things... You studied all of 600-something Nobel laureates. Actually, there's 800. 800 now, okay. In different fields. Oh, signs and non-signs, yeah. Yeah, but basically, and looked for what I call chains of Nobel laureates, i.e. who was a Nobel laureate who worked with another Nobel laureate?

And it's actually quite common. And then I actually said, well, who is the Nobel laureate who has spawned the most Nobel Prizes? And there's actually one person who stands out, who's a South African Sydney Brenner, who ended up becoming really, really important in Singapore. He became an advisor to the Singaporean government. When you retired from Cambridge days of 65, he basically moved to Singapore. and actually put him up in the Orchard Hotel, I think. Or raffles.

There were some really claims. They paid all his health care. He had a suite there. And he basically died there of cancer maybe 10 years ago. But he and I were both from South Africa. And he'd be in Cambridge when I was a student. But he's the person who actually has five Nobel offspring. ring. Many have two, because Nobel Prizes are often given for three, and they're often given for

the professor and two of his students. I never worked with carpalice, so he didn't get me. He got partial. But Brenner actually had two in the area that he worked for, and an extra three who got their ideas from him. Now, when you met this guy, he was a bit like, you know, these lawn sprinklers that spin around sprinkling water, but he was basically spitting out ideas like that at an incredible rate, also telling jokes sometimes of color, but he just couldn't stop spreading out ideas. And I realized that this is a very important characteristic. Mike, I want to pick up on your comment on diversity. What would you think of nations that are of high homogeneity then in terms of their chances for survival in a very long future? I think that they will

become more diverse. I think that these ideas, I think globalization is happening. I think that these media have been great forces. For example, in China, people living in South China are much better at speaking English

than people living in North China because of Hong Kong TV. I've met people in that area who speak perfect English have never been out of China from looking at Hong Kong TV. You know, even with all the restrictions put in place,

If you're a kid, you can listen to Pepper Pig in Russian if you want. And whatever language. And kids are very able to do this. So I see that as being an important voice. The fact that we all, this sort of capitalistic globalism, we all want to have smartphone. We all want to have maybe an electric car. These are all forces for globalization.

I think that these countries will become more global. I think, you know, one issue is, We have countries that push for immigration, like the United States, countries that are close to immigration like Japan or South Korea or China. I thought about this a lot. I think, in fact, in a strange way, AI is going to help. One of the reasons why you bring in lots of people into America is you want people to work in nursing homes, often immigrants.

You want people, who's you want people with ideas? Now, I think that in a country like South Korea and Japan, they're going to have robotic healthcare very, very, very soon. They both have very good automotive industries. Great skill at robotics are open. Another area of the world that's going to be very important of this is actually in northern Italy. Northern Italy has an incredibly age population. This is why COVID hit them so hard.

They also have automation. they also have, so I think we're going to see home care robots in five years' time. So this now takes away the need. So in Israel, Israel is fairly open. Almost everyone who is old has a carer from India, China or the Philippines, who have basically left their family, sending their salary back, but other countries restrict having these people there. In Japan, at one point they were out.

actually sending the aged to the Philippines. But robots will be a much, much better solution. So that takes care of the immigration effect at the old side of things. Now, one worrying thing is that the world is getting older. And this worries me enormously because I believe that young people are essential. So what I actually see happening is that young people will be fewer. They will be more valued because they are fewer. And they will be very enabled by AI, because they're the group that's going to pick it up.

And that's going to infuse diversity. So I hope it's their diversity. I mean, if you like, me plus AI, am much more diversified than me alone. Interesting. It's great. You know, you have no idea. I've used it for social, you know, I had an argument with my sons. I have three sons.

I asked it advice. I had an argument with my wife about hailing taxis. And AI was so helpful because basically if I'd asked my brother or my sister... Because out the clutter. Not only that I would think they have an ax to grind. Say if my brother didn't like my wife, who would say, I'm right.

Maybe if I could have asked her mother, that would have been an objective person to argue, but her mother passed away many, many years ago. GPT told me in a very dispassionate way exactly what the issue was. That basically I was ordering taxis too soon and then getting upset that she wasn't ready. and this is completely logical

you know AI has I think it's AI's emotional intelligence is It changes It changes the way people spiritualize

It does And you can really But plus the ability To have conversations In the sense that I was reading a certain Science fiction book That I actually thought

was all about avoiding censorship But it's not seen it that way And I And GPT didn't see it that way But then I discussed it And he said

You know you have a point. And we went back and discussed, emphasize those regions. For me, an immensely important development, which actually was not,

thanks to GPT, but was actually published in Science magazine, I think, in November 2020, was that the world champion of the game diplomacy is a program called Cicero that came out of meta.

And this is a game which doesn't involve moves. It involves negotiation. Essentially, the board is Europe 1901, and the game basically says, and you get random bits by throwing the dice, and the thing is to end up controlling Europe, and you control Europe by surrounding people. And the game basically goes, I will give you this province of Belgium if you give me this province of Portugal, and you make swaps. And these are made between people, so the communication is like this, but there was an article in wide magazine,

and I was reading about this, saying that they'd interviewed in some depth the players, the human players. And all the human players said that this AI is so nice. It never stabs you in the back. It basically wins by strategizing in a much, much cleverer way than human beings can. And the people who lose actually enjoy having played with such a good player, whereas, you know, you could easily say, well, I'm your ally, no, no, I'm not your ally anymore. And it doesn't do that.

So I was so encouraged by that. It just seemed to me that this is where we need a lot of intelligence. Also, one very, very nice thing about these devices is you ask them questions in total privacy. And I worry that leaders become surrounded by people that they have chosen. Whether with the head of a company, even the head of a lab, if I can say, well, this is my idea. none of my students will tell me, come on, it's garbage.

I tell my students, anyone who tell me my stuff is garbage, gets extra points. But they still don't want to do it. I mean, you know, GPT, you can say, well, why is this idea good? Why is it bad? You know, and I remember, so one of the first signs of AI came out of actually out of IBM labs called Watson. And Watson's great claim to playing was that it was a very good Jeopardy player. And I remember, and this was probably 20 years ago, I remember being in a meeting saying that I really wish

that leaders would have access to these devices and it would be mandatory that they ask the devices. They would in no way have to listen to them, but the replies would be recorded somewhere. And I had this image of, at that time, George Bush saying, well, you know, hey Watson, should I invade a, Iraq. And he would get an argued thing for and against. And if he then decided as leader to invade Iraq, that's fine. But I actually believe that these discussions, which you would, none of

the people you were comfortable working with. And I actually feel that this would be true. You know, diplomacy is a very difficult thing because like any human relationship, it, it, you win by coming in without projecting power. You win by projecting openness. And people aren't always good at doing it. Often people who were very good at winning elections are not necessarily good at diplomacy because that's not a skill.

Maybe it's a skill that's important to lead a party. So I think that for me, the great hope is that, and essentially it's on your phone, and it's on your phone for free. These devices have been making amazing progress. We've heard a lot about chat GPT. It was the first, and it led to a hundredfold increase in the company's valuation, which is quite incredible.

But they keep pushing out things. So if you actually have chat GPT on your phone, it can activate a microphone. And what amazed me about this microphone is that it has completely perfected transcription of voices. So if you go to Alexa, and you try to set a timer, it gets it wrong every time. It doesn't listen to you.

You can sit down and talk for 15 minutes to your phone, and it will not, the names will be correct and so on. So, and it'll work in any language. Works in the car too. It works in the car. And it just is a way of keeping notes. So, you know, you can say, well, I've come out of a meeting, you know, let me just tell you what I'm doing.

And then, of course, you'll get all the comments. You know, you'll get all the references and things that were mentioned and so on. and comments on what you've said. So I'm going to start keeping a daily diary just by talking in, you know, in three minutes you can say a lot of stuff. Now, this is something that has not even been publicized. I mean, no one knows that the iPhone version of chat TV

as opposed to the computer version is spectacularly good at transcribing voices. Wow. And they just did it. And I'm sure I could, now that I know about it, I could look for it and they would discover that, yes, they did make a big deal of it. So I think that,

we are in a time, and, you know, probably the three-year-olds who are playing with their phone found at first. I mean, I find that, for example, I can speak Hebrew, but I cannot spell or write. The phone will do it for you. The phone will do it for me. So these things, I think, are great democratizing forces. I also believe that having solved the transcription problem,

the language transcription problem, which is also a transcription problem in molecular biology, but having solved it, we will have simultaneous translation on our phone in five years' time from all the major languages to all the major languages. Language will no longer be a barrier. We just got to make sure humanity uses it in a good way. They will.

You know, people, so my wife speaks English fine, but she still likes to write by writing Hebrew, having it translated, because she can write in her style. and I think people being able to use their own language will be really, really important. Again, you know, you may actually argue that if there aren't any barriers between countries, then getting back to your original question, the homogeneity or heterogeneity of a country

becomes less important. Yeah. Because whatever, so in some senses, no one says we want the species to be mixed. But I think we will have, I think people need, meeting in person is still really important. I believe, for example, that China is going to have to open up. It's interesting, China loves to have inbuilt contradictions.

So it doesn't mind at all if one place is very open and one place is very closed. You know, one country, many systems, is actually a good idea. because this heterogeneity is aware of getting diversity without necessarily causing too much unrest. I think the United States is paying a big price for having neglected the working class. And I think it is not fair, and I think it didn't need to happen.

Again, a little bit of control, you know, a much more progressive tax system. And I think it's going to come because I think we're going to realize that it's actually more fun to live in a country where people are more equal and hopefully more productive. But I do think that right now

one of the United States' great strength has been the diversity that has managed to encourage. And again, this is an interesting story because if you look at Nobel Prizes, Until 1950, the United States had hardly any Nobel Prizes. It was really, really good at manufacturing and mass production.

So the motor car is invented in France and Germany by Benson and whoever. Henry Ford gets it out there. Same thing is true of TV. Same thing is true of power distribution. Tesla, Edison, Marconi, so on. Bell. So America was really, really good. And a lot of these ideas were bought, maybe not stolen, but bought when Europe was bankrupt.

Very low, patents were bought very, very cheaply from Europe in the 30s. Then what happened is, and there's a book of this title, Hitler gave a great gift to the world. By persecuting the free thinkers in Germany led to a massive, influx of people from the part of the world to United States and to Britain and to Switzerland. And the number of Nobel Prizes in 1950 is suddenly the highest in the world. And a lot of them have been immigrants. Immigrants, one thing about immigrants are that they select. In other words, the average person is not prepared to root up and move.

It's a hard thing to do. And it doesn't matter whether it's out of a poor village in Vietnam or whatever. and I think this is something we can use. So I think, you know, in Stanford attracting, the best and the brightest, wherever they are, is a way of increasing the diversity of Stanford. Stanford isn't diverse enough. It needs more right-wing people.

It needs more, you know, the medical school and the science departments are way too left-wing, from my liking. There needs to be much more acceptance of realizing... As with many other universities. I think we're relatively good. I think we're actually way better than the East Coast University. We've seen now in the attack on Israel and Israel's response,

and I think neither side is correct. I'm not allocating blame. I think there's actually basis for discussion. I wish it would happen. But there was stamp and handle it better than the other universities. Mike, this is fascinating. I want to touch on COVID-19. You came out in 2020.

Basically what happened again. Putting it in the context of more than 7 million people having died allegedly because of COVID-19, comparing that with what happened in 1918, compared out with 1346, 0.08% mortality based on the 7 million figures, right? Talk about it. So basically, as I talked about serendipity in my life, so basically, I actually went to China for a day from Israel on the 20th of January 2020. I was in Changsha, which was quite close to Wuhan. Right. But came back from Hong Kong. It was clear that something was going on.

Chinese New York that year was the 26th of January. My wife had lots of friends in China. so she wrote messages on social media to them saying how we hear about this pandemic now, we're worried about you and so on. And the response was incredible. They were outpouring. They said, thank you for thinking about us.

It's amazing that you care and so on because people weren't like this. So I decided, well, basically my wife had gotten so many likes from her thing, I needed to do something. This is kind of a joke. So I decided I would look at the numbers. So I started out, there were very few numbers on COVID then. They were very hard to find, but I found websites, and I think I had numbers for the first six or seven days of COVID in China.

And basically, immediately looked at the previous SARS, SARS 2003, and saw that it was very, very different. SARS 2003 led to something like, something like, 8,000 infections and 800 deaths, but almost all of those deaths were in Hong Kong and in Canada, all over the world, and not in China. Although China was traumatized by SARS 2003, and even before the COVID pandemic,

they were measuring temperature of people coming in at the airport. So I started to look at the numbers, and then I looked at the numbers and basically felt that I need to publicize my numbers. I did a, wrote a wait-to-weigh-wit-wit-weigh- white paper for myself written on the 1st of February 2020, where I looked at COVID in China, if all there was, and I looked at the time series of cases and deaths. I'm not an epidemiologist, but people were talking very much about exponential growth, and as someone with some mathematical

knowledge, there's a very easy way to detect exponential growth. If you have a bank account, you ask, well, did it increase the same amount last year? Last year, it increased the previous year. If it did, I'm still being paid the same interest rate. So the ratio of today to yesterday should be a fixed number. So I plotted this ratio, and to my amazement, it was actually dropping like crazy. And by the 1st of February, there were actually four points, the foremost recent days of death, but not cases, that were along a straight line. And you could draw a straight line through four points, which is extremely crazy. But when you did this, it looked, if you extrapolated like this, that within a couple of weeks,

it would be getting much, much better. So I wrote this in this report, which was sent to friends by their WeChat and WhatsApp and by email to various people. I sent it to the Dean of Stanford. I sent it to widely. And then we got into a flight from Israel to New York City to visit my wife's son and granddaughters, I landed in New York in my email, are you the Michael

Levin who just published widely about COVID? Michael Leavitt at Stanford.edu, yeah, that's me. One of the people that I sent it to in China had actually posted it, translated it into English, into Chinese, and posted it on their equivalent of, say, Facebook. And it had been seen

by several million people while I was on the airplane. So I suddenly felt, would you, I didn't mean. this to happen, but I sort of have an obligation. So immediately I was interviewed by CGTN in New York City and a few other places. And then for the whole of February, I wrote daily reports on the procession. I saw things peak in China. I saw things end. I followed very, very closely the Diamond Princess, where you had a close population and the mortality there was 0.04% of people. It was 7 out of 1,400 people who were old,

but maybe healthier than normal. And at this point, I realized that this disease was basically hitting old people. It was a very important report published in China in the middle of February, which wasn't quoted in the West. It was published in English. But Google, I think, decided not to index it,

because it was China. Really important. They published what was the age profile of the deaths of the first thousand people who had died in Wuhan. And we didn't get Western data on that for months afterwards. But basically what they saw was people who were old or sick tend to die. So then we had, I was now, I'd written 20 reports on China, a little bit on Diamond Princess, then moved to work on the West. I published my last report on the 14th of March. By this time, I was getting media retention. I still wasn't on Twitter,

but I was interviewed by Laura Ingram on Fox. As a result, CNN refused to interview me. So basically, they canceled me at 5 a.m. in the time of Israel, five minutes before the... This is Comor. Chris Coma. I was very angry, but, you know, It doesn't matter.

No longer with CNN. Then I wrote my first public announcement, there was a source called The Medium. And I happened to read it for whatever reason. And an important British epidemiologist had said he'd basically put the risk of COVID instead of saying it was this number of percent. He related this to the natural risk of dying. And he basically said that, you know, COVID in its prison state, and this is the middle of March would lead to one year of additional death, which actually seemed quite consoling.

But basically it means if your life expectancy was 10 years, it would be nine years. And different groups have different life expectancy. So for somebody whose life expectancy was 40 years, one year was not much. But then I looked at my numbers and I said, no, no, no, you're wrong. It's actually one month of extra death. And then he just fell on me like a ton of bricks. And suddenly everyone was getting very upset. At that point, I decided to go into Twitter.

It was very difficult. It was no one believed I was who I am. So at some point, they said, please show who you are. So I put a picture of myself with a Nobel Prize, with my signature on it and so on. And my way photographed it with freight engines, so it would have been hard to Photoshop it. And then very quickly, I was active in Twitter for about three years, went up to about 120,000 followers, basically seeing more and more that the response was highly exaggerated. You were saying in your question, going back to 1918 to 1357,

but the fact remains if you go back to 2010, which was actually a very bad flu year. So I started to actually look, as part of my examination, looking at one of the important things in science is you immediately asked what would you expect. So one of the first things I did was to look at how many people die every day. And basically every week, more than a million people die in the world. I think it's 60 million a year. So now you put your, what you mentioned is 7 million, and that number might be 5 million. But that number, some people say it's 20 million.

7 million is basically seven weeks of extra death over three years. we're talking about the whole pandemic. The amount of natural death in the world during the pandemic is 180 million, of which seven million... Over a three-year period. And over that same three-year period, we have seven million deaths. So that is something like three and a half percent, which is about two weeks of extra death.

Now, this is because it went up and down, and this is the best measure, because one of the troubles is excess death, there are many reasons you die. I mean, basically everyone dies of something. Often it's pneumonia. But then there's the latest cause. But if you're 95 years old and you have pneumonia, you know, is it a pneumonia death?

Is it an old age death? Is it because your heart was really weak? You know, basically, like an old car is full of dense, an old body is full of defects. Nothing we can do about it. It's very sad, but, you know, mortality is a very, very strong function of age. I think an 85-year-old is 100 times more likely to die than a 20-year-old, which is a good thing. And because COVID's death profile followed the natural death profile, you know, you could count deaths.

But if I do something which I wouldn't have dared do back then, but people do something called disability and age-de-death level, prolate deaths by what you would useful years of life lost. And when you do this, anyone who dies over life expectancy is set to zero. And then if you die five years before life expectancy, see now, this probably would have got to be banned from Twitter by even saying this. But economists do it all the time. Not only that, but if I went to Stanford Hospital and said, gee, I want a new heart. My heart is weak. They would say, well, you know, with all due respect, you're 77 years old, 76 right now, but going

on 77, and we think that somebody with more life left should get the heart. maybe if I was very rich I could buy one but the fact remains that all decisions are made were basically you could also say for fairness you know if you're giving out a meal the five-year-old should get it

before the 85-year-old because whatever happened the 85-year-old has had 85 years of life the 5-year-old has 5 years of life they deserve 80 80 years of meals before giving one to the 85-year-old Just by fairness. Now, people don't believe this.

They don't like it. We also have another confounding factor for COVID. Baby boomers, the average baby boomer turned 65 in 2020. 55 was like the middle of the baby boomers. Suddenly, we had a whole generation that was super concerned about aging. My work on NIH that I described before had shown that when you're 65, 50 seems young and 20 is like a three-year-old. You can't see it. Ageism, unfortunately, is how we work. And, you know, I love old people. I like diversity. But I think we need to realize that 40 is not

a new 20. 20-year-olds are special. I often give the example of, look at people who completely revolutionized the world. Jobs, gates. They couldn't finish their college degrees. They got into good universities they had to leave. Sergei Brun, Harry Page, and so on, Mark Zuckerberg. These guys actually couldn't wait to start their companies. 20 is special. 20-year-olds are special

because they don't know too much. Nowadays with postdocs and PhD students, they say, oh, you have to do your PhD, now you have to do your postdoc. That's nonsense. The smart people are the guys who don't know enough. The senior people don't have good ideas because they know too much.

And you have a good idea. by saying, well, what is really crazy? This is why when I thought about teaming up. So, you know, if you and I were thinking about anything we think about, neither of us know anything in that area because it's an area sitting between us. It's got to be an area we both can talk about.

So we're not experts in the area. So that becomes provocative. But in your own area, you know, you've been in the field for 20 years, 30 years, and so on. You know too much. And you shouldn't expect to be truly innovative in that area. So anyway, COVID it was a wild ride.

I was on a lot of media and interviews and things like that. Basically a year or where I suddenly got very bored with Twitter because basically the way you get likes on Twitter is by posting

stuff that is controversial. And I didn't mind posting things that were controversial when my view was the outside view. But, you know, I have a lot of friends. In fact, I actually have members of my research group whom I've never met, whom I pay as consultants,

who I met on Twitter. So these are people who are doing research for me, paid research by, paid by my NH grant as consultants, who are doing things that I want to do. And it's great. I don't need to meet them. I mean, I would love to meet them. They'll be on the papers.

But there's a kind of democratization here because people who, I know that they can do what they do, because they did it. Show me an example of what you do well. You've been following me what I can do and it's amazing. I think it's amazing that I don't. So I think that it's been a very broadening experience.

I feel right now that it was a little bit alienating at Stanford because my colleagues are not in the business school, are not in the Hoover Center, or not in the Institute of urine. And as a result, most of them were unhappy

about what I was doing. the NIH National League of Health took a very specific view on COVID. At one point, the director spoke against me personally, but I was very happy to get an NIH grant. So I sort of feel I'm getting back into the fold, and that's good. But it is true, though, that most of the casualties would have had comorbidity, right? I think, you know, the, the, it turns out that there's a lot of ignorance about death. And if you look at in these countries where there's good statistics, so Sweden has statistics

that go back to 1750. They know how many old people were dying. You know, it's a lot of states you can go back 30 years. Some countries you can go back five years. But only 34 countries in the world keep this data, which is simply who dies on what day at what age. Not even who. X dies today at a certain age. And that should be very easy to keep. And you have to keep it not just during COVID, but for preceding years. Three or four years is enough. This data actually, you can go back further. And you can find that in, say, Sweden, there were peaks

above background that existed in 2010. 2010, 2011 was actually worse than COVID in about half the countries for which we have data. Sweden, Germany, and whatever. So epidemiologists knew this. I think for whatever reason, epidemiology is a field part of whose job is to raise alarms. And I think that they didn't expect the world to listen. They'd be. in saying how bad 2010 flu was going to be. And it was. But no one did anything to it. But in fact, the going back to lockdown

is going back to medieval practices. And fortunately, one country right from the beginning said, we're not going to stop schools, and that was Sweden. And although there were political issues, Sweden did way, way better than almost any other country. certainly in Europe. I mean, Denmark and Norway also didn't do badly. Neither did Finland.

Countries like New Zealand and Australia did really, really well. South Korea, Japan, Taiwan did amazingly well. Other countries did less well. And when we actually analyzed, we have a paper that came out in the proceedings of the National Academy of Sciences at the end of the last year, we basically showed that if you asked death during pandemic, it doesn't matter what it was caused by,

it could have been caused by vaccine side effects, lockdown, illness, suicides, overdoses, anything. The amount of death, extra death, as a percentage of normal death during the pandemic, correlated strongly with basically one thing, three different things, but they're all related,

low GDP, high genie inequality, and high percent poverty. And each of these things had a correlation. And basically these are all pre-existing conditions because the poverty was not measured during COVID. These are measured five years previously. And Sweden has a very low level of poverty. It did very well.

If you actually look at this in a more granular way for the United States states, where you again have all the data, and this hasn't been published yet, but you find that in the United States' poverty alone correlates to excess death, at 0.85. 0.85 is a very high correlation coefficient. I asked chat, JPC, and it said it's significant at one in 10 to the 15. It doesn't matter. It's highly... And this means that states that had low poverty

did much, much better, and I don't think it is because the poor are dying. It's because a state that has high poverty is mismanaged in the same way. On the world scale of the United States as a whole was most like Romania and Poland and Chile. So these are the, in the graph of when you plot who is like whom, the United States, Romania, Poland and Chile are close neighbors.

The countries that we heard about early on in COVID, like Italy, Spain, France, Germany, in some ways, equivalents of the United States in terms of education, richness and so on, are far away. They are a third as much. Mike, I want to ask you about the vaccines, right? How would you compare the RNA vaccines with the non-RNA vaccines? In terms of, you know, there's a lot of talk about long-term or potential long-term consequences and all that. I think that the biology, the molecular biology, is very different.

I think neither vaccine was subjected to the kind of testing that flu vaccine is subjected to. Flu vaccines typically take nine or ten years to develop. This was developed at breakneck speed. I think from our work we haven't seen a strong correlation between being vaccinated and not being vaccinated in terms of outcome. A very interesting example is provided by the four large states in the USA.

New York, California, Texas and Florida. And if you actually look at the trajectory of their deaths, they're actually very different. So Florida had a lot of deaths towards the end of the pandemic. New York had all its deaths at the beginning. But what you find is that the totals are all the same. So by the end of the third year, when I show my graph of the excess death versus poverty, all of these states are sort of midway in the poverty

and they fall on the line over there. So it didn't look like the pathway mattered. New York really had massive excess death in that first wave. They, in their worst week, they had seven times more death than in a typical week. So this really means that every place

where there are dead people, there will be seven people, every morgue. Other places never had more than 25% more. This was a super, super high peak. Because it was so focused and so concentrated. And remember, New York probably has the best hospitals in the world as a city, and they have amazingly.

New York actually is an amazingly good academic hub between Colombia and Sloan Catering and NYU. I mean, it's a very academic place. City College. City College and so on. So it makes me, I think that the RNA technology is very interesting. It's potentially more open to side effects. Essentially, the idea is instead of injecting the protein product that is meant to alert

the immune system, you're injecting the RNA of the virus to actually use the cells to make the protein. Now, this seems like a very efficient idea. It's also very easy to engineer. It's much easier to make RNA in large quantities than it is to make protein. Protein is actually quite hard to make. So the cost per dose is much higher.

And basically, the RNA is not in a virus capsid. It's in a little oil drop, which means that it's taken in by any cell type. normally vaccines have on their surface little keys to only open certain cells so natural COVID is only infecting certain cells RNA droplets can go into any cell now the biology is complicated because we actually have two immune systems we have antibodies that recognize proteins so basically if I have headpiece proteins from COVID My antibody say, no, no, no, I don't recognize this.

I'm going to go in there and attack it. And if you are immunized, you've got practice of this. So you've built up a lot of these antibody cells that recognize the headpiece. So as soon as the headpiece comes in, you get it. Naturally, immunity works the same way. Now, if you were to have an inactive virus, it would look the same. You can also inject the protein headpiece. So many of the vaccines, Cinovac, for example, the Chinese,

really due to heroic bulk technology, made large quantities of this protein, purified it, kept it intact, because the protein cannot be allowed to fall apart. I mean, a protein has, the headpieces recognize not because of its sequence, because of its shape. Okay. Now the RNA. So the second immune system of the body is a different immune system. A virus gets in, and let's say the virus is a particularly tricky virus like flu.

Flu is a really tricky virus because it mutates at an incredible rate. And if I have flu, no two cells of my body actually have the same flu. If you talked about a flu strain, in a particular year, there's a strain, but it mutates incredibly quickly. Normally when you copy RNA in a cell, it has proof reading. It copies the RNA and checks if it's right. And if it's not right, it corrects the errors. flu actually has a very short RNA and doesn't bother to copy. So flu is a truly diabolical virus.

How the body copes with flu? So basically flu can change its face. So basically the headpiece of the virus is the face of the virus. It doesn't change very quickly. Change with the different strains, one or two mutants. Flu has a different face every time. So how can the body treat it? Certain of the proteins made by the flu are essential for its function.

These are not proteins that are on the face of flu. They're proteins that are used in the process. And the body has a wonderful system. Every cell in the body, when it's making proteins, displays on its surface and a sampling of what it's making. Short pieces, little peptides. This is actually connected to blood groups and histosability systems. It's very diverse.

So you and I can be infected by the same bit of RNA. So essentially, RNA vaccine is infecting you with the RNA that makes the protein. The cell sees the cell making a foreign protein and kills it. So some fraction of cells making RNA are killed by the body's natural defense system, not all of them, and some of these cells make enough of the headpiece to create any immune response before they kill. But they're killed not from making the headpiece sequence, but for making something that isn't going to change.

Okay, now, let's imagine that there are certain regions in your body where killing cells is not a good idea. And particularly in tissue, in endothelium tissue, skin, because skin is a barrier. And if you, by chance, get messenger RNA for the vaccine into skin tissue, it can cause a hole. Which may or may not be bad. The trouble is that the potential side effects of an RNA that can go anywhere are much large. And I don't think I took the vaccine, the RNA vaccine in December 2020, a time that I was using Twitter all the time.

I really did it so I could travel. I also saw that my wife, who had been exposed to my evangelistic approach to COVID-19, not being dangerous, was really happy to take the vaccine. But I remember writing at the time that as a... Would you have not taken the vaccine? If you could have traveled? No, I would have taken it. Traveling was important.

But actually wrote saying... No, no, if you could have traveled without the vaccine? I don't know. I thought, but I did think... I wrote at the time saying that as a 74-year-old or whatever I was then, I have a 3% chance of dying in a... in a year, and a chance of dying in a month would be a quarter of a percent, and I don't think that the vaccine is more than a quarter of a percent chance of dying.

So I, and for a month, I don't really care, you know, really I don't care about a month. It turns out a month is what COVID was causing. I don't know what the mortality is. We need to do tests. It turns out that the hard thing about doing tests is, if they're done under blood, blind, controlled systems where basically you have some vials containing active vaccine and some vials containing placebo, probably salt water. And these are injected by people who have no idea what is what, and they don't know,

but you keep track. And this is what was done in England for the initial tests of the vaccine, but they were only tested on 40,000 people. And there were very few deaths, and they weren't followed up. no one looked at the group, because we were at too much of a hurry. I am encouraged by the fact that some countries have decided that they can actually test vaccines on the population. Now, this is somewhere unethical, which means that you have a population, you're offering the flu vaccine, but some random subset of those flu vaccines are salt water.

The doctor doesn't know it, but the batch number is kept in a computer somewhere. and they're now doing this both for flu vaccine in Denmark and for COVID vaccine. And I think we may learn. But I think, you know, the, it becomes, in hindsight, we cause a lot of damage. If you look at the overdose deaths in the United States or in Canada, shut up like crazy, people basically destroying the fabric of society, which was essentially what was done in these countries, is very, very bad for people. Zoom conversations are great, but they're no substitute for people on people.

And I think global communication is really, really important. So I think some of these lessons have been learned. I think I really don't know about COVID. I actually hope that the side effects will be minimal. I think it's a good way of giving a vaccine if there are as many as a – flu also has side effects. I mean, if you actually ever get any medication, and let us say if they list the side effects.

And it's a huge long list. You buy cough medication. And it's got a huge list of, you know, and they listed just for, I guess, legal reasons. But, you know, I don't know. People have postulated. Some of my Twitter community have said that where a vaccination can be dangerous

is if by chance when the vaccination is given to you, it happens to go into a blood vessel. and then it gets into the bloodstream and then it can travel very quickly. Then the vaccine can travel very, it's a little droplet. It can get to a place in the heart and kill a heart cell. It kills a heart cell,

not because it kills it, but it gets into the heart cell, starts to make the vaccine, along comes your T cells and kills that cell. Part of the natural protection of the immune system, which can also be highly variable. Different populations, different blood groups will read to different populations.

And we all have T cells that naturally recognize COVID, because COVID viruses are natural calls. So I actually believe that there are different susceptibilities. I think a lot of research could have been done on T cell repertoire

say in Southeast Asia versus Americas. Because COVID was way, way worse in the American quadrant than it wasn't the Southeast Asia quadrant. And all the countries in Southeast Asia, countries like Vietnam, all did relatively well. Even China, I think, did way, way better. Yeah, Vietnam did okay. Yeah,

so I'm saying, but compared to Chile, if you compare Vietnam to Chile, there's no comparison. I mean, Chile had quite massive excess death. Now, we don't have the excess death numbers for Vietnam, but we have the anecdotal numbers. And, you know, I'm sure people died during that year. you know, basically, the last three or four years before COVID had been particularly good years. And remember, in good years, people get older. So you could imagine, you know, the Grim Reaper, basically taking down people who are close to death.

If you have very good years, global warming would make the Northern Hemisphere good years. We had an excess, and you don't want to use these words. There were more elderly people than you would have expected. These are the people who died during COVID. You know, one, for me, one of the great things about COVID is that I found a new collaborator, this man, John Eonidas. Yeah. And he and I had dinner with him yesterday.

And, you know, he took a lot of, I mean, it's his field. He took a lot of flak. I got flak, you know, as somebody on Twitter, and, you know, he's a Nobel Prize when he thinks he can talk about anything. I felt that I had to take talk up if I believe something. With the Nobel Prize comes to responsibility. and there are two main responsibilities. One is to imbue young people with the fact that science is cool.

So I'm giving lectures all over the place to basically tell them, maybe they should do more on YouTube. I feel very enthusiastic. And remember, in my case, it was John Kendra talking on television in 1964 that got me into science. That you inspired.

So it's very important to do this. So you want to talk in this wide a possible forum I will probably go into YouTube, having seen my grants. And I have a lot of YouTube talks recorded, but, you know, more specifically. And also, if you believe something, being brave. Yeah. You know, I was not worried about, in fact, I was surprisingly unworthy about some of the Twitter comments I got. And some of the awful I was accused of killing two million people with my bare hands.

And, you know, it still didn't bother me. I think also, unfortunately, 2020 was a highly political year, like that. this year is going to be. And people, the level of politicalization was horrendous. And I think that... Politics could use a bit more AI. I hope AI could help. To reduce the neurosis. You know, the thing is we need people to believe in AI. In the same way, for me, I see the first example of AI entering our lives are programs like Google Maps and Ways and other GPS devices. most of us initially were very skeptical of being led by a GPS device only a fool will now say I know better than Waze or Google Maps

we just do what they say I think for a lot of families where the wife and husband had different beliefs about the best way to go you do what Waze does and everybody's happy I think we need to have east increasingly other fields I mean AI and Ways is good because it's using AI it's using an algorithm that was derived of in the 60s by Dagstra, a Dutch computer scientist, just about how to find the best way between two points. But it's AI. And I think when we can use AI, for example,

put a picture up there of how my wife is dressed for this dinner, how should I dress? It can give you advice on that, and it will give you advice. So we have to get used. And this is why I'm hoping, I want quick adoption of AI. And then in the same way, instead of really listening to panicking people, And, you know, there was a lot of false information put out deliberately, a lot of suppression of ideas they didn't like.

Because everyone, I mean, everyone thought that it was, people were panicking. And they didn't want to lock down, or they didn't really care about being locked down because they were university lecturers with Zoom, actually quite convenient to be on Zoom instead of going to your class. But they wanted everyone else to lock down because they would be carrying the disease in danger in their lives. It was a hugely asymmetric issue. I mean, a lot of people did very well during the pandemic, both financially and in terms of their research and so on. So I was very allergic to this.

And in an article that I actually, an opera that I wrote, I can't remember if it's the Wall Street Journal of Washington Post, it was a Wall Street Journal that actually finished writing in my final line was I'm very disappointed about, this is in 2020. So I was just early disappointed. I would have been much more disappointed after three. that I'm very disappointed about how humanity has reacted to this pandemic, but I do hope that by the time the next pandemic comes along, AI will be sufficiently developed for me to say,

hey, Alexa, Google Theory, should I panic and believe the answer? And I hope we have to get there. I want to ask you about that. How much worse do you think this virus is going to mutate in the future? This new virus is not going to mutate. Let me tell you, if you look at the biology, I said a bit about flu, but if you just take the two viruses, they're both RNA viruses, they're small, etc., and compare them, I made this analogy. COVID, for all these things, is like the Pope, and flu is like the head of the mafia. Flu is a really, really nasty virus. Weaponizing flu. So to give you some things, so the flu virus is a third of the amount of information as COVID.

It doesn't even copy itself properly. Inside every cell, the flu virus is copied so badly that the coronavirus has one string of RNA that's 32,000 base pairs long. Flu is deliberately divided up into five pieces whose total is 12,000 long, and the reason is that flu mutates so much that many of the small pieces it makes are defect.

So in a particular cell, able to choose the good bits to make a functioning flu molecule, flu virus. So flu is truly diabolical, and we live with flu. We've had flu variants. You know, I think we need to assess flu better. Is that going to mutate to something much worse? Mutating virus is better than the degree of mutation. I don't think so.

I think, you know, maybe if we're locked down all the time, we would be able to mutate it or have vaccines. that are, but basically, you know, the way flu works is that there's a bad variant of flu in the southern hemisphere. We use that to make vaccines. Most of the world's population is in the normal hemisphere. We make vaccines for the normal hemisphere. These vaccines are not 100%.

People get flu. You know, I, maybe we will become super good. I think flu is a truly nasty virus. I mean, compared to COVID, it also turns out that COVID, the coronaviruses, of which COVID a member, half the common colds are coronaviruses. Our body, it's not a new virus. We have T-cells that recognize COVID. And I think my hypothesis is that in East Asia, where there's a lot of East Asian tourism,

Chinese tourists are going all the way from Korea to New Zealand in a very strong way. I'm sure in Malaysia and Vietnam and Indonesia, all these countries do have a lot of, I think they all have T cells that they've built up from common colds. And that's fine. And I would imagine that common colds maybe are less severe in Indonesia, because common colds generally propagate more in cold climate. So overall, we're there. We're human beings.

Our immune system is very, very smart. We would not be alive if it wasn't for our immune system. We worry so much. I think, you know, I'm very worried about overuse of antibiotics. I'm also very worried if we keep on cleaning our hands like we do with all these disinfectants, that's bad for us. You know, I think germs, immune systems, need to be exposed to germs.

And the fact remains that in places in India with poor hygiene, they didn't have massive death rates. There wasn't massive death. You know, Africa hardly noticed. And people say, oh, well, we're not counting them. But you can see deaths in food. Most countries celebrate deaths in some way. There are burials.

If any country has seven times more deaths in a given week, believe me, it's impossible to hide that. Even twice as many deaths in a week is impossible to hide. So it didn't happen. And I think for good reason. So I think I wouldn't be worried. I think human beings, you know, I think, again, if we became diversity is very important.

because we all, and again, the immune system has taken this to another level. The police cells in our body are connected to our blood groups. People have massively different blood groups. You know, some are common, some are not. And again, it's put in these different groups again, because if you really think about survival, you want the immune system to not be hit by one virus that gets us all. So you actually expect from the diversity principle

that there will be massive differences in susceptibility. And there was during COVID. Again, this has all been hidden, but it's true. Now, in principle, you could actually, and I hope people are doing this, ask what is the Tseille repertoire in America, Europe, Asia? And I bet you will find significant differences

and so on, you know, in South Korea and Japan and Taiwan, they didn't have big outbreaks of COVID until Omicron came along. So they were essentially, whether it was lucky, controlled, or whatever. They had little outbreaks, but they never really caught fire. And then they all had these massive outbreaks during Omicron, where not that many people died, but they had nothing until that time, and then suddenly the outbreak.

So I think differential susceptibility I think we need to realize we need to be told medicine doesn't tell us this enough basically we are really good at staying healthy

we need to worry about nutrition exercise and sleep don't wash your hands too much and don't wash your hands too much don't drink too much alcohol maybe don't smoke

unless it makes but you know on the other hand being happy is very, very good for you. So if smoking makes you happy, then you can probably justify it. Again, it's comparative risk. Yeah.

And I, you know, I think we need to realize that there are an awfully different, lots of different ways of dying. Right. And it's often not what we expect. And, you know, I, for many, many years, I've been studying mortality. It actually started, so I spent quite a long part of my life in Israel.

Basically, before coming to Stanford in 87, I was a professor in Israel for eight years. And during that time... This was at Wiseman? In Bratman. During that time, there was actually the Lebanese war. And I had kids who were not yet in college, you know, but they were growing up in Israel. They were, in a few years, liked to be, go to the army. So I was worried.

and at some point I said, well, let's look at the numbers. And I don't know what made me do this. So the World Health Organization, all the countries are meant to deposit data on diseases and death. This data is not age categorized, so it's not that useful. But it is categorized by what you die from. And they're looking for heart attacks, cancer, and so on. And one category is accidents. And accidents are anything that isn't a disease.

So, for example, if you're killed in a war, that's an accident. If you're killed by a suicide bomber next to you, that's an accident. Okay. And then I looked at this data for the countries for which I had data. And I was speaking, and I was saying, what countries are safest? What countries have, and, you know, I look at the data. Number one was Holland, okay, not a big surprise.

Number two is Sweden, again. Number three is Singapore. Okay. Four is Israel. Israel is the fourth safest country in the world. Now, you can see this because of the life expectancy and things like that, but it came as a shock. And then you find things like, if you're an 18-year-old, and I think they did have age categories, I need to go back to this data. If you're an 18-year-old, or between 18 and 25, the accident rate in the United States is five times higher than in Israel.

So it turns out it's safer to be in the army than it's just to be in the United States as a teenager. And it turns out that in France there's a high accident, right? You know, I really need to write a paper about this again because everyone said, oh, we all know this. But I haven't seen this properly formulated. We're looking in categories. And it's fascinating.

I think it's really important, you know, when you say you're 7 million deaths and I say, okay, that is... Out of 180 million. Then you put it into perspective. But I think 7 million is a big, big number. And if you told me these are 7 million 5-year-olds, I would have said this is incredibly terrible.

But the age profile of that 70 million, 7 million, is exactly the same as the other deaths. So it's an increase in a group. So, you know, I think we have to always put things... One of the things you learn in science is you're always trying to take the other viewpoint, putting into perspective and so on. Mike, this is fascinating.

It's going to take us to the last question. What advice do you have for the young in order for them to be as curious as you, to become a good scientist like you? So I think being curious is a really good idea. The world is amazing. These three intelligences have contributed to an amazing world. How do you make somebody curious, though, if he or she's not?

But I think people are naturally curious. I actually think, so once I was asked, what is the aim of good schooling? Often, I'm provocative. I would say that when a person leaves school, he shouldn't hate learning. This is a pretty low bar. I mean, the school basically should not make you hate learning. Now, unfortunately, some schools don't achieve that. I think

So basically try to be uninterfired with, be curious I think be take chances often, you know, one way to be lucky is to take a chance

and taking a chance can be all sorts of things but basically even you know I didn't want to go to Israel but then when it became quite clear that somebody very important wanted me to go

I said okay I'll do it I didn't say under no circumstances were like, that would have changed my whole life. So I think you need to be open. I mean, the world is fascinating, open to amazing opportunities. And, you know, I almost feel that I am very busy. But every opportunity meeting you was an amazing opportunity. You know, I feel that I've become enriched by interaction. I hope we can remain connected.

I was happy to give this thing, even though this is my fourth meeting of the day, and I have more to come. Thank you so much. So I think being open is very important. I think another thing is do something you love doing. I think in any area that you love something, and often I give the example of somebody who is very talented

and whose mother wants them to become a doctor, and they go to medical school, but they would have much wrong. they'd done something different. Well, then they could be trapped because they will go to medical school, they'd be very successful, they'd become a doctor, but all along they wish they'd been a violinist.

Now, if they're smart, they can work on music and have that side of them. But if they're not, so I think, and one of the nice things these days is you don't have to do one thing. One of the great things about the internet has made it possible to learn things. And again, AI, you know,

it's explaining abilities. are incredible. Tell me what about blockchain as if I was a five-year-old. It will do it. Then you say, now I think I get that. Explain to me what the loopholes or what are the problems and so on. And very quickly, you'll become a conversant expert on this field, and it will be inside you.

Only oh, I can remember what the book said. You can ask you to say, I'm trying to learn beginners German. Please ask me quizzes. I mean, one thing I didn't do, and I should have done, I had to do my driving test yesterday. I knew about it. And I managed to pass. You had a cheat sheet.

I had a cheat cheat. But the cheat chip was actually out of date. And I should have gone to GPT and said, look, I'm going to driving test tomorrow. Can you ask me test questions? It would have done it. And I bet it would have been better. What happened was I, it's actually not too bad. You get through the whole process.

You're in front of the computer. And it tells you you can skip three questions. I decided I wasn't going to skip anything. And I failed the first time. When I look at it and it says, don't start again. for less than two minutes. So the lady said, move away from the machine for two minutes. Wait.

The computer is still yours. Put your thumbprint and you do it again. Now, the second time, about half the questions are the same as the previous time. And things that aren't the same, you can skip three questions. So basically, you have a very high probability of answering the second time. I got through, she said, oh, wow, you got through the second time. Some people take 10 times. but basically you're learning all the time

because there's nothing like answering a question and suddenly seeing Buh, rely. It's very, you know, there's a multiple choice that is a moment where your brain is primed to learn. I found a great app that I was going to write about on Twitter but it turned out to be out of date because the handbook has evolved

but now believe me, I know more about driving than I've known for at least five years and I actually feel good for it. I mean, I think that these... You don't have to read the manual. I told you to read the manual. I know. You got away with the cheetah.

And, you know, you actually mean RTFM. There used to be a website called RTFM. There's a very useful website that came out of MIT. RTFM at MIT. I'm not going to say what RTF stands for, because it's not nice. You can imagine it. But I think being passionate is very important. I think being prepared...

Passionate, persistent, original, kind and good. Remain curiosity. Yeah. originality comes from the fact that you're doing what you want to do, but also realize, I think another thing I would add for young people today, you are precious. We need all those old people who think they're controlling things need you to break the system.

They need you to do innovative things. We know so little about what we can know. I think the fourth thing, the fifth thing, and I wish I could learn, and I need to actually think about this, once one way you succeed is being wrong a lot. And I tell people, as again, as part of my lectures, that a good scientist is wrong 90% of the time and a really good scientist is wrong 99% of the time.

And the reason is you ask harder questions. And this is true of anything. If you're a bureaucrat and you cannot be wrong no matter what. You know, you're fired. You'll be a lousy bureaucrat because oftentimes a good bureaucrat can find a creative solution where you cut down the burden by 90% for a 10% risk and it's worth. taking. But if the price for penalty is huge, in any field, you can become much better if we're

prepared to experiment and make a mistake. So I wonder, you know, people, young people who have succeeded have generally done, have generally not made mistakes. Getting through school, you said, well, gee, I failed this and this and this. I mean, I made social mistakes like playing snooker, but I got through the exams. And I wish there was a way to teach people. how to make mistakes. Because this is something every Nobel law will tell you. One of the most important things is to make mistakes. Now, making mistakes is important because you shouldn't take them too seriously.

If you make a mistake and you say, well, gee, the system hasn't fired me, but I'm a failure, I'm worthless, I got this wrong. That attitude is terrible. So I think we need to find a way in education from making mistakes. one final thing. I think education systems, a bit like governance systems, haven't changed enough. And I believe that there's going to be a scope where we've now learned how to teach machines, machine learning, and it doesn't work like human learning. It doesn't work by having an expert that's trading the system. Expert systems were tried. Siri worked that way. It's a complete failure. The way it works is by generative adversarial networks,

which really should be general adversarial learning. They call it GANN, but it should be GELW. Basically, you have a student and a teacher who start off knowing nothing. The student is trying to fool the teacher that he knows how to draw a dog. So he produces a random picture. The teacher is trying to learn how to discriminate. a real dog from a fake dog.

At the beginning, the teacher, 50, 50 says, no, no, that squiggle doesn't look like a dog to be. Then you show a picture of a dog to the student and to the teacher and say, try again. And basically, it can be summarized as, fake it till you make it. I actually think this has super potential for learning. Basically, what you really need to do is take the class,

today you are the fakers and you are the discriminators because to fake it till you make it somebody's got to say whether you made it so there's a discriminator or the adversal and the game is how often how much can you win how often can you draw a non-dog that fakes the teacher and how often can the teacher be fooled and that way you learn to draw really good dogs so on and this has been true of all so basically in large language models you're trying to guess the next word And basically, this is how it works. It is an incredibly powerful technique.

I believe it could be used on human learning in amazing ways. But, you know, after my driving test, I actually think asking multiple choice questions and being in a buzzer going off when the answer goes wrong. I think it really, I mean, I remember all my wrong answers. So I think that there are ways of doing this. You're allowed, what, nine to 14 wrong questions or answers? I was fine. second time and I basically wanted to hug the lady in the DMV, she said it probably wasn't a good

idea. You know, so seriously, I mean, it was very interesting. But I think there are many, many things to learn. I think basically, you know, people think, well, are we running out of stuff to learn? And basically, learning is like an expanding frontier in an infinite universe. And as we learn more, the frontier gets bigger. So for young people today, I mean, I think that young people may be despondent by, the aging of the population, they were in a better position than any young group.

They have the internet. They have access to the information. They have AI as an assistant, as a friend. You know, my girlfriend just dumped me, what do I do? And the advice will be really good. It won't be stupid advice saying, oh, you know, you'll get another girlfriend, they're many fish in the water. It'll actually be, and the answers will be very thoughtful.

And answers that you read them, you'll say, whoa. You know, I knew that, but boy, this is actually really important. And then if you come back and say, well, I'd like to discuss with you, I think she left me because of this. Can we discuss it more? You can have long discussions. This is an amazing tool. So I think that, you know, from I sort of went a bit back onto Twitter when the AI came out. And I basically said, look, this is the most amazing thing.

I am not worried about fake. We're going to have fake news. We're going to have fake Bidens. We're going to have fake Trumps. you know, we have fake everywhere. We had fake news 2,000 years ago. But we had fake news 2,000 years ago. And some of it was actually called religion.

Don't quote me on this one. But, you know, in some ways, I mean, I actually like spirituality. Yeah. But what I don't get is mine is better than yours. And any God who made something as wonderful as our universe is not going to say, sorry, you bleed in the wrong thing. You're out, you're in. I mean, universal belief in the wonder of the world.

for me is wonderful. But religion in the name of pushing forward my group, my caste, is understandable. In a very hostile world, you may need to have that tribalism. But I think we're edging towards a world where embracing diversity instead of reinforcing diversity is the way to go. And I think that for me is very uplifting. And I think we have the tools. We have the phone.

We have AI. we have this global commercialism. And, you know, it's going to be very, I think, I mean, I see China's having the potential to solve the energy crisis in the USA. The trouble is, though, that the USA is such a rich country that it doesn't really have an energy crisis. But China could certainly solve the energy crisis in Europe,

which is a crisis, because of, you know, geopolitical issues. And it can, and it'll do it very, very well. And if you look in Shanghai now, about 20 or 30% of the vehicles are electric. Most of them locally made. We see a lot of Tesla's. But I'm actually very happy about that. I think democratizing IP is a really, really great idea.

I don't know, I haven't spoken to Elon Musk, although we went to the same high school. In Pretoria. In Pretoria. We were both of Portoria boys high school. He was there 20 years after you. You South Africans have done so well. Yeah.

In fact, during COVID, my nemesis had also gone to the same high school. A man called Leo Pachter, who was a professor at Caltech, who basically thought that I was evil-embodied and was really very good at social media until I overtook him on Twitter, and then he didn't matter so much anymore. Then he blocked me. But, you know, I think that good ideas are great and democratizing.

You know, in the same way that Henry, if you ask, well, who really got motor cars accepted? It was Henry Ford. and Mercedes invented it. But that's good. Yeah. I mean, I really think it's good. You know, we need these two steps.

Yeah. And if IP was watertight, it wouldn't be good. I agree. And, you know, and I'm not talking about ripping people off and patents need time to last. And you need, because some things are very expensive. I was involved quite earlier in my career when I came at Stanford in designing antibody therapy for cancer.

And it was done as a small set of company. and they wrote an important paper and they wrote a very tight patent and this patent was very strong and it meant that big companies could license the technology and then invest hundreds of billions of dollars

to get it to market without worried about being scooped when they got it to market and at the present time a cancer drug that is in current use called Herceptin which is for breast cancer is based on a paper that I wrote in 1989. So that's kind of a paper that I wrote in 1989.

So that's kind of a nice feeling. But you had to get the whole process, and you realize that you need to protect IP if the development costs are very, very high. That's fine. We'll get that. Wow. Michael, you've been very kind with your time.

Thank you so much. Thank you so much. Can I ask for at some point getting a copy of what you have? Yes. I mean, you know, we'll edit and what you like to use. We'll give it to you first. Whatever. I probably want to look at it first, but, you know,

It's very hard for me to listen to myself. What I might do is ask GPT to transcribe it. Because now, as you know, subtitles are really easy. Done. And you can put subtitles on things. We'll do it. And a lot of people like subtitles because what's nice about subtitles is you can skip. Oh, he just said that.

Anyway, thank you so much. I'll have to say thank you to the camera. Thank you. That was Professor Michael Levitt, Professor of Structural Biology at Stanford University. Thank you. This is Endgame.