Endgame with Gita Wirjawan - Eric Betzig: We're Killing Science with Politics

Episode Date: June 17, 2025

About Eric Betzig:Eric Betzig is a Professor of Molecular and Cell Biology at UC Berkeley, holding the Eugene D. Commins Presidential Chair in Experimental Physics. He is also a Senior Fellow at the Janelia Research Campus and an Investigator of the Howard Hughes Medical Institute. After earning his Ph.D. at Cornell and working at AT&T Bell Labs on near-field optics, he left academia in 1995 for the machine tool industry. He returned to science in 2005, building the first super-resolution single molecule localization microscope with Harald Hess, work that earned him the 2014 Nobel Prize in Chemistry. Today, he develops advanced microscopy techniques for biological discovery, including correlative super-resolution fluorescence and electron microscopy, and 4D dynamic imaging of living systems.About Gita Wirjawan:Gita is an Indonesian entrepreneur and educator. He is the founding partner of Ikhlas Capital and the chairman of Ancora Group. Currently, he is teaching at Stanford as a Visiting Scholar at the Shorenstein Asia-Pacific Research Center (APARC); and a fellow at the Harvard Kennedy School's Belfer Center for Science and International Affairs.Explore this episode and be part of our communityhttps://endgame.id/Collaborations and partnershipshttps://sgpp.me/contactus

Yes, I still want to be an astronaut. What do you think would have caused a divergence between China and the US? One of the things that I love about most of the Chinese people, work ethic. I want to be the best of whatever I do. If I'm not the best of what I do, I'm exceptionally unhappy with myself. If there's a day in which I don't feel like I earn my paycheck, I feel really shitty. One of the big problems scientists have is that they go to too many things. they go to too many talks, they go to too many conferences, and they read too many papers.

And as a result, they start thinking too much like other people. If you work hard and have a good heart, you will be successful. What you're successful at will be complete luck. Hi, friends. Today we're lucky to be grazed by Eric Bedsick, who is a Nobel laureate. He won in chemistry several years ago. Eric, thank you so much for grazing our show. Nice to be here, Gita. I'm amazed by your journey so far.

Tell us about how you grew up in the Midwest and what made you so curious about so many things. Well, I mean, I grew up in Ann Arbor, Michigan. My family started fairly middle class. My dad was at the very end of World War II in the war, in the war, in the Navy. got involved in wrestling in the Navy and then ended up going to University of Michigan in Ann Arbor to be for his degree under the GI Bill. And he ended up being on the wrestling team with the same coach he had in the Navy, ended up getting a degree in PE and then stayed on as an assistant coach on the

wrestling team. and they won several Big Ten championships and so forth. And my dad learned through that wrestling the value of hard work. And I sort of inherited that from him. I don't have a lot of other attributes, but one of the things that I will always say is that there's not a lot of people who work harder than I do. And that was part of this Midwestern ethos that I think we both had. When I was born, he was chief engineer at a machine tool company in a close by town.

And so he was making reasonable money. There was after my brother was born in the following year, there was four of us. And so we were middle class. But as he worked his way up to president of that company, he started to make more money. And then we started to move from middle class, kind of upper middle class. by the time I went to college. And so, yeah, it was all public schools. Ann Arbor schools were great because of the influence of the university in the town.

And I got a fan, you know, I went to Caltech as an undergrad. And when I went there, I went with a lot of trepidation about, am I prepared for this place? But, you know, once I went there, once I went there, I realized, you know, my education was probably better than most of the other kids, including the foreign kids, were coming from the best places overseas. What were some of the areas you were curious with? For me, right from the beginning, Apollo had a tremendous infancy. As far back as I can still remember, you know, maybe five, six, seven years old,

Apollo was something that just captured my attention. And to this day, space is a huge interest of mine. And it certainly influenced me to want to do science and engineering and really not just science for science sake, but science in an applied way. as to do something that, as I keep saying, move the ball downfield or move the needle or something like that to improve society, improve the, improve the state of humanity, right? That's always been kind of a motivating factor for me, largely with an engineering bent. And that and then, you know, once, although I didn't watch it when it was in its first run, the original Star Trek.

That was 67 to 69 was originally on, but it was probably when I was in middle school or high school, I was watching reruns of that. That had an amazing influence on me, I have to say, that television. A lot of people around the world. Yeah, yeah. And so you add Apollo and Star Trek,

and you pretty much describe what makes me tick. You made a bold statement about wanting to be an astronaut. Yes, I still want to be an astronaut. Yeah, absolutely. What age was that? I probably want to be an astronaut since age seven. In fact, I went to Caltech specifically because I wanted to become a scientist astronaut. I viewed this as a path either through aerospace or physics or other things to eventually try to become a scientist astronaut.

But it was also true that this was the era in which the shuttle was being developed. And once I understood enough of the science and the engineering, I realized, even before it flew, that shuttle was a very bad idea. It was a mistake to go. It was a politically driven mistake. Explain. The architecture of the shuttle with solid rocket boosters, which were there because we used solid rocket boosters for intercontinental ballistic missiles, and this was another market. for them to be able to do that. Having to lift wings and all of that stuff to orbit and back,

the risks involved in having fragile things like wings and so forth on this thing. There were many, many decisions that were driven politically in terms of the design of that as sort of a continuation of something to feed all of the contractors that were developed. you know, there was a nationwide, Apollo would not have existed without having this nationwide distribution of money from the program to all the congressional districts. It wouldn't have gotten the votes to continue. But once that was created, then the beast had to continue to be fed. And so the architectures, and NASA eventually became dysfunctional. I loved what NASA did in the Yeah.

But, 60s and 70s. And you know, the science part of NASA continued very well for a while. And, you know, one of my greatest memories from Caltech was when I was a sophomore in the classrooms we were taking, there were closed circuit TVs connected to the jet propulsion laboratory that Caltech run. And the Voyager spacecraft were going by Jupiter then. We were the first to see live the closed circuit TV. circuit TV, like the volcanoes on I.O. and stuff like that. So Jet Propulsion Laboratory was just

knocking it out of the park for years until around 2010. And then it too became dysfunctional. And so there's just this natural thing that if things don't kind of are renewed properly, they just grow and become sclerotic, you know, just too overwhelmed. with bureaucracy and so forth. How do you compare the space shuttle with the starship? Of night and day. The starship is exactly the right architecture. Without all the fancy dandy wings and stuff.

Right, right, right, right. So starship, when it's when probably this year, they'll be able to catch the upper stage. When they do, that's crossing a Rubicon. The holy grail of spaceflight has been. to have a fully reusable rocket because that's the thing that will cut cost by orders of magnitude. Already Falcon 9 with the reusable booster has cut costs by an order of magnitude. But we'll get another order of magnitude if when we get to the point where Starship can be reusably used. And so we'll be down to, you know, tens of dollars per kilogram to orbit or

hundred dollars per kilogram versus initially in the shuttle era like ten thousand dollars and current money per kilogram right what does that mean it means like you know you take things that jp.l used to do right is is that you have to shave off every gram off the spacecraft you have to design everything incredibly delicately in order to save weight now you can put tanks in okay so you'll be you'll be able to make telescopes that are 10 times or bigger than the web telescope that's gone up, you'll be able to send spacecraft that size to every planet in the solar system. It will revolutionize astronomy and planetary astronomy and intergalactic astronomy. And yet there's many scientists who seem to resent the

idea of what they're doing in building this architecture. It will change everything. I've been waiting my whole life for a space economy. There will be a space economy. Yeah. It's sounding a lot more real now. You're seeing the first product, Starlink. So Star ship, going back to Starship, it's really not an original idea. It's a reinvention of Yeah, it's just... A preceding idea from the Apollo's, right? Oh, yeah, absolutely. So, and I mean, I think everybody who is knowledge in,

in astronautics understands the type of architect, all going all the way back to Goddard and Oberth and those guys, they understand the architectures needed. But the, you know, the devils and the details, right? There's a lot of details to get that kind of thing. to work, right? You saw that with the explosion of the ship a few days ago, right? There's a lot, you know, even with our amazing ability to simulate everything these days, computation, which we didn't have an Apollo. Even with that, reality always will have surprises, right?

And so what they're doing is exactly right. This architecture of try and fail and try and fail, that's exactly what you have to do. Other than the element of, you call it bureaucratic viscosity, what other elements that you think would have derailed the scientific pursuit? Well, again, it's bureaucracy plus. So one of my favorite quotes of all time is Charlie Munger, show me the incentives and I'll show you the outcome, right? That's a great one.

So the incentives that are behind NASA are not incentives of let us get to the Mars or make space fly cheap. The incentives are get us reelected. Okay. And we get reelected by sending money to all the congressional districts, right? And so that over time, initially the incentive was land a man on the moon before the end of the decade, right? But once that was filled, then the incentives shifted, right? And then the whole thing. Now, Musk is motivated by other incentives.

He wants to live on Mars, right? He wants to be the first guy to land on Earth. Yeah, yeah. And he wants, and he believes, and I agree with him, that ultimately, if we do not become a multi-planetary civilization, our story will end. Okay. it's not necessarily urgent right now, but there's a window of, certainly a window of time. Who knows what kind of ups and downs humanities will have, whether we have technological collapse or whatever, even if we don't go away, right? But we have an opportunity now.

Our technological skill is good enough that we could make this, for the first time in our history, could make this happen now. So why would you want to throw away that opportunity when it exists? I totally understand where he's coming from. Is there hope in Doche being able to weed out some of the... To a degree, it's the question is, is, again, incentives, right? So ultimately, the people who make the decisions, right, are the elected people is the way it should be, right? So ultimately, the Congress, the executive branch, all of these people will be the final arbiters of what happens. And if you cut a lot, you're going to hear a lot of screams, right, from the people who are affected by those cuts, as we see now with the NIH.

Economic domains and stuff. And so, question is, is where will the equilibrium finally hit between the desire to reduce deficits versus the versus the thing. And I think the other part that Doge will be doing, which you haven't heard about yet, but which would be very valuable, is reducing regulation. Unnecessary. Regulation is necessary, but it can get to be extreme. Another hobby horse mine is nuclear energy. And the level of regulation of the nuclear industry has effectively killed it in the United States. And yet, I think it has tremendous benefits for the U.S. and the world done properly. And so that's just one example of millions of over-regulation that needs to be addressed. And I think that would be, that one's

easier because it's, it will be beneficial to all if done properly. So it'll be interesting to see how that develops in the new administration. Well, and with respect to nuclear, if you take the market dynamics, alluding back to what Charlie Munger said, it doesn't seem to be incentivizing, you know, for nuclear, you know, to be further developed in this part of the world at least. Yeah, no, right. They're creating negative incentives for it. Right.

So, yeah, exactly. And that's, we've had one nuclear project approved since the nuclear regulatory commission was started in 1972. And that was the vocal plants that came online last year in Georgia. That's it. So, yeah. Ouch. And those were tremendously over budget, as nuclear has been every time in the last 20 years. A lot of that over budget is because of the degree of overregulation, right? Is it they'll even change the regulations as well as, so there was like concrete being put down for the voltal reactors. And they changed the specification after, it was done in terms of what needs to be done.

So they have to rip out the concrete. It's like, you know, how can you possibly make an economic solution when they keep changing the rules on you midstream? It's not possible. What do you think can be done as to fix this massive or seemingly massive structural issue that that has caused, you know, misallocation of resource? Yeah, I don't, I, it's, again, it all comes down to what collective. society wants to do, right? And certainly there's an effort, you know, the new energy secretary and

others who want to make change. Again, everything has to go through Congress. There's some Congress people who are for and many who are against. And they are responsive in the end to the will of their constituents and and nuclear has been vilified since you know for what was the movie the the one with a meltdown with three mile on yeah what was the movie though yeah that's i remember them uh yeah yeah can't remember but um but ever since then right i mean it's like or he takes simpsons you know three-eyed fish and and stuff i mean it's it's pervasive that that nuclear has been vilified in the u.s right And yet it's it's by far, if done properly, the cleanest, safest, cheapest form of energy possible. Yeah.

And so in order to get it to happen, you know, a lot of these things require long periods of time of education. And yeah, I think education and critical thinking generally in the world, the United States in particular has taken a significant decline in my lifetime to our detriment. Wow. You know, let's talk about energy. Yeah. I know you're big on nuclear because it's scalable. It's clean.

Yeah. This is an issue for about 84% of the planet. You think. I mean, you belong to the 16% of the planet, right? Right. So there are three billion people on Earth who still use dung or wood. for heat. There are 800 million people with no electricity.

There are, you know, including my part of the world. Yeah, I know. I know. Indonesia is a prime example, right? You're one of the big facets from. India, sub-Saharan Indonesia. Oh, absolutely. Absolutely. Right. I mean, you guys would benefit more

than anybody from scalable nuclear power, you know. But yeah, people don't understand everything is a, as in engineer, I say, if you don't understand the trade-offs, you don't understand the problem. Everything is about trade-offs, okay? And all we hear is about the negatives of nuclear power, or negatives of different energy sources. The reason, look, in the 19th century, average life expectancy in 1850, worldwide, there wasn't a country on earth in which average life expectancy was greater than 40. Today, there isn't a country on earth in which life

expectancy is less than 55. Why is that? Because fossil fuels, the industrial revolution powered by fossil fuels, it changed the world. And it's still changing the world. And fossil fuel growth is still going on. Indonesia is a prime example of this. China is still a prime example. renewable energy than anybody, but it's a drop in the bucket to how much they spend on coal. On coal. Yeah. And we have been exporting more and more coal to China every damn year. Yeah.

And I think it's about 250 million tons last year. Yeah. And they built 13 times the amount of power generation and coal compared to what we did last year. And, you know, they're, except for, you know, they're probably one of the places where nuclear is having a little bit of a resurgence. And so, but the resurgence of nuclear and what's on their books to build is about a tenth of what's on the books to build for coal. So, yeah. How do we fix this? You have to make coal cheaper or you have to make nuclear cheaper than coal.

And it's from an engineering and physics perspective, totally doable. From a political perspective, thus far not doable, right? And so it's- Economically by way of scaling. Yeah. That's how you make it cheaper. Yeah. Well, yeah, it doesn't even need to scale that much to be cheap, right? It's, it's again the regulation that is really making it insanely expensive. Okay.

When you have to stop a plant halfway through for years and you have all that capital already invested and, you know, a lot depends on interest rates, right? And so, you know, we missed an opportunity. we had this period of incredibly low interest rates, right? And it's going to get harder as interest rates go up, right? So, yeah, it's much easier. Whenever, you know, for a nuclear plant, all the capital is upfront, right? If you have a coal plant, all the costs are, or natural gas, much of the costs are the continuing costs, right?

So you pay as you go there, whereas with things like nuclear, you pay it. front, right? So the economics are different depending on interest rates. You know, I'm just a bit unsettled. You know, the kids out there when they use OpenAI, 4.0, the energy that's used for one particular query is roughly 50 times compared to a simple search on a typical search engine. And if a kid out there wants to create an AI, generated image on Zora, it's about 10,000 times the amount of energy. I didn't know that.

That's interesting. 10,000 times. I mean, which kid out there is not discouraged from wanting to do stuff like that, right? So the structural limitation is energy availability or right there off. Certainly for AI, the first barrier will be the energy barrier, right, in terms of how far it will go, right? There's no doubt about that, right? And, you know, you can argue from at least my perspective that maybe that will be the opening for nuclear. Certainly you hear that from the companies involved in AI is an interest in nuclear from the perspective of running all the server farms and the GPUs needed.

But even then, it'll be very interesting to see how far AI will scale before it hits these energy limits. And, yeah, but at the same time, you know, I wonder if there will be, you know, breakthroughs in the energy efficiency of AI. This takes 20 watts. It does quite a bit with 20 watts. Okay. So you know. You've won a Nobel with that.

So, so you know, so you know, minus probably 15. You know, you know there's an ability to go from, from what, what AI's take now to what is theoretically possible based on what this does, right? So, but it may need completely different architectures than it has now. Well, I'm with you. I mean, intuitively, I think data intensity is not going to translate to energy intensity on one-on-one basis, right? There has to be some non-linearity here.

Yeah, right. Yes. Yeah. But if you take a look at the amount of, or the length of the queue that wants to enter of grid in the U.S., it's about 2,600 gigawatts, on top of the pre-existing 1,300 gigawatts. That's the United States, which is already highly modern, right? Exactly. Think about Africa.

Think about the developing or the global south. Particularly Africa. Oh, my goodness. Yeah. I mean, you know, industrialization of Africa would be, you know, a major task. You know, and, you know, this then gets onto the topic of renewables to us. right because a lot of people would like to use renewables you know there are a lot of renewables in the right place you know I have solar panels on my other house and

in California but it's sunny there 80% of the time right in Germany where they have 50% you know that the amount of of solar radiation they get between weather and latitude between summer and winter varies by a factor of eight, okay? So it's not working. There it's really silly. And so again, the incentives are so, they're not tied to reality. It's really strange.

And so, and, and then people keep talking. You know, I, because, you know, I, I, I search for this stuff on my phone and on my computer, my feed is always filled with all sorts of energy stories, particularly by our renewables, you know, renewables are now 30% of our electricity in this country, or 80%. And electricity is 18% of all energy use. They keep talking about, and if you try to electrify all the other sectors of the economy, do you know just to create the grid for that, but that would entail? And whether you can even mine that much copper to even get close to that?

Not enough. And the material cost to make solar panels and all the mining that's done for cobalt and everything else, basically they end up in these massive, you know, tailing ponds that are the biggest structures on Earth, that man-made structures on Earth that are naked eye visible from space. It's filled with all sorts of toxic stuff. Yeah, there's in the U.S., Australia, everywhere, they're everywhere, right? and advocates of renewables never talk about the environmental devastation from doing this. Nor has there been a sufficient analysis of what we're going to do at end of life of all of this stuff.

It's like hell-bent for leather to do all this stuff and not having thought about the whole life cycle of what's going on. It's insane. And even the energy costs to create the polysilicon to make the solar panels. it's all run by coal in China. I do this stuff. So you have to look at the embedded cost of the carbon you've already expended to make this stuff. And, you know, it reduces the effectiveness of that stuff. Or electric cars.

Electric cars, when you think of all the material costs that go into it and so forth, you have to drive an electric car roughly 250,000 miles before it breaks even in total carbon output. You know, after that it's in the green. But, yeah. So I really don't understand how this whole renewable thing got untethered from reality. So you're suggesting the high degree of stickiness with old paradigm. Yeah. And somebody was telling me the other day, somebody really sparked that, you know, about four kilojoules of energy translates to about $1 GDP per capita increment.

And that explains about the stickiness for most of humanity. and he's making a prediction that it's going to stay like that for the next few decades. Could be. And the dent by way of, let's say, not decarbonizing, it's about 5% on GDP on a cumulative basis. Yes. Not on a yearly basis. Yeah. I mean, if you're in Africa for the next few decades, I can afford a 5% dent on my GDP.

That's right. You know, if you're growing at about 150 to 200%, yeah, yeah, take it. I'll take 5%. Absolutely. You know, it's, it's, that's the kind of realism. I think that needs to be infused in day-to-day conversations. Yeah, yeah. But, you know, just the sun, it's, it's just so much energy, right?

I mean, people are saying it's about what, we get about 8,000 times the amount of energy. Oh, way more than that. Way, way more than that. So intuitively, it's just going to depend on technological innovation. Yeah, just. That was the key word there. Just, right? Yeah.

Yeah. Is there hope like in our life? For solar? For things to get so cheap that everybody can afford it, batteries included. Your best bet is nuclear. I mean, in terms of the amount of energy density, right? I mean, you only have one kilowatt per square meter at space. if right when it hits the atmosphere and any clouds or whatever will reduce it go thereby right so you need

lots of material over lots of area in order to create whereas nuclear is orders of magnitude more energy dense right so you can have a plant that would you know fit in this building that could be nearly a gigawatt right so orders and orders of magnitude difference in our guys are talking about SMRs, right? Yeah, right. Even in Singapore, they're talking about SMRs for data-centric. Absolutely. Yeah.

And there's a whole ecosystem of companies with a lot of great ideas, many of which were tried out in the early days of nuclear, from molten salt reactors to fast breeder, you know, liquid sodium reactors to high-temperature graphite reactors, all from all the way down to like one megawatt, all the way up to multi-gigawatts. Every point in scale. There are good designs for this kind of thing, but nobody's been able to get anywhere because, first, the regulation, right? What we should do as a country is what we should have, you know, the thing, look, I was in the machine tool industry for a number of years. My dad was in it for 50 years.

In that business, we were making parts for the auto industry, okay? the assembly lines are running 24-7, right? If they don't have, if the machine that we build to make a brake caliper or something breaks down and they're left without parts and they have to stop the assembly line, you are done. Done, okay? So reliability is essential. To make something 24-7 reliability in a complicated system. with no faults, takes a lot of work, a lot of work. And the only, just like we go back to Starship again, how do you do it?

You have to test. You have to run things to their limits, right? What we should do as a country is we should have a program where we go to, I don't know, maybe Hartford, where they're still digging up some radioactive or someplace that, or Oak Ridge or someplace else, and set up a bake-all. of all these SMR designs and so forth, help subsidize them to build their designs and test them out and run them to death, okay? And then find out what works best, what's most economical and so forth in a controlled way, right, where we can test all this out. The government can help. Companies can help each other out, do this bake off and find out what works best at what scale. We should have done that 50 years ago.

We should still do it today, right? And test and find out what works best and where things break. Because, you know, yes, in a nuclear reactor, as in any complex machine, there's all sorts of, you know, limits of life issues, you know, where the neutrons go, the corrosives of molten salt and how it interacts with the metals around it. But it's no different than what we've already learned by running natural gas plants now with single crystal blades that run at thousands of degrees and get us now 60% efficiency where we used to have 30% efficiency. It's just like anything that's market driven and has a big market and lots of money and lots of time will end up becoming almost science fiction in terms of. of how sophisticated it gets, like iPhones and laptops and all the rest, and the natural gas plants that we have now today. All of that is incredibly technically sophisticated because there's been money and time behind it, right?

Did you get a sense that finding the right intersection between power and talent has become a more difficult job? by way of some of this, you know, neurosis in decision making. Yeah. I think so to a degree. I do feel like, again, and this could just be my own personal biases speaking. But I kind of feel like that advice from scientists and engineers, say in the 70s and 80s was less politically driven than it is today.

And it was taken, you know, there was a greater, seemingly, maybe I'm being naive, a greater degree of objectivity about the advice. Back then, yes, say 50 years ago. What do you think causes that? I don't know. We're getting way out of my pay grade. Me too. Am I understanding of this?

I just generally don't understand politically, you know, the trends that have happened and how what used to seem like a belief in the, and even if you disagreed with, if, say, Eugene McCarthy on one end and Richard Nixon on the other end, they were two pretty damn different political. people. But you kind of felt like they could at least converse and didn't believe that the other guy was was Hitler or or acting, you know, everybody was self-interest, of course, everybody's self-interest. But at least there was sort of a certain mutual respect and a willingness. It feels like we've lost the thread of conversation. And there's been this sort of, you know, complete balkanization and separation of and and and a lack of willingness to speak freely and a lot of people who will just immediately jump um on anything that you might say and and so it makes it really hard to to come up with you know the when I was at Bell Labs the best thing about

Bell Labs was the willingness of everybody to just say what was on their mind and to just argue things out and just boom, boom, boom. And it wasn't personal. I mean, one of the things that drives me nuts about science today is you'll go to a scientific talk. And somebody will give a talk and everybody at the end. Great talk. And there's no like, what did you mean by this in this talk? You'll still hear occasionally people outside of a room or something. Did you hear what he said about this? What is the problem with just talking and talking things through? This is how science is supposed to be done.

So even if even science has been affected to this point where, or everything is disinformation, right? There's no such thing as disinformation. There's information of various degrees of quality. Even something that's an outright falsehood is a type of information which is useful. Because once you understand that the person who said something is a falsehood and is holding it as a truth, you know that you should dial down how much you trust that source in the future. So that's valuable information. Okay.

Right. So, yeah. I believe people should have, I am the firmest advocate of free speech you will find. I totally believe that free speech is the fundamental right upon which everything good appears. You know, Elon has referred to this as sort of like the demarcation between truth seeking and political correctness seeking. Yes. You get the sense that we're leaning. towards this more. Well, there has been for a while. Yeah. I mean, again, you know, it's happened

over the course of my entire life. I have another pet theory. Again, I'm just rambling here, but until what is it, who would be the last? I guess who would be Bush the first? Those guys all went through World War II. There's nothing to kind of get you to feel like your fellow countryman is is on your side than having to fight together in a war. And since then, have we had a single president who's fought in the war? I don't think so. No. How many of the current congresspeople have fought in a war? I don't know. I'm sure it's less than it used to be. And I think to a degree that that's part of what's going on, right?

You're not willing to see the other person as being on your team and on your side, right? And there's also, you know, just look at history, right? You look at empires over history and how they devolve and how they, you know, it's the more power the more riches there are, the more spoils there are to be fought over at some point, right? And so, yeah, it's... What about the degree to which you want to attribute this to how lots and lots of people are equating algorithmic amplification? I was going to get to that as well.

I mean, that's, I certainly feel like in the last 10 years in particular, that this, this you know, it used, now propaganda has been with us forever, right? But propaganda used to be, to a certain degree, what an engineer like myself would call open loop. You know, you try something out and you cross your fingers and you hope some fraction of the people are swayed to buying Coke if that's what you're doing or whatever the heck it is, right? but once we had the internet the loop was closed right so you're able to find out exactly what are the

things that people are resonating with from your message immediately and to do that at scale right and so therefore you can figure out exactly what all our biases are and what buttons to push right to get to whatever your aim is whether it's to sell more coke or whether it's to get you to vote a certain way or to do whatever, right? And so, yeah, you know, I tend to believe that when we make decisions, the decisions are not conscious. Our conscious mind is nothing more than a way to rationalize decisions that we're making at a subconscious level, right? And they're trying to tie into your subconscious directly in order to influence how you make decisions, right? Man, I'm in the camp that believes that this machination of misinformation,

call it disinformation. Yeah, which I don't, but yeah. Yeah, it's on steroids. Yeah. And it's causing people to not be able to agree to disagree. Yeah, yeah, yeah, I know. But at the same time, remember I said, I am the most fervent free speech advocate you will find, right?

Yeah. So there's this contradiction, right? I don't think censorship is the way out of this. Anytime censorship has been applied, it has let us down a bad path where now instead of having competing forces trying to get into your subconscious. It's only one side. Yeah, yeah. Okay.

I'm with you. And so I don't have anything. answers to these problems. The primary way one can try to get out of this, which again has changed dramatically over the course of my lifetime, is critical thinking skills, which comes from education. And education over the course of my lifetime has dramatically declined in quality. And that is, I think, really a fundamental driver of a lot of our problems is the lack of critical thinking skills, which comes from a lack of good education.

And that's where we're paying the panel. Well, it gets worse to the developing economies, much less underdeveloped. If you go to many, if not most parts of Southeast Asia, 80 to 90% of the households are not headed by anybody with a tertiary education. Right, right, right. But that's like an effort, an effort we need to get them started. right yeah we have the inverse problem in a way right where where where where there's a lot of the developed world yeah where um where education has really declined you know the at sometimes i you know

i'll i'll be a conspiracy theorist and think this is intentional and sometimes i'll think it's just an a byproduct of our affluence um that it hasn't been as necessary education hasn't been as necessary to upward mobility or people have been sufficiently upward mobile that they haven't need, they haven't strove to get the degree of education that they got the so I don't know what are the total factors but the result is. Well, I can throw something at this. I mean, if if people are trying to equate algorithmic amplification with democracy slash free speech, which you and I kind of don't agree with.

This gets compounded by, I think, certain economic phenomena, inclusive of rising inequality of wealth, rising inequality of income, rising inequality of opportunities, and rising centipatalism of economic development. So this might, you know, resonate with. Yeah. No, I understand. Again, that's where you go down the conspiracy theorist, route, is that it's all part of a means to greater wealth for some fraction and less wealth for everybody else.

It's a hypothesis that seems reasonable. Do you see a fix to this? Midterm, long term? Not obviously. No. You know, again, throughout history, there's trends that extend until they break. Civilizational trends, yeah. Yeah.

And then there's a bit of it. Exactly. So who knows where, when, how, why. We'll hit a... You mentioned orders of magnitude a couple of times. And let's talk about Deep Seek. You've got certain views about this. Yeah. Again, I'll say this 100 times in this talk. There's many things I'm not an expert in. And so take my point of view on AI in particular with a grain assault. I've only become recently interested in the topic. But deep seek, yeah, I mean, from what I can tell is that it was a highly optimized solution as an LLM based off stuff from OpenAI that they've optimized. And they do a number of things in the model architecture to make it fast on inference that you don't need to use necessarily. the whole network for different tasks, but can actually use parts of the network. And that's called mixture of experts. So that's part of what they do. And another part is

lots of tweaks like every weight of the model instead of being like 16-bit precision. They figure out exactly what's the minimum precision necessary to reduce the compute costs. So with all of those tweaks, it looks quite impressive. But again, certainly should not take Chinese AI lightly by any stretch of the imagination, but it isn't like a Pearl Harbor type event in terms of the history of AI. How would you suggest that be tweaked as for anything like that or anything else to be inspirational to that 84% of humanity that doesn't have the kind of lifestyle that the Americans do. I mean,

we, you know, how to make AI inspirational? Well, no. I mean, how do you, how do you get the developing economies to be able to educate themselves? Uh-huh. To develop,

to modernize, you know, in a non-linear manner. Yeah. I mean, if that were true, meaning if Deep Seek were to be truly marginally more efficient, cost of,

effective and what have you, right? Somebody in Africa would be thinking, if they can do that for $5 or $6 million, maybe it's possible for us to be able to do it for $200,000 so that I can educate the masses. Yeah, I don't really see the connection there, honestly. I don't think that, you know, China's a long way away from, say, Ghana, okay, in terms of economic development and what can be done and what infrastructure was behind. Yeah. You know, what was involved in deep seek and how much it really costs and how much it depended upon. I'm looking at it more from a data intensity and energy intensity.

Yeah. I mean, if it's cheaper to energize it. Yeah. I mean, if it's got the compute power with less energy, I think that's inspiration. Yeah, certainly from an inference perspective, it will be cheaper. Yeah. Training it isn't clear that there was any real gain there. But from inference, yeah.

certainly that would make it more affordable for places to apply the model but at the same time you know the compute for inference can be anywhere particularly for an LLM it doesn't have to be local to any particular place

and how it would help or monetize developing economy I'm not sure I think there's more immediate needs for developing economies than AI. Than AI. Yeah.

Putting food on a table. Yeah, to begin. That's more than energy. Energy again. Energy is number one, right? Energy is the foundation of all modern civilization, right? So, yeah, clean and affordable energy is the start. That's what made China in the 20th century in America in the 19th century, right?

It was exactly that. Yeah. And in the 21st or 22nd century, It could make Africa, right? It could make the rest of the developing world. But it's really energy. It's the foundation. What do you think would have caused the divergence between China and the U.S.

in the last few decades? Which divergence? China going this way? The U.S. seemingly not going this way. Well, I mean, a couple things. First, China, say 1980, was starting from a very low baseline, right? And again, it was allowing, you know, allowing market forces finally after the Mao era, right? And I have many Chinese friends.

Most of my postdocs have been Chinese. My wife is Chinese. one of the things that I love about most of the Chinese people, at least I deal with, right? And obviously I'm seeing a distorted sample because people I deal with are the ones who've come over here. So it's highly distorted. Work ethic. Which you know very much about it. Yeah, exactly.

I think work ethic is central to everything. And the Chinese love to work. Harder than most. Harder than most. And so they work and they. Um, yeah. And they, they, you know, also great believers in family. Um, very strong family relationships. Um, very, uh, generally speaking, want to do better for their children. Uh, and, uh, and once they took the, the straight jacket off the economy, it was going to happen. You know, they started from a low base. Um, and, you know, you're hungry then, right? I mean, the U.S. suffers from, you know, affluence, right, that that's part of it. And the other things we've already talked about in terms of what's happened with politics and information and how it's weaponized, monetized, whatever.

But at the same time, considering how mature the U.S. economy is, and how large the U.S. economy is, it does pretty damn well. I mean, it's still a growing economy. You can't say that about much of the industrialized economy. It is, I saw, I don't know whether it's true, like many things that you see on the Internet, but there was a graph showing that in the last 50 years, there's many, many, companies that have exceeded in the U.S. $50 billion of market cap. So they said Home Depot, which is one of these, has a market cap bigger than all

startups in Europe over the past 50 years, the integral of all startups in Europe. What does that tell you about the difference between the U.S. and Europe? Yeah. And you see it. Europe is something else. Europe is becoming a museum. Yeah. A really nice museum.

But what do you think would have caused them to miss the plot? I don't know. I really don't know. I don't know whether it's a question of scale or again, this sort of vulcanization, right? I mean, there is the EU, but the countries are very. different in outlook and philosophy from one another. Yeah. I'm, you know.

And they seem to be pretty adamant on unionizing on lots of things, right? Well, unions are, despite the differences. Yeah. Unionization, you know, I'm, I've a mixed mind of unionization. I mean, I've seen both sides of the good and bad of it and not it. but I do feel like, I mean, particularly German, you know, I mean, I'm three quarters German, right? I don't speak German, but I have a, you know, I have a relationship with Carl Zeiss because they have some of our patents. And I really resonate with the technical Germans that I know and like that.

but I do not understand their politics. I don't understand the Green Party and where they're coming from. I don't understand the decisions they make. It seems economically suicide. And their car industry, which when I was, even back in the day in the 80s and 90s, when, you know, they were serious competitors. Oh, my. To say the least.

They're more of an afterthought now. Yeah. Especially if you take look at some of the recent products from China. Yeah, exactly. Oh, God. If BYD ever came over here. Oh, my gosh out. They're taking everybody.

Yeah, exactly. Exactly. Now, why couldn't Europe have made a BYD, right? You know, you think of Europe now as a hardware as opposed to software. Yeah. Yeah. You know, it's like everything they've invested is more for hardware. Yeah.

Certainly Scandinavia has done a little more on. the software side, right? But yeah, it's really strange to me that, that, um, uh, yeah.

Um, I, I, it's, it's hard to understand like coming out of World War II and, and the post war era and, and again, I can start weaving stupid conspiracy theories in my mind that maybe this was, this is by,

by intent and and maybe NATO and the EU are all part of trying to keep, keep, keep them from actually being completely independent and hence, you know, sort of tethered more to reality in terms of their economic decisions. I mean, you know, based on some of the stuff we talked about earlier, it just seems kind of intuitive that the imminence of the calculus or political

calculus moving to the right. Yeah. It is not to be underestimated. Yeah. Yeah. Certainly, that's, you know, things, I've watched it go this way, this way, this way. And I have no doubt that, you know, and the post-Trump error eventually will go back in the other direction, you know. But Europe has been for a while now pretty marching in sort of a leftist direction.

Yeah. And certainly AFD and other things are trying to. change that trend, whether they, whether they, you know, social programs are even more important. You see changes though in France, Italy, Hungary. Again, yeah, yeah, there's no question. There's some change, but the amount of change is TBD, I think, okay? Like I said, social programs are really, really key over there, right? Yeah. And, you know, if they had to increase military spending, they don't really have the option, right? I mean, You know, without affecting their social programs, which will cause a major backlash.

So, yeah, I, it's kind of sad. I mean, I, you know, I had a lot of good friends and collaborators from Western Europe. And, you know, I was there again this last summer. But I certainly wouldn't want to live there. Yeah. Hey, let's go back to your childhood. Yeah. You mean not a bold declaration that you're going to win Nobel by the time you turn 40.

To my sister. And a billionaire besides. Well, I think you could be or you would have been, you know. No. But you missed it by 14 years. Yeah, well, what the hell? Yeah. Not so bad.

Yeah. Honestly. What made you say that? Again, I've been heavily influenced by my dad, right? So in addition to hard work, the other thing that I have instilled in me is a desire to compete. Okay. I want to be the best at whatever I do. If I'm not the best at what I do, I'm exceptionally unhappy with myself.

Okay. And so I have the serious, you know, it's okay to be not the best tennis player in the world. Is it more paranoia, insecurity or jealousy? There's certainly that. There is certainly there that is that is certainly in a factor right. I always feel that that but I also feel that I should always, I should always give value for money. Okay.

That whatever I do should be more valuable to the people who's paying me to do it than the cost to do it, right? That's that's really influenced my research. throughout my whole thing. But as a kid, it was more like, I want to be the best at being interested in science. What is an indication of being the best that's winning a Nobel Prize, right? So it's like, you know, some kids say he's going to, you know, be on a Super Bowl team or whatever. Yeah, it doesn't, it doesn't mean, you know, anything except a kid feeling his outs about, you know, this is the goal I'm going to set myself, right? Okay. So I also said I'll be an astronaut, right? So one of them happened by weird circumstance, but many of the other things that I do have not. I'm not a billionaire.

I haven't been to the moon, you know, whatever, right? Was that why you wanted to go to Caltech? I wanted to go to Caltech, like I said, to first off, I want to do science. The jet propulsion stuff. Well, yeah. JPL was certainly one of the reasons that I chose Caltech as a place to be. But it was really, I wanted to be a scientist, I wanted to be a scientist to astronaut at some point. Caltech's reputation was a big deal.

Not bad. The Nobel laureates who were Feynman and Gellman and, you know, Delbrook and those guys. Yeah, it would be. So being the, and it was. small, right? And it was going to be a small little thing where it was small enough that I could measure myself, right? I could get pushed and I could measure myself. And although I work hard, I don't think I've ever worked harder in my life than I did at Caltech. That was, that was a meat grinder. Yeah. So much so that that after I graduated, I think I've had PTSD from being there. So I know until, until,

they invited me back after the Nobel, I never went back to that. I had no desire to get. I mean, I value the education I got there. What are we talking about here? 18 hour days or more? Yeah, yeah, at least. In seven days ago? So that was my first burnout. Okay. So in my, what was it? Junior year. Yeah. You know, because I insisted on getting a four point, right? So it wasn't enough to just graduate from Caltech. I wanted a 4.0 from Caltech, right? So it was, it was like round the clock, seven days a week of just study, study, study. And, and I was actually like, you know, my, my hair was starting to fall out. And I had eczema so bad, my face was like, you got a lot of hair still, oozing, you know, I mean, it was, it was like that level of hitting the wall, right? And so

there was one, a professor there that, that I respected a thermodynamics prof. And, And he said, you got to take some time off, you know. And so, and so I left after mid-junior year in the third trimester. I took that left and went to Europe and with my sister who wanted to go with her boyfriend, now husband. And they went to Italy and I went to the German Alps. And I just hiked up the same. My weight had ballooned during that time, too.

And so I went to Germany there, 210 pounds. I came back 155. Well done. After like six weeks. Well done. But when did you tell your sister that you wanted to win the Nobel? In college or when you were a kid? No, wait.

Like when I was a kid, like eight or nine or something like that. I mean, once I was in the Apollo and science thing and so forth. Yeah. It was really third grade is when I, Apollo hit me right from the beginning. but I remember it was third grade that I really wanted to become a scientist because there was a kid in my class in the elementary school whose father was a new assistant prof at the university. And so that kid was into science and then he turned me on to science. And I never looked back after that. But you know, you sound like you can talk about anything.

You would have been equally interested in other types of science. Other types of science, yeah. Or any topic. right? I mean, I'm interested in everything because everything influences everything, right? I mean, it's all interconnected, right? But I'm, I really consider myself an applied scientist. I'm a, I call myself an engineering physicist, right? Yeah. And I don't have, you know, I mean, I've obviously know a lot of Nobel laureates now, right? And most of them are, I feel feel like me. I mean, it's kind of like, you know, lightning struck kind of stuff, right? It's like, it could have been some other person who got struck by the lightning. But there is a subset

who were destined. I mean, just they have the brains or they have whatever that makes them different from the rest of us, right? And, yeah, those people are, those people are different. Okay, they're, they're just born different. They're born different. They're destined for greatness. And it just, you know, I mean, Feynman types, right? I mean, they're rare, a lot rarer than there are Nobel laureates, trust me. But, but yeah, for me, it's all about, I wanted to do science for practical good.

I was not the kind of guy who said, I really want to understand how why T cells do not disrupt cancer tumors, right? Like a Jim Allison or somebody like that, right? And or really delve deeply into the science, right? I like the science. I'm curious about the science. I'm very interested in science. but I'm not so driven by a specific problem or a specific hypothesis or anything. I want to make the warp drive.

I'm the guy who's going to want to do that, right? I'm not going to be the guy who's figuring out the theory behind the warp drive to begin with. Talk about or draw or connect the dots between your experience of the Bell Labs and your FSU experience, Florida State University. to you. That led you to the discovery. Bell Labs was by far the most influential thing I've, a place I've ever been at. It totally determines the way I believe science should be done. It was from what I learned there. So, you know.

Explain that? Yeah. So, you know, again, when I was at Cornell for graduate school, I was already working on a form of this super resolution microscopy to see smaller than what people thought was possible by a different means. And I like that project because, again, it was an engineering physics project, right? We're trying to, we believe that there's sort of a loophole in this law of physics that will allow us to do something that people didn't think could be done. We think this is a rational loophole. we start working on it.

But at the time, I was just, again, focused on the engineering of it and getting it done. I wasn't thinking about what I was going to do after graduate school. And I wasn't really interested in the idea of a postdoc or academia or I wanted to do something real. And this project was a good real thing. And so, you know, Bell Labs was not on my radar. are. But they would come and recruit on campus every year. And they would usually recruit the physicist. I was applied physics. So I'm not a real physicist, right? But they had an open door policy. So I came in and with my stuff and I took them down to see my microscope.

I work hard. And I work. That was a pretty cool microscope. And I think it impressed them. Okay. And so I got an interview and I went there and I prepared, they said prepare a half hour talk for the interview. So I prepared a half hour talk. It took me like two hours to skip that talk because they just interrupted me over and over and over. I have never seen anything like that before. And these were not random questions. These were ones that kept me really on my toes and made me think about things I hadn't thought of before. And I said, after the end of two hours, I said, I got to be at this place.

I got to be at this place. This is just so amazing that there are so many brilliant people who not only can push me, but who care, you know, to actually care to push me, right? And so, you know, I got the job. And at Bell, the most you could have was one postdoc and one technician, whether you had a Nobel Prize or whether you were a new hire. That's as big as you could get, okay, for your group. And so what did that mean? Well, there were a hundred principal investigators in one wing of the building where I was, right? what does it mean if you can only have two other people?

You're forced to collaborate, organically, not because, well, let's put eight people together who have similar interests to write an R.O.1 to the NIH, you know, a grant to the NIH. Because not that we really fit together well, but we're all kind of doing similar stuff, and we're more likely to get it together than separately, right? That's kind of the way it works, okay? Not there. Okay. It was like all of a sudden says, oh, you've got this microscope that can see really small.

Well, would you like to look at this optical fiber we have? Would you like to look at this laser we have? Or we have this new optical recording medium. Would you like to do that? Or, you know, we had got somebody upstairs doing some biology who would like, you know. And all of a sudden, I'm doing all these different applications. Every paper was different. With a different group doing a different thing, pushing me to my own,

making me learn more about science and technology across all sectors because by, you know, I don't know how many times I would be stuck on something and I would start reading the literature about something. Well, the expert is some guy who I passed a hundred times in the hallway but never talked to, right? It was amazing. And it was, it really, it really taught me about how science should be done. And I've learned a lot more through studying sort of history of science, how science should be done, and how far we've diverged from that in the United States.

And so last year I went back because one of my buddies, Lou Bruce, our 10th Nobel Prize out of Bell Labs, even now, even though it's long since been whittled down to nothing, they're still producing Nobel Prizes from work we were doing 30, 40 years ago, right? And yet, those lessons have been forgotten in the way we do science today. So, yeah, Bell Labs was... How many scientists were there?

It depends on where you draw the boundaries and what you call a scientist. So I was in the physical research division at Murray Hill. We had roughly in the physical research division, we had roughly... 100 PIs. In the building, there were probably 2,500 people between, you know, engineers doing like circuit stuff and other things, but we would interact with those people. That would have included the postdocs and... Yes. Well, no, 100 PIs, so now multiplied by roughly 2, 2.5 in terms of their staff. So, 250, something like that. But yeah, I mean, just lapping the world in almost every field, right?

It was awesome. And again, we worked like slaves. You had a bit of a burnout in 92, right? Yeah. So was it 92? It was more like 94. When you joined an 88, right? I joined an 88 and burned out in 94.

Okay. Yeah. So again, it was the same thing, right? It's like the Caltech thing, right? Is the, so again, I met my best friend and the guy who did the palm with me for the Nobel, Harold Hess there. And yeah, we would come in 4.30 in the morning. That's crazy, man.

We would, we would, you know, if he beat me, there's spot number one, spot number two, right closest to the door to go in. And if he beat me, I'd put my hand on the hood of his car to find out by temperature, how many minutes he beat me by. Because we were both incredibly competitive, but best friends. Then when the sun rose, we would go to the high school tennis court and pay tennis, then we come back and work. We worked to dinner.

Like half a mile away was the same Chinese restaurant we'd eat at every night. Then we'd go back to work and work till 10 and do that seven days a week. Right. So we both made really great, did great science here. Both of us really great science. Our stuff was, he was doing another what's called scan probe microscopy different from my technique. But it was similar enough that, that we had a lot of overlap. He was from the Midwest. I was from the Midwest. We're still

best friends. And yeah, so I did a lot of things. Once my techniques started working well, we applied it to everything under the sun. And in the end, basically, I mean, part of it was the burnout, but part of it was finding the limitations of that technology. And basically, I did every application that it was good for, I did. And then I kind of run out of applications. It was good for. And I was like, I was going to have to pivot one way or another, right? It was time to pivot, but everything was so invested in that.

I hadn't even had any time to think about the future. And while my boss, Horstormer, who also won a Nobel, the guy who hired me, said, well, just stay on and think about what you want to do next. I didn't want to stay for two reasons. The first is that you could already tell the culture was changing. Because once in 84 was when they broke up the monopoly. But it didn't really affect us impact-wise until about 10 years later. Right. And then you could kind of see people were being forced to start thinking about the bottom line,

which is fine. I mean, as a company, it's their money. That's fine. it was different from the culture that existed before. But the other thing was, was that even if I stayed and tried to think about something new, I just have this thing inside of me that I feel like if there's a day in which I don't feel like I earn my paycheck, I feel really shitty, okay? If I don't feel like I created value during that day and just I know there's value in trying to think about something new, but this sort of like tightness in the chest about the days passing and I still don't have a new idea.

I'd rather do that on my own dime, okay, rather than forcing somebody else to pay me for while I, because I know what's going to happen is I'm going to make bad decisions because I have this tightness. I'm going to choose something too early and that may not be the right decision, not fully take the blinders off to think about what's the right decision. And so the best decision was the decision I made, which was to quit. What you do? You went to the Alps again? No, by that time I was married. We had had our first kid the year before. I was a house out of this.

So my wife had a job. And so I was helping take care of the baby. and so it was like, what was it, how many months after I left, three to six months after I left, I was pushing my daughter in the stroller, and I wasn't trying to think about what I used to do, but it popped in my head that two experiments I did with my old microscope. The first one was, I was the first person to be able to not only see single fluorescent molecules at room temperature, The other guy who shared the Nobel with me was first to see it at liquid helium near absolute zero. But I was able with my microscope to see them at room temperature.

Which was a breakthrough. Yeah, it was a breakthrough of sorts. And furthermore, I was able to determine by trying, you see a fuzzy ball. And yes, it's a smaller than the diffraction limit fuzzy ball, but it's still a fuzzy ball. But you can point to the center of the fuzzy ball with better precision, the diameter. So that's what I did. And so I could say, this molecule is here to within, you know, a hundredth of the wavelength of light.

I could tell where it was, right? So that idea, plus with my friend Harold, the last experiment we did with something in his microscope, but with my technique, where we were looking at these semiconductor structures that are used to make semiconductor lasers. So they'll glow with light. And we were able to show that where the light is generated, where the electrons combine to create photons that create light, it isn't just anywhere, but there's these little potholes in these structures where they're created.

And even though there's way too many potholes to resolve, even with my high-resolution optical technique, because every one of those photons of light that were coming out, they were all slightly different colors. So if we put it in a spectrometer, we could isolate them and study them individually and then look at those fuzzy blobs and then localize. So the idea was, you know, you have two steps. You have an isolation of lots of discrete things. Right. right? And the second is to localize, figure out where they are, to better than their fuzzy

blobs in the microscope. So I put those two ideas together while pushing my dog in the stroller and said, well, gee, just the general concept is to isolate discrete objects in a higher dimensional space. In that particular case, that third dimension was wavelength, but it could be anything. And I pitched it as any higher dimensionality. Okay. And then once you've done that, you have these fuzzy blobs at the resolution of your microscope. You find the centers of the fuzzy blobs. And then you project all that back down to the spatial coordinates. And now you've determined where every particle is to high precision. So that was the idea. So I was unemployed. I was interested in that idea, enough that I was working, I was paying,

you know, my own money and some little office park and some, it wasn't even as big as this room, right, where I had a PC and stuff and I would do some simulations. So I wrote up this paper on my own, as called myself New Millennium Research LLC. You know, I had an LLC. And I published that paper, and that was that. And I was thinking about doing it, but at that time, there wasn't a good way of doing that discrimination, except by color at low temperature. And what good was this for doing live image?

From the beginning, the dream was to be able to look at living cells with the resolution of electron microscope. Well, cells are not alive at absolute zero. So I wasn't interested enough to try to then get into a lab and do it. But I published the paper while I was an LLC, aka unemployed. And that was one of the two papers in Nobel Committee's side for giving me the prize. The other paper, was that written after you went to Tallahassee? Yes, so we'll get to that. Okay.

Sorry, I'll cut you off. So, so that was the first paper, right? And so unemployed, published that, that was that. Then I ended up working in the machine tool industry for my dad for six years and then eventually burnt out of that. And so then I'm on. Burned some money too. I burnt some of my dad's money too.

And once that was done, and then again, I'm unemployed. And now it's 2002. That's right, 2002. Hang on. Was your daddy pissed? It's interesting working for your father. Let's just say that. It's pretty uncomfortable now.

Well, we're so similar. He and I were so similar, right? Because incredibly competitive, you know, incredibly hardworking. but he was the boss, right? I mean, it was his company, right? So it's hard, right? And he'd been doing that business for 30 years already, and I was just new to that business.

And I was telling him, you know, this business is changing. You don't have much time, okay? And he had gone through so many business cycles of recessions and growth and like that. He says when he loved recessions because it squeezed out. all the weak competition, right? And then they would make it back in spades during the next stop. I'm saying, this is more, more, you know, cataclysmic than that. There is a long-term trend that is killing your business, and you need to come up with.

You're trying to tell this to a guy who's been doing this for his whole life, and has been wildly successful doing it, right? So it's like, anyway, so we can get back into that story later, if you want, But in any case, let's just say in the end, my scheme didn't work out. Okay. And so that and the burnout again, because, again, I tried like hell to make it work out. So it worked crazy hours. And so in 2002, when I left, yeah, again, it was back to trying to think about what to do next.

And, you know, that idea I had published was kind of in the back of my mind, but it wasn't exactly where I wanted to go. I kept saying to myself, there's only two things I know at this point in my life. Did you feel that that was not, or it was going to be game changing? The original idea. No. Really? No, I thought it was a good idea that needs to be out there so other people can, but, you know, until the Nobel, it was probably one of my least cited papers of all time, right? I mean, it was probably decided maybe a dozen times.

Now it's been cited like 600 times. I've got another paper on optical lattices, which has been polished about 20 times. I'm more proud of that paper than probably any but about two or three other papers in my career. But it's been cited about 20 times. But that's the don't believe citations. That's a horrible metric. Does that explain to some extent how ideas are not recognized or how ideas are recognized? Yeah.

Yeah. I mean, you know, I told you at the beginning of this, right, is bandwagon. right? I mean, it's when, you know, it's kind of little red hen, right? Who will help me bake the bread, all of this? Well, once the bread is baked, a lot of people want to come and help eat it, right? But there's a lot of work to make the bread, okay? So it was an idea. It was there, and it wasn't really at the top of my mind. And I kept saying to myself, you know, I'm now in my 40s, right? I've done 10. two things with my life. I've done super resolution microscopy and I've done machine tools. And the two

things I knew I didn't want to do going forward with either super resolution micros or any microsby for that matter or machine tools. Okay. I wanted to do something new. So I want to take the blinders off and look. And, you know, I had crazy ideas about like doing powered exoskeletons and, you know, things like that that kind of built off the machine tool thing. And, and, but I had forgotten a lot of. But I had forgotten a lot of science during those years I was in my dad's company. And so I just started going back over my old homework sets from Caltech and trying to relearn stuff. And in the end, I became far more competent of physicists by relearning that stuff, not because I was trying to get a grade now, but because I really cared about knowing it. Okay. That's what led to this paper that got

the 20 citations, right? It was a theory of diffraction and optical lattices that... Diffraction limits? Well, not so much, but ways one can manipulate light to make interesting patterns that eventually got used in my optical lattice microscope eventually, but not fully. It's a more broad idea that I think still has broader implications that people haven't followed up on. But anyway.

So first I had to learn, and then after I kind of learned, I started reading the scientific literature again. And I think, again, one of the big problems scientists have is that they go to too many talks, they go to too many conferences, and they read too many papers. And as a result, they start thinking too much like other people and what the current thing is, as opposed to what the next thing should be, right? When you said papers as in newspapers. No, I'm saying like journals, you know, scientific journals, right? And so I started peeking at the literature, which I hadn't looked at since I was doing machine tools.

And one of the first things I ran across was this thing called green fluorescent protein. So this one, the Nobel bell in 2008. But again, I was learning about it in 2002. It first came out in like 1994 right after I left science. If I had seen the paper on green fluorescent protein, I would have had my next thing at Bell Labs. Because what they did is they took part of the DNA of a jellyfish, splice it to any protein you want, and then you can make a glow. When I was trying to do biology by my old technique, it was so difficult because no technology. existed to get fluorescent labels to light up the proteins with enough specificity without

attaching to everything else you don't want it to or not being dense enough to decorate it finally enough to see the structure but with green fluorescent protein the cell did it all for you and I knew this was going to transform my cross it hadn't really yet even as of 2002 okay sorry that that paper was written in 94 94. And it won the Nobel in 2008. And it won the Nobel in 2008. And you had not read it in 94.

It came out months after I left. Ouch. Yeah. Yeah. And I was thinking about what to do next and eventually machine tools. I wasn't looking at the literature. No. And I just couldn't believe how elegant that was.

And so I said, I got to do microscopy again. This is going to change everything because you can do it in live cells. I'm going to make a microscope to do live cell imaging, okay? Because my old technique could only look at fixed and dead cells. And so I said, okay, so what can I do? So I had been working on ideas or working to learn the literature. Like I say, I got to know physics better than I ever knew before. And I started thinking about, I knew what my microscopy tools were in the field at the time, and I knew their limitations.

And I started thinking about, well, can I come up with ways to get around that? And that's where I came up with this theory of optical lattices. And that paper that's been cited 20 times. And then I said, now, okay, I've got an idea. I can make this massively parallel series of spots that will be incredibly fast at doing live cell imaging of cells with GFP. So that's the idea. Now I got a problem is I've got an idea. I just don't have any money or a lab to do it in.

And so I called up Harold, my buddy from Bell, who as Bell continued to shrink, he ended up working for going out to the West Coast working for a startup that was making test equipment for disk drive industry. And then that got gobbled up by KLA 10 Corps, a larger sort of semiconductor manufacturing company. And then he and I just started meeting in different national parks. And he was talking about his, you know, how much we both misspell so much. And how, you know, how, you know, How, you know, his stuff was going fine, but he was still kind of missing science. I was missing science. I hated all the shit about science.

I hated conferences. I hated, you know, reviewing articles. I hated all that nonsense. But I missed science itself. I missed the freedom to think and do that stuff. And I wanted to find, how could I? Bell Labs doesn't exist anymore. How am I going to ever find a place?

I wasn't interested in going to academia. How was this going to happen? How was I going to be able to do this idea? So we thought, you know, he liked my idea, but he didn't really want to do it because he said it would be chewing my cut. He's just as much, you know, a competitor and self-interested as I am. And I'm sure I would have said the same thing if he came to me with the idea, right? is it seems worth doing, but it's not my. But he was willing to help me, right?

Find a place because he was still a little bit connected to some of the old Bell types. So I tried knocking on several doors, and then this is where Florida State comes in because, and the Bell Labs network saved my. The fact that I had a good reputation from the time I was at Bell, Well, once there was this diaspora after Bell imploded, right? How many in total? The diaspora? Again, again, probably how many people?

In the tens of thousands? Again, on the order of 100, right, that physical research division, to this day in condensed matter physics, they still basically, all of these old farts now, right? They're still basically control the APS meetings, right? This would be in the hundreds or thousands or hundreds of thousands? Hundreds. Yeah, hundreds. Wow. But, but, so I was known still, right? I mean, I was, I was the weirdo who, who had this great success and then, and then just fell off the face of the earth, right?

So I was known for that, but so they knew me. And so with Harold's help, you know, we were trying, I was trying to rely on Harold, was one of those contexts, but others tried to get into a lab to try to do this idea of, of this live. imaging with GFP. And Harold is the only guy I will say is the better scientist. Okay, he is the best scientist I've ever known because I'm good in a lab, but he's also theoretically, as good as theoretician as he is an experimentalist. And he's Michelangelo with a screwdriver in the lab. So you can imagine how good he is as a theorist.

So one of the many people of this diaspora was a guy named Greg Bobinger, who was a colleague of ours, who was working on super high magnetic field magnets for experiments. And he ended up becoming the director of the National High Magnetic Field Lab in Tallahassee at Florida State. And he had been trying to recruit Harold to become chief scientist for the magnet lab. But Harold wasn't interested in being a chief anything. And so during that trip, he had met this other guy who didn't have a PhD, who was involved in doing microscopic measurements of like the wires that go into these superconducting magnets and stuff like that.

But he had at one time put a powdered cocktail mix under a polarized light microscope, took pictures of it and printed on neckties. He sold enough to make millions of dollars off of that. So he funded his own live cell imaging research. So when Harold visited, he had learned about this guy, Mike Davidson, who had self-funded his own research because he had the bug too of GFP live-cell imaging. We thought this would make a good match. So we went together to Tallahassee to talk to Mike.

and, you know, the three of us hit it off quite well. I mean, he's an oddball, too. He never was a scientist, really, you know, but he became a scientist. And so live cell imaging was in that era about fluorescent proteins like GFP. Well, people wanted other colors, other ways to label other proteins at the same time. And so Mike had hired this army of failing undergraduates to become. molecular biologists to clone. So we had the world's largest library of fluorescent proteins and an array of microscopes

to look at them and test them out. But not for any, they were just making the library. They weren't doing any real science with it. And there's other groups elsewhere. So we went there and Mike and I kind of hit it off, but it wasn't clear whether he'd have space or money for me to build my fancy microscope. understood what its utility would be. There would be so much faster and less damaging to cells than the standard tools that

people use. But we kind of left it at that, except one thing he said was that there was now this new kind of fluorescent protein, that instead of just you hit it with blue light and it glows green, you hit it with blue light, nothing happens. But if you hit it with violet light first, it then goes to a state. where when you hit it was blue light, it goes. So, okay, that's fine. So Harold and I are going to the airport.

We're sitting in the airport to go. And then it was like, holy, do you realize that if you turn down that violet light so low, only a few proteins will come on at the same time? Then they'll be physically isolated enough that we can find their, so that idea I had 10 years ago, it's now fallen in an or lapse. It would be the easiest experiment ever to do.

And guess what? We got this guy, Mike, who can make all of these fluorescent protein fusions with that weird protein now to do it. Okay. So all that was great. Okay. So this was part of my trajectory of trying to get back into science. I called in every contact I had had.

Now there's this crazy domino effect that's happening in April and May of 2005. So first, the first part was that trip to Florida State. But even before then, I had set up two talks. One at NIH, because there was this guy Rob Tico, who I knew at Bell, who was doing NMR. And I asked him, could I give a talk there to try to drum up interest in my live cell imaging idea? And the other one was at Columbia, because my old boss horsed. After he won the Nobel, he went to Columbia. And I told him about my D.A. said, fine, come and give a talk, but don't give him the physics.

department where I am, give it in biology. So who did he get in biology to do it? Marty Chalfee. You know who Marty Chalfee is? The guy who discovered GFP. Okay. So that talk was set up. The talk at NIH was set up.

Florida State was the week before. So we come up with the idea. And so first I go to NIH. Well, once GFP existed, who was the person who invented the photo act available form. Jennifer Lippen-Cotch, Schwartz, and George Patterson, where were they?

At NIH. So the week after, it was like, I told Rob Tico, please, please, please invite these two people to come to my talk. I need to see them. Okay. So they came to the talk, and I took him to lunch, and I said, this is a secret. But my buddy and I have this idea for try to make this,

easy super resolution microscope. And we need your photo-activated fluorescent proteins make work. Can we work with you? If we build an instrument, can we bring it to your lab? Because we're not biologists. We don't know what to do biologically. And Jennifer said, fantastic, sure. So that was all set up.

And so now Harold said, Harold said, okay, I'm going in with you on this idea because I'm not chewing your cud. This is mutually developed intellectual property, right? and so boom, then we put pedal to metal, start designing the microscope. My laugh line from my talk is that Harold's much smarter than I am because when I left Bell, I told them to all go to hell. But when he left Bell, he was able to take all of his old equipment with him.

So a lot of this equipment was the optics equipment we used to do that semiconductor quantum well experiment that was going to be damn useful for us to be able to build our new microscope. So that was all sitting in a storage shed in La Jolla. So we took that out. And then we had to put a lot less of our own money in it to build our money. So we built the microscope on his living room floor. We built it in three months. And then we were ready to ship it to NIH.

And then at the same time, just the week after the NIH trip, I went to Columbia to give the talk there. And this would have felt different. this time around compared to 94. Yes, yes. And you knew something was... Oh, yeah. We were... Wanted to something big.

The idea is so simple. Yeah. That once you learn a photo activated fluorescent proteins and you're aware of my earlier paper, it's obvious. I mean, incredibly obvious. We were terrified of getting scooped. Okay. We knew it had to be... You don't write a grant.

You don't get VC funding. You open your own checkbook and you'd do it. Okay. That's it. Okay. Um, there's a lot of money. We'd probably put 50,000 in, which when you're unemployed. Yeah, he was still working. I was unemployed, right? And I'd been unemployed now for two years by this point, right? So, uh, it was an ouch, but, you know, you know, it, yeah. What? You got, you got to do it. So, um, so the, so then I give the talk of Columbia. And Marty's my host, like I said. I give a talk about this microscope, but because it's still all theoretical, right, it was probably too physics-y for the bio-crowd.

But they could kind of understand when I said it would be this much faster, this much less invasive than your existing microscopes. And so, in academia, you give a talk, they'd take you out to dinner afterwards. So we're in the cab going to dinner, and Marty turns to me and said, well that was certainly an interesting concept. How are you going to do this? And I said, well, I don't know, but I read last week in physics today, which is sort of a monthly journal, that there's this guy I've never heard of called Jerry Rubin, who works for some institute. I've never heard of called the Howard Hughes Medical Institute. And he wants to make a biological Bell Labs, the way he put it. And, you know, I love Bell Labs. Something like that would be awesome. And Marty said, well, you know, you're probably going to have to reestablish your reputation first or something, you know, but maybe someday that would be an option, right? This, you know, by this time, you know, Marty's already on the short list for the Nobel and stuff, but, and Horst had already won the Nobel. And so, and so I kind of figured that was that,

right and then a week later i get a call cold call says hi my name is jerry rubin i was at party last week with marty chelfy he said you might be interested in genelia oh my gosh that's when it happened and well well genelia wasn't necessary to get the palm done but but still this was 2005 still 2004 still oh my god all of this happened in april and may of 2004 of 2004 okay okay Yeah. A month before that, I was, I was in despair that, that, you know. You're in Virginia. Well, no, at this time I was still in Michigan, right? I was in Michigan, right, doing the, because that's where I stayed after, after I left my dad's company, right?

And so I figured I was washed up. And so all of that happened. And then Harold and I are racing to build the microscope. We have it done in September. we ship a 10 iH we stopped by genelia on the way which is just you know a few advisors jerry and a mud pit and a steel frame and there's a little outbuilding that we went and i said you got to talk to this guy harold because he's fantastic you should hire this guy here and harold just opens up the suitcase the whole microscope fit in a suitcase and so he opens up the suitcase and they were

kind of sold wow and then we and then because that was just Sorry, this was the old leftover equipment from Bell Labs. Yeah, we had to, and then the other 50,000 of each of us to machine parts and stuff or things that they were, it's amazing coming back to science after 10 years. I felt like Rip Van Winkle because there was so much new technical widgetry that I could use as an engineer that didn't exist 10 years previously. So it all became much easier than even I thought it would be. It was, it was like, you know, trying to knock down a ducid tree. door and it's not bolt and it's false. It was that easy. And

a month later we had, we put in our first sample where we just put on these photo activated proteins just on a cover slip and turned on the violet light, boom. And we say, we got it. This is going to work. Wow. And the rest of it was just dotting eyes, crossing teas and for the paper. But yeah, it was just, yeah. To what extent would you attribute this to serendipity? Just being able to walk out of whatever you got burnt out with and then pursue something else. Yeah. Then just seize the moment.

It's, of course, serendipity, right? I mean, you know, it's like, generally speaking, I feel if you work hard and have a good heart, you will be successful. You know, that will determine success deterministically. What you're successful at will be complete luck. But you just keep shots on goal, more shots on goal, more shots on goal, right? And sooner or later, something will click. What sort of degrees of magnitude was this about? In terms of resolution, in terms of whatever.

Factor of 20 or something. Between 9.4 and 2005? In terms of, well, my old microscope could get about a, so in using units that probably don't matter much of the people talking. The old microscopes would have a limit of around 200, what's called nanometers, okay, which is about roughly 200 protein molecules wide, something like that, okay? My next microscope, the one I developed at Cornell and Bell, could see down to maybe about 50. This can see down to about 10, okay?

So, so boom. But the other one could never look at live cells or there were many, many limitations of the ones I developed at Bell. that were put away by the new microscope, which is easy enough to build yourself in your living room floor. Wow. That's how. And so, poof, talk about bandwagons and science. This is a bandwagon that grew really fast. Talk about photo-toxitic.

Yeah, toxicity. Yeah. So basically, you know, if you go out to the beach, you're going to get a sunburn, right? So since we're using light to look at cells, you will do some damage from the light when you look at the sample. This ended up turning out to be, this has been a problem all along in biology for any kind of, it became even more of a problem once fluorescence came on the scene because you need

more light generally to excite these little glowing molecules, right? And you use lasers to do it, so forth. So part of my idea with this massive multifocal thing was a way of distributing the light. So it wouldn't have to be as intense at any one spot, right, in order to do this. And with the super resolution technique called Palm, photoactivated localization microscopy, you have to put quite a bit of light on it. And that violet, particularly viola light is really damaging the cells. And it was violet light that you used to photoact.

You didn't need a lot, but still wasn't great. And so that was turned out that for all the excitement about that technique, we eventually did live cell imaging with it. But it's because you're turning on molecules just a few at a time, and you have to turn on then repeat that process tens of thousands of times to get every molecule figured out. it's slow, right? Because you have to do that over and over and over again,

and you're throwing more and more light at the specimen. So it really burned into my brain. What I already knew, but really put it in is that there's always trade-offs. And if you want to have an image that has more pixels in it to have more resolution, it means you're making more measurements. If you're taking more measurements,

it's going to take more time. If you make those measurements by throwing damaging light at it, it's going to do more damage if you have more pixels. So there's always these tradeoffs of resolution, phototoxicity, speed of imaging, depth of imaging. I make this little tetrahedral pyramid in my talks in which I described that. And Palm is all about going as far as you can up to that one vertex of that pyramid resolution. And once I got sick of Palm, has burned out a palm, you know, by, what, 2008?

So it was my life from 2004 to 2008. But at 2008, I knew what all its limitations were, right? This is exactly when the rest of the world is catching up and thinking it's going to do everything, right? And I'm already well past that point. I know exactly what it meant. And they think it's going to do this, this and this. Now, I can't do that. Been there, done that.

But they don't listen. They don't listen because the incentives aren't. structured for them. The incentives are there for them to write lots of grants. And of course, it's, it's, it's, it's, there's prizes to be had and awards be won and all of this stuff. And so, yeah, it was a gold rush for sure. But yeah, I pretty much turned my back on that gold rush long before the Nobel Prize. Yeah, I didn't care about prizes. I cared about, you know, I knew what it was good for. It has, it has great. And, and, and eventually, the thing that worked was, was around that time was this guy Bob Teigen, who was president of

HHMI at the time. He was a molecular biologist who was one of the pioneers of really describing how that there's the central dogman biology is that you start with DNA and every cell in your body has the same DNA. And in order to make the proteins that actually do the work, the enzymatic reactions and all that that make the cell, there's an intermediate called RNA. So DNA is a template to make RNA that's called transcription, that process. And then the RNA goes into things called ribosomes, and then spit out proteins that then become the rest of the cell.

So obviously it's a key player, that RNA. And so he had studied the whole process about how DNA is made in RNA transcription. And there's a lot of proteins that are involved in that process. And they thought he had done all this molecular biology, or not biochemistry, to determine what proteins were involved in what sequence and so forth to do this. And this fills textbooks. And he had the brilliant idea to use our microscope. When we were at Janelia, we collaborated.

And we said, let's look at live cells. And let's just look at these protein molecules that are involved in the transatlope. transcriptional process. And there were key players that were known from the biochemistry, and they thought that these things bind to the DNA for considerably long periods of time, because multiple ones have to eventually get to the spot in order to start the process. What they found is that no molecule bound for more than a second or two. And their models and their heads were they bind for minutes or hours. And so it completely blew apart what Watson and Crick and all those guys had done to develop this central dogma of molecular biology.

It was there, the, the outlines are right, but the details were totally, it's the problem that biologists always have is because they can't see what they're looking at. They're making hypotheses in their head on the basis of Western blots or, you know, basically these things that, that tell them what proteins are there. life is the most complicated matter in the known universe. Every cell of your body has 20 million protein molecules of 20,000 different types banging around like this under Brownian motion. And that an emergent process of how they stick together eventually makes larger and larger

structures that create cells, that create tissues, that create you and me. and it all is down to single molecules randomly bouncing around, and that's crazy. But we understand neutron stars better than we understand a cell. And this idea of just look at it, okay, just immediately blows away a lot of hypotheses that you have, right? This is the power of live imaging, right? And so that then led to, you know, well, why do they,

Why do they even, why do certain molecules stick together? Why do they only stick as long as they do? How does this process work? Well, it turned out in this particular case that these protein molecules had parts of the protein that don't fold like normal proteins in the normal confirmation. They're called intrinsically disordered regions, right? And they're like brillo. Okay. They can, when they're with the right partner, they can be more sticky when they bounce instead of immediately bouncing off.

turns out a number of diseases are due to either the absence or the addition of intrinsically disorder regions from mutations that shouldn't be there. So then Tej has the idea that, well, we have a tool now that can see when the kinetics of proteins have been affected by some kind of disease. Well, maybe this can be a drug discovery screen, you know, because then we can put different compounds on and see if we can we can find out what is the normal non-diseased phenotype of these kinetics. Then we can take cells that are the ones that have the disease phenotype and put different

compounds on and see if we can recapitulate the undiseased phenotype of motion with these compounds. And then so teach had the brilliant idea. So the reason I met at Berkeley and I have no affinity for academia. Not where your wife is there. My wife, well, there's two reasons I'm at Berkeley. My wife is a graduate student in Berkeley. Always love Berkeley.

Want to be at Berkeley. So, we're a Berkeley. So that's reason one. But the other reason is Teague needed me here to help start the startup company because I had the shiny metal to help get in the door with other VCs, right? And so, so, yeah, so he droid. I got to learn the VC culture because we've been all across. the bay talking to VCs and starting a company.

And so that's icon therapeutics. And so that opened in 2019. And at first it was kind of a little fumbly. And then by some kind of weird providence, I don't understand. There's somebody up there who likes me. A guy who got interested in was this guy, Roger Perlmuter. Okay. So Roger, Roger's brilliant.

He started first at Caltech as. as a new professor, then went to University of Washington, then became head of research at Amgen, and then became head of research at Merck, and then became also an executive vice president at Merck. He led the development of Keatruda, which is, I'm sure you know, one of the biggest immunoncology drugs out there. And he was interested. He thought, you know, as Roger says, it's a miracle that any drug makes it to market. Because we don't know the connection between a compound and all the stages, the mechanisms of action going all the way up. So all the clinical trials, phase one,

of phase three is it's such a crapshoot because you're just, you know, you're just like, and so the idea. Sounds pretty controversial. So the idea of being able to see what's happening at some scale and using that as a screen could be really accelerating, right? And so he was intrigued by ICON and he came in as the CEO and then he took the head of clinical development, Roy Baines at Merck with him. He took the head of business development at Merck, Ben Thorner with him, and so now ICON is Merck 2.0.

They've got a compound, not a compound from the screen yet, but they bought some compounds since they were able to get a lot of VC cash from China. That actually, the first one, which is already in phase three, works in concert with Ketruda to make it better. if it comes out of phase three, they'll be on their way. You should be able to get some money from South Asia. But it could crash and burn. But they just did their series D, right? They have no problem raising money, not with the pedigree of those guys. They could be selling bottle caps, okay?

It's not about the single molecule, but the single molecule screen is important. We got stuff that's about to go and. phase one that is coming out of that screen. And it's been really useful for optimizing SAR, structure activity relationship. So, you know, as Roger said, most of the time he feels like he's been one carbon or one hydrogen in the compound away from a good drug, right? But with these screens, you know, you can, you can have medicinal chemists tweak every carbon and every hydrogen. And very quickly, with the single molecule screen, find out exactly how it affects the You can do that the same day.

You know, so it's, it's, and I think this is just the start because, you know, we have micros, we haven't even gotten all the microscopes I've developed since there. By being a genelia was for the first 10 years was Bell Labs 2.0. And, and we kicked ass. I mean, we developed microscopes. We lapped the, I never had a group bigger than three in those 10 years, and we lapped the world. with great microscopes. And those microscopes, when they get brought to bear on drug discovery,

I think they're going to be really impactful as well. You've been talking about translational medicine, right? Yeah. How translational is this? Will this get a lot more translational in the future? Yeah, yeah, absolutely. With your discovery? Yeah, I think so.

Yeah, absolutely. Yeah, that's what icons about, right? Is compounds to help people. Again, I don't, I still can't understand, particularly in the 2014 era, why Palm won a Nobel Prize. I don't think it's that. But if thanks to Tejj, thanks to Roger, if it ends up leading to therapeutics that significantly help people's lives, and if in the dream level beyond that actually changed the course of how drug discovery is done, hell yeah. Then it's worth an Oval price. Give one or two examples how this thing is going to be translational.

Well, again, like I say, in the end, at the most fundamental level, a lot of diseases are related to how proteins come together. Okay. And so, you know, another big areas, for example, the membranless organelles are phase condensates or stuff like. is another big field in biology right now. All of that's about how molecules come together to form these compartments and so forth. So molecules have to work in – proteins have to work in concert for enzymatic reactions, and they have to even be able to get together to do enzymatic reactions. By being able to directly visualize their ability to come together or not,

you're getting right at the most fundamental level about how life is happening, right? So I didn't really appreciate this when Teague was on this kick at the beginning. But now I understand it could be a really, really big deal. It's like facial recognition. Well, I don't know if I make that analogy. I would respect to molecules. It's just again, when you're a scientist with limited tools, and we're all limited in our tools to understand the universe,

you hypothesize, you guess, right? Your mind starts to wander. There's nothing like a little bit of direct observation to really kind of, you know, bring it back down to earth, right? And that's what imaging really does. It's a very powerful tool in that regard. So I lucked into it. Yeah.

Talk about when you got that phone call, when they told you that you won something really big. Yeah. that was that was a weird day um so i was uh in munich uh to give a talk um i was going to be the keynote and that so it's uh yeah i guess it's still what was it i guess morning over there or whatever right and so uh my my host was a professor there um and uh so i was actually working on he had gone out of the office before the thing and I was there myself in his office and I was working on the proofs of my what's we may eventually get to this lattice light sheet microscopy paper which in fact my opinion is a paper I'm most proud of in my whole career um and my focus was

entirely on lattice light sheet microscopy and what this would mean for biology and so forth and and then my phone buzzes and I look at it and I don't I wasn't thinking hey it's early October hey people are talking Nobel Prize or whatever I was not in my mind at all but as soon as I saw it was a European number I just said oh to myself I mean I just I it just felt like the floor fell out I felt like my heart just kind of fell to the ground because you know I was so hyper focused on my lattice light sheet stuff and I just started shaking. You didn't even think you would have been or could have been that organizer at the Munich event or what? No, I don't know how, I don't know how, but I knew who was on the other end of that call.

And so I go yes and say, it was this Dr. Betsy and say yes. And I'd like to congratulate you on sharing the Nobel Prize in chemistry. and I'm, well, gee, it was a very brief call, you know, I said, you know, we'll be in contact with more details or, that's pretty calm, man, or whatever. You didn't shout or scream or joke or what? It got flabbergasted is just the way to put it, right? Because to me, I've said this many times, it felt like getting hit by a bus.

because, look, obviously I was happy. I would have been, let's just say that if other people in the field got it and I did not, you would have been pissed. I would have been bitter, right? I would have been bitter. I mean, one of the most amazing things about Harold is that he's as pure a heart of scientists as you will ever find. He doesn't care about it. You know, it didn't hurt our relationship at all that he didn't.

He took all the risk I took in order to do all of that. But because only three can get it, Harold didn't get it. He deserved it, but he didn't get it. So they took that paper I did, you know, the concept paper by myself as well as the paper we did together, which was the other one they cited once we actually did it. In his shoot, if the things were flipped, I still would have been real good for. friends with him, but I would have harbored this bitterness. I have never, in the 11 years since, ever felt even the touch of bitterness on his part about this. He's an amazing guy, and I'm just so fortunate he's been my best friend. But anyway, getting back to this, it was like I was so

focused. I already knew what the old technique could do. I already knew its limitations. It was ancient history to me. Here's my lattice light sheet paper, which is just now knocking it out of the park. I mean, I'm revealing biology that, you know, we brought 100 collaborators to my lab over between, say, 2012 and 2016. And every single one of them was seeing systems they'd studied for 20 ways, for 20 years in ways they had never dreamed of before. and it was just so exciting. And I knew that it was all going to get ripped away from me, that this was going to be just like if you got hit,

if you're doing, you know, your life is going trying to get hit by a bus. You wake up in traction in a hospital and you realize, you know, all my plans are changed, right? I mean, maybe I can get back to that someday,

but it's not going to happen soon, okay? And so that was my initial, feeling, right? And, um, and so, uh, so, uh, a couple funny things. One is, is, I was sitting there just kind of like getting dazed and, uh, some grad students came by and said, uh, hey, we're going to lunch, we'd like to join us. And I said, I'm really not hungry. I, I, I just found out I've won the Nobel Prize and they go, ha, ha, and then they go away. And then about 10 minutes later, and They go, come back, oh, my God! And then after that, it was an anomalously beautiful day in Munich in the 70s in October.

And I just went walking around the campus. My talk wasn't until two. And, you know, finally, like my son called me, who was the one who's the high-frequency trader now, But then he was, what old was he? This was 2014. He would have been. The teens? Yeah, I guess 15, something like that, maybe.

Yeah, yeah. It's 26 now, right? He was born 99, so yeah. Yeah. And he said, oh, I found out, and I said, how do you know? And he said, they called him first. No kidding. Yeah, they.

Oh, that's how they're able to get your mobile phone. Yeah, exactly. They didn't have my mobile phone. so they called my ex-wife's house. And so it was five in the morning, then he's like me in early riser. And so he picked up the phone and said, we speak to Dr. Betzig. And being the idiot, he is, he says, I'm Dr. Fentzzi. And I said, I'd like to tell you, just won the no-bo.

And he's rattling off all this stuff. And my son is trying to interrupt him saying, wait, wait, wait, this joke. I'm not. finally gets through them and then gives him the number, you know, so, so he knew before I knew. Okay. Wow. But then, and then I'm walking around the campus, and the next thing I know, then it starts. They found me as I was walking.

They dragged me over to where I'm going to give the talk, but outside, and just the gigantic army of media period. And it was like that for the next, at least until after Stockholm, at least until after Stockholm. It was like that, right? Just, yeah, nothing but that until after Stockholm. Yeah. So it's, you know, Stockholm's early December, so it's not that bad. But, you know, but then, yeah, then it's, then it's, you know, you have so many people you owe in the course of your career and every one of them wants you to give a talk, right? Yeah. So those were, 2015, 2016 were the years of living in an aluminum tube, I called it, right? Because I did 250,000 miles each of those years of travel. So,

yeah, it was 250,000 miles each year. Each year. Yeah, yeah, in each year. Yes, correct. Dude, that's a lot. That's a lot. You're right. I was doing more than that. Yeah, yeah. I'm sure. I'm sure. But that's a lot of my match. Yeah, yeah. Living in an aluminum tube, that's what I call it. right um so uh but lots of people to thank yeah and pay back and at the meantime you know my lab was i mean we had all this momentum and i did what i could you know when i was when i was there but but i i do feel like like we could have gone a lot farther a lot faster if i had been there and really with that microscope i was still very connected that's that microscope right to there. And again, I designed it myself, right? And so, you know, I know every bit of it, right? But

starting from around 2016 till 2020, my lab started to get away from me in the sense that I wasn't fully engaged in everything, okay, which is the way most PIs are, but not me. I've always known everything about what was going on. And I hated that. Your father was around when you won? Yes, he was. Yes, he was very proud. Oh, yeah, he was over the moon. He was very proud.

Yeah. He would have forgotten the money that you call him to me. Yeah, I think he kind of figured, well, this made up for. But yeah, he was very proud. Yes. Excellent. Yeah. But, yeah, it was just, it's just a very weird.

To this day, it's a weird experience. whenever anybody, you know, brings it up or, you know, get a random person or, or, you know, we went back, they have this meeting of Nobel laureates every year in Lundau. I've been twice. The first was right afterwards, right? And then we just went this last year. For two reasons. One is because the kids want to see Europe and they paid for my wife's in my thing and they paid for our hotel there.

So it's a cheaper way to take the kids to Europe. but but also because I had prepared to talk on energy I wanted to give. And so I gave that. But again, I don't run with that crowd. I don't run with the Nobel laureate crowd. There's a lot who, you know, just they're basking in fame of stuff they did 30 years ago, right? And they're still considering themselves important, you know, they're not. or to make like they made another declaration against nuclear war there.

I think I was the only guy who stayed out of it, right? Because it was like, you know, I'm not an expert on nuclear war. I don't think my opinion on nuclear war really matters. I don't think that, you know, 50 Nobel laureates signing a declaration. You guys think you're important, but I don't think you're as important as you think you are, right, with this stuff. Um, so, uh, yeah, uh, it was nice to see the young people. I mean, right, really a lot, they invite like 600 just really, really, you know, great kids, right? And I tried to give my propaganda about how I believe science should be done and what's wrong about the way science is. And yeah, some of them will take heart to that. So, yeah. Listen, you know, I come from Southeast Asia. where there's only one Nobel laureate. If you got any message for a region like Southeast Asia or anywhere,

that doesn't have the kind of number of Nobel laureates, like perhaps the U.S. or Europe or any others, what message would you have for us? Don't worry about it. Awards are official. Maybe the context of scientific discovery or whatever. Yeah. again, in terms of scientific discovery, you have to follow your passion and follow your interests and let the chips fall where they may.

If you do science in order to get citations, positions, awards, you're doing science for the wrong reasons, and it may work on random occasions, but generally speaking, it will be counterproductive because you're not for. focused on the science, you're focused on what the science can do for you professionally. I think awards are toxic to science. If I could wave a magic wand and get rid of every award and honor for science, I'd do it in a minute because it's just, you know, and for everyone who wins one, there's 10 who are bitter that they didn't. And it's, look, the accomplishments, research accomplishments are objective. What Harold and I did in the lab is real. What we did when, what our priority is, what we did, what the quality of the work was.

Those are measurable metrics. So accomplishments are objective. Any kind of accolade is subjective. It's a bunch of people, generally who aren't expert in the thing that they're giving, you know, the Nobel Committee. They take a lot of outside input, but it's not like the guys on the committee who make the decision. or experts about super resolution or about everything in the world of chemistry, right, to decide. So it's all subjective. And it doesn't really have a meaning.

The distortions of the Nobel Prize are just insane. I mean, how people react to it just makes me seriously uncomfortable when people just like, It's, yeah, I... How many of them are like you that would have won the... I don't know. I think there's a subset. I think like Horst, you know, my boss. He's an interesting case because, you know, he went to Columbia.

And I think that them trying to use his Nobel, again, to get more institutes, more of this, more of that, whatever. He, he, in his probably, around 60 maybe, he dropped out of science. He now lives on Lake Winnipe Socky and Winters. You know, uh, sounds pretty good. He's, I don't, he's not really interested in doing the Lindau thing or any of this other kind of crap.

The vast majority, though, you know, like Steve, too, he seems to relish it. Yeah. and all of that, but, um, which is weird because I knew him at Bell. And he was, he was a definitely grinder in the, in the trenches physicist back then, but, but, um, but now he's much more of a, you know, public figure instead, right? Yeah. Which is totally different skill set than, than, then, uh, scientific grinder. They got to think about different things.

Yeah. Yeah. Yeah. Okay, my last question. Yeah. You want to be on a starship to go to Mars? I would like to, yeah. Or at least to lower Earth orbit, but Mars is... You see yourself in your lifetime being able to land on Mars?

It all depends on how fast starship develops and how fast my body deteriorates and what the competition would be, right? And for seats, right? The other decision I'd have to make is whether to abandon my family. But, you know, if I abandon my family, it's, say, 70, how many more years? years do I have anyway, right, before I'll be abandoning my family because I'll be dead, right? So, you know, like I say, I mean, everything I do in my life, I'd like to think that I'm giving more than I'm receiving, right? So I don't think I'd want to go on a starship if I felt like I was on Starship to be the token Nobel laureate on a Starship, right? I'd like to believe that I'm going on Starship because I'm the right guy to do some particular job that needs to be done on Mars, right?

Or I could be helpful, right? Is that more on the fundamental belief that we ought to be multi-planetary? Yeah. Yeah, yeah. I'd like to be able to contribute to that. But in addition, there's a non-logical part, right? It's why do salmon swim upstream kind of thing, right? I mean, I was wired, wired to want to go to space, all right?

I mean, from the beginning, from the beginning of my life. And so I'm, I can't tell you how relieved and happy I am after years of Mordabund space to watch the price. not just SpaceX, but, you know, Blue Origin and the others, you know, Rocket Lab and others. Well, the Chinese are working on this. And Chinese coming up to, we're finally coming to the type of space industry we should have developed. Apollo was great, but Apollo was actually counterproductive in the sense that it didn't lead to a economically viable space industry. But thanks to, you know, the military, thanks to Starlink, Starlink is huge. Starlink will not, is not only changing the world in terms of communication and access

information for places like Ghana or wherever, right? That's going to be big. Okay. Southeast Asian like that. You and Borneo or it's... Kalimantan. It's going to be different because everybody's going to have access. Absolutely. to information worldwide instantly. It's a big deal. And it's going to a big deal because it's also going to provide the cash to fund Starship.

And they will find other ways of monetizing space. So, yeah, it's going to take years longer the musk is alive for sure. But a real space economy will develop. and when it does that and AI together because they go hand in hand. You can't colonize Mars. The reason he's so much into AI and into optimist is because if you don't have autonomous machines, self-replicating autonomous machines out the wazoo, there's no way you'll be able to.

Yeah, there's not going to be enough humans to make it. You can't transport enough humans to make it. That's right. And every human you transport has so many needs in terms of food and water and so forth that robots won't need. So, yeah. So that, you know, I kind of feel like, you know, human progress happens in sort of bursts within kind of slow when the burst. The really last big burst was 1870, 1920. that was fossil fuels in the U.S.

Okay, that burst happened in China in 1980 to 2000, but in different parts of the world at different rates. But I do think that with the caveat of limitations on energy, that the leverage that we could get through AI, particularly coupled to autonomous machines, and that's why you, he's in Autonomous Driving and Robots and everything else, right? It's all part of a plan, okay?

A good plan that would really super leverage what humanity can do. And so I think I won't be alive to see most of it, but... No, your kids will. Yeah, and there will be good and there will be bad coming from it. But there's going to be a period of rapid change, really rapid change. and buckle up. Well, I mean, Elon has referred to how some of the or most of the platforms of AI are more interested in political correctness seeking. Yeah, right.

That, I think, is a distortion. Sure, of course it is. Yeah. But all the things that AI will do. Again, there's many good things that AI will do, right? And, yeah, but it will all happen so fast as it. it accelerates, it will be, it's going to take human, human social structures and so forth will take a while to catch up to what's happening technologically, just as, you know, you went from

70% farmers to 3% farmers in 50 years in the U.S., right? I mean, that's a big dislocation, right? You're going to have dislocations like that. All sorts of, you know, again, if it leads to abundance, right, what did humans do for worth? Yeah. So there's going to be a lot, a lot of. Think about what sort of a dislocation is going to take place in the sub-Saharan developing economies around the world. My gosh.

Yeah, yeah. We're exposed. Yeah. I mean, if technological innovation gets so cheap. Exactly. Right. Yeah. Yeah.

Well, that's good. I mean, we want the rest of the world to be able to live prosperous lives. This is a good thing. But what would it take, though, for multi-planetary living to not go well? To not go well? Yeah. Oh, many things. I mean, look at the colonization of North America.

You're going to have my part of the world, too. Yeah, you're going to have plenty of James Towns, okay? You're going to have plenty of things like Jamestown, right? I mean, it's going to take a while, okay? There's going to be a lot of, a lot of deaths and things to go. wrong, but there's a line that I like, you know, one of my science fiction authors I like is Robert Heinlein, you know, from the 50s. And he said, despite the naysayers, the world steadily gets better because the human mind adapting itself to its environment makes it better with horse

sense and hard work. Yeah, that's makes sense. Yeah. Okay, I got one last one, man. Okay. What would it take to recreate Phillips? Anywhere. I'm not sure it can be recreated. It's not just money, right? No, it's not just money.

That's the problem, right? I mean, what could recreate Apollo, right? I mean, there's several things that made it successful beyond money. The non-politically correct thing is, this was before the women's liberation, right? So when you have people where one side of the equation is taking care of the household and the family, and the other is working the 18-hour days, there's a big difference between working eight hours a day and working 18 hours a day.

It's highly non-linear. The amount you can get done, all the... Anytime you're in a creative process, it's a weeding process, right? You're thinking of all sorts of ways you can go forward in all sorts of branches. You have to weed those branches to find the best option going forward, right? And anytime there's a disruption, you know, whether it's having to go pick up the kids at school, or whether it's going to a talk on campus or having to go to a meeting of your department, All that, you create this edifice in your head when you're thinking alone of all these different pathways to go.

And if that's stalled, it all comes crashing down. And it takes hours sometimes to rebuild it again. So if you have, academia is a horrible system for doing science because the disruptions are continuous. And it's nearly impossible to build these edifices like you could do at a place like labs. So you need isolation and long hours. And to do that, it's money, but also it's about some kind of compact where, whether it's men or woman or whoever, they're given the freedom to seal themselves off for long periods of time to think creatively. Okay. And so I don't know whether that could easily be recreated.

I would say to a degree we have our Bell Labs right now. It's called SpaceX, right? I was going to say that. Those guys were the 18-hour days. If you look at, you see some women in there as well, of course, but it's clearly a dominantly male culture. It could be all female. If all the females want to work 18 hours, that's fine, right?

Yeah. But it's a bunch of people who are, who are, you know, dedicating their lives to a mission, right you see it in professional football players or things like that right where you just work insane hours to gymming for six hours a day yeah yeah yeah cardio and that's studying tape and you know all that stuff because they because they want excellence right there will always be a subset of humanity will chase excellence right but the one thing that it requires that you can't get around is hard work, right? And you have to carve out somehow an environment where you can do hard work. You look at all the Apollo guys, how many divorces there were through that thing and so forth, right? There's a lot of

sacrifices. A lot of sacrifices. Yeah. That's what the culture of perfectionism does. That's right. Exactly. But it's, it's necessary for some subset to do that to push us forward. The benefits for everybody else are enormous, right? Yeah. Yeah. Man. It's been a long conversation. Okay. Thank you so much, Eric. Sure thing. Yeah.

Anything else you want to? No, I think that'll do it. Good. Thank you. All right, sure thing. Thanks for having me. That was Eric Betsick. No, Gloria.

Thank you. Inla, end game.