Network effects, AI medicine, and the fight for free speech

Reid, it is delightful to have you here in New York in the Notion office. First question is actually about cities. So I feel like for the past few years everyone's been talking about the death of San Francisco, the death of New York, sort of anointing Miami and Austin as the next tech hubs. The data that we've seen from Silicon Valley bank says that actually over the last three years San Francisco is the only city that has seen company growth in terms of VC backed companies being started. And, and this past January, David Sack said, and I quote, as a response to socialism, Miami will replace New York as the finance capital and Austin will replace San Francisco as the tech capital. Why do these people keep saying these things and why do they keep being proven wrong? Or do you think something's going to change in the next five, 10 years?

0:00

It's certainly not going to change. And I think that the question is, you know, Silicon Valley and New York are not the world organized according to how David Sachs thinks they should be organized. So he, if, if he uses as a proof point Miami's taking over of the tech capital or the financial capital as a proof point for his beliefs, which of course he won't, then he would have to acknowledge he was wrong. Because the actual thing about these things are they create these cities and economies create network effects and people who understand network effects understand how they have persistence, growth, compounding. That's one of the fundamental things about what made Silicon Valley Silicon Valley. And I'm less knowledgeable about the New York financial scene, but I suspect that it's the same way there as well. Now as Americans we'd like to have as many different tech growing hubs as possible. The fact that the others aren't growing is not a fact that I take any joy or delight in. I would prefer to be 10 or 20 different cities. As a matter of fact, I try to help that in various cities in the US and also in other countries that I think we have values alignment with like for example, London and Paris and you know, Rome and Milan and other places as ways of doing this. So I think it's a, it's a good thing if most of these things are the case. I think that we want as many of these tech things as possible. But it's also one of the reasons why the death of Silicon Valley is something that's been said for the last at least 20 years that I've been tracking this peak Silicon Valley, et cetera, et cetera and all of that comment doesn't understand the fundamental strength of Network effects, networks of talent, networks of capital networks, networks of knowledge. And it's, it's, it, it, it draws it in. It, it, it is part of what leads to blitzscaling. And so the Silicon Valley bank data does not surprise me at all with the Silicon Valley growth. Now it does say we need to focus some more on these other cities because they should have growth too.

0:48

Yep. And so if you're a 25 year old founder today, well, I feel like you're going to say San Francisco no matter what. So I'm going to say if you're a 25 year old founder today, you can't start a company in San Francisco. How should you choose where to start? Proximity to the industry that you're trying to disrupt, Your own network, universities vibes, a city on the rise. What should you be thinking about when you're choosing a city to house your startup?

2:59

Well, fundamentally it's the network, the economic Network or in LinkedIn terms, Economic Graph of the city that fits the industry company that you're going for. And so for example, if someone says hey, I'm moving from New York to San Francisco to create a new finance thing, like that's pure finance. Now tech is important on everything. So Silicon Valley and San Francisco helps on that. But it's like, well actually the finance industry is here more. Be a little bit more assert. I'm going to Silicon Valley to start a fashion brand. That seems like an impossible mission. So where's New York or LA would make sense. So it's where, where the network for. And how do you know where the network is? Well, it's kind of where the scalable companies emerge from, where they financing emerge from. Where, where? When you're hiring talent because you scale the talent, including how to go to global scale, because the real relevance blitz scaling is always going to global scale is where are the networks best for doing that? Now sometimes there's like nowhere. Then it's like, okay, well think about talent networks, think about capital networks. So it could be for example that something that's near university with a bunch of raw talent, a bunch of innovation. It could be that if you're creating something that's radically new or different, being somewhat askew works and like, for example, part of like the way to say, hey, like I always take things like Shopify and Spotify as interesting lessons because they said, okay, we know that we don't have the benefit of being in the Silicon Valley network, but how do we play this technology game? Like which technology games work as a kind of A we learn from, but we build separately in order to do and frequently that's build in a different direction. Do something like for example with Spotify, it's like, well, in order to get it to critical mass we had to first just guarantee the record labels, Scandinavian revenue and could do it within that focused area and then get it to scale. Similarly, because Silicon Valley kind of thought, oh, all shopping is owned by Amazon. You could play the long game compounding in the network effects with Shopify because no, no, no. Actually in fact I'm betting on the network effect of the Internet relative to E commerce and I'm building up a connect culture run it. But like for example, Toby Lutka, who's one of the world class anywhere, not just Silicon Valley, but anywhere founders and CEOs. Look, I'm learning intensely from it. He does board meetings there, you know, some of his board meetings. He reads constantly, make sure that the team is, is drawing from the knowledge base of Silicon Valley as much as he can to build his alternative path and build something that's, that's, that's extremely successful and competitive elsewhere.

3:24

Awesome. So talking about another industry, let's talk about biotech. So you have AI which is compounding so quickly. And we're sort of at the intersection of these two different curves. And one curve is AI has been getting so much more efficient, so much better and so much cheaper over the last few years. But then you have the biomedical curve and it is heavily regulated, it is full of failures, you have few hits and it takes a long time. Even with the introduction of AI, it still moves much more slowly than the world of technology. And you often talk about sort of the difference between the world of atoms and the world of bits. And how do you get technology to help the other grow more quickly? So as many of our listeners know, you started with Siddhartha Mukherjee, the company Manus AI. Can you give us an update on how that's going? What is the latest that we can expect from this company that hopes one day to have cures for cancer?

6:09

One of the things that Sid and I talked a lot about was where should Monas be? And because of the fact is, is the classic Silicon Valley approach to, you know, kind of the pharma, biomedical, etc. Tends to be too oriented only in the world of software and bits. So like, you know, hyperbolic examples are oh, we're just going to create new drug research or AIs and they're going to do everything or we're just going to create everything in simulation. And the simulation will output everything. And by the way, if those things work, that will be amazing transformations. It was like, okay, well we need to have this new approach that is not just bits, but kind of biological atoms, right? So it's not just, you know, physical atoms, but biological atoms are kind of that midpoint, they're dynamic, they're somewhat programmable, they have, you know, the language of biology, the language of cells, the language of chemistry in terms of how it's operating. And part of the reason why Sid and I kind of thought that the time is now for this specific approach was that we were like, okay, what are the challenges that in development of what is essential for human well being and prosperity is like, you know, curing cancer kills everybody, kills young, old, men, women, you know, races, nations like everybody. And yet, you know, our solutions are very, very barbaric and old school. Now if we catch it early enough, we can do a simple surgery in a number of them. Not all, many not. But you frequently can't. Doesn't happen that way. Or is that okay, now we're going to chemo or car T which is basically we're going to try to kill you and the cancer at the same time and hope that we kill the cancer first. It's like, okay, there's got to be better ways of managing all this. And the reason the insight that's adjacent to the classic Silicon Valley way of doing this is say, well, AI is like matching these search problems. It's like a Google for what should the right kind of small molecule be that could be a solve a cure, a therapy, et cetera. You can also look at it as kind of like the intersection with generative AI. It's like, okay, what would be the, in your ideal universe you would go and say, I would like to solve triple negative breast cancer. And it would go and here's your molecule and it'll be input output as kind of, as a. Yes, as kind of a way of operating. Obviously the models are nowhere close to being able to do that other than pure hallucination. And so it's like, okay, what would be the things that are reconfiguring this that allow us to, to use all this amazing new scale compute, scale learning, et cetera. And so what we've done since we've kind of announced is we've hired a whole team, we've identified problems that go all the way from kind of like how do you create new kinds of generative models that are the best predictive for therapeutic molecules? They're not like, which is great. We use it alphafold to say all protein folding because we, what we care about is therapeutic molecules. We care about what makes a difference for human else. So what's the set of things in that? We said, okay, part of one of the things that everyone knows is kind of limitations on data. So we've got multiple solves that one of them we've been public about, which is a partnership with Schrodinger where we go, okay, we use the fact that they've encoded a lot of chemistry and physics knowledge to configure the data set for, for how we find those molecules. And we've got a bunch of others. And then we've also got thoughts about how it goes through clinical testing, how it goes through to business models, because you have to look at the whole field and it makes it much more complicated, makes it slower. But now here in New York we have a whole company that's doing it. And I don't know exactly when we're planning on being more noisy, but progress is in full motion.

7:02

But it's exciting. So some of the heads of the frontier labs have said that they expect within 20 years practically all diseases are going to be cured because of AI advancements. So do you agree with that and, or, and I know you hate predicting what's the end number of years you think is going to come before the first sort of AI drug that cures a disease.

11:08

I think the number of years before AI drugs cure disease is, is probably more driven by FDA and other processes than it is like creation. I think the technology was probably already in our earliest prototyping phases. We've actually filed some inds, have some things that are prospective patents, other things, and that's just us prototyping our technology to get the factory running. So I think that the, the notion of that there will be AI discovered, invented, found drugs, I think is very small and years. But the process by which we get that into clinical trials, the process by which we get that into affecting human health outcomes, that is also a key part of that. And that's part of the reason why it gets harder to do. Now if you said do I think that it's completely feasible that because of AI techniques, all current human diseases will have cures or the vast majority, I think the answer is that seems very plausible. It's possible that there's a drug or there's a disease or two, that just because something structural about how biology works, it's just like there's no fix for it that isn't Also like mortal. Right? Or something as kind of equivalent. Like it just doesn't. There may be some that just don't have that infinite solve capability. And it's also that diseases evolve. So just as we, we don't know

11:30

what the disease landscape is going to

13:07

look like in 20 years, so the all disease cured unclear. But I think, look, the advancement of like part of what we a major part of human progress over the last, you know, 50 plus years has been like, like solving diseases through for example, vaccines and other things, which all of the biomedical folks, you know, kind of know and do. It doesn't mean that, you know, they say well you said there were no vaccines, there were no side effects for vaccines. No one smart ever says that. Of course for some individuals or side effects just as like for some individuals or side effects for aspirin. For some individuals there's side effects for kind of eating a particular shellfish. And so there's of course, but the question is, oh no, no, for a vast majority this is life saving and for some there's some side effects. And then you try to navigate that. That's essentially a statistical trade.

13:08

It's really hard for people to wrap their head around life expectancies in 1900 and how radically different they were. And that is changing. Changed because of vaccines, public health, technology. Like it is pretty wonderful. And we just forget honestly that what it was like to live 100, 120 years ago.

14:06

And I think AI is the next phase of acceleration.

14:24

Absolutely. So to end the episode, I want to switch gears a little bit. Recently we got a very 20, 26 sentence. Stephen Colbert says CBS wouldn't let him air an interview with a Democratic Senate candidate because they were scared of the fcc. For those of you who are listening or watching and you haven't seen the Colbert episode on this, please go watch. It is hilarious and also informative, but it's a little scary. What happened was that Colbert taped an episode with James Talarico who is running for Senate in Texas. He is one of the Democratic candidates. And the CBS lawyers called Colbert and said you cannot run this episode, citing the FCC's evil equal time provision because Brendan Carr wanted to change it. And so Brendan Carr did not himself call cbs, but CBS was pre obeying. They were guessing about what was going to happen in the future. They saw the Trump administration get mad at various media outlets, threatened to pull licenses. So again, this is a pre obeying that in some ways is a little scarier because it means that people aren't even fighting against it. Luckily, Stephen Colbert said, I don't care, and he put the episode on YouTube. And now I think as of, as of when I saw it, it had 10 million views and 60,000 comments. People were really pissed that censorship was happening. So do you think companies are afraid of retribution from the Trump administration? Is this a normal course of events? And what do you think about sort of the pre obeying versus actually the administration cracking down on this?

14:27

Well, it's precisely part of the autocratic playbook to create fear in citizens, but also in organizations like media organizations, because it's the. If everyone stands up and disobeys, then it's very hard for them to do something. So it's kind of the make an example do something. This is the whole Jimmy Kimmel, you know, kind of early way of doing it and saying, we can hurt you very badly. And so everyone goes, okay, well don't hurt me. Like maybe hurt somebody else, but don't hurt me. And so, and this is precisely where I think, as citizens, as leaders, it's like, look, when you're feeling fear for this is a time to kind of show courage. And I think that, you know, we all have a responsibility to humanity first, then society and then to business in terms of doing it. And so how do we have a responsibility to society in doing this? Now, I found the Kimmel stuff bemusing because, you know, maybe for the first time ever, I found myself on the same side as Ted Cruz. I found myself on the same side as Tucker Carlson, who are both much smarter than a lot of these other crazy people who are supporting this administration's crushing of free speech, crushing of free assembly. I mean, being anti constitutional on this, because they're like, well, wait a minute, if that happens now, what happens in the next Democratic administration? Like if, if you're all these, you know, kind of crazy, you know, kind

16:02

of just be free speech, the speech that I like. Because what happens when there's a different administration who doesn't like my free speech.

17:33

Yes, exactly. So you have to be. And of course I find it, I find who is really legitimately free speech or not, is if they were speaking up against, you know, Carr, who, frankly, I think on this, you know, I think there was. There would be a good reason for him to lose his job because of that. But as opposed to that, it's like, no, this is the kind of intimidation and fear we want. It's the kind of bullying that I think is anti America, anti our 250 years of creating, you know, kind of freedom of Press, freedom of assembly, to be able to have a free democracy. It's precisely the anti American that everyone should be speaking up on. And as I mentioned, my bemusement, it was like, well, actually, in fact, now people I rarely agree with, I agree with them. And the other people who are between quiet and supportive, I think are demonstrably un American.

17:39

Absolutely. And credit where credit is due, you can disagree with 90% of what someone says and actually say, thank you for speaking out because you're representing the Constitution. So some people are saying that after the midterms, and nothing is a guarantee, especially with the shenanigans of the Trump administration, but a lot of people think the Democrats are going to win the House. And so after the midterms, you could argue that perhaps this media, this retribution, is just a blip. And after the midterms, since the Democrats will have the House, we will see less of this. Other people will say, oh, no, no, this will be a lame duck administration. They will see that they're losing their grip and they will tighten even more to ensure that all this negative press doesn't get out there. How do you see the landscape shifting after November?

18:31

I think that I'll get worse and more volatile. I think that part of that's because, I mean, it's like, for example, the, the public loyalty oath for the Trump administration is that the 2020 election was stolen. Now you have to, like, say that in public. Now it's like, okay, let me just repeat what I understand that claim to be, which is when Trump was president with a Republican Senate and mostly in states that had Republican secretary of election sleepy, Joe Biden stole the election.

19:14

Yep.

19:46

But when Biden was president, he didn't. Right, That's. That's literally the claim. It's like, that's the claim. And it's amazing to watch people do gyrations. Well, but there were activists who were bust, and you're like, well, why weren't there activists bust then, too? I mean, like, it's just like. It's like, if it, like, what do human beings do? If it worked once, you're gonna do it again. Totally. Right. And it's like, it's not, you know, so it just, it's. It's literally the. I must say, you know, up is down.

19:47

But also, they only stole it for the presidency. Decided to not steal Senate seats or House of Representatives, which of course, was

20:16

a deliberate, very, very. A very detailed conspiracy.

20:22

Exactly.

20:25

And so now what I think will happen is Trump will either go one of two directions if The Dems won the House, he'll either go, that was a fake election. Like the kind of prediction that I see. It was like, oh, the Democrats are trying to steal the election with illegal immigrants, you know, blah, blah, blah. And so that, of course, now that we have this massively funded ice, which is mostly terrorizing blue cities. Right. As opposed to, like, for example, doing stuff on the border, which is, I think what Americans want. Right. Is, you know, kind of be kind of crazy. So it's either going to be the, oh, the Dems stole the election, or the Republican Party is so weak because they're not using me. Right. You know, et cetera. Like, but it won't be the. No, this is actually, in fact, a good referendum on how bad things have been in only a year.

20:26

Yep. No, that all makes sense. Well, Reid, it is always a pleasure. Thank you so much.

21:15

Thank you. Possible is produced by Palette Media. It's hosted by Ari Finger and me, Reid Hoffman. Our showrunner is Sean Young. Possible is produced by Tenasi Delos, Katie Sanders, Spencer Strasmore, Emo Zhu, Trent Barboza and Tafadzwa Nimarundwe.

21:19

Special thanks to Surya Yalamanchili, Sayda Sepieva, Ian Alice, Greg Beato, Parth Patil and Ben Rellis.

21:35