BIG IDEAS BY NEW ECONOMIES
00:05:41 · Richard Socher
[00:05:41] S0: In many ways, there are abundant opportunities in every field right now. I actually love the fact that right now so many people are charging hard after who gets to solve hard, meaty problems for humanity first. There's always this joke that very successful people say, the only thing worse than me saving the world is other people saving the world faster or better than I do or something silly like that. But it is a bit of a race. Who gets to solve more hard math problems before anyone else does, which I think there will be a race to curing all the meaty and interesting and important and hard and debilitating diseases out there. And so that I think is a major opportunity. But then, of course, if you really improve fusion, if you really build much, much cheaper batteries to store energy, if you can harness energy way more efficiently from way more sources, fission or fusion, And then solar panel chemistry and all of these things like, I think there's also a lot there, but biology just has this sort of built in mechanism where if you develop an interesting molecule, you can also make a lot of money. In the past I used to struggle with this, like why should medicine make people that wealthy? But then in many ways you want more smart people to be attracted to medicine no matter why and how, ideally just to help humanity, but in practice if you make a lot of money in it, And you have a lot of smart kids from Princeton, Harvard, and so on. They need to pay off their student debts. They're just going to go in high paying jobs. That used to be consulting and now it's really AI and startup tech and so on, big tech. But I'd rather have more people go into medicine because they make more money. Why should people selling ads make more money than people curing diseases? In many ways, I'm excited for AI really making incredible progress. This isn't just hypothetical. Sure, cancer is a particularly tricky set of diseases. But there are certain diseases, for instance, single genome kinds of diseases that will be curable in the next 12 to 24 months. And those have fewer people. But in aggregate, there are actually a lot of people who have individually different rare diseases that are often based on one single genome having been wrong in their DNA. And that can become fixable. So I think this isn't just sci-fi anymore.
00:08:11 · Ollie Forsyth, Richard Socher
[00:08:11] S1: This will happen. And this is what's awesome about AI, right? We were just chatting before we came online, like, you know, AI is moving so fast. People are concerned, like, it's going to change jobs forever. That's true. But people who have, you know, some form of disease, I think they're probably super excited about the opportunity that's unlocked right because they want some form of cure for these diseases that are happening in the world. Have there been any diseases that you've been surprised about that have started to be cured and where do you think we are on that timeline for that to become fully unlocked? [00:08:44] S0: Yeah. So rare genetic diseases, I know several people are working on and have already cures that they're being submitted and so on. So those are the most common ones that I think have a fix and a way to deliver the fix and so on to people. Some first versions where babies were born with a genetic disease that would have not helped them or would have prevented them from leading long, healthy lives were cured. And I think we'll see more of that. I think that would be the first set. And then HIV made a lot of progress already without AI. It used to be a death sentence. And for some countries, it was like 50% of all their deaths were from HIV. Already, there are a lot of ways to... Is [00:09:36] S1: there a disease that you think is going to be just very hard to solve with the current technology advancements that are currently available?
00:09:50 · Richard Socher
[00:09:50] S0: So the final enemy in medicine will be aging. And I think in the next few decades, as we cure more and more diseases, which will require us to collect more and more data so that biology can learn the bitter lesson that we've learned in natural language processing, where A lot of times people are like, you have no idea about how complex biology is. And I fully acknowledge how complex biology is, but language is pretty complicated too. And if you asked all the experts in natural language processing 10, 20 years ago, if we have one model, you can just have And I'll just always give you a reasonable answer and help you work through any problem and do all your homework and so on. I would have been like, no, that language is too complex. You have no idea how language works and blah, blah, blah. And I happened to study a lot of linguistics and I didn't know a But I also knew that indeed I could never manually write out all the rules as an expert of doing that. And so that is what we're seeing now. But that bitter lesson of large models with a lot of data being able to learn incredibly complex things. We'll take a while to arrive in biology because unlike the internet, we have not collected enough biology data just sort of naturally and billions of people kind of collaborating on that. But once we have enough data, then we will be able to cure more and more diseases. And then I think the ultimate hardest one will arrive at at the end that will get us all is aging. But then aging is also incredibly hard because every organ in our body ages differently at different speeds and different people have varying aspects of it. There's a lot of lifestyle factors that come in and so on. So, you know, that will probably be the hardest one.
00:11:30 · Ollie Forsyth
[00:11:30] S1: So here's a world question. If you weren't building your companies and you wanted to solve aging, is there a particular area of focus you would like to really double down on to maybe help us all live longer? Are we going to be in the world in 50, 60, 100 years where we all live past 100? Maybe we start living to 120. This is just crazy, right? But maybe is this going to be available and possible in the future?
00:12:00 · Richard Socher
[00:12:00] S0: Yeah. I mean, generally life expectancy has improved already massively. And so I think we'll continue seeing that trend. I think there is a built in mechanism where many people also lose the will to live. And I think you need to have a special mindset to even want to live beyond a certain time and keep fixing, like working on really hard health issues that arise as you get older. But if you have the will to live, I think, I hopefully think it'll become more and more of a choice for how long you want to live. And can sort of in a healthy way. Obviously, no one wants to be like a vegetable for another 50 years or just like vegetate in bed. But like, I think that that is absolutely possible. At the same time, you know, the future, a lot of people think the future is kind of this prediction exercise, but it's often a construction exercise. We need to actually build these things. And so if I was to do something else, it would probably try to help And efficiently in a computer will be able to allow AI into an experiment on very large scales. And so that is just not possible right now. We don't have enough data that we've collected in biology. We did collect a lot of proteins and so we're able to build a language model for proteins and now we can generate new kinds of proteins that have certain antibacterial properties and so on. I think we need to collect a lot more data to Be able to build, for instance, a complete virtual cell, then a virtual tissue, and then a fully sort of virtual twin of multi-organ systems and ultimately full people. And I think there are a lot of exciting mixtures of robotics and biology companies that are going to be possible and necessary in the next few years.
00:13:52 · Ollie Forsyth
[00:13:52] S1: Do you think we are on a very short timeline for this to become possible? Is this 12 to 18 months away for this to actually start happening?