Superconvergence: The Dawn of Human-Engineered Intelligence with Jamie Metzl

[00:00:00] This isn't your average business podcast and he's not your average host. This is the James Altucher Show. So Jamie Metzl, you've been on the podcast a gazillion times for the first time since COVID. And you're our favorite futurist. You keep track of all the amazing things going on.

[00:00:28] Like in previously we've talked about genomics, but now of course there's genomics combined with AI combined with all sorts of other things. And you write about that in this excellent book, Super Convergence, How the Genetics, Biotech and AI Revolutions Will Transform Our Lives, Work and World.

[00:00:45] Great cover by the way. I like the cover. Thank you. You know, James, these covers, I'm very happy that you like it because there were multiple iterations and I had to kind of fight in a loving way. It's like, no, it's not just right.

[00:00:58] So we spent a lot of time getting that cover. So I'm glad you like it. Well, what's exciting you the most in the future? I read the book, but there's a lot of complicated stuff in there.

[00:01:08] You talk about everything from GMOs to creating new animals that you call new animals for food and of course the latest in genomics and CRISPR and combined particularly with AI. So what's exciting you the most?

[00:01:26] So the big summary of the thing I'm most excited about and most worried about because it's two sides of the same coin is that after nearly 4 billion years of evolution, this is the dawn of human engineered intelligence and human re-engineered life.

[00:01:44] Our one species suddenly has the godlike ability to recast life, to give essentially give birth to what is whether we want to call it a species, a new form of intelligence. And either it's kind of a binary outcome.

[00:02:00] Either we'll use these superpowers to build a much better, safer world with mistakes along the way, but all in all build a safer world. Or we will use these powers to do inestimable harm. We won't destroy the planet because the earth keeps going.

[00:02:20] Knock us with an asteroid, whatever, we keep growing, but we're going to reshuffle life and maybe not to our benefit. Well, it's interesting. Other than clearly we've seen evidence or possible evidence that you can use genomics to create a virus that could infect all of humankind.

[00:02:41] But other than that, which is always a scary scenario and we're all scared of that. But other than that, what's a scary thing that we could do now? So I normally like to start with the great stories, but it's equally healthy to start

[00:02:57] with the bad stuff because I think that it's part of the same story. Yeah, and let me just add that. So I speak at a lot of conferences, as you do, about many of these topics.

[00:03:08] And I would have to say, I mean, I spoke in LA last week about AI and what sort of industries it will affect. And the main question people have is, is my job going to be loss? So people are worried more than they're excited.

[00:03:24] The benefits of AI are unimaginable. You talk about it in your book and we can guess and guess and guess, but they're going to be great. But everybody first is worried about the horror stories. Yeah, it's just the way that we are wired.

[00:03:41] And there's a reason why evolution hasn't gotten rid of anxiety. It's actually a very useful feeling for us. We worry about stuff. And our worry gets us to take action that prevent our fears from being realized.

[00:03:55] So I think it's great for people to be worried, but we shouldn't be paralyzed by fears. We shouldn't just imagine that the worst case scenarios that we can imagine are the inevitable futures of these technologies because these technologies have the potential to do incredibly

[00:04:13] great stuff that we're going to want and do harm. And that's why I wrote the book. Now is the time when we need to be understanding what's happening and what's at stake and doing our best to increase the odds of good stuff happening and bad stuff not happening.

[00:04:29] But now I'm willing to go to the fear stuff if you want. Okay. And before you get to the fear stuff, the book's title is Super Convergence. This implies, and I agree with this, that we've reached some sort of tipping point.

[00:04:41] We're right there teetering on this tipping point where there's a point of no return. This convergence of AI, which is like the peak of software engineering, this convergence of that with genomics, which is like the peak of, call it bioengineering, call it medicine,

[00:05:01] whatever you call it, it's the peak. These two things are converging and we're on the point of no return after that. Yeah, exactly. So basically there's two kind of core essential points. One is that we have these shorthand names for our different technologies, but really

[00:05:20] there's just one technology. Almost all technologies are embedded in other technologies. You're talking to me through this microphone. Agriculture is embedded in that microphone. If humans hadn't figured out agriculture, this microphone wouldn't exist. Another revolutionary human innovation is embedded in our interaction and all of the

[00:05:44] computer codes are written in languages which come from, we call it the Latin alphabet, but Phoenician and these numbers that come from India and the Middle East. So all of these technologies are woven into every other technology, but that process is speeding up.

[00:06:03] Just a shorthand example, the computer revolution gives us the machine learning revolution, the machine learning revolution helps us interrogate evolutionary biological designs that have evolved over a long period of time. And with that, we're understanding new models using nature's models to build better computer

[00:06:23] chips which create better machine learning AI, which lets us understand and manipulate the natural world. So it's all of these technologies are connecting to each other. Then there's just the point of acceleration. You don't need to start now with acceleration.

[00:06:39] Literally, you could start 12, 10,000 years ago at the dawn of agriculture and all of the things that agriculture unlocked, whether it's cities, civilization, writing codes, and then step by step. What we're seeing is that the space of time between big deal revolutions is getting shorter and shorter.

[00:07:03] And so who knows whether there's a tipping point because every technology, I write about this in the book, the coolest technology that we have, like right now, open AI just released GPT 4.0.

[00:07:18] And it seems really cool to us that this technology can kind of listen to us, it can kind of see us, but this is pong compared to where we're going to be. It's always pong.

[00:07:29] The coolest thing that you're doing today, as exciting as it is, is just the beginning of the next thing. And that's why in conjunction with this acceleration, we need to get better at all the other stuff,

[00:07:43] at our understanding, at our thinking about governance, not just regulation, but how do we manage these technologies about inclusion, and not just so there aren't people who are left out, although that's important, but so that our combined wisdom as a species can

[00:07:59] be brought to bear in some pretty fundamental decisions that will have big implications for our lives and for future generations. So we just have to, the technology is racing forward, we need to accelerate all the other stuff.

[00:08:12] Well, I had this conversation with Yuval Harari, you know, the author of Sapiens, where he said one of the big problems in the 21st century was going to be that there would be the haves and the have-nots in terms of this new AI technology.

[00:08:26] And I disagreed with that because I felt it's going to develop so fast, there won't be time to really develop a haves and have-nots. Like right now, you know, something like a billion people have used chat GPT at some point.

[00:08:39] So it's not like society is being deprived of the technology, but, you know, maybe we could start off, you could explain a couple of things. Where are we at now with genomics? So with all of it, it's the same thing that I just said.

[00:08:57] So let me talk about the Yuval Harari point and then where we are. So definitely the benefits of these technologies are going to be diffused because these technologies are just getting easier and easier for people to use.

[00:09:12] I mean, right now, over the last year or so, we've had a 50% acceleration in how quickly top coders can do computer coding, just because computer coding is a language. And when you're coding, you have GitHub or other programs that are just suggesting, hey,

[00:09:29] if you started this line of code, here's what you may want to finish this line. And maybe it is or maybe it isn't. That's speeding up code. But now we have millions, tens of millions, soon hundreds of millions, and then billions

[00:09:42] of people who are interacting with these coding technologies every day. So we're learning from them and they're learning from us. And so now we're on the verge of natural language coding, where rather than knowing how to code,

[00:09:58] I just say, hey, algorithm or hey, whatever I'm calling it, make a program for making my lights flicker on and off every five minutes. And I don't need to know anything about coding. So now we have billions of people who can be coders.

[00:10:14] That doesn't mean everybody is great. So we're seeing this kind of acceleration. But the haves and have-nots thing is not about the distribution of the technology. And I think that a lot of people are going to be empowered that if you're starting a

[00:10:28] company and you used to need 100 people to start a company, now you can start your company with two people. And that's very empowering. But if the benefits and certainly the capital associated with all of this gets over-centralized, I do think that would be a worry.

[00:10:46] And these are not- How would that happen? Just right now, I mean, we have this capital structure. So let's just say it's a small number of big companies that are able to get the benefit, primarily the benefit of these technologies. And they probably won't be distributed everywhere.

[00:11:03] I'm saying this is just one possibility. But you look at what happened in newspapers when Google basically took the money from classified ads. There were all these people who used to be in this whole ecosystem of newspapers, and that all migrated to Google.

[00:11:19] You could imagine a small number of companies who have this concentration, centralization of power, who are then able to leverage that power into every other industry. And just to move across and say, all right, now we have access to all of this information.

[00:11:35] We have access to these tools. We can do whatever business probably better than people doing that business. It's like Amazon when they're tracking what people are buying, and then they have their own Amazon brands, which just does those things at a lower price. So that's one scenario.

[00:11:55] You could also imagine another scenario where everybody is so empowered. And this is a new renaissance where you have all of these new areas where people are innovating and creating new opportunities, not just for wealth, for creativity.

[00:12:10] And because both of those are real possibilities, then the next question is, well, what's the difference between the options that we want and the options that we don't want? And that's why this word governance, I mean, it sounds very boring.

[00:12:22] But it's not like these technologies come with a built-in value system. We're creating the value system, the superstructure in which these technologies play out through our laws, through how our societies are organized, through how people are empowered and engaged.

[00:12:41] And so that's why it's one of the reasons why I wrote the book. But right now, it's a really important time to think, well, what do we want that future to look like?

[00:12:48] And if we want to have a future where the benefits are distributed, we should say, how do we weave those values into our decisions today? Well, OK. Let me take a step back and say, I'm going to give the 60,000-foot view of your book. And here's the benefits.

[00:13:08] Basically, we're going to use genomics to edit our genes and cure all our diseases. And we're going to use AI to fit. I remember the last time we spoke, it was a real problem to find diseases if they required more than one gene.

[00:13:25] Because there's these thousands of genes, and if you require multiple genes, it's exponentially too hard a problem. So we were focused on single gene mutations. But now, with some of this AI stuff, like AlphaFold and so on, we could figure out multiple

[00:13:42] gene mutations and cure lots more diseases potentially. With genetically modified foods, we're going to feed the planet and never run out of food. And with AI, every industry is going to be more efficient. And presumably, those efficiencies will be passed to the consumer, both in terms of

[00:13:59] the quality of their products as well as pricing. So that's the 60,000-foot view of how things are going to be great. You can even be greater. We could even have more humans, and we could all be eight feet tall and so on. Those things could be.

[00:14:16] But certainly, my book isn't saying that we're there now where it's even inevitable that we're going to get there. Certainly, when we cure these diseases, like our ancestors died of infectious diseases, and now they die of other things just because we've extended the range of possibility.

[00:14:35] So nothing is inevitable, but certainly, these overlapping technologies are creating new opportunities for us. In a step-by-step way, like we've done in the past, we're going to be able to treat and prevent and cure more diseases and a broader range of diseases.

[00:14:52] And exactly as I said, we're going to move up the complexity scale from right now where in a very, very limited number of cases, we can do gene therapies addressing single-gene mutation disorders.

[00:15:03] Like there's a woman I write about in the book, Victoria Gray, one of the first people to be treated for sickle cell disease using CRISPR genome editing as part of a gene therapy. And that's great.

[00:15:15] But we're going to move up the complexity scale as our tools get better and as our understanding of complex human biology increases. Same with food right now. We humans slaughter 82 billion land animals per year, 200 million metric tons of fish.

[00:15:35] And I'm not a vegetarian, but industrial animal agriculture and certainly industrial fishing are just devastating our planet. And not everybody is willing to become a vegetarian, although it seems like a good idea. So how do we do it? How do we feed people?

[00:15:51] And I think, again, agriculture is a form of radical biotechnology. It may be 10,000 years old, but it is really radical compared to how our ancestors beyond that time lived. And we're going to use these tools to think differently, to innovate in our food supply

[00:16:06] and so many other areas. Perhaps we can use all these latest developments in biotech and genomics and so on to create meat. Yeah. And so these innovations that primarily happened in human health care, like regenerative medicine,

[00:16:27] where we can say, all right, we can grow cells to do things that we want them to do in medicine, a lot of people who are actually doctors, actually regenerative medicine doctors said, hey, wait a second. We're growing tissues for human health applications.

[00:16:44] What if we just grew animal tissues for food applications? And so we now have a way to extract stem cells, essentially, from healthy living animals and to grow them in culture and then in industrial bioreactors.

[00:17:00] And if, a big if, but if we can do that at scale, we can get biologically identical animal products from the ones that we consume today. But rather than killing a cow, we'll grow the cow and send it to the spa and play classical

[00:17:18] music and make it as happy and healthy as possible. And then we'll just extract a few cells and grow those cells. And we don't need to replace all of animal products, but let's just say 30% of the beef that we consume and 50% of the beef is already ground beef.

[00:17:34] And most people who eat ground beef, it's like, what's in that ground beef? I don't know. But let's say 30% of just the ground beef that we eat is cultivated, cell cultured meat. That would have profound implications on all sorts of things, including the environment. Right.

[00:17:55] So a couple of questions. One is you're basically cloning enough of the cow to extract the food. You don't have to actually make a whole cow. You could just grow the tissues that make the food.

[00:18:07] From the perspective of those of us who are eating meat, unfortunately, I wish people ate meat, who eat meat in every moment. Like they said, all right, I'm about to have this burger and I'm going to say a prayer for this cow.

[00:18:20] And I'm going to go through the slideshow of the highlights of this cow's life as I honor this cow. No, it's like, hey, I'm going through the drive-thru. I'll take the burger. We don't even think about it.

[00:18:32] But insofar as we should think about it, like the soul, if you believe in soul of the cow, the relationship with its children, its emotions, how it negotiated with other cattle in the herd, that's all kind of wasted for us because we don't care. I wish we did.

[00:18:49] We don't care about them. We just want its products. So if we could get all of these products and not harm the cow, not have deforestation, not have increased antibiotic resistance because we're pumping these animals with antibiotics

[00:19:08] and all these other negative externalities, that seems like a pretty good deal for me. Take a quick break. If you like this episode, I'd really, really appreciate it. It means so much to me. Please share it with your friends and subscribe to the podcast.

[00:19:25] Email me at altatra.gmail.com and tell me why you subscribed. Thanks. So what's the... I know some people have an ethical dilemma around kind of lab-grown meat. What's the issue? Why do they care? I have to say it's really crazy.

[00:19:51] So Mark Post is this Dutch scientist and more than 10 years ago, he came up with... It was the first lab-grown burger. And so I met him a decade ago and I posted on my then social media that this is really exciting.

[00:20:10] I can't wait to eat a lab-grown burger. And then there was this whole exchange like, I would never eat that. That's so unnatural. And then somebody said, I would only eat beef that comes from grass-fed cows.

[00:20:28] And from the perspective of the cow, it's like, yeah, I just got murdered. But that grass was really delicious. That made it worthwhile. Also like you mentioned, you can basically make tissues as if it was from grass-fed beef. So I just think it's just a silly taboo.

[00:20:46] It's just a silly taboo because... It's kind of like how when the car started, everyone thought if you go faster than 30 miles an hour, you would have a heart attack. Exactly. Exactly. It's just... So I think we can get over that.

[00:21:00] I think we can get over it pretty easily. But there's another issue of just scaling these technologies. It's one thing to do something in a relatively small scale. But if we're talking about disrupting the industrial animal product business, that's a really, really big business.

[00:21:23] It's not just that you need to make enough of this stuff. It needs to be done as cheaply and at least as well, in this case, as this highly subsidized industry of cattle farming and beef and other animal products.

[00:21:40] So that I think is the bigger challenge other than that taboo. I think it's achievable, but there needs to be a lot of innovation. And governments need to play a big role in funding the innovation. But from where we are now, we can see that possible future.

[00:21:58] And I believe we should want that possible future. In the book, I talk about some of these reservations and why I think they're unwarranted. We have 8 billion humans alive today because of agriculture, because of industrial agriculture. We're on our way to 10 billion.

[00:22:16] And mostly the increase are poorer people who are getting wealthier, who want to live lives like us. If 10 billion people living lives like us, consuming products like us, just have their way using the capabilities we have now, we're going to decimate this entire planet.

[00:22:33] So we need to do what we've always done is to say, well, what are the hacks? What are the ways that we can do the things that we want and do them in a sustainable way using our superpowers in a smart and wise and thoughtful way?

[00:22:51] Nassim Taleb is really against GMOs. I don't know what it stands for. Genetically modified organisms. Genetically modified organisms, yeah. Yeah. Basically Monsanto makes these genetically modified foods. And if we didn't have GMOs, we probably couldn't feed the current planet. And so what's the big deal?

[00:23:11] So I totally agree. And again, I write about this in the book, but let me give you this story. I just think it's just nuts for all sorts of reasons. So genetic modification of crops that used to be called recombinant DNA technology, mostly developed in the 1970s.

[00:23:29] And basically when Taleb is referring, Nassim is referring to this, he means transgenic crops. So transferring genes from one type of crop or even one type of animal to another crop. And there are great reasons to do this, like to make our staple crops better able to resist

[00:23:49] weeds and insects, which otherwise could wipe them out, which is why so many American farmers are excited about. The GMOs save the papaya industry in Hawaii, and it's probably going to be necessary to save much of the chocolate growing industry in Africa.

[00:24:08] But the reason was, and certainly I'm not saying that Monsanto, and I'm much less of a critic of Monsanto than many other people, Agent Orange notwithstanding. But there's reasons to be concerned. We don't want big multinational corporations controlling our food supply. There are certainly valid things.

[00:24:27] But there has been a massive misinformation campaign led by Greenpeace and others who have actually lobbied against the labeling of a lot of foods, because they think if people realize that we're eating GMOs every time we have beer and cheese and bread, that

[00:24:46] people would say, hey, wait a second. GMOs are just how human beings in the developed world do agriculture. And if we had zero tolerance for GMOs, like we really wouldn't have, we'd have no animal products because all of our animals are being fed with GMO crops.

[00:25:03] And pretty much all of the food, certainly all the processed foods that we eat, including the foods that say no GMO, have GMOs in one way or another in their supply chain. So it's a misinformation campaign.

[00:25:15] When I was in Berlin and I met with all these German government and EU regulators talking about this exact topic, they all told me privately, we don't believe a single word of what we're promoting.

[00:25:31] And 40 plus years of research hasn't shown any single example of GMOs being unsafe for human consumption. Not one. And this is by everybody, by the World Health Organization, by the EU, by everybody. But there's this misinformation campaign that GMOs are unhealthy.

[00:25:52] And once that idea sinks in, it becomes just this accepted truth. And that's why I think we all need to kind of take a step back and say, well, what is the thing that we're trying to achieve?

[00:26:04] And the thing we're trying to achieve is to feed well, as many people as possible, with as little cruelty to animals as possible without destroying our planet. And I think that advanced biotechnology must, I repeat, must be part of that process. Yeah.

[00:26:23] So what, I mean, you mentioned in the book what you just said, that there's not a single study that's ever shown this food's unhealthy. So where's everybody getting the information that it's unhealthy? No, but it's been a sustained misinformation and I would even call it a propaganda campaign

[00:26:39] by Greenpeace and other organizations. And again, I want to make clear there are reasons to be critical of various companies, whether it's Monsanto, Syngenta or others. But it is just, so that part is legit.

[00:27:00] But to say that GMOs pose a health threat to human beings, there's just maybe in 200 years it'll end up being true. But in 50 years now almost, there's no evidence of that being true to date.

[00:27:16] And if we didn't use GMOs, then the amount of pesticides and insecticides that we would have to use would increase astronomically. And we know for certain that that would do a tremendous amount of harm.

[00:27:33] And so there are just things that people feel and there are people who are investing in having people feel those ways. And I just wish we could have a common sense conversation, not saying that GMOs are all

[00:27:51] good and not saying that GMOs are all bad, but just saying this is a very important, useful technology. How can we best use it? Our farmers have already made that decision with the soybeans and corn that's grown certainly in this country and in many other countries.

[00:28:11] The cotton farmers in India already made that decision, even when there were regulations trying to prevent them from using GMO seeds. And even when there was a whole misinformation campaign wrongly saying they were committing suicide because of these GMO seeds, these farmers were doing everything they could to

[00:28:29] get those seeds because they saw that the insecticides and pesticides were actually killing their families who were having to live with these toxic chemicals. So there's a conversation to be had and it's just unfortunate that we're not able to have it. Yeah.

[00:28:46] And again, and look, I want to get to AI and some of the genomic stuff also, but let's take Nassim Taleb as an example. I'm picking on him, but I'm picking on him because I consider him one of the smartest people out there.

[00:28:59] Why does he think there's basically zero nutritional value to many of these GMOs? Well that's just... He's smart. He won't just take propaganda and believe it. It's 100% irrefutably wrong that there's no nutritional value to GMOs because if you

[00:29:19] lined up GMO corn and non-GMO corn and you did the nutritional analysis of both, there would be no possible way. There's no nutritional difference in terms of the percentage of genes influenced by these transgenes. It is a tiny, infinitesimal fraction. So that is just wrong.

[00:29:43] His general fear of... I haven't heard him or read anything that he's written on this, but just assuming that he's kind of like standard Greenpeace issue, I just think it's misinformation and I'm sure

[00:29:59] that he could and maybe he should say, all right, here are these studies I've posted certainly on my website from a while ago. I have a whole, and in my last book and in my current book, a whole list of the studies that I cite.

[00:30:15] And it's literally every study over the last 45 years, not a single study has shown that GMOs are unsafe for human consumption. There was one study out of Spain, which I don't actually believe, but it apparently showed that GMO corn was somehow healthier than non-GMO corn.

[00:30:34] I'm not going to go there, but at least it's the same. It could be possible. Again, if these stem cells... We assume when we get human tissue transplanted into us, that's been grown from stem cells. I assume that's healthier than my old disease tissue that's being replaced.

[00:30:52] It's such a great point. And I write about it in the book because you can imagine as the future of genetic modification, we talked about cell cultured animal products. So maybe step one is you make it just like the animal product.

[00:31:08] So let's just say that you are making a cell cultured burger and you replace the unhealthy saturated fats that are just the natural fats in the cow with omega-3s or healthier fats. And you have the same product.

[00:31:27] So in the book, I talked about golden rice, which basically is rice that's genetically manipulated so that the people who eat it get an extra dose of vitamin B, which is a

[00:31:41] big deal because if you're in a poor country and you don't have vitamin B, it can lead to all kinds of problems, blindness and other things. So this golden rice is this incredible thing.

[00:31:51] And yet it's not able to be realized in the world, at least at scale, because there's such an aggressive campaign against it. So now with genomics, again, you've been an expert on this for a long time. You've followed all the developments closely.

[00:32:09] Jennifer Dudna, who you know, I don't know how to say it, but you know very well, who won the Nobel Prize for her work on, I guess, CRISPR. And what's going on now? What's been the latest developments? Can we start cloning little versions of me?

[00:32:27] Well, so we already probably can do that. We're already at the stage of cloning primates. And so are there people now trying to clone humans? Probably. I don't know who they are. Not yet. The Chinese. Yeah, probably. That's the answer to everything. Who's doing that?

[00:32:50] Oh, yeah, it's the Chinese. So but certainly the tools and capabilities of genome editing are advancing with unbelievable rapidity. So Jennifer Dudna and her colleague, partner Emmanuel Charpentier, they published their groundbreaking paper, which won them the Nobel Prize in 2012.

[00:33:15] Six years later, in 2018, the world's first genome-edited CRISPR babies were born. So six years from a basic science paper to genome-edited humans. And since then, the tools for genome editing have just gotten better and better. There certainly is CRISPR-Cas9, and Cas9 is the cutting enzyme.

[00:33:38] But now there's a bunch of different CRISPR enzymes that cut in different ways. David Lu at MIT, he has innovated prime editing and base editing, which are basically you can edit a genome without doing the double-stranded cut. And double-stranded cut is what George Church calls genomic vandalism.

[00:33:59] The accuracy, the error rate, all of these things are getting better. The applications of tools like CRISPR and other genome editing tools are just getting much more and more targeted. And as I write about in the book, then there's a range of applications where they're being

[00:34:17] used, whether it's health care with gene therapies, whether it's agriculture in manipulating plants or animals or manipulating the microbiomes in soils, energy, developing new industrial materials like spider silk that's stronger than Kevlar and stretchier than plastic. There's just tons and tons of applications.

[00:34:40] And that list is just expanding with unbelievable rapidity. What surprised you the most? And I think that's a reasonable question. With AI, several years ago, and you mentioned this in the book, AI beat the world Go, the best player in the world at Go.

[00:35:18] I'm a technologist by education and my early career. And a chess player, right? That surprised me. Aren't you a chess player too? Chess player. And I worked on the AI for all the different chess programs.

[00:35:29] I even worked on AI for Go, which is why when AI for Go happened, it surprised me. That was a miracle. And then that of course led to what is now basically chat GPT. That was the same type of neural networks that were used.

[00:35:44] So the whole thing is just incredible. And so as a futurist, I like to say, well, I predicted everything, which is not the case, but I definitely hope that somebody cares about me enough someday to audit everything I've

[00:35:59] been saying for the last 40 years and say, all right, here's what you said was going to happen and didn't happen. And I think my record will be pretty great. The AI is going to audit you and let you live. Exactly.

[00:36:13] And in my congressional testimonies, I've said, hey, here's what's coming. Here's what we need to be ready for. And so the whole story is what I said earlier, just about speed, scope, and scale. And it just gets more and more. And so it's one thing to say it.

[00:36:29] It's one thing to intellectually believe it. But when you kind of keep seeing it every day over and over, it's just kind of incredible. I mean that kind of this chat GPT moment where our AI systems went from being kind of stupid

[00:36:50] and my, I don't want to say the name because she's listening, S-I-R-I and A-L-E-X-A. They're still kind of dumb. But then we kind of watched in front of our eyes chat GPT get smarter.

[00:37:07] And then just a couple of weeks ago with the Gemini 1.5 Pro release and with the GPT 4.0 release, we saw Mr. Potato Head that all of a sudden this intelligence suddenly it had eyes, suddenly it had ears and they were crappy eyes and crappy ears.

[00:37:27] But the first little multicellular organism that could see a little bit of light or hear a little bit of something, those were crappy eyes and crappy ears. And all of this stuff is getting better.

[00:37:39] So it's literally like when you watch those time lapse movies of something like a baby growing or something like that. It's like we're watching that movie every day and it's not just one technology, it's a whole slew of technologies. So what has surprised you?

[00:38:02] I mean, certainly the speed of AI systems getting smarter has surprised me. The speed of popular adoption, I mean, this is nothing that exciting, but the speed of popular adoption of chat GPT and chat GPT wasn't even that much better than other stuff.

[00:38:23] It was just it kind of reached people in a specific moment. And if I just look back over the course of just my life, and again, as someone who's been saying this stuff is coming, would I have...

[00:38:40] And someone who actually said we're entering the age of genome edited human babies. And I said it in congressional testimony 11 years before those babies were born. And actually in my last book, frankly, that I talked about with you and Hacking Darwin,

[00:38:59] I said, and this was it came out in the final version was in 2018 when the book was already in print being printed. And I called the publisher and I say we need to pull back the book from because the first CRISPR babies have just announced they've been born.

[00:39:20] But the edit that we need to make is really tiny, because I predicted this would happen. I predicted it would happen in China and explained why. And I gave a list of five specific genes that I thought were the most likely targets.

[00:39:36] And one of the genes, which is the gene that was edited in these three, what became babies were on my list. So all I need to do for this first version is say add a little paragraph and saying, and this thing happened and was announced on this day.

[00:39:56] And specifically, if I remember correctly, that was the gene that prevents, that if you have that gene, you won't get AIDS. That's the aspiration. So people, largely Europeans who have disrupted versions of this genes are less susceptible to HIV.

[00:40:14] But these kids weren't going to be born with HIV. They had one parent who had it. And so that's why it was so unethical. The goal was to give them increased resistance, but it's increased resistance for some time

[00:40:27] in the future if they happened to be exposed to HIV. So that's why it was so unethical. Why is that unethical? I don't get it. Because my feeling is if you're going to do something so aggressive as genome edit a preimplanted

[00:40:46] embryo, which is really big, and especially when it's the first time it's ever been done on a human embryo to take into term, that's a really big risk. If you said this kid, if we don't do this edit, will be born with this genetic abnormality

[00:41:03] that will cause this terrible harm, death or something else, then we could have that conversation. It's like, well, there's a big risk on doing experimental intervention on an embryo, but we know that the harm is clear.

[00:41:19] But in this case, there was no risk to that embryo and future child. And so what they were saying is we're going to take a huge risk of doing this experiment on this potential future child.

[00:41:34] And even if we're successful, and it turned out that the edit was not sufficiently targeted, even if we're successful, the only benefit will be that if at some point in the future this child is exposed to the virus, and maybe it's through a dirty needle or unprotected

[00:41:54] sex or something like that, that they will possibly have some percentage of additional protection. It just seems it wasn't worth the risk. The reason why I'm not against the, in principle, the editing of pre-implanted embryos is that

[00:42:10] you can easily imagine, and I described them in my last book, Hacking Darwin, what would be scenarios where you'd say, hey, this is really worth the risk. And that's why I've called this what happened in China, Nuremberg-style experimentation.

[00:42:23] But you know, okay, it's yes, Nuremberg-style, but it's happening to an embryo. So it's not quite Nuremberg-style where it's happening to adults. But they implanted the embryo. If it was just an embryo in a lab, then that's embryo research. And I'm actually pretty supportive of embryo research.

[00:42:43] But when you implant the embryo in the mother and grow that embryo to term, and you don't really know what's the implication of the intervention that you've made, in my mind, that is an unsupportable risk. I sort of agree.

[00:43:03] Like, I see what you're saying, because you're risking a life that didn't need to be risked. And even though that life is not born yet, it's going to be born, it's going to live and maybe have undesirable side effects because of this experiment. And you don't know.

[00:43:19] It's just an interesting— And you don't know when you're implanting it. Like if you could say, we're doing this, we have 100% certainty, what is the implication of the edit we've made on the pre-implanted embryo? So then you have another decision point, implant or not implant.

[00:43:37] But these guys, they did it, they didn't and couldn't at that moment because of just the state of technology, known what they'd done, whether it was good, bad, indifferent. Then they implant it.

[00:43:50] And so that's why I think that I can easily imagine an ethical way of doing exactly this type of thing. But this was not that. I agree with you. But I also think though ethics, this is like a societal thing or a cultural thing.

[00:44:07] And I don't think—like we always say, oh, China's willing to break the ethical rules. But for a microsecond, I'm going to defend them, which is that they think in terms of the collective, you know, that the individual—like we're individualists.

[00:44:24] Like America, the West, we believe that the individual comes first and the individual's happiness and protection and so on comes first. And that's baked into our legal documents and our religion and our philosophy.

[00:44:37] With China, because of the influence of Marxism or whatever else, they believe in the importance of the collective before the individual. So for them, I don't think they go into this thinking it's unethical, even though we think it's like a clear case of breaking ethics.

[00:44:52] See, I don't know. I mean, as you know, I have a PhD in Asian history. I live a lot of my world in this thinking about China. And I don't fully know the answer to that question.

[00:45:07] But if we just take He Jiankui, the doctor who took the lead on this at his word, what he was trying to do was to essentially bring nationalist glory to China by being the first

[00:45:24] and being a scientific pioneer and hero, which is a different motivation than saying I'm going to be the first in doing this great thing to benefit humanity. And I think that even with that aspiration—and who's to say?

[00:45:41] In a way, we've gone mad with our almost out of control individualist society. There's a role for individualism and there's a role for communalism. But for these technologies are really powerful life-altering technology. And my kind of core point is it's not that we shouldn't use them.

[00:46:01] It's just that we need to do so wisely. And to do so wisely, we should do so within frameworks. He Jiankui, the doctor, he went to prison in China in three years. So although he was praised for the first couple of days, he was then condemned.

[00:46:20] And there's lots of great science that's happening in China. But what we're talking about, as I said in the beginning, is our species has the ability to manipulate living systems. And we are living systems and we live in a world of living systems.

[00:46:32] And if we're making these kinds of decisions, we should do so as thoughtfully as possible. And so that's why if it's just individual people running off and doing it on their own outside of these frameworks, I think that becomes certainly riskier.

[00:46:49] So can you explain protein folding and AI that operates on proteins? This is like a new thing. You didn't really talk about this that much in Hacking Darwin. But there's a lot in this book about it. And it's very interesting and it's game changing.

[00:47:07] It's going to change the whole world. So A, protein folding, but then B, the AI that is figuring this all out and what it's going to do. Yeah, it's really important. So just a little bit of biology.

[00:47:19] And again, for people who are thinking about reading the book, my entire reason for writing books is to make complex stuff accessible to people. And so I think a lot of people are like, oh, protein folding, that sounds scary. That sounds like biology.

[00:47:32] And so I really want this to be kind of a book that you take to the beach and you think, oh, yeah, that was fun. And then, oh, my God, I accidentally learned a lot while I was having so much fun. So protein folding.

[00:47:45] So proteins are the part of our biology that does stuff. Like proteins are just the building blocks of life and certainly of our life. And as we've entered the new era of analyzing biology and sequencing biology, you can actually

[00:48:05] sequence a protein and proteins are made of amino acids. And you can get a string of letters that just tell you the order of the amino acids in that protein. And that can tell you a lot about the protein, but it can't tell you everything.

[00:48:21] And it certainly can't tell you enough to be truly meaningful because the two most important determinants of how a protein functions are, one, the order of these strings of amino acids, the letters, and two is the shape of the protein.

[00:48:39] Because it's these long things and because there's so little real estate in our biology, they have to kind of fold up in these tiny, beautiful shapes. Mark, you praised the cover of my book. That is a protein on the cover of a book.

[00:48:52] It's the folded protein from a skin cell. And so one of the hardest problems in biology called the protein folding problem has been can you predict the shape of a protein from the string of amino acids?

[00:49:10] You wouldn't be able to ask that question if we hadn't entered the world of genome sequencing and protein sequencing. And so it was such a hard problem that somebody set up kind of an Olympics of protein folding every two years.

[00:49:22] And basically, people would be given this string of letters and they'd be asked to use whatever programs or strategies they would have to predict the shape of that protein. And the way that you could test whether they were right or not is that we had a traditional

[00:49:37] model, which is the last innovation, called X-ray crystallography. And so with X-ray crystallography, you take this tiny, tiny, tiny protein, you turn it into a crystal and you X-ray it a gazillion times, and you're able to get a 3D model of that protein.

[00:49:54] And then you compare that 3D model to the string of letters of amino acids. To do one takes about three years for a graduate student or a postdoc or a professor. Three years for one.

[00:50:11] And is that because, and just the importance of this, again, the importance of knowing the shape as well as the letters is because it could have the same letters, but if it's different shapes, it does different things. 100%. Yes, exactly. Because both of them determine what it does.

[00:50:27] And before we move on, it's really important because if you're trying to make a drug, if you're trying to have a chemical that does something, let's say eats up the oil in an oil spill or just really just anything you can imagine, those two pieces, done with

[00:50:43] proteins and because life is done with proteins, that's kind of everything. This is a really important thing. So people have been trying to build computer models for predicting the shapes of proteins from these strings of amino acids for a while. So you mentioned AlphaGo.

[00:51:01] So the first there was AlphaGo, which defeated the world Go champion Lee Sedol in 2016. In 2017, AlphaZero, which didn't, unlike AlphaGo, it didn't train on the digitized games of Go. It trained by just being fed the rules of Go and asked to play against itself.

[00:51:19] And after three days of playing against itself, it became better than AlphaGo, which had beaten the world champion one year before. And so then in 2018, they said, all right, now we're going to try to address the protein folding problem. They created this new algorithm.

[00:51:35] This is Google DeepMind called AlphaZero. And then AlphaZero entered into this Olympics of protein folding and came in a disappointing 20th place. So they went back and they rejiggered the algorithm. They worked for two years, came back, as I said, it's biannual.

[00:51:51] In 2020, they won the competition so handily that Nature magazine declared that the protein folding problem had been solved. So that was a big deal. Now, did they fail initially because there weren't enough examples for them to train on?

[00:52:07] No, it was because the algorithms, I mean, certainly that's the kind of the rule of thumb for all of these areas is you need more data, more computing power, and better algorithms. Like that's the formula.

[00:52:19] And with those three ingredients, we can decipher more complex patterns that would be more and more complex, more and more difficult for our unaided minds to identify. That's kind of the essential formula of everything. And so all of those things got better.

[00:52:38] There was more data, more compute, and better algorithms. Certainly the better algorithms were key here because these algorithms were so great. So that's 2020. They won this competition. 2021, they released the predicted shapes, folds of 350,000 proteins, including all of the proteins in the human body.

[00:53:03] So 350,000 times three years, which is how long it would take to characterize one, that's like a million years of saved time. In 2022, they released 215 million predictions, all of the proteins known to science. So if you do 215 million times three years, 645 million years of time thrown back into

[00:53:32] the pot for humans who would have spent that time trying to characterize proteins now can spend even a fraction of that time trying to figure out what do we do with characterized proteins. It comes back to the earlier point of acceleration, that everything, because we're so connected,

[00:53:53] every day we're resetting the baseline, the starting point for everybody else. And we have more people and more technology and we keep resetting the baseline every day. Now that this is done, this seems like really big news, but how are our lives going to change?

[00:54:12] How is this going to make our lives better? So a big chunk of the book is about exactly that. It's the applications. And so basically the way the book is organized is the beginning is about the nature of change,

[00:54:25] how to think about technological change, how to internalize technological change. And in some ways, how do we think like science fiction writers in a world that just feels to us correctly like science fiction? And then I talk about the applications, which we'll talk about now.

[00:54:42] And then it's what could go wrong, your first question. And then the final chapter is what are the things that we need to do now to optimize the benefits and increase the odds that things will go right? So for the applications, this has the potential to revolutionize healthcare.

[00:54:59] And we're moving from our world of generalized healthcare based on population averages to our new world of precision healthcare based on understanding each person's biology. But as we get more and more data about each person's biology, we're going to have these

[00:55:13] massive data sets and we're going to be able to decipher patterns both in how human biology works and how each of our biology works. And that's going to unlock doors for specific treatments like gene therapies, personalized pharmacology, pharmacogenomics based on our biology, systems biology approaches to diseases

[00:55:36] where we're kind of less instrumental. And it's going to move us to a new world of healthcare that's more predictive and preventive where we recognize that we live in a range of possibility.

[00:55:47] And the goal of healthcare and health and life maybe is to optimize what's possible for us at the upper end of our capacity. And maybe in some cases go a little above, beyond our innate possibility and that's just

[00:56:00] healthcare but we can do it in lots of other areas. So give an example though, like let's say I have brain cancer. Is because of these new proteins that have been mapped out, will we be able to make a drug that will cure me?

[00:56:16] Let me give you a very, very, very personal answer to something like that question. And I just, so I don't upset any of your viewers or listeners, there's a really nice ending of this story.

[00:56:29] But while I was writing the healthcare chapter of the book a little less than two years ago, my father was diagnosed with stage four metastatic neuroendocrine cancer, which is the same cancer that Steve Jobs died from. And it was this huge shock.

[00:56:47] And I have, I'm one of, I have three other brothers. All of those are MDs. I'm a JD PhD for a mix of whatever reasons, including family dynamics, I've been the one overseeing my father's medical care, working with his oncologist.

[00:57:06] And from the beginning, I insisted that we do full genome sequencing of my dad's cancer cells, which was not the standard practice for this cancer. We have a really great oncologist in Denver.

[00:57:22] I worked very closely with him and the first chemo my dad was on, he tolerated it, it didn't work. He wasn't a candidate for what people had hoped for. The second, this radiation therapy.

[00:57:33] And then we were at this turning point where the oncologist was recommending a very aggressive chemotherapy and the sequencing had come back and there was a potentially targetable mutation. And there was a treatment that had been approved by the FDA, not for my dad's cancer, but just

[00:57:49] more generically like three weeks before. And I said, if we go on chemo, it's going to knock him on his ass and it's probably not going to help. This thing is new, but we have a specific target. Let's go after that.

[00:58:02] And so the oncologist had said at the time of the diagnosis, the best that we can hope for is to slow the spread. Remission is out of the question. My dad has had so much remission. I said Denver, but we're originally from Kansas City.

[00:58:17] We got him through last year's, the 2023 Super Bowl and the Chiefs won. And then we said, all right, we're going for next year's Super Bowl. He's doing so well. My brother and I took him to Las Vegas.

[00:58:29] We were right there, like right above where Nicole Hardman caught the winning pass in overtime of the Super Bowl. My dad is doing great. I just remember today he's at his grand, with my mother at his granddaughter's eighth grade graduation in Denver.

[00:58:46] It's because of these technologies that my dad is alive. It's because of these technologies that people like I mentioned, Victoria, or maybe I didn't mention, I can't remember. Victoria Gray. The woman who was essentially cured of sickle cell disease. This was, it's like-

[00:59:04] Is that because the identifying all these, the shapes of all these proteins allows you to look into the genome and see what might be mutating and what we can correct? And you saw a treatment that corrected this possible mutation related to this cancer?

[00:59:19] It's not all the protein folding. It's the integration of all of these technologies. With every one of these, there's a bunch of technologies that are woven together. Like with the sickle cell disease, certainly there's all of the sequencing.

[00:59:36] There's the gene editing to take these cells out of her body. Then there's basically what you do is you turn on the fetal hemoglobin. We have one mechanism for creating hemoglobin when we're fetuses. And then we have another mechanism when we're adults.

[00:59:54] With sickle cell, generally their adult hemoglobin manufacturing facility isn't working. So basically they turn on, turn back on this thing that biology had turned off. How much do you need to know about that?

[01:00:09] And then to reintroduce those cells back into the person in a way that their body isn't going to reject. There's no one technology that makes all of this stuff possible. It's a million technologies. Like in the book I write about the COVID-19 vaccines.

[01:00:32] And it's another, it's just incredible story where there were just so many different innovations that made those possible. Obviously, understanding how messenger RNA functions, but figuring out how to do genome edits so that our bodies wouldn't reject an intervention, figuring out how to make little

[01:00:52] balls of fat essentially that could deliver these payloads without being attacked by our bodies. And so that's why it's like there are certainly blow your mind technologies and certainly predicting protein folds and CRISPR genome editing.

[01:01:09] But the real story, hence the name of the book, is the super convergence of all of these technologies which are making incredible things possible. But the super convergence is also making ever more incredible things ever more possible.

[01:01:24] But you know, it's interesting though that like the doctor made his one prediction about remission and you had other thoughts about that because perhaps you knew the cutting edge of some of these technologies.

[01:01:35] If someone is sick or knows someone who is sick, how can they right now, there's such a wide spectrum of different, like the doctor is an expert, right? He's a great guy. You said he was an excellent oncologist.

[01:01:49] He's an expert and you're an expert also on all these futurist type technologies. How do you now know what to do? How does somebody think, like if I'm on my own, how do I figure out, oh, they just approved

[01:02:02] this obscure gene therapy that I could use for this? It's a really tough question because we want our doctors to be conservative. There's a reason why we have regulations and the reasons why, frankly, I was so critical

[01:02:16] of He Jiankui in China is there's a built-in conservatism in healthcare because it really matters to us. And certainly in this country, our liability controls are so strong. Like I mentioned the COVID-19 vaccines. These were historically incredible vaccines, saved millions of lives.

[01:02:39] But certainly there were small numbers of people who were likely harmed by this vaccine. And Joe Rogan and others have talked about teenage boys who had myocarditis and some of them probably died from this and it may well have been connected to the vaccine.

[01:02:59] So our standard is zero tolerance for things going wrong. And so if that's the message that we've given to our healthcare system, we collectively don't want our doctors to be kind of taking these kinds of risks.

[01:03:14] And like I said before, maybe it's not coincidental that I'm the one non-MD in my family and I was the one who was pushing for the new stuff because I have a younger brother who's a phenomenal doctor. And he in the beginning was saying, what are you doing?

[01:03:28] You're only causing harm. The strategy is don't do anything and trust the doctor. And he's a great doctor. I think he knows what he's doing and he doesn't like when people heckle him. I have a great relationship with our oncologist in Denver who's literally unbelievably phenomenal.

[01:03:46] But yeah, but certainly things are moving so fast that there's a lot of education that's required for anybody. How would someone even know though to pursue this? Disease now is getting such multi-dimensionality, let's call it. There are so many new factors now introduced into what a disease is.

[01:04:09] How do you know, how can you know what can cure it or are we just going to have to wait now until... I mean that by itself is going to become a profession, being able to navigate between traditional medical care and this new stuff with genomics.

[01:04:23] Yeah, so again, I think everybody needs to educate themselves because there are things that the system will not provide. The system's not organized to provide certain things. If we said, all right, everybody gets a whole genome sequence, the system would collapse

[01:04:38] because everyone's saying, oh, I found some rare mutation and I'm making 600 doctors appointments and then the doctors don't know what it is. So I certainly think that people should educate themselves. And I'll tell you what I do just for me personally.

[01:04:54] There's a test, a GRAIL test, which is a liquid biopsy and it costs like $1,000. They send the phlebotomist to your house, they take blood, they send it away for sequencing and they find basically biomarkers. They look for biomarkers for 50 different cancers. Luckily I didn't have anything.

[01:05:13] Once a year when I can, I go to India and at Max Hospital they have a preventive health checkup where it's basically you go at 830, they have a little guy. They run you room to room.

[01:05:23] You get like 50 gazillion checks and they serve you lunch, come back a couple of days later and they have a stack, a thick stack of all these reports and you meet with primary care doctors who tell you what they've seen. I personally believe that knowledge is power.

[01:05:39] The sooner we have that knowledge, the better off we'll be. And for sure- Why is that hospital in India? It happens to be in India. You could do it here. It would just cost you a gazillion dollars in India. This whole thing is $250 and lunch is included.

[01:06:03] And why specifically is it a little guy taking you from room to room? Does he have to be little? That's a very important question. I think it has to do with village nutrition in India.

[01:06:14] I'm sure if you brought this guy here, this little guy as an infant and they ate the crap and all the protein and meat that we eat, they would be like the big guy. This guy and the other guys seem to not be huge in India.

[01:06:32] Well, I want to also ask about AI. You both know chat GPT 4.0 was just released and it's a nice improvement over chat GPT 4, which was a huge improvement over 3.5 and 3. Are there areas where you think AI might plateau in terms of its benefits and other areas where

[01:06:56] it will keep increasing at an exponential rate? For instance, AI is getting better and better at rendering a great movie. To the point where Tyler Perry, the famous movie producer and director, he stopped building

[01:07:13] a $300 million facility because he says, AI is going to do all my stages and sets and makeup and sound and cameras and everything. He doesn't need a facility. On the flip side, I'm wondering if storytelling like screenwriting will plateau because ultimately AI doesn't have human experience.

[01:07:35] I don't know. I'm just making this up. It's a great question. I for sure think that LLMs, large language models, will plateau. That's just one philosophy, one approach, one algorithm. I think like everything else, it'll be good at some things and not good at some things

[01:07:54] and we'll figure that out. That's just one approach. Under the umbrella of AI, there may be thousands of equivalent algorithms like the LLMs. The LLMs themselves might be able to come up with other algorithms with different philosophies about how to do AI.

[01:08:15] Those different systems would also have, like every person and every species, some mix of things that they're really good at and some things that they're really bad at. I also believe, like people talk about AGI, artificial general intelligence, the whole

[01:08:29] concept doesn't make any sense to me because if we're talking about machines that can do a bunch of different things well, we already have those. We have AI systems that can play Minecraft and chess and go and other things.

[01:08:45] If we're talking about an AI system that can do everything that humans can do, I would really be terrified because humans, we're this mixed species with 3.8 billion years of evolved bodily, evolved intelligence that's connected to all of our other senses.

[01:09:05] It's embodied in this human form that we have. As I said in the beginning, I don't think that we're moving toward AGI, whatever that is. I think what we are doing is giving birth to machine intelligence and probably machine super intelligence.

[01:09:23] Then we're going to have to figure out just like if Martians landed on Earth or if we gave birth to Martians somehow, what's our relationship with them? It doesn't mean we're totally disempowered, but it does mean that now is the time we

[01:09:38] need to start thinking about what are our goals. It's like you said though about the protein folding. One year it did 315,000 proteins that it figured out the shape of. The next year, 200 million and saved us 600 million years of time. That's something that's not plateauing or it didn't plateau.

[01:10:04] Whereas let's say AI's ability to write a love letter to your girlfriend, that might plateau. Right. Because ultimately, I don't know why that might plateau, but it seems to me looking at the output of when you ask the AI to write something creatively, it doesn't really seem

[01:10:23] to get that much better. Maybe it uses a few less adjectives and the writings are less cringy, but it doesn't really seem to. These are the pong days of AI, so who knows where things will go.

[01:10:33] What I'm saying is I believe that humans, we have our unique superpowers. We just don't yet fully know what they are relative to our machines. There could be things that we really value now that it turns out these are just commodities that will have no value.

[01:10:55] There could be things that we don't really value that much now, like somebody who has like tremendous empathy or compassion or the most loving person who's working in an assisted living facility making $33,000 a year. Those are the human superpowers.

[01:11:15] I think that's why we just don't know what the strengths of our machines are going to be, although they are going to be incredible based on their just period, I should say. We don't know what are the attributes of us that we're going to value the most.

[01:11:35] That's why we need a dynamic, continuous process for trying to figure this out. Say, well, what are the guardrails around our machines? What are the goals? How do we achieve them? What type of engagement do we want with people?

[01:11:53] How do we think about the future of to insert the thing because technology is going to touch that thing, whatever it is? Also, Jamie Metzl, author of Super Convergence and previously Hacking Darwin, so many great insights in all of your books about what the future...

[01:12:14] It always gets me so excited talking to you because it's sky's the limit really, but there's a lot to learn and a lot to know to understand that. Give us a prediction. Tell something in the future that doesn't exist yet.

[01:12:29] Before I do that, there's a lot to know. I say this a lot. This is a conversation that's ultimately not just about the technology. It's about the values. It's about what values do we want to infuse into our technology and into this journey

[01:12:48] so that when we get wherever we're going, it's going to be familiar enough to us based on our essential sense of who we are and what we stand for. That's really the denouement of the book is to say, well, how do we think about doing that?

[01:13:10] In terms of predictions, and again, it's hard not to... I also, as you know, James Wright, science fiction, it's hard not to just sound boring, but I just think that we're going to be able to do all these things that we love to do

[01:13:27] in just more sustainable ways. We're not going to get rid of all diseases because if we cure these diseases and live longer, there'll be a whole new set of diseases. I hope we're going to have a different relationship with the natural world around us and whether

[01:13:45] that's through plant and animal agriculture or industrial materials, and we can get away from the killing, digging up, cutting down models to the growing models where we can think differently. Data storage, none of us are any smarter than our ancestors 50,000 years ago, but we live our lives...

[01:14:09] Actually, there's a lot of evidence that we're less intelligent. Probably. Because we don't have to know. 50,000 years ago, they had to know in a five-mile radius every crop, wild animal, place where they could sleep. I don't even know what's in my closet.

[01:14:25] Don't eat any crops or wild animals you find out on the street in New York, by all means. I don't know what's 30 feet away from me right now. Exactly. In New York City, there's at least one rat within 14 feet of you on average. Exactly.

[01:14:39] Even if we were desperate, I don't think we would know how to catch it and eat it other than the poor owl. I can't remember his name. May he rest in peace. I think we're going to have to just think differently about how we interact with the world.

[01:14:55] Then cultural inheritance, as I was saying, the reason we live our lives is because of our cultural inheritance. We're generating more data every two years than in the entire history of humanity up to that point.

[01:15:07] I think that DNA data storage, as I write about in the book, is going to give us... Under the right conditions, you can store data reliably in DNA for five million years unlike the 30 to 50 in magnetic tapes.

[01:15:20] I do think it's our inevitable future that we humans are going to leave this planet. I don't think we're going to be living in Alpha Centauri, but I do think that we're going to be living longer term in space.

[01:15:37] I think that we're going to have to use these technologies and we're going to have to recognize our future is not human alone. It's not AI alone. It's human plus AI. That means humans interacting with our machines and, in some ways, humans merging with our machines.

[01:15:55] That scares people. We already have cyborgs, people with cochlear implants, people with pacemakers. I just think that that is going to increase. There's just a whole set of experiences that we can't even imagine now because of these interfaces. I'm speaking with you, James.

[01:16:15] Imagine if I had just kind of... There are all these things that are happening in me as we speak that even I am not aware of. Imagine if we all had sensors and we were able to know what was happening in another

[01:16:28] person in a way that that person themselves didn't even know. I think that we can really, when we get beyond ourselves, and that's the story is that we're this one species that is pretty significantly getting beyond ourselves, there's a whole

[01:16:44] world of possibilities that we really have to kind of take a step back to imagine. Certainly with my books, what I want people to do is to kind of take a first step back with these ideas and then say, all right, well, what's another step back?

[01:17:02] That's why I love hearing from readers because I try to think of a lot of stuff, but there's a lot of stuff that I haven't thought about. I love that's what's so exciting about sending out a book into the world is you put so much

[01:17:14] heart and soul into a book, and then it becomes this object that other people absorb in their way on their terms. It's always very exciting for me to hear about what comes back.

[01:17:26] Well, after I read one of your books, I always feel like I want to write a science fiction novel because there's so many new ideas and so many things I can think of.

[01:17:35] That's often a way to communicate what some of these ideas are and what some of the potential is through storytelling, through fiction. And you do such great work, James, because not everybody, myself included, has time to read every one of these books or ideas.

[01:17:51] You do such a great job of making these ideas accessible to people. Somebody was over my house recently and looked at my library of books and he asked the typical question which is, I bet you've only read like 5% of those books.

[01:18:07] And I said, no, unfortunately, I'm one of the few people who's probably read all of the books on the bookshelf because they're all books for podcasts so that I just have to read all of these. I love it. For good.

[01:18:19] I mean, but I'm not like, I don't have the... There's a Japanese phrase for it where most of your library is unread. So you have this anticipation of reading it all. And I've read everything on my bookshelf.

[01:18:31] I have to always get new books to have stuff that I haven't read. I love it. Well, Jamie, thanks so much again. You're always welcome on the podcast. Anytime you want to talk about anything or even if just some of your predictions come

[01:18:44] true and you want to brag about them, come on back and we'll talk about it. Awesome. James, I always love joining you and it's great to see you. And the book is Super Convergence, How the Genetics, Biotech, and AI Revolutions Will Transform Our Lives, Work, and World.

[01:18:59] Super Convergence.