Alexandr Wang - CEO, Scale AI | SRS #208

[Music]. Alex Wang, welcome to the show, man. Yeah, thanks for having me. I'm excited. So am I. I like I was telling you at. breakfast, I don't I don't know a whole. lot about tech, but ever since Joe came. on, I've been trying to wrap my head. around it all and it's just fascinating. subject. I I love talking about this. subject now. So, thank you for coming. Well, it's becoming so critical to. national security and all the stuff that. you're very passionate about. So, I.

mean, I think I think fundamentally tech. is like we got to get it right, otherwise stuff gets really dangerous. Yeah. Yeah. Scares the [ __ ] out of me. In fact, we were just having a. conversation downstairs about about you. having kids and you were waiting and and. and Neurolink came up and I had to I had. to I had to pause the conversation. Dude, I'm like I'm worried about. Neurolink, but it sounds like you're. pretty gung-ho about it. So yeah, a few. things. So yeah, I I mean what I mention.

is basically I want to wait to have kids. until we figure out how neural link or. other it's called brain computer. interfaces. So other ways for brains to. interlink with with a with a computer um. until they start working. Uh because so. there's a few reasons for this. First is. in your first like seven years of life, your brain is more neuroplastic than at. any other point in your life like by by.

an order of magnitude. So there have. been examples where you know for example. if somebody if a kid is born like you. have a newborn that has let's say they. have cataracts in their eyes so they so. they can't see through um uh the. cataracts and then they live their first. seven life seven years of their life. with those cataracts and then you have. them removed when they're like eight or. nine then even with those removed. they're not going to learn how to see. because they're it's so important in.

those first seven years of your. development that you're able to you're. you're able to see that your brain can. like learn how to read the signals. coming off of your eyes. And if you if. that's not if you don't have that until. you're like eight or nine, then you. won't learn how to see. So because it's. so important that your neuroplast your. your neuroplasticity is so high in that. early stage of life. I think when we get. neural link and we get these other. technologies kids who are born with them. are going to learn how to use them in. like crazy crazy ways like it'll be a.

actually like a part of their brain in a. way that it'll never be true for an. adult who gets like a neural link or. whatever hooked into their hooked into. their brain. Um, so that's why to wait. Now, Neurolink as a as a concept or like. taking hooking your brain up to a. computer. Um, I kind of take a a. pragmatic view on this, which is, you. know, my day job, I work on AI. I. believe a lot in AI. I think AI is going. to continue becoming smarter and.

smarter, more and more capable, more and. more powerful. Um, AI is going to is. going to continue being able to do more. and more and more and more. We're going. to have robots. we're going to have. other forms for that AI to take over. time. And so, and humans, we're only. evolving at a certain rate. Like, humans. are, you know, we are, humans will get. smarter over time. It's just on the time. scale of like millions of years because. natural selection and evolution is. really slow. I don't know. Are we. getting smarter?

I don't know about recently, but uh. little setback. Yeah. A little a little. blip. Um, so if you play this forward, right, like you're going to have AIs. that are going to continue getting. smarter, continue improving, like. they're going to keep improving really. quickly. And, you know, biology is going. to improve only so fast. And so what. what we need at some point is the. ability to tap into AI ourselves. like. we're going to need to bring biological. life alongside all of the silicon based.

or artificial intelligence and we're. going to want to be able to tap into. that for for our own sake, for. humanity's sake. And so eventually I. think we're going to need some interlink. or hookup between our brains directly to. AI and the internet and all these. things. Um, and it's a it is potentially. dangerous and it's potentially, you. know, to your point, terrifying and. scary, but we just are going to have to. do it. Like AI is going to go like this.

Humans are going to improve at a much. slower rate and we're going to need to. hook into that capability. I mean, what. you know that I've already expressed. fear in this and and so I'm I'm curing. my own fears, I'm just curious like what. what in your mind what could go wrong? I. mean the there's like the obvious thing. is that some corporation hacks your. brain. Well, if a corporation hacks your. brain, which even that's pretty bad, but. that'll be like what? They'll like adver. they'll like send ads directly to your.

brain or they'll like make it so you. want to buy their products or whatnot. But then even worse, obviously a you. know foreign actor, a terrorist, an. adversary, a state actor, you know, hacks into your brain and um and takes. your memories or takes you know like. manipulates you or all these things. I. mean that is that's obviously pretty. bad. Yeah. Um and I think that's I to like. it's definitely a huge risk. I mean for.

sure if you have a direct link into. someone's brain um and you have the. ability to like read their memories, control their thoughts, read their. thoughts, like um you know that's pretty. bad. Uh I've I've talked to a lot of. scientists in this space and a lot of. people working on this stuff including. the folks at Nerlink and um you know. mind reading and mind control are like. those are the that is where the.

technology will go over time right and. so um it is like it's something that we. have to you know like any advanced. technology we have to not [ __ ] that up. um but it's going to be pretty critical. if we want if we want humans to remain. relevant as AI keeps getting better. I. mean, I interviewed um Andrew Huberman. Do you know who that is? Yeah. Yeah. Yeah. And and um and talked to Ben Car.

Dr. Ben Carson about it too as a kind of. a follow-on discussion. But what Herin. was telling me is that cuz this whole. thing is it sounds like it's it's I. don't know a whole lot about Duralink, but from what I've gathered it's it's. going to help the blind see and it. sounds like it helps with some um. connectivity in your joints and bones. and stuff for people that are paralyzed. But something that Huberman brought up. is that I was like, well, if if it could.

is going to help the blind see, then. could they project a total false reality. into your head? Meaning, you're seeing. who knows what [ __ ] in the skies. everywhere? Sounds like they could. recreate an entire false reality. He. said, "Yes, they will have that ability, but not only will they have that. ability, they can they can manipulate. every one of your senses. touch, smell, taste, uh, insert emotions into your into your. brain, fear, what, whatever it is. And I.

was like, "Holy shit." Like, they they. could manipulate your entire reality. into a false reality. I mean, you think. that's And then I asked Dr. Ben Carson. about it and he said, you know, who's a. a worldrenowned neurosurgeon, he said, "Yes, absolutely. They" He goes, "Or, you know, they could use it for good.". But he goes, "What?" He was he kind of. put it on me. He's like, "Well, what do. you think would happen?" And and like. would it be used for good event? Uh or. would it be used for evil? And I I mean,

what are your what are your thoughts on. that? You think that's a real. possibility? I mean, yeah. So, first of. all, like we don't understand the brain. too much today, but eventually we will. Like, we're like science is going to. solve this problem, right? And um. everything you just mentioned is. ultimately going to be on the table, you. know? um manipulating your emotions, manipulating your senses. The senses. thing is already happening where I think. in monkeys they've shown that like um. they can, you know, they don't know what.

it's like from the monkeykey's. perspective, but they're able to project. like on a grid of a monkey and get them. to like like click on the right button. really reliably. So they they somehow. they hook into basically the neural. circuits that are doing the visual. processing visual like image processing. in the brain and they're able to project. like things into their into their vision. such that the monkey will like always. click the button that you want it to. collect to to click. Um and then you.

know you give it you know a treat or. something. Damn. And so yeah. manipulating vision, manipulating your. senses, manipulating your emotions. Um. uh this is this will be longer term but. like leveraging your memories um. manipulating your memories, manipulating. like uh those are that stuff is on the. table. The other stuff that is I think. more exciting is like being able to hook. into AI and like all of a sudden I have.

encyclopedic knowledge about everything. and just like you know ChachiPT or other. AI systems do. I can like think at. superhuman speeds. I can um all of a. sudden I can like uh I have like way. more information I can process like I. can like understand everything that's. going on in the world and process that. instantaneously. Like I think there's. there's an element here where it'll. legitimately turn us superhuman um from. a just cognitive standpoint. But then to. your point, like the the flip side of.

that is the um is the risk the other. way, which is that you're going to have. uh it's a huge attack vector. Um, yeah. I mean, in. like I said, I'm not I'm not super tech, but your company Scale AI, you. basically, correct me if I'm wrong, scale, scale AI is basically the the. database that the AI uses to come up. with its answers and answer your prompts. and all of that. Correct. Yeah. So, we.

do we do a few things. So we help large. companies and governments uh deploy safe. and secure advanced AI systems. Um we. help with basically every step of the. process. But the first thing that we. were known for and we've done very well. is exactly what you're saying which is. creating largecale data sets and. creating data foundry is what we call it. but creating the large scale data. production that goes into fueling every. single one of the major AI models. And. you know if you ask questions in chat.

GPT you know that question uh you know. it's able to answer a lot of those. questions well because of data that. we're able to provide it. And as AI gets. more and more advanced you know we're. continually f fueling more advanced. scientific advanced information and data. into those models. And then we also work. with you know the largest you know. enterprises and and governments like the. DoD and and other agencies in the US to. deploy and build full AI systems. leveraging their own data. And our.

strategy as a company has been you know. how do we focus on we have how do we. focus on a small number of customers who. where we can have like a really big. impact. So we work with the number one. bank, we work with the number one pharma. company, the number one healthcare. system, the number one telco, um the. number one country, America. Uh and uh. and we work with all of them to like how. can you no kidding take how you are. operating today and take sort of the. workflows that you're doing today or the.

operations that you have today and use. AI to fundamentally transform them. So. if you're like the largest health care. system in the world, how do you and you. have to, you know, provide care to all. of these patients, you know, millions of. patients, how do you do so in the most. effective manner? How do you do it. logistically better? How do you improve. your diagnosis? How do you improve the. the overall health outcomes of all of. your patients? Like that's a problem. that we help solve with them. or for the. DoD, you know, there's so much that we. can do to operate more efficiently and.

uh and ultimately in a more automated. way. I mean, you'll know this, I think, better than anyone. And so, how do you. how do you start implementing those. systems with AI? Mhm. We we'll dive way. more in the weeds of that later in the. interview. kind of where I was going. with this was if so if originally it was. it was feeding the AI you're given the. data center you're giving the data to. the AI to you come up with the answers.

and and and and answer the prompts and. so where I was going is if if you have. Neurolink in your head and it's. accessing your data centers how easy. would it be to just feed [ __ ] into. the data center that then feeds all. everybody that has a neural link in. their head. So it could be I mean it. could be anything. I mean here here's an. example. I'm a Christian. A lot of. people think that AI is going to.

manipulate the Bible and change a lot of. things. And so how easy would it be to. just feed that into the AI data center. and then. that's that's the new whatever you feed. it that becomes the new truth because. that's what everybody's accessing is. that specific data. Yeah. I mean I think. a yes for sure that's a huge risk and. this is one of the reasons why I think. it's really important that US or other.

democratic countries lead on AI versus. the CCP like the Chinese Communist Party. or other or Russia or other autocratic. countries because the potential to. utilize even AI today by the way you can. use it to propagandize to a dramatic. degree but yeah once you get towards you. know you have neural link or other brain. computer interfaces that are that can. directly, you know, um insert thoughts. into into people's brains. I mean, it's. it's extreme power that has never.

existed before. And so, who governs that. power? Who governs that technology? Who. makes sure that, you know, it's used for. the right purposes? Um those are like. some of the most important societal. questions that we'll have to deal with. Man, I mean, where do you even where do. you even start with that? Who do you. trust to control your [ __ ] mind? Yeah. I mean, I think well, it's.

interesting. I think the one thing that. I think has been um I think a lot of. people kind of understand it now and we. were talking a little bit about this at. breakfast is like even the degree to. which even just general media today kind. of controls your mind or controls the. like opinions you have or the beliefs. you have. And you know, um, you know, we. were talking about like, you know, is. does does the media prop up certain. military forces to make them seem far. more fearsome than they actually are?

And like, you know, there's like some. lowgrade you can kind of view like some. lowgrade um forms of like, you know, um, propaganda, propaganda, manipulation, all that stuff is like happening like. let's say like on a scale of 1 to 10 at. the one or two level today. And then. once you have Neuralink or other. devices, it's going to be like a nine or. a 10. And um and I think it's really. hard. I mean, I think I don't think.

any country is prepared to govern. technology as powerful as a technology. that we're going to be developing over. the next few decades. Like AI, I don't. know if we're prepared. Um brain. computer interfaces, I don't know if. we're prepared. Large scale robotics, I. don't know if we're prepared. Like these. are technologies that are just so much. more powerful than anything that has. come before. Sometimes people will say. like, you know, AI is the new mobile. You it'll be as big as mobile phones and.

it's just no, it's going to be like a. thousand times bigger and more important. and like more impactful. Um, and it's. not clear that we did the best job. regulating mobile phones even. So, um, there's it's going to be uh it's going. to be really important that we get it. right. If you ever feel like the modern world. is wearing you down, things like EMFs, artificial light, seed oils, microlastics, chronic stress, it seems. like our biology wasn't designed for.

these modern assaults, and it's probably. taking a toll on all of us. Armor. colostrum is a bioactive whole food that. can help revive cellular signaling and. help bolster our health from within. Colostrum is nature's finest whole food. packed with over 400 bioactive nutrients. that work at a cellular level to help. strengthen your immune health, help. fortify gut health, and help kickstart. your metabolism. I've been using Arma. ever since they sent me some to try and. now I have a lot more energy. It's part.

of my daily routine now. I take it in. the morning and after workouts. Are you. ready to reclaim your health? We've. worked out a special offer for my. audience. receive 15% off your first. order. Go to tryarma.com/srs. or enter SRS to get 15% off your first. order. That's tr.com/srs. These statements and products have not. been evaluated by the FDA. These. products are not intended to diagnose,

treat, cure, or prevent any disease or. condition. When your metabolism is working. properly, you can feel the benefits in. literally every aspect of your life. Lumen is here to help. Lumen is one of. the world's first handheld metabolic. coaches that can help measure your. metabolism through your breath. Just. breathe into your Lumen and get a world. of insight. Because your metabolism is. at the center of everything your body. does in optimal metabolic wellness.

translate to benefits like improved. energy levels, better fitness results, and more. I check mine every morning, and on the app, it lets me know if it. detects if I'm burning fat or carbs, and. gives me tailored guidance to help. improve my nutrition, workouts, sleep, and even stress management. It's amazing. and gives me the insights I need to take. control of my health. The warmer months. are coming. Spring back into your health. and fitness. Go to lumen.mers. to get 10% off your Lumen. That's.

lumme.me/srs. for 10% off your purchase. Thank you. Lumen for sponsoring this episode. These. statements and products have not been. evaluated by the Food and Drug. Administration. These products are not. intended to diagnose, treat, cure, or. prevent any disease or condition. everybody that gets what I mean. You. could you could basically. instantaneously have your have an entire.

army, an entire nation that's linked. into your thoughts, your way of thinking. and manipulate that entire population to. do who the hell knows what. Hopefully. something for good, but you know how. things wind how things generally wind up. going. But you're gung-ho about this. stuff. Would you put it in? I would. I would put it in, but I would I would. be, you know, I there's a few things. that need to happen before I I'd be. willing to put it in. First, I would. need to really feel good about the cyber.

offense defense posture. Like I need to. have really good confidence that I would. be able to defend from uh any attacks. like any sort of cyber attacks into, you. know, my brain interface. Um uh and. that's like that's one big bar. Um and. then I would need to feel pretty. confident. I would need to feel. confident that there were um that uh it.

wouldn't deeply alter my consciousness. in any major way like and that I think. you would see from data of other people. who like use it and you you know you. kind of get a sense just from like other. people adopting it. Um those would be. the two things I would need to like feel. really really confident about. It's a big thing. It's a big thing. Well, the last thing, you know, and then. we should talk about other stuff, but. the last thing about this is um. uh you know, one of the things that you. know people are there's a lot of talk. right now about how humans will live.

forever, right? Or like can humans live. forever? How do you not die? And a lot. of that's a lot of that's focused on. keeping our human bodies healthy and. keeping our, you know, how do you like. how do you take care of yourself? How do. you take care of your human body? How do. we cure diseases um such that like. humans can live to hundreds and hundreds. of years? But I think what's the the. actual endgame is that we figure out how. to. upload our consciousnesses.

from our from our meat brains into a. computer. And I kind of think about um. Neuralink or other like other bridges. between your brain and and computers as. like the first step there. Well, hold. on. What? There's a whole another rabbit. hole we can. So, you're saying that we. we we should be able to upload our. consciousness or you want to be able to. upload our consciousness into. whatever. Yeah, I think I mean now we're.

like we're on the like deep end of. sci-fi, but um but yeah, I mean I think. I think there will over time be. uh there. So, one I think the technology. will exist at some point. We're we're. not close today, right? We barely have. Neuralink, you know, kind of working, right? So, we're not close, but the. technology will exist to upload your. consciousness onto a computer. Holy. [ __ ] And then, okay, let's say, let's.

say we're sitting here, you know, it's. like 50 years from now, this technology. exists. Um, and you're asking the. question, uh, you know, are people going. to upload their consciousness? Well, first off, there's a lot of people who. who naturally would like people with. terminal illnesses, um people near. death, um you know, uh people who are. like very fringe and you know, like. experimenting with this new technology, there will be a class of people who will.

just initially do it. Mhm. And then um. and then as that starts to happen and. they upload their consciousness like the. if you have a digital you have these. sort of like digital intelligences. um they're uh you know that's true. immortality. That's the closest thing. you'll get to to true immortality. Um. and so the uh I think it's going to. become. like once the technology exists, you. know, when it exists, it's going to.

become quite uh uh it's probably going. to become a very natural path for most. humans to go down. So what do you what. do you think what do you think happens. if you get your consciousness uploaded. and what would it even be uploaded into. like a cloud or something? Yeah, it' be. uploaded to a cloud. What do you think? Do you think that you can experience. life by uploading your consciousness to. a cloud? Yeah. So, so uh yeah, this is. uh few things. So, first um I'm a big.

believer in robotics. I think we're. basically at the start of a robotics. revolution. Um and we're in the very. early innings of it, but people are. starting to make humanoid robots. They're going to get really, really. good. people are starting to apply them. to manufacturing and industrialization. and other contexts. Um I think the costs. are going to come down dramatically and. so eventually yeah if you you would. believe that if you uploaded and then. you could download or down link down to.

a down to a humanoid robot then you. would kind of experience the real world. like any other world. Um, or you would. you could continue in some kind of like. simulated universe in uh you could. almost like play a video game in the. cloud kind of thing and that could be. like the other alternative. Wow. What do. what do you think happens when you die? uh.

you know the as AI has gotten. so um so Elon always talks about how. we're in a we live in a simulation right. um uh and I remember when I first heard. him talk about this I was like ah no. this is like I don't believe that I. don't believe we're in a simulation but. um but as AI has gotten better and. better at simulating the world like I. don't know if you've seen these AI video.

um generation models like Sora or VO or. some of these models but you know they. can produce videos that are totally. realistic um you would most people could. not tell the difference between AI well. we're seeing this AI generated video and. uh and and real video and as that's. happening it's making me think more and. more that. we probably live in a simulation no [ __ ]. it. Yeah. How do you just This is. already fascinating. We haven't even got.

to the interview yet. How How do you. think we're living in a simulation? I. mean, I know they they say they they. cannot disprove it. Yeah. You can't like. It's kind of one of these things. There's there's no way to prove or. disprove. that that you live in a simulation. And. so, but it's like it's like it's like. any, you know, afterlife thought or. religious thought like all these things. that are like fundamentally unprovable. But the reason I think it's the case is.

I think in our lifetime we are going to. be able to create simulations of reality. that will be hyper realistic. Like I. think we are gonna create the ability to. um simulate different versions of our. world with hyperrealistic accuracy. Um. and uh and that will happen over the. next few decades. And if if we can like. it's kind of like that Rick and Morty. episode where if we have the ability as.

an intelligent race to produce, you. know, millions of simulated worlds, um. then the likelihood is that we're, you. know, we're probably also the simulation. of some other uh more intelligent or. more capable species. Where do you think. consciousness goes right now when you. die? Uh, what if we are what if we are the super.

advanced. robotics? Yeah, I think um and your consciousness. just gets downloaded into another body. generation. Yeah, that's true. That would be that's. that's something like one way to think. about it which is like yeah it's all. this big simulation that's running and. as soon as like you know you get you get. kind of like downloaded or like taken. off or like decommissioned from you know. one entity you get like you know.

uploaded to another entity kind of. thing. Um it's kind of that that's. plausible. I think there's another world. where like consciousness is like is. consciousness may not like be that big a. deal so to speak. like it could be the. case that you know I definitely as as. the models have gotten better and better. as the AI models have gotten better and. better um you look at them and uh. you know you definitely wonder if at. some point you're just going to have.

models that are properly conscious and. it may just be the fact that like you. know it's something that can be. engineered and if it's something that. can be engineered then um then all bets. are off I think damn. it's pretty wild to think about. Yeah. Yeah. But uh let's move into the. interview. You ready? Yeah. All right. Everybody starts off with an. introduction here. So, here we go. Alex Wang, founder and CEO of Scale AI,

a company that's backbone of the AI. revolution, providing the data and. infrastructure that powers the AI. revolution. Child prodigy who grew up in. Los Alamos, New Mexico, surrounded by. scientists with parents who were. physicists working on military projects. Coding wizard who by age 15 was already. solving AI problems at Kora that stumped. P PhDs. Visionary entrepreneur who. dropped out of MIT at 19, turning a Y.

combinator startup into a national. security powerhouse that's helping the. US stay ahead in the global AI race. youngest self-made billionaire in the. world by age 24, built a company valued. at nearly 25 billion while staying laser. focused on solving the biggest. bottleneck in AI highquality data. Unafraid to call the US China AI. competition and AI war, warning that the. Chinese startups like Deepseek are. closing the gap faster than most.

realize. guided by your mission to build. future where AI drives progress, security, and opportunity. And so. there's a big. question right now that everybody's that. everybody's thinking about. Is AI the. next oil? Yeah, I think uh few thoughts there. Um. in some ways yes, in some ways no. So uh. AI is definitely the next um some ways.

in which it's it is the next oil. AI. will fundamentally. be the lifeblood of any future economy, any future military, any future. government. Like if you play it out, you're like the degree to which a. country or economy is able to utilize AI. to make its economy more efficient, to. automate parts of its economy, um to do. automated research and development,

automate R&D, like you know, push. forward in science um using AI. All that. stuff is going to mean that countries. that adopt AI effectively will have. like, you know, nearly infinite GDP. growth and countries that don't adopt it. are going to get are going to get left. behind. Um, so it is it is sort of the. the fuel that will power the future of. of every country. And by the way, I. think the same is true of of hard power. Like if you look at what the militaries.

of the future are going to be like or or. what war looks like in the future, AI is. at the at the core of of what that is. going to look like. I'm sure we'll get. into that. Um and then the ways that. it's not like oil is, you know, oil is. this finite resource. you know, we we. you know, countries that stumble upon. large oil reserves, they they have that. large oil reserve. At some point, it's. going to run out. Like in Norway, you.

know, it runs out at some point. And um. and so it it lends the country power and. economic riches for a time period. Um. and then you exhaust it and then you're. looking for more oil. Whereas AI is. going to be a technology that will just. keep compounding upon itself and will. keep, you know, um the smarter AI, the. more economic power you're going to get, which means you're going to build. smarter AIs, which means you have more. economic power and so on and so forth. And so it's going to there's going to be.

a flywheel that keeps going on AI, which. means that um it's not going to be a. timebased. a timelmited resource, let's say. It's. going to be something that that will. just continue racing and accelerating. for the entire per perpetuity and and. data is part of that. Data is a big part. of that. Data is the core part of it. Yeah. So, so a lot of times actually um. uh I like to compare data to oil versus. AI. That's actually what I meant. I.

[ __ ] that up. I meant to say data. Yeah. Yeah. Well, I mean I think that's. totally true. like data. If you think. about AI, it boils down to like how do. you make AI? Well, there's like three. pieces. There's um the algorithms like. the actual code that goes into the the. AI systems that you know really smart. people have to write. Um I used to you. know write some of these algorithms um. back in the day. Uh then there's the um. then there's the compute the. computational power which boils down to.

large scale data centers. you know, do. you have the power to fuel them? Do you. have the chips um to go inside them? Like that's like a large scale. industrial project in question. And then. um and then data. Do you have all of the. the lifeblood or do you have all the. data that feeds into these algorithms. that they learn off of? And it's really. kind of like the raw material for a lot. of this intelligence. And and so that's. why I think data is is the closest thing.

to oil because it is what what gets fed. into these algorithms fed into the chips. to make AI so powerful. Um and. everything we know about AI is that you. know the better you are at all three of. these things algorithms computational. power data the better your AI get. And. it's just all about racing ahead on all. three of these. So when when we see like. chat GBT gro these types of things are. they sharing a data center or are they. all are they completely separate data.

centers? They all use they they all have. separate data centers. Um this is. actually one of the one of the major. uh lanes of competition between the. companies is who has the ability to. secure more power and build bigger data. centers um because ultimately. you know as AI gets more and more. powerful the question then becomes how. many AIs can you run so let's say for a.

second that we get to you know a really. powerful AI that can do automated cyber. hacking. So it can do like it can log. into any kind of server or log into. another you know or or try to hack some. website or try to hack some other um try. to hack some some system. Um then then. the question is just okay if I have that. how many of those can I run? Can I run. a,000 copies of that? Can I run 10,000.

copies of that? Can I run a 100 million. copies of that? Wow. And that all just. boils down to how many data centers do. you have up and running. And that then. that boils down to okay, how much power. do you have to fuel those data centers? How many chips do you have to run in. those data centers? And how do you keep. those online for as long as possible? And what data is constantly fueling. those models to keep getting them to. become better and better and better. And. so this is one of the reasons why one of. the major ways that the AI companies.

compete, you know, between. XAI, Elon's company, and OpenAI and um. and Google and Amazon and and Meta and. all these companies. One of the major. ways they compete is just who right now. is securing more power and more real. estate for data centers 5 years from now. and six years from now. Um, and so the. the battles five, six years down the. line are being fought literally today. Wow, man. That's fascinating stuff.

Well, couple more things before we get. into your life story here. Got you a. gift. Oh, man. Everybody gets one. Love. it. Vigilance Elite Gummy Bears. There. you go. Legal in all 50 states. No funny business, just candy. Made here. in the USA. Yeah. And um and then one. other thing, got a Patreon account. It's. a subscription account. It's turned into. quite the community. And um they've been. here with me since the beginning when I.

was running this thing out of my attic. And then we moved here and now we're. moving to a new studio and the team's 10. times bigger than what it was, which was. just me and my wife. But um it's all. because of them. And so they're the. reason I get to sit here with you today. And uh so one of the things I do is I. offer them the opportunity to ask every. guest a question. This is from Kevin Omali. With AI now able to essentially. replicate so many facets in our of our.

reality, do you see a future where all. video or photographic evidence presented. in trials become suspect based on the. ability for any of it to have been. replicated through artificial. intelligence tools? Uh yeah, so this goes back to what we. were just talking about. I do think AI. is going to enable you to do crazy. levels of simulation and um I don't. think our courts are ready for it. I. think that like the like like Kevin was. saying, AI will be able to generate very.

convincing video, very convincing images. um in a way at a like we we're not even. really at that point yet. Like right. now, you can still tell when these. videos or images are AI generated. That's going to keep getting better and. it's going to be indistinguishable um. from from real video. So, how the hell. are we going to discern what's real and. what's AI generated? I think that there's two things. I think. first people are going to need really.

good [ __ ] detectors, like. like insanely good. And I think um I. think kids today, by the way, already. have much better [ __ ] detectors. because they grow up on the internet. where there's just so much there's so. much of everything that they they. already kind of like learn to have. better and better um [ __ ] detectors. Um but uh so that's one. And then the. second is I mean I think there's going. to be um there this is an area where I I.

know there's a lot of push for for. various forms of policy and regulation. but um this is going to I mean it's. going to be a major question like hey if. if there's fabricated video or um or. imagery used in a trial and it's. discovered that it was fabricated like. you know what what are the what are the. consequences of that and I think it's. about tuning that such that if you. fabricate evidence or you fabricate. things then um then you know that's.

maybe a worst def then maybe that's the. worst offense of all uh then I think. people would then you deter a lot of. usage of those tools then if if you set. up the incentives in the right way. Yeah. I mean what you know first thing. that goes to my mind is the US. government. I mean, just showing you. around the studio and stuff talking. about, hey, this is what the what the. government did to those Blackwater guys. I was telling you about. They deleted. the evidence. Well, instead of deleting. the evidence, they could make new.

evidence that is a fake gunfight in the. source square, Baghdad, that proves. they're guilty. And and then it's the. government behind it. You know, we've. seen it with Brad Giri. We've seen it. with Eddie Gallagher. We've seen it with. the Blackwater guys. We've seen it a ton. just just in my small network circle and. I could I mean you see what's going on. with the elections all over Europe. They. they they pulled Georgescu calling him.

uh what was it? I don't know some under. Russia Russian influence Marie Le Pen in. France done. I mean, they were talking. about pulling somebody in Germany not. too long, maybe about 6 months ago, and. it's it's just, man, it's [ __ ] crazy, you know, and and um scares the hell out. of me. Scares the hell out of me because. then they can just frame anybody they. want. Yeah. I think uh.

definitely one of the one of the. outcomes of AI is that institutions that. have power today will gain way more. power. Yeah. Um it will it's not. naturally democratizing. It's a. centralizing um kind of technology and. so uh. and so yeah we need to build mechanisms. so that we can trust those institutions. otherwise um it doesn't end well. Yeah. Well, let's get to your story. Well, I I. have gifts, too. Do I do I love gifts?

Okay, great. Um, so a few things I mean, we're going to talk about this, but I. grew up in Los Alamos, New Mexico. So, my uh my parents were both physicists. who worked on the n at the national lab. there. This is the birthplace of the. atomic bomb. Um, I don't know if you saw. Oppenheimer, but uh half of that movie. set in Los Alamos, where I'm from. So, we got a Los Alamos hat. Uh, Los Alamos. National Laboratory hat. Dude, it's uh very cool. We have some.

Los Alamos coins. So, oh man, about the there's one about. the atom bomb. Uh one about the the. Norris Bradberry who's a lab director. Um and then uh and then also coin about. the you know the father of the atomic. bomb. Here we go. We have a uh. a like a copy like a basically a copy of. all the the manual that they that they. gave to the scientists uh that got. declassified.

um uh from the from the uh actual uh. from the actual Manhattan project. Wow. And this is cool as [ __ ] And uh this. one's just a fun one. It's a uh it's a. rocket kit for you and your kids. Oh, man. They're going to love that. Yeah. Thank you, dude. Thank you. This is going to look. awesome in the studio. That's very cool. Yeah, it's been kind. of surreal. I mean, everybody calls uh.

AI the the next Manhattan Project. And. so, it's been uh it's been funny cuz. that's where I grew up. Uh it's like I. don't know. Feels weird. I'll bet it. does. Yeah, I'll bet it does. So, what. were you into as a kid? So, uh, yeah. So, again, both my parents are. physicists and my and my dad's dad was a. physicist as well. So, I grew up in this. like.

pure physics family. Um, so science, technology, physics, math, these were uh. these were the things I was like I was. like I was really excited about as a. kid. Um, and uh I remember like around. the dinner table we would talk about. black holes and wormholes and you know. alien life and uh supernova and you know. far away galaxies and all that stuff. That stuff was all very captivating to. me. I was thinking about kind of like.

basically like you know understanding. the universe for lack of a better term. Um, and then I I really liked math and. uh I realized. kind of, you know, in about four in. fourth grade I entered my very first. math competition, which is a thing. Uh uh and I I like uh. it was in it was in the whole state of. of New Mexico. Uh and I scored the best.

out of any fourth grader in New Mexico. Um which uh and then that like activated. this like competitive gene in me and. then I just started like you know I got. consumed by math competitions, science. competitions, physics competitions. What. kind of math are you doing in fourth. grade? You math are you doing? Yeah. Yeah. fourth. I remember let's see my. parents taught me algebra.

in. I want to say it was second grade maybe. between Are you serious? Yeah. You. mastered algebra in second grade? I. don't know if I mastered it but I was. Yeah, I was playing around with algebra. They they taught me the basics of. algebra and I would just like spend all. time thinking about it in second grade. It's like seven 8 years old, right? Yeah. Like eight eight. Yeah. Holy [ __ ]. Um and then and so by the time I was by. the time I was in fourth grade, I could. do kind of like I could do some basic.

algebra. I could do um some basic. geometry stuff like that. And then uh. let's see where where did I do from. there? By the time I was in middle. school, I was doing calculus. and then um and I was and then I was. doing college level math in middle. school as well. So, those are the two. things I was doing in middle school. And. then, um, in high school, I just became. obsessed with computers and I just spent.

all day programming. Um, and I realized. like science and math are cool, but um, but with computers and programming, you. could actually make stuff. Uh, and that. was that ended up, you know, becoming. the the major obsession. Back to the. dinner table conversations. Yeah. I. mean, Los Alamos, there's like a lot of. conspiracies and all kinds of stuff. going on about that place. Remote. viewing, all all this stuff come seems.

to stem to Los Alamos. But. I have two parents that are physicists. in Los Alamos. You guys are talking. about black holes and aliens and [ __ ]. What do you think? Are we are there. aliens? Uh so there's there's this famous. paradox, the Fermy paradox, which is you. know what are the odds that we live in. this like vast vast vast universe and uh. and there's like you know there's.

there's billions, hundreds of billions, trillions of other of other stars and. planets and um you know what are the. chances that like none of them have. intelligent life? I mean, I think like. definitely somewhere else in our. universe there has to be intelligent. life. I think so. For sure. The the but. the benefit or I don't know if the. benefit but the but like part of the. issue is if we're really really really. far apart like like millions of light. years apart, hundreds of millions of. light years apart, there's no way we're. ever going to communicate with each.

other. Like we're just like super duper. far away from each other. Um so I think. that's plausible. And then the there's. the um you know uh there's the what's. called the dark forest hypothesis. Um I. think this is one of the things I I. actually believe the most in probably. So you have the firmy paradox that says. basically like hey what are what are the. odds that there's no intelligent life. out there in the universe? Um there h. it's probably zero. There has to be some.

intelligent life somewhere else in the. universe. And then the question is like. why aren't we seeing any like why aren't. we seeing any aliens? Why aren't we like. coming into contact with them? And so. then there's all these like how do you. explain why that is? And there was this. um there's this hypothesis called the. dark forest hypothesis which originally. came out of a sci-fi novel actually uh. but is the one that like jives the most. with my thoughts which is um the reason. you don't run into other intelligent. life is uh if you play the game theory.

out. uh if you're an intelligent life you. don't actually want to be like blaring. to every other intelligent life that you. exist because if If you do that, then. they're just going to come and take you. out. Like you're basically like a you. become like a huge target for other. forms of intelligent life. And there, you know, some intelligent lives out. there are going to be hyperaggressive. and are going to want to take out, you. know, other uh other forms of. intelligent life. So the dark forest.

hypothesis is that once you become an. intelligent life form and you become a. multiplary species and all that, you. realize that you're kind of best off. minding your own business and not, you. know, sending all these sorts of signals. and trying to like make contact with. other life because um it's higher risk. to do that than to just kind of like, you know, stay isolated. And so there is. intelligent life out there. There are. aliens out there, but everybody's. incentive is just to stay isolated. Interesting.

I don't know. I used to believe in it. Then I interviewed a bunch of guys. I. don't know. I don't know. I think all. this shit's a big distraction to be. honest with you. Yeah, there's. definitely I mean there's definitely the. the other portion of this which is you. know um UFOs are a conspiracy such that. you know the military can do all sorts. of airborne testing and uh and it gets. discredited because you know people say. it's UFOs and then uh and then nobody. believes it. Like there's just no I I'm.

of all the people I've talked to there's. just no hard evidence and then and then. and then it's the well that's. classified. It's like I mean is it. you're on a podcast tour you know but. I don't know sometimes I think you know. this is like all I watch is the. expanding you all the black holes all. the this is what I fall asleep to at. night and uh I don't know I mean they. they found what like Saturn's rings are. all water they think they may have found.

you know there's a possibility of life. on some of the moons on Saturn that. would Neptune I think it's made of is. meant is it Neptune that's made of water. like a lot of oceans that are frozen and. so there may have once been life then. there's a they think they found a. pyramid on Mars or something I don't. know I sometimes I think maybe. maybe at any at any one given at any. particular given point in time there.

there is only one planet that holds life. as we know but at a time and then maybe. when that planet, you know, becomes. obsolete, everything goes extinct. Maybe. it moves, you know, maybe it was Mars, I. don't know, 5 billion years ago and. that's where life was and then somehow, you know, [ __ ] changed and then it. developed on Earth. I don't I don't. know. That's that's that's where I'm at. right now. I go back and forth on this.

[ __ ] all the time. Yeah, totally. Well, cuz the cuz our star has a life cycle, right? And as it goes through that life. cycle, different points of our solar. system become different temperatures, have different conditions, you know, all. that kind of stuff. And so, um, that's a. plausible theory. I mean, I think, uh, I. think it's I mean, I think both that and. what we were talking about before in. terms of like consciousness in the. afterlife, these are like some of the. some of the great questions because you. just, you know, we'll probably never. know the answers. Yep. Yep.

What were your parents working on at Los. Alamos? They were um Are they still. working there? Yeah, my mom still's. working. Uh my my dad's not working, but. uh but my mom's still working. And so. they were part of uh of the divisions in. Los Alamos National Lab that were that. worked on classified work. Um that uh. they were they had clearance. Uh my mom. sells clearance um with the DOE. Uh, and. I actually remember like when I grew up,

I just assumed they were working on cool. physics research because I was like a. kid and I I didn't put two and two. together. Um and so I I remember when I. grew up I thought the Los Alamos. National Lab like used to be the place. where the atomic bomb was built and then. uh decades later is just like this like. advanced scientific research area where.

they're doing research into you know all. of the you know the frontier of human. knowledge and it's just this like great. scientific research area. And then um. and then it wasn't until I I it wasn't. until I literally got to college where I. was talking to a friend about it and it. like dawned on me that oh wait is. probably still mostly weapons research. Um and uh and oh that's why you would.

need a clearance to. stuff in New Mexico. And then uh since I. left they actually restarted um they. restarted uh uh what's called nuclear. pit production but they restarted. basically manufacturing the cores of of. nuclear weapons. Um this was this must. have been like 2018. 2019 in Los Alamos. Um, and then I was. like, "Oh, yeah, no, it's it's mostly a. research facility to to.

research new nuclear warheads and new. new nucle new nuclear weapons." Um, uh, and so that dawned on me that didn't. dawn on me until I was like all the way. in college, but yeah. Wow. So, I my. guess is my parents worked on that, but. uh, probably. Yeah. Damn, that's crazy. Wow. What else were you into as a kid other. than other than mathematics? I loved math. I loved I loved coding. I.

loved science. I loved all that stuff. Um I uh I uh was really into violin. I. was really into to um I uh I would like. I would practice like you know an hour. of violin a day. Um, a lot of that was. because there was sort of like uh, you. know, in some in some, you know, fields. or some areas there's like there's just. a real beauty to perfection. Mhm. Um, and I think this is true in like a lot. of arts, um, a lot of music, a lot of a.

lot of frankly everything. I mean, I see. it even in my current life, in my. current day-to-day job, but um but there. was just like, hey, if you could if you. practice enough to get to play a piece. perfectly, then it would like it would. be beautiful. And if you like along the. way, it's like total dog [ __ ] until you. get to the point of like perfection. Um. there's kind there's a lot of beauty to. that concept to me, which is like, you.

know, once you get something totally. perfect, it becomes beautiful. Um that. was that was captivating when I was a. when I was a kid. So you were a. perfectionist from a young age and. you're still a perfectionist today. Yeah. I see a lot of beauty in like you. know now I would say I I don't think I. don't think we have the luxury to be. perfectionists. I'm much more pragmatic. now. Like, you know, like we were talking about, the world is. extremely messy. Like, like the the.

reality is, you know, stuff is super. chaotic. There's a lot of bad [ __ ] going. on constantly. Um, there's a lot of good. [ __ ] going on constantly, but perfection. is not really a like plausible. objective. Like, we're never going to. get perfection. Um, so I'm a lot more. pragmatic now, but I do see a lot of. beauty and perfection. I mean, I I'm. also a perfectionist. I battle it every. [ __ ] day. Like I it I'm OCD. I did.

it. But, you know, and I've I've read. about it. I've watched talks about it. It's And I came to the conclusion, which. I hate saying this because I am a. perfectionist at heart. you know the. perfectionism can get in the way of. success. Did you find that I mean it. sounds it sounds weird even like asking. you the [ __ ] question because you're. the youngest billionaire in the world at. age 24 and I mean you're 28 years old.

now so it sounds weird saying did. perfectionism hold you back but did it? I think um yeah, at some point I just. like I I like some bit flipped and I. realized like you got to just do the. 8020 lots of times. Like you got to do. 20% of the effort. That's 80% as good. and you just have to be okay with that. Mhm. Um and you just have to do that. over and over and over again. Um so at. some point I internalized that and it's.

like it's like anathema to. perfectionism. It's like the exact. opposite. And so now I think about as. like hey there's some things where. perfectionism really is the right answer. and there's some things where you just. got to you just got to like be okay with. imperfection and just like speed is the. objective versus perfection is the. objective. Um so and yeah I would say. now honestly I think more things like. most things are speed is the objective. not not perfection. Um so yeah I would.

say I've kind of had like a whole. journey with it. What what was it that. flipped you? I think what like uh. so um. there's this thing that um Elon says to. uh people at his company when they're in. like when they're like a crisis. situation um and he says like uh. hey like you know let's say you're in a. crisis situation like people are like. not figuring out how to deal with it and. then he asked like imagine there was a.

bomb strapped to your body that will go. off if you don't come up with a solution. to this problem. Like then what are you. going to do? Um and then you know most. time when people actually like think. through that scenario they like focus. and they get their act together and like. figure out um like like something to do. Um and I think a lot of times startups. are like that. like you're like there's. so many moments that are so life and. death and so high pressure that um.

you're just in these situations all the. time where you're like you have to act. and you have to like do something. otherwise you're toast and you just have. to like figure out what the best plan of. action is and the best course of action. and just do it. Um so I think that that. the realities of you know having to. operate quickly I think just over time. remolded my brain. Interesting. Do you have any brothers? Do you have. any siblings? Yeah, I have two brothers.

Two older brothers. Um they uh they're. both I dropped out of college and both. my brothers have PhDs. So um uh uh but. my my oldest brother is an economist. Um. and my my uh my other brother is PhD in. neuroscience. So they're uh Jeez, they're smart. Yeah, they're smart guys. Whole lineage of geniuses, huh? Yeah, I think uh my uh yeah, I think my. parents are are are uh are probably.

still a little a little myiffed that. none of us became physicists, but. Oh, man. Well, I'm sure I'm sure they're. they got to be happy with how everything. turned out. I mean, wow. Yeah. Yeah. No, I think I my uh my parents are super. proud of me. So, where do you go to. where did you go to school? I mean, where do you were you homeschooled? I. went to uh Los Alamos uh public high. school. Los Alamos public middle school. There's there's like the town is 10,000.

or so people. Um now it's more cuz they. do pit. They do manufacturing of these. like nuclear cores. So now there's a lot. more people there. But when I was. growing up there was like 10 to 15,000. people. So pretty small town. And um and. there's like one public middle school, one public high school, a few elementary. schools, and uh and yeah, that's the you. know, I went to I went to public school. Um I was lucky like I I think those are.

those are amazing public schools. Uh but. it's like it is public school like any. other public school. And then I would. just get home every day and um and. effectively like do math and science. like every day. What. like what how do you go what what is the. average second grader? I mean you said. you had learned algebra in second grade.

What what is an average? It's been a. long time since I've been in second. grade. things may have changed, but I'm. pretty sure it's basic addition. Yeah, I. think it's like addition. Maybe you get. to your times tables. Not sure. Yeah, maybe some multiplication tables. Yeah. Yeah. I mean, so how do you. dude? What's What is that like to go to. go from the night before studying. algebra to. 2 plus 2 is four? Yeah. I uh.

I like. I definitely remember in school like I. think like a lot of a lot of kids in. general just sort of like. generally kind of um buying out of the. whole thing. Does that make sense? Like. like kind of just um tuning out and. daydreaming and just kind of like. ignoring what was happening in classes. Um uh that definitely that definitely.

started happening and then I what you. know what what I would actually do or. focus on is like go back and then do. math at home. I mean you're more you're. more advanced than the teacher. There. were I remember one time there was like. uh there was the good thing about what. you know this the school of the I went. to is like the teachers. were really like also invested in my. education. like I think they um many of. my teachers wanted to see me like thrive.

and continue learning and um and that. was that was awesome. Like I could I can. imagine a totally separate school where. it's like the teachers don't care. because you know um. you know it's just like their lives are. chaotic, the classroom's chaotic, all. that kind of stuff. But but I'd lucky to. have teachers who really cared. Yeah. I mean. seems like it worked out well. I mean, for all the success that you have. amassed in 28 years, I mean, you're a.

very grounded person, and I never really. know what I'm going to get with you. guys. At breakfast, I'm I'm I was super. impressed. I'm like, "Wow, this guy's. like really grounded person." And seems. like a really good person. So, Oh, too. nice. Kudos to you, man. But, hey, let's. take a quick break. When we come back, we'll get into MIT. You've heard me talk about Patriot. Mobile for a while now. They've stood in. the gap for Americans who believe that. faith, family, and freedom are worth.

fighting for. And they're the real deal. They've got cutting edge technology, and. switching is easy. Keep your number, keep your phone, or upgrade. Their 100%. US-based team can activate you in. minutes right over the phone. They're. one of the few carriers with access to. all three major US networks. That means. exceptional nationwide coverage. They. can even put a second number on a. different network on the phone. It's. like carrying two phones in one. They. have unlimited data plans, mobile.

hotspots, international roaming, internet onthe-go devices, and home. internet backup. Make the switch today. and experience the difference. Go to. patriotmobile.com/srs. or call 972 patatriot. And right now, use the promo code SRS for a free month. of service when you sign up. Switch to. Patriot Mobile and defend freedom with. every call and text you make. That's. patriotmobile.com/srs. or call 972 Patriot.

Summer's here and if you're anything. like me, you didn't spend the winter. just sitting around. You stayed sharp. and kept moving. And now it's time your. gear caught up. And that's why I want to. introduce you to Roku. I've been looking. for eyewear that can handle any. situation with performance and style. And let me tell you, these aren't your. average shades. I've tested them in the. real world from shooting to fishing to. off-roading, and they hold up. They're.

lightweight, don't slide around on my. face, and can take a hit without falling. apart. And the best part, they look. good. They're clean and modern. No. frills here. just premium eyewear that. performs without compromise. That's. something that I respect and that's also. why every time I head out the door, I. reach for my ROA shades. ROA is based in. Austin, Texas. American designed, no cut. corners. The optics are crystal clear,

cutthrough glare, and the fit stays. comfortable all day long. Need a. prescription? They've got you covered. with both sunglasses and eyeglasses. Not. only does ROA have awesome shades, they. also have these that protect you against. blue light. I wear these every night. when I'm winding down for the day and I. still got to look at my phone or my. laptop or my iPad. It just helps you. wind down and get ready for bed. They.

are a one-stop shop for eyewear that's. built to handle whatever life throws at. you. ROA is the real deal. Ready to. upgrade your eyewear? Check them out for. yourself at roka.com and use code SRS. for 20% off sitewide at checkout. That's. roa.com. All right, Alex, we're back from the. break. We're getting ready to move into. you going to college. So, you you. started at MIT, correct? Yep. How did.

that go? Yeah, so let's see. I was uh so. I'll say the first the few years before. that. So, I dropped out of of high. school, actually. Oh, you dropped out of. high school? Yeah, I dropped out of high. school. Um, why not? Why was wasn't. challenging enough for you? Uh, I. dropped out a year early to to go work. at uh Quora at this tech company. Um, I. think a lot of people run into Coror is. like the question answer website. Uh,

but uh but I went to go work at a tech. company for a year. Um and uh and then. after a year of that I decided okay it's. time to go to college. So I went to I I. went to MIT. Yeah. 15 your stump in. PhDs. It was maybe not quite that maybe not. quite that early but uh but yeah like by. 16 17 um yeah was uh I was more I was. more competent by that point. What what. are you stumping these guys on? So um. well at that point that was like early.

early AI. It wasn't even called AI yet. It was called machine learning. That was. like the more popular term. Um and it. was about training different algorithms. that would you know uh rerank content. It was just like all the like um all the. algorithms for like these social media. style um style things and it's like okay. what algorithm creates the most. engagement or what algorithm like gets. people you know the most hooked on on. these feeds. That's what I that's what I.

was working on back then. Gotcha. Um, and so, uh, so I went, so I I worked I. worked for a bit and then I went to MIT. and, um, when I What are you, sorry to. interrupt. Couple more questions. What is it like for you to be 16, 17. years old. stumping PhDs? I mean, is that is that just like normal. life for you? I mean, you you know what.

I mean? like does it does it set in like. holy [ __ ] I'm really [ __ ] smart you. know or. I think um I think something that I. internalized pretty early on was that um. was that focus was really really. critical and so I didn't think. necessarily I mean like I think a lot of. people are really smart and I don't know. if necessarily I'm like way smarter.

fundamentally than a lot of these other. people, but I was like hyperfocused on. math as a kid and then hyperfocused on. phys physics and then in high school I. was hyperfocused on programming and then. um and so if you if you're like. hyperfocused. and you're just like you like really. invest the time and the effort, you can. make really really fast progress. Mhm. So, one of the things that I always like.

I I've believed in for a long time is. that if you if you overdo things, like. you like really like invest lots of. time, lots of effort, you go the extra. mile, you go the extra 10 miles, and. you're like constantly overdoing things, then you will improve faster than. anybody else by many times. Um, and a. lot of other people maybe they're just. not going the extra mile or maybe. they're just not as focused or, you. know, they're like meandering a bit.

more. And so that's really like I I. definitely like for me I think a lot of. a lot of what I attribute um being able. to accomplish so much to is really about. focus and and overdoing it, going the. extra mile. Um, that's that's what I. think boils down to. What did your. parents think when you dropped out of. school? Um, you know, they my parents I. think still probably really want me to.

get a PhD and and do scientific. research. So, um, uh, they. I think they view and I respect this. belief uh, you know, I think they view. the pursuit of science, the pursuit of. knowledge as above all else. Um. and and so I would always tell them, hey, I'm just, you know, this is like a. little detour, but ultimately I'm going. to come back and, you know, finish my. degree and finish my, you know, get a.

PhD and you know, I'll be on the. straight and narrow. Um uh so that's. what I always what I was always tell. them, but uh and then at some point it. just didn't be it wasn't believable. So. I just stopped telling them that. Why. did you decide to go to school? I went to school because um. uh well there were two things. One was. like genuinely I wanted to learn a lot. about AI very quickly and I knew I could.

kind of do that while working maybe but. um the best thing to do really would be. to like go to school like invest all my. time into it and and uh and try to learn. learn very very quickly. Um and then the. second thing was like you know almost. anyone you'll not anyone but like many. many people if you ask them like what. were the best years of your life like a. lot of people will say their college. years and so I was like [ __ ] I can't I'm.

not going to sacrifice the college. years. Um so so uh yeah I went to school. I like I decided to just go really. really deep into AI. I took all of the. AI courses I could um uh while I was at. MIT. I was only there for a year, but I. I started out I remember I took a um I. wanted to take the the sort of like. hardest machine learning course the. first semester I got there and the my. freshman adviser, the person who was. like I get all my courses approved with.

was the professor of that course. Um, this just like happened to be the case. And uh, I like signed up for her course. and then she she said like, "You're a. freshman. You're you're not going to, you know, this is going to be this is. going to be too much for you." And I was. like, "Ah, just give me a chance. Like, you know, I I I just want to try it. Like, I'm really passionate about the. topic." And she's like, "Okay, well, we'll let you uh we'll let you go till. the first, you know, for the first few. weeks and see how you do." And so then I. get in and then uh I remember I was like.

I felt uh I felt like the stakes were. really high cuz like I wanted to like. prove that I could do this. And so the. first test rolls around and uh I think. by like sheer luck it just happened to. mostly be about things that like like. there were a lot of things in the course. I didn't understand but happened to be. about stuff that I did understand in the. course pretty well and I got like one of. the top marks in that course and there. were like hundreds of people in this. class. Um, and so then after that point, the professor let me do whatever I. wanted. And then uh, and so then I did.

all of these I I was I went really deep. into AI and all the and all the AI. course work at MIT. Um, and then this. was the year when uh, Deep Mind, the. this like AI company out of London, came. out with Alph Go, which was the first AI. that beat um, the best Go players in the. world, which was viewed at that point as. like probably the hardest strategy game. or the hardest sort of like um, yeah,

the hardest strategy game for AIs to. beat. And that was a big deal. And then. I started tinkering with AI on my own. So, I built I wanted to build like a. camera inside my fridge that would tell. me when my roommates were stealing my. food. And uh and and so I started tinkering. with it. And then I pretty quickly. realized. um uh kind of what we're just what we. were talking about earlier that data was. going to be like that everything was.

going to be blocked on data. like if we. no matter what you wanted AI to do that. was that was going to rely on data to. make the AI do those things. Um and so I. and I looked around I was like nobody's. working on this problem. You know you. have plenty of guys working on building. great algorithms. You have plenty of. people working on building the chips and. the computational capacity and and um. and all that. Nobody working on data. So. I was you know I was impatient. You know. I was 19 years old. I was kind of. impatient. And I was like, "Well, if.

nobody's going to do it, I might as well. do it." Dropped out, started the. company, and was off to the races. Um, Damn. So, did you uh perfect the the. refrigerator AI to tell you if your. roommates are stealing your food? I uh. that was part of the problem. I was like. I was I I was trying to build it and. then I realized I didn't have anywhere. near enough data. So, it always like. fire incorrectly and always have false. positives, false negatives, etc. And. then um and I realized like uh then that.

was like the light bulb moment. I was. like, "Oh [ __ ] if I really want to make. this, I need like like a million times. more data than I have now." And that's. going to be true for like every AI thing. that anyone ever wants to build. Um and. so that was kind of the the genesis of. the the idea really. So you left MIT. Left MIT. I remember I moved I I flew. straight from Boston to San Francisco. um to start the company. Uh and um.

basically immediately went from like at. 19 years old 19 years old. Yeah. I. immediately left and then I started. coding. um in San Francisco and I was part of. this uh this like accelerator like I was. part of this program called Y Combinator. and um and it's kind of like the Hunger. Games for startups. Um so there's like. there's like it starts out there's a 100. startups at the start of the summer and.

you're all like grinding away. You're. all working. and you're all trying to. like show milestones and show progress. and then it culminates at the end of at. the end of the uh of of Y Com at the end. of it all there's a demo day where. everybody presents their companies, presents their progress and tries to get. investment and uh and it so it literally. it quite literally is the Hunger Games. It's like you go through this whole. thing at the end if you get investment. you get money you've won. If you didn't. um you've lost. Uh and uh and so that.

was like that was that was the beginning. of the company. We ended up getting good. investment. What what did you do? Uh. well at that time we were we were it was. it was around data for AI. So it was all. around like uh how do we fuel data for. for um what people want to build with. AI. But at that time it was like so. early that like the use cases were. pretty stupid. Like we were helping one. company try to detect like it was like a.

t-shirt company. They made like custom. t-shirt designs and we're trying to help. them detect when people um were like use. a t-shirt design that was like that was. like um like uh that was like unfit for. to print like you know it had like gore. or or like um you know you all sorts of. like illegal stuff like if basically. like identifying illegal t-shirt. designs. It's kind of like stupid now. they say it. And then we're helping.

another company um it was like a. furniture marketplace where we're. helping them like improve their search. algorithm with AI. And then maybe a few. months in maybe 3 months in we started. working with autonomous vehicle. companies and self-driving companies. Um. and then that and that ended up being. like the real. uh the real meat behind our effort for. the first 3 4 years. So, we worked with, you know, General Motors and Toyota and.

um Whimo and, you know, all of the major. automakers in helping them build. self-driving cars. How many people are. you competing against? I mean, um I think in anything you do in. startup plan like you have like tens of. competitors um you know and and there. were there were definitely tens of. competitors at that time. Um and uh and. so it's like you know these are. competitive spaces but um where. uh as we described I don't mind.

competition um from math competition. days and so um and so we we were just. like really focused on the problem. really focused on how do you what are. the best possible data sets um for these. self-driving cars a lot of that had to. do with it's called sensor fusion so you. know there's so many different kinds of. sensors And how do you combine all these. different sensors to get, you know, one. output? So like if multiple sensors.

sense a person, how do you like collect. all that together to say that's one. person right there and that's one car. right there and that's one, you know, bicycle over there. Um, so that was kind. of our specialty as a company. And then. um then we're kind of off to the races. just on that. We we grew the company to. like 100 or so people. Let's go back. just a little bit. Okay. So, you you go. to San Francisco by yourself as a. 19-year-old kid who had just dropped out. of MIT. How do you.

I mean, you you're immature at that. point. And. so, how do you develop leadership. skills? And I mean, how do you have how. do you have the knowhow and make the. connections to build a company as a. 19-year-old kid? Yeah, you so um. let's see what happened. So basically. early on like um it's about who you get.

investment from. And so if you get So it. was just you with the competition. There. was no team. No team. No team. And then. um and so I and I was coding every day. And then I got um we got Y Combinator to. invest in us. And then we got um this. this investment firm called Excel which. was who were one of the early investors. into Facebook to invest. And so we got. um some some good investors and then. they.

helped me build the team like find. people to hire. I also hired you know. what actually happened is I mostly hired. people I knew from school. Really? Yeah. So like cuz you could trust them. I. think more that they could trust me. because I think if like at the time if I. went to like a a 25year-old engineer in. San Francisco and I was like, "Hey, we. should we should work together." I had. no credibility. Like um I remember I.

wast I like I would get coffee with. these people and I would say like, "Yeah, this is what we're working on. It's super cool. You should join us.". And then they would all just be like, "Okay, um cool. I guess I'm going to go. back to my job now. Um, so early on I had no credibility. except for with people I went to uh. college with uh who we were just like. friends and we liked each other and so I. managed to recruit a bunch of them over. Um, and they dropped out too. Some of. them dropped out. Some of them just.

happened to, you know, were like seniors. or whatever, finished school and then. joined. Um, it was like a mix. It was a. mix. Um and uh and that was like the. early nucleus of the team, the early. sort of like cohort of the team. And. then um and then we started picking up. momentum because we're starting to work. with large automotive companies. We're. starting to work with, you know, these. very futuristic autonomous driving. companies. And then as momentum started.

to pick up, like, you know, we were able. to grow and build up the team over time. I mean, so so where did you get your. business sense? Or did you hire somebody. to run all of that and you were you were. the mastermind behind everything? Um I. uh maybe about a year in I hired. somebody literally with the title head. of business. Um but uh but until then I. was just kind of like I was just trying. to like learn it all. How did you get. the product out there? Uh I uh I just coded it all up and then.

there like I like put it out on one of. these there's all these like websites. where you can launch startups and I put. it out on we put it on one of those. websites and uh it went like microviral. you know um like viral among. like people who were on Twitter to look. for new startup ideas. Um, and then it. was kind of that was like the early seed.

that just that ended up uh enabling. everything to grow. But it was like I. mean. at the time it was I mean it was it was. tough going, you know? You you're like. like I would just like we I would just. spend all my time coding. Then every. once in a while I would like post. something to the internet and just like. and then I would beg all of my friends. I was I would say like please go up. this, please go like this, like please. like you know give me some ounce of.

traction and uh yeah that was the early. days. Damn. Was it scale AI at the. beginning? Yeah scale AI actually it was. called it was uh it was scale API at. first and then because that was just. like that website was available and then. it became scale AI like a year and a. half later. Um but uh yeah so so the whole the whole. I mean early startups are so gnarly. Um. it's I mean it's really crazy if you. look at like all these big companies and.

you like you know think about what they. were like in the early days. They're all. they're all pretty pretty uh pretty. rough and tumble. Um but but the coolest. thing like we cuz we started working. with all these automotive companies and. working on self-driving. Um. uh it quickly became. hyperinteresting. um because you know this was like one of. the great scientific and and and. engineering challenges of the time. Um.

and uh and we ultimately ended up being. successful like Whimo, one of our. customers is now launched and driving um. large scale robo taxi services in you. know San Francisco, LA, Phoenix, they're. launching in more cities like Wow. Um. it's pretty amazing. Wow. Damn. And the. company grew how fast? So let's see. I. think the numbers are something like. five years you are the youngest five.

years from when you started it you. become the youngest billionaire in the. world. Yeah that's crazy to think about. That did not feel obvious. The first. year it was like it was like. for the first ye first 12 months it was. like. one to three people. Like it was like it. was like almost nobody. It was like me. and like one or two other people working. on it for the first year. That's it for. the first one year. And then after the.

second year, we go from that like. one to three people and we start hiring. more people. We get to maybe. I think like 15 or so people. And then that third year we went from 15. or so people to. like maybe 100. and then we were kind of off the then it. was like 100 and then we and then we're. like 200 and then 500 and then we kept.

growing and now we're up to like,00. people. Um but the f it was like really. slow going at first and um. yeah and we we we. uh we focused on first it was autonomous. driving. and then and then starting um starting. about 3 years in we started focusing on. defense. um and working with the DoD. What are.

you guys doing in defense? So, uh, we do we do a few things. So, one of the the first things we did was. help the DoD with its its own data. problem to help them be able to train AI. systems. So um you know one of the first. things that we worked on was like you. know they wanted to the DoD wanted to do. image recognition on satellite imagery.

SAR imagery you know other like all. forms of overhead imagery but they had. this huge data problem you know just. like me with the fridge um they had the. same problem like how you know they need. to be able to have data that lets them. detect things in all this imagery and so. we the first thing we did was fuel um. the data sets and data capabilities for. the DoD that was true for the first few. years and then um more recently we've. been working with them to do large scale.

fielding of AI capabilities. What what. what kind of stuff is DoD looking for in. imagery? Uh so I mean so let me let me let me. also so basically the way I understand. this is. you don't need a human to detect. something maybe like a nuclear reactor. Is that is it am I on the right track. here? So they look or a missile silo or. Yeah. And so AI is detecting all these. which drastically reduces human error,

human manpower, all that kind of stuff. It's more accurate. Yeah. And it's and I mean mostly it's. it's scalable like I mean the we we the. number of satellites in space has like. exploded. So we have so much more. sensing um today like way more imagery. way more sensing today than it's even. like feasible for humans to to work. their way through. Wow. Um so that was. yeah that was like the first problem. How do you fuel it? You well you have to.

build So there's there's two parts. So. first you have to build effectively like. a data foundry. You have to build a a. mechanism by which you're able to. generate lots and lots of data to fuel. these algorithms. Um a lot of it. synthetically so using the algorithms. themselves to generate the data but then. a lot of it you still need humans to. validate and verify. So one of the. things we did actually for this whole. project is um we created a facility in.

St. Louis, Missouri, next to uh NGA, the. National Geospatial Intelligence Agency. And we produced a center for AI data. processing where we uh hired up uh. imagery analysts to be able to validate. the outputs coming out of the AI systems. to ensure that um we were getting the. correct, you know, we're getting. accurate and high integrity data to feed. back into the AI systems. Wow.

Wow. Damn. Where do we go from here? Yeah. So then, so we were doing so we were doing um. lots of stuff around imagery and. computer vision and then um uh and then. we started working with the DoD on you. know more ambitious and larger scale AI. projects. So one of the things we're. working with them now is this program. called Thunderforge which is using AI. for um military planning and operational.

planning. So um more broadly so so the. basic idea here is can you use AI to. effectively like automate major parts of. the military planning process so that. you're able to plan within hours versus. taking many days. This sounds like. Palunteer. It's um yeah they target. different parts of the problem and we. target different parts of the problem. and ultimately we work together pretty. well but the this is part of a broader. concept that we have around agent what.

we call agentic warfare. So the use of. AI and AI agents in warfare and the. basic idea is can you go from these. current processes where humans are the. loop to humans being on the loop. And so. can you go from you know situations. where you know these workflows have to. go from a person has to do a bunch of. work then pass the next person they have. to do a bunch of work pass the next. person to the AI agents are just doing a. lot of that work and humans are just.

checking and verifying along the way. Um. and it's it's a big change. So going. from you know you know if you compare. both set setups side by side here you. have individuals humans with decades of. single domain experience who are doing. each step step of this process. And then. if you have the AI agents doing it, ideally you have AI agents who have, you. know, thousands of years of of. knowledge, all domain knowledge and are. are, you know, a thousand times faster.

at under at doing the actual tasks. And. so it's all about taking and this exists. at many many different levels. So you. know there's you can think about this. for the sensing and intel portion that. we're talking about before. So you know. can you accelerate the intelligence. gathering you know the process by which. we take all the sensor data and turn. that into insight. You can think about. it for the operational planning process. like how can you accelerate that uh that. entire flow. You can think about it in.

terms of um you know on the tactical. side, how do you accelerate tactical. decision-m um so it you bleeds into. every sort of like level of warfare. every or every component but at its core. how do you use AI agents to be faster, more adaptive and have humans just check. their work. So when you're talking about. it helps with mission planning. especially in a tactical environment. because that's where I come from. I mean. what what is it could be any example but.

g can you give me an example of how it. speeds up the mission planning process. in a tactical environment. Yeah. So, so. let's say that so this thing that we. have by the way, you know, we're working. on it with Indopaccom and Yukcom right. now and and um we'll deploy more. broadly, but um let's say that there's. um a uh what's a good what's a good. example? Um let's say there's some kind. of alert that pops up like there's.

something that um we didn't expect that. we need to figure out how we're going to. respond to. Um like like what kind of an. alert? So I mean let's say there was. like uh you know um there's like I mean. you can imagine at different levels but. let's say there's like a ship that. popped up that we didn't expect okay as. a simple example. So then that alert. flows into a bunch of AI systems that. are going to the first step is sensing. So what like let's look through all of.

our sensing capabilities and um let's. like go reanalyze all of the data that. we have and figure out how much do we. know about that ship right so now a. person would like an analyst would go. through and like do all this you know. all the ped and all the stuff to to be. able to undergo this work but ideally. you have AI agents that are just going. they can look through all the historical. sensor data they can figure out um oh. actually there's like kind of a thing. that showed up on this radar and there's. kind thing that showed up on this. satellite imagery and we can kind of. like sketch together this like you know.

the trajectory of this of this ship. Okay. So you go through that process you. try to understand what's going on and. then you and then you go through and and. figure out okay what are the what are. the possible um courses of actions. So. once you have situational awareness, then what are the courses of actions. against this particular scenario and you. can have an AI agent honestly just. propose courses of actions. Um like hey. in this scenario given this ship is is.

coming here you know we could fire at. it. We could just wait to see what. happens. We could reposition so that. we're you know we're able to to um you. know handle the threat better. you know, all sorts of we could we could. reposition some satellites so we have. greater sensing. You know, there's all. sorts of different courses of actions um. that we could take. And then uh once the. AI produces those course of actions, it'll run each of those different course. of actions through a simulator. So it'll. then run uh it war games at real time.

Exactly. It'll war game at real time. And so then it'll run through a. simulator and say, "Okay, what's going. to happen if we fire at it?" like, you. know, this is what we know about red. forces. This is what we know about blue. forces right now. Um, if we fire at it, this is like, you know, this is the war. game of how that plays out. If we um. just increase our sensing, like these. are the things that that the red forces. could do to [ __ ] us up. And like that's. the risk that we take on. And um and. then the benefit is because all this is.

automatic, you can run it these war. games and these simulations a million. times. So it's not just like one, you. know, military planners just like trying. to like war game and plan it out like. you know in human time. It's like you. could run a million simulations cuz you. don't have perfect information. You. don't have perfect knowledge. So you. need to kind of figure out based on the. uncertainties of the situation, what are. all the potential outcomes that that pop. out of that. Wow. And then so you run.

like a million different simulations of. each of these different courses of. action. And then you can give a. commander direct like you just give them. this whole like brief and presentation. which is basically these are the courses. of actions we considered. This is the. this these are the likely outcomes in. those courses of action. We can show you. the simulated like outcome in each one. of these scenarios. So we can like show. you what it would look like in every one. of those scenarios if it happened like.

representative um simulations and then. the commander makes a call. Wow. So it's. this is what it is. This is what it's. doing. These are the possible courses of. action. These are the consequences of. each action. This is the percentage. Yeah. Exactly. And and it spits that out. in what? A matter of seconds. Yeah. Now. it takes a you know probably takes even. now it probably takes a few hours cuz. you know these models are a lot slower. than they will be in the future but yeah. I mean compare that to I mean depending. on the situation like that could take.

you know that could take days for humans. to do today like it's and and it's not. from lack of will or effort or or. capability. It's just it's a really. complicated situation if a ship pops up. out of nowhere like there's a lot of. stuff you have to consider. Um, and so, uh, that's really the the the step. change here is just like a, uh, like. dramatically accelerating situational. awareness, dramatically accelerating. like an understanding of what the.

different course actions are, what could. happen, what are the consequences, um, and surfacing that to commander. Does it. make a recommendation? Um, this is kind of an interesting. thing. We. we go back and forth if we want to make. a recommendation because ultimately like. we don't want um to just be like you. know we don't want to let commanders. kind of like sleepwalk if that makes. sense. We want them to like, you know, our military commanders are the best.

humans in the world like considering all. of the potential consequences of these. different course of action and also. considering you know um uh and and. ultimately making a call based on those. potential consequences. So I think we. want to ensure that. commanders are still exercising their. judgment in these decisions versus just, you know, making it easier for them to. just say, "Oh, go with what the AI. says.". Interesting. Wow.

But this but then, okay, think about. what happens next. So um and this is. where stuff gets really freaky. So, let's say that um obviously in a world. where just the blue force, just the. United States has this capability, that's great. You know, we're going to. we're going to be running circles around. everyone else. Um but then what happens. if the red force, you know, China, Russia, whomever also has that. capability? Then you're in this. situation where.

I've war gamed out the whole situation. you know, they've instantaneously. wargamed out the whole situation and. then it's like then then it I think I. honestly think so then it's like we know. and you know like blue forces, red. forces, we both know that we both have. like you know this perfectly war game. scenarios. Which avenue do you pick? And. then it becomes this really complicated. almost like psychological.

you know kind of kind of situation which. is like then it like all comes down to. how good our intel is. So how good is. our intel about that commander? How good. is our intel about what their collection. capabilities are? How good is our intel. about you know what they likely know. about us and vice versa. Um and it gets. pretty so this is actually. let's just. so let's say China Russia. our enemies have this capability we have.

this capability then it then it kind of. becomes. it's like the same process that we deal. with now who has the better intel right. it's just developing. and in and you're going to a course of. action quicker and the enem is doing the. exact same thing quicker. So it's. essentially it's the exact same thing. that we're doing now. but faster and so if we develop it first.

then. we achieve basically global domination. Am I correct here? Yeah. I think and I. think timing really matters here because. if we get this capability. and this will go for I mean there's like. there's way more there's there's way. more AI will be able to do but let's say. we get this capability you know a year. ahead of adversaries.

then you're then like we're just going. to be able to respond so much faster. the the analogy I often use is like. imagine we were playing chess, but for. every one move you take, I can take 10. moves. Like I'm just going to win. Um uh. and that's what that's the asymmetric. advantage that that comes out of this of. this capability. Um and then once it but. then once it equalizes then. then it's like this very you know it's. like to your point becomes this like. adversarial intelbased you know.

capability based kind of conflict. How. how do we. I mean how do we combat our adversaries. from having this type of intel from. having this type of AI system? So. I think the then. I mean China's demonstrated with.

deepseek uh and you know models that. have come out since then they're going. to be very competitive on AI and in. uh I think in 2024 so last year there. were something like 80 contracts between. uh large language model AI companies in. China and the People's Liberations Army, the PLA. Um. that number is not 80 in the United. States. Like the United States is like. way way less than 80. So they're very.

clearly accelerating the integration of. AI into their um national security and. into their military apparatus very. quickly. I don't think at this point. realistically we can stop them from. having. this this capability I described. So. then you go to the next layer down. So. uh Intel. So um well the next layer down. the next two things that you look at is.

okay how does AI impact Intel and how. does AI how can we what is the. adversarial AI dynamic? Like can we use. our AI to sabotage their AI? Can they. use their AIs to sabotage sabotage ours? Um and it's like AI on AI warfare. effectively. Um then when you look at. that scenario, okay, so the so let's dig. into that. Um. the first level analysis here is kind of. what we were talking about before, which.

is that probably just boils down to how. many copies of these AI systems do I. have running versus how many copies do. you have running. So it turns into a. numbers game. If I have 10,000 AI copies. running and you only have 100 AI copies. running, then I'm going to run circle. I'm still going to run circles around. you. And that boils down to who has So, so let's say um so let's say you have. you have 100 AIS. I have I have 10,000.

AIs. Um I will I will take half of my. AIS. I will take 5,000 of my AIS and. just focus them on hacking your AIS. So, I'm going to they're all going to be. looking for vulnerabilities in your um. in your uh in your information. architecture, in your data centers. I'm. going to look for vulner I'm going to, you know, I'm just like purely focused. on cyber hacking of your 100 AIS and. then my other 5,000 copies are going to. do the military planning process for.

myself. Um then then look at think about. the adversary. I have this choice. I. have a 100 AIS. If I have them all focus. on doing um the military planning. process, I'm going to get hacked cuz I'm. not doing any cyber defense. And then. even if I have all of them focus on. cyber defense, even those numbers are. bad. It's like 100 AIs versus 5,000 AIs. from you. And so I probably still get. hacked. So the numbers end up mattering. a lot. Um uh if even if they had even if.

the other adversary, let's say it's only. a 2x advantage. I have 10,000 copies. running and the adversary is 5,000. copies running. I can do the same thing. 5,000 my copies are just focused on. hacking your AI so that your AI is. incapacitated or has incorrect. information or um or is poisoned in some. way like basically is incapable. incapacity for some reason. Um and the. other half my eyes are focused on the. military playing process. Again, the. adversary is screwed because to properly.

deal with a cyber attack, I need. probably all 5,000 copies to be focused. on cyber defense. and then I have no capacity left to do. the military planning. Wow. So it really. turns into this like uh very. like just in the same way that you would. you would command your forces um today. like all your your you know your various. your forces across all domains to like. try to pins or outmaneuver the enemy.

You'll do the same kind of planning for. your like AI army so to speak or your AI. allocation of assets. Yeah. Your. allocation of assets. Exactly. And a lot. of it will be okay, how many am I. dedicating towards um uh hacking and. sabotaging the opponent? How many am I. dedicating towards my own military. planning and wargaming process? Um the. other thing is how many you allocate. towards um uh towards you know the the.

other key component here is drones and. uh how many you're allocating towards. doing the like very tactical mission. level autonomy to accomplish you know. mission level objectives. Um, but it'll. be it'll be like I think it really boils. down to ultimately who has more. resources and then what are those. resources? That's going to be about. large scale data centers. So who has. bigger data centers and more power to. run all these AI agents?

And who who makes the determination of. how many AIs we're going to put in. tactical environment? How many AIs are. going to go after. cyber security trying to hack into the. other AIs? Is that a human or is that. another layer of AI that that that spits. out. exactly what you just said? This is what. we this is our situation. Here's the. courses of action. Here's the here's the consequences of.

what happened. So is it just AI after AI. after AI that's doing all of this all. these simulations? Yeah, then yeah. No, you're exactly right. Then I Yeah, exactly. You have another AI that's. planning out and mapping out, you know, how should I allocate my AI resources to. properly deal with the adversary given. what I know about the adversary. And. then the so then what are the ways in. which you know what are so then what are. the key dimensions that would give you.

an edge versus your adversary? Well, it's if a your AI is different somehow. So, it actually is like hard for your. adversary to know exactly how you're how. you would act like basically strategic. surprise in some form in the form of. like a different thinking process or a. different sort of like way of reasoning. of the AI systems. Um, and then the. other one is like uh ambiguity of how. many how what your resources actually. are. Like if somehow I can make the.

adversary think that I have way fewer. resources than I actually do or way more. resources than I actually do, that'll be. a critical element of of um yeah, of. strategic surprise in those kinds of. situations as well. Wow. Would an AI be. able to be able to Would would would AI. be able to. alert. if it if it will it know it's been. hacked?

So yeah, this is this is a great. question that you know um. right now probably yes. Uh but the. you it's definitely possible in the. future that you will be able to. effectively hack into a system or. somehow poison an AI system and uh have.

that activity be relatively untraceable. because you would basically um you would. you would hack into that AI system. So. there's two ways you would do it. One is. you poison the data that goes into that. AI. So I'm not hacking into the AI. itself. I'm just poisoning all the data. that's feeding into that AI such that at. any moment in the future I like I can. activate that AI and basically hack it. without any sort of active intrusion.

But I can just do it because I've. poisoned I've like poisoned the AI that. go the data that goes into the AI such. that if I like you know. say it alters the decision-m process. Yeah. Exactly. But the but the the end. decision maker which would be a human. would not realize that. Yeah. Exactly. Okay. So so data poisoning is going to. is but this is what's so terrifying. about deepseek. One of the reasons why. deepseek is really scary is um.

uh you know China chose to open source. the model right so there's a lot of. corporates large scale corporates in the. United States that have chosen to use. deepseeek because they're like oh it's a. good model and it's a good AI and it's. free why not use it um but deepseeek. itself as a model could already be. compromised could already be poisoned in. some way such that, you know, there are. characteristics or behavior or ways to.

activate deepseek that. this the CCP and the PLA know about that. um that we don't. Uh so so that's why. deepseek is scary and why so so the. first area is just data poisoning. So. basically, can you poison the data that. we're using to train the AIS such that. to your point, I've altered the behavior. of your AIS in a way that you don't know. about and that's going to affect that's.

going to have cascading effects across. your whole military operation. That's. one. And then the second one is um. uh is basically. uh you know. if if you're able to do the whole. operation quickly enough you basically. hack in and you uh kind of as we were. talking about before you would like. destroy the traces. You destroyed any. sort of trace that like you had hacked. in and you have an agent that like.

hacked in like removed that trace and. the evidence of you hacking in. um uh. before anybody before it was alerted or. notified. That's maybe a bit more. extreme, but definitely the data. poisoning stuff is is more concerning in. the near term. Damn. So, how would you. how would you defeat it? I mean, it it's. so if if it were to be hacked and you. knew it was hacked, then AI becomes. completely irrelevant. Correct. Well, the issue is we're still going to rely. on it for lots of things. So, um, it.

would it would have to come down to. the human mind again and you would have. to you would have to, let's say it's a. ship. You would have to. know everything that you've done in the. history so that it it doesn't detect. what tactic you're going to use and do. something. just something that's never been seen. before in order to confuse. the adversar's AI. Correct. Yeah. So,

you have to make a drastic change that. you don't know know if it's actually. going to work so that the AI doesn't. detect, oh [ __ ] we've seen this before. this is what it's about to do. Yeah. Yeah. So, so to your point, yeah, strategic surprise becomes the name of. the game very quickly. Um, and and how. do you create an operation such that you. maximize the amount of strategic. surprise against an adversarial AI? That's one. And then honestly the second. thing that's that's really critical is a.

lot of this will just plain up boil down. to like straight up boil down to how. many copies you have running and how. large your data centers are and um how. much industrial capacity you have to run. these AIS both centrally and at the edge. in all the war in all the theaters in. all the the um in every in every. environment. um how fast will it learn.

new technology? So, let's just take for. example Seronic. They're making. autonomous surface warfare vehicles or. Palmer Lucky, you know, he's doing the. autonomous submarines and and. so when when. am I trying to say here? So, let's say. we're at war with China. China has all. the data, all the history back from. whatever World War II on different. capabilities that we have. And what.

happens when a new when something new is. introduced onto the battle space like. Seronics autonomous vehicles or Eperus. or. uh or Palmer's rockets or his. submarines? How how would the. how would the AI. get the data set. to make a decision or or not make. decisions but come up with what you're. talking about courses of actions. consequences what it's about to do p you.

know probability of what's going to. happen how how fast will it be able to. learn. when something new is introduced onto. the battle space? Yeah, this is this is. a great question. In general, so the so like the first time it sees a. a totally new, let's say a USV or UUV or. whatever it might be that that it's. never seen before, um it won't be a, you. know, it won't be able to predict what's.

going to happen like cuz, you know, it. won't know. how fast it's going to go. It won't know. what what, you know, what um uh what. munitions it has. It won't know what its. range is. It It won't know all the key. uh the key facts unless, by the way, they have really good intel and they. already know all those things because. they've hacked us. But um let's assume. they don't know. So the first few. conflicts, it's not really going to be. able to to figure out what's happening. And that that's a that's a key component. of strategic surprise is always having.

new platforms that won't be sort of. simulatable, let's say, by enemy. wargaming tech. Um, so that's that's. definitely part of it. Um, but at a. certain point it's going to know what. the hardware are capable of and it's. going to be able to run the simulations. to to understand how that changes the. calculus. Um because ultimately right. what's going to happen is.

and some of this stuff like you know. this is this is like. you know some of the stuff is dissonant. because obviously if you look at what. happens today in the military it looks. nothing like this but let's play the. play the tape forward and like see what. happens in the future. Ultimately, you're going to run large scale. simulations and it's going to figure. out, hey, this new, you know, uh, uh, unmanned surface vehicle has this much. range. It can go this quickly. It can. maneuver in this way. It has this kind. of munitions. Um, it has this kind of.

connectivity. Uh, it is vulnerable to. these kinds of, you know, EW attacks, whatever they may be. Um, it can be. jammed in these ways. And those will all. just be parameters for the simulation um. to run. So I think but initially it. would have no recommendations. Initially. you'd have strategic surprise. So OBSAC. when it comes to weapons capabilities is. still just paramount and it will I mean. will it always come back to the human.

mind? Uh yeah I believe so. I believe that you. know we have this concept that we talk. about a lot which is human sovereignty. So um AI systems are going to get way. better but how do we ensure that humans. remain sovereign? How do we m ensure. that humans maintain real control over. what matters? So maintain control over. our political systems, maintain control. over our militaries, maintain control. over our economic systems, you know uh.

our major industries, all that kind of. stuff. And so um and I believe it's. pretty paramount in the military. You're. ne you are not going to want to take. certainly just as like a as like a. simplistic thing. We're not going to. give AI the capabilities to unilaterally. fire nuclear weapons. Mhm. Like we're. never going to do that. Um and so. ultimately so much of what is going to. become really critical is.

the aggregation of information, simulations, wargaming, um planning to. humans. to ultimately make the proper decisions. And by the way, so much of this will. will start bleeding into the diplomatic. like diplomacy, diplomatic decisions. that need to be made. Um, it'll bleed. into like uh into economic warfare. Like. it'll bleed into I mean this this goes. all the way into.

I could see this going all the way into. relationship building with with uh in. between nations. Should we, you know, what are the what are the outcomes if we. become allies with. Russia? Yep. You know what what what are. the courses of action? What are the. consequences? I mean is it does it so it. bleeds into everything? Politics, allies, adversaries, warfare, economics,

all of it. Yeah, totally. Because if you. ultimately boil it down, what is the. capability? The capability is. sensing and situational awareness. So. I'm I'm going to know I'm going to be. able to go through troves and troves of. data. OSENT other forms of um uh like. open source intel uh different kinds of. of various Intel feeds that I have and. know what is the current status what's. going on what is the what is the current. situation it'll be able to aggregate all.

that data in to provide a a. comprehensive view as to what those. behaviors are and then it'll give you. the ability to predict um and it'll give. you the ability to effectively play. forward you every potential action you. could take, what would happen in those. scenarios with some probabilistic uh. view, some some probabilities and then. yeah, you're going to use that. for every major decision like the the. military and the government should use.

this for every major decision we make. We should do it for trade policies. We. should do it for diplomatic relations. We should do it for um uh we should do. it you know we're looking outwards but. honestly we should also do it for like. internal policies like you know what are. our healthcare policies what are our um. you know uh all that kind of stuff too. but um so it will this capability of. sort of um effectively.

all domain sensing plus planning um is. going to be paramount. Do you. and I have so many questions. Do you see a world where. AI becomes. so powerful. throughout the world that it becomes. obsolete. and we're right back to where we we are. we were I don't know 10 years ago, 20.

years ago where it's all human. decision-m. Well, will it outdo itself? Um, a few thoughts here. I think so. One of the thing, so I think the first. stage of what's going to happen is like. kind of what I'm saying like human is. the loop to human on the loop. We're. going to right now humans do a lot of. just like like brute force manpower.

work in all sorts of different pl you. know in the economy and in warfare etc. Um that'll that's that's like the first. level of of of major automation that's. going to that's going to take place. So. then it's like about you know your. um strategic decision- making. and your ability to um and your ability. to make high judgment decisions um that. considered long-term, short-term,

medium-term, all that kind of stuff. Um. at a certain point of of well. at a certain as the AI continues to. improve and improve and improve and. improve um it will operate at a pace. that is very very difficult for humans. to keep up with. Um and in you know this. will start happening in R&D first in re. research and development like AI will be. able to start doing lots of scientific.

research lots of R&D into new weapon. systems lots of R&D into new you know. military platforms etc um much faster. than than humans are you know would be. able to do and then humans will just. check over their work and and decide and. so it's going to sort of race faster and. faster and faster and Um and the so then. what happens I think it'll what it'll do. is it'll create dramatically more weight. on the few decisions that humans make. So any decision that like all the way to.

the extreme right is um you know the. president or or you know whomever making. decisions about do I let my AI. collaborate with another country's AI. like that'll be like a decision of just. like dramatic consequence uh much higher. consequence than like similar decisions. today. So I think it almost to your. point it like it will as it accelerates. we'll end up at a place where you're.

right it all boils down to human. decision-m but those decisions will. carry. like a thousand times more consequence. Mhm. How do you decide who you're going to. work with? I mean it's an international. company. Yeah. Um, so we've had Who all. are you working with? Uh, well, so first. thing is we're pretty we're pretty picky. about who we work with ultimately just.

because we have um we only have so many. resources and building these systems and. building these data sets like is pretty. involved um as as kind of we've. discussed. So, you know, our aim. generally is how do you work with the. best in every industry? You know, how do. how do you work with, you know, like. kind of was mentioning the number one. bank, the number one pharma, number one. telco, number one military, etc. Um, the. only addition to this that I would say. we viewed as as as important is how are.

we. um as you as we play the tape forward. and everything we're just discussing. It's really important that. um as much of the world runs on an. American AI stack uh versus a CCP AI. stack that becomes really really. important. Um and uh it matters not only. for. ideology and you know kind of as we were.

talking about before like propaganda and. control and all that kind of stuff but. it also really matters just for like you. know at a pure operational level like. we're going to want to be able to have. as extended of of of AI capabilities as. possible. So, okay. So, the way I understand this is. you're working with X country. We'll.

just say, we'll just say country X. You give country X the AI model to. utilize for whatever they're doing. Let's just say warfare. we own, but they they have to tap into a. US-based. data center. Am I correct here? And so, as long as we control the data center. that's feeding that AI model, we. essentially own it and that and country.

X just has to trust that. scale AI has their best interest. Yeah. It's like next level. And if they. change, if they change, let's say. country X now forms an alliance with. China, they decide. they don't want to be a part of America, then we just yank the AI or the not the. AI, the the the the data that feeds that. AI or manipulate that data to where it's.

essentially been hacked. Am I correct? And that's how we keep. ourselves safe. Uh yes. And then with. the addition like I think the way that. um at least we think about it today and. I think a lot of people think about it. today is like. it's okay for the data center to be. located elsewhere located in the. country. Um as long as it's US owned and. operated. um because then we still have control in.

you know any sort of scenario that. happens. And um the only other thing I. would say is we're much more focused. initially on just um low stakes uses of. AI. So can you use AI to help. uh the education uh industry in one of. these countries or can you use it to. help the healthcare industry or can you. use it to aid in um in like you know. permitting processes or you know low I. think low stakes use cases matter a lot. more initially. Um but I really do think.

like uh you know we have this concept of. geopolitical swing states. There are. there are a number of countries right. now in the world where whether they side. with the US or China over time is going. to have immense consequences for. certainly what a what a potential. conflict scenario looks like but also. even what like the long-term cold war. scenario looks like. like what happens. um over time in this as you know our.

countries are interacting. So um so I. view I view AI as like one of these key. elements of diplomacy and long-term sort. of uh like. long-term. um strategic impact in the in the. international war game. How would AI be implemented into our. government? I mean, I can't remember. exactly what you said, implemented to.

run, you know, our political sphere. What does that look like? Yeah. So, um, uh, because so much of that is people's. values and and what people believe in. and stand for and, you know, I mean, and. it like today for example, I mean, country is probably more polarized than. it's ever been. And so, how do you how. do you get an AI model to run government. when it is this polarized and there's so.

many different ideologies and. part of the country is way over here, the other part's way over here. How how. would an AI model. run that? Yeah. So, um the we have this. concept of kind of like agentic warfare, agentic government. So can you can just. like the same thing can you take these. very inefficient processes in government. and start replacing those with AI.

related functions so that you're you're. just you're just improving efficiency. and improving outcomes. Give me give me. uh a specific example. Yeah. So what. like one super simple one. Right now I. think the the average time it takes for. a veteran to see a doctor in the VA is. something like 22 days. Mhm. um it's way. too long and part of that is because of. a host of antiquated processes and. workflows and you know um just in.

general that system's not working. I. think we'd all look at that and say. that's not a that's not a functional. system. And so um can you use AI to you. know AI agents to automate some parts of. that process automatically get whatever. approvals need to be gotten get whatever. information needs to be gotten such that. that that 22 days becomes a day or two. or something like that. Um that I think. is like a no-brainer just pure win for. government efficiency overall. Um,

another one that, uh, other ones that. are like big are like, you know, permitting processes. So, if I want to. build a new data center somewhere or. even I just want to like remodel my. home, the, you know, permitting. processes depending where you are, it. could take could literally take years. uh, for all of that to go down. And part. of that is like there's so many. different approvals that need to happen. There's so many like there's all these. like different workflows and things that. need to like happen. What if instead we. just codified what are the rules of the. system and had an AI agent just go. automatically go through that permitting.

process so that you could get that. permit or or get the permit denied. within like a day, right? Um so and just. that times a million like like the uh. like um like one of the things from from. Doge that they found right is that you. know the uh the retirements are stored. in the mine Iron Mountain mine uh. literally a literal like iron mine um. are like the paper copies of the. retirements for all the federal.

employees. like can we just take that. which is two generations behind um in. terms of tech like it's like literally. pen and paper um and then use AI to go. from two generations behind to two. generations forward like can we just. automate as much of those processes as. possible so um so I see as just like you. know all over the there's so much low. hanging fruit in terms of just making um. current government services and. government processes way more efficient. I think that I I haven't met anybody who.

doesn't think this is the case. So, um. that's just that's just all the level. one stuff. Um I think uh the. Yeah, that's just all the level one. stuff and improving how our government. operates. Would it would it eventually. replace politicians? That's a good question. I think. ultimately like we. um so.

first off just like um uh taking a step. back it's definitely the case that. policy the speed of policym and the. speed of legislation and the speed at. which the government reacts to new. technologies like that's going to have. to speed up. Um, you know, we uh I've. spent a lot of time in DC trying to make. sure that, you know, as a country we get. the right kind of AI legislation and the. right kind of AI regulation to ensure.

that this all goes well for us. Um, it's been years of trying to get that. done. You know, we still haven't really. figured that out as a country. What is. what is the right AI regulatory. framework? Like that's still it's still. undecided. I mean, how do you even. describe this stuff to the dinosaurs. that are still sitting in DC? I mean, we've got people stroking out on camera. We've got people literally dying in. office. I mean, we got people up there. that probably can't even figure out how.

to open a [ __ ] email. And then you. come in, 28 years old, built scale AI. I I I mean I just I mean just going all. the way back to when you know. Zuckerberg's sitting there you know. talking to Congress. It's it's I mean. and I don't agree with everything he did. and whatever. It doesn't matter. But I. look at that and I'm like, you guys have been sitting in DC,

probably don't even know how to open. your own email. and you're talking to a tech genius. who's trying to dub this down and make. you understand. I mean, I get one day. with you, you know what I mean? And to. try to wrap my head around this and they. have 50 million other things they're. dealing with. They're not up to speed on. tech. I mean, how how do you even begin. to. Yeah. tap in? I mean, I think a lot of. it I think um the first thing and I.

think this is like a lot of people in. the know understand this like a lot of. the minute decisions really end up being. made by staffers, right? And um and. I think like generally speaking like. staffer you have to be extremely. competent as a staffer um no matter what. like there's just it's a very chaotic. job. There's a lot that's there's a lot. that's going on and they have to make. very fast decisions. Um.

uh the other thing is I think I think. analogies are are pretty helpful. Like I. think you know everybody alive today has. seen the pace of technology progress. just increase and increase and increase. and increase. Like I think that you know. you'd be hardressed to find anyone who. doesn't believe that AI will be this. worldchanging technology. Now exactly. how it'll change the world I think. that's where it gets fuzzier but um but. it will be worldchanging technology. Um,

but I but the issue is like I mean the. the political system just doesn't. respond very quickly, right? And and. that's that's going to that's going to. be very harmful. I mean we need to be. able to respond very quickly to these. new technologies. Um, and so. uh I and I think they'll become more and. more obvious. Like I think I think as AI. and other technologies accelerate, it'll. be very obvious that like the world will. just change so quickly and frankly I.

think voters are going to demand faster. action. Um and I so I think I think our. government is set up to um to accelerate. but um. but that's that's what needs to happen. How do we power all this? I mean that's. that's a big discussion you know and. everybody is seems so apprehensive to go. nuclear. The grid is.

extremely outdated. I mean we just saw. the light flickers here about I don't. know 30 minutes ago. Power outages. happening all the time. There was just a. big one. All of Spain. Uh Portugal, Italy. I mean, it's happening all the time in the US. Power outages. How are we going to be able to power all. this stuff? I What would you like to see. happen? Yeah. I mean, first of all, if. you look at if you take a graph of.

Chinese total China's total power. capacity over the past 20 years versus. US total power capacity over the past 20. years, the China graph is like straight. up and to the right. They're just adding. crazy amounts of power. They've doubled. it in the last decade, I think. Doubled. doubled doubled their power capacity in. the last decade. Um, and uh, the United. States is basically flat. Um, it's grown.

like a little bit. Uh, and so. we're like that. That's what's happening. right now. Right now, China's doubling. every decade or so. Um, US is is is. basically flat. And we're looking at, you know, the for to just power the data. centers that that today AI companies. know they want to build. we're going to. need something like a doubling of our. energy capacity and that needs to happen. very very quickly like almost you know.

that has to happen almost immediately. Um and so you have to believe that our. graph is going to go from totally flat. to vertical faster vertical than than. China's energy um uh growth. And China. on the in the meantime is just is. growing is is growing perfectly quickly. They'll accelerate. they'll add more. power to their grid. Like I think it's. very hard to imagine realistic scenarios. where without drastic action, the United.

States is able to grow its energy. capacity faster than China. Um, now. where are we on the So if China's going. straight up and we're flatlined, I mean, does that mean are you saying that China. has surpassed our power capabilities or. are we still above them even though. they're on the rise? Uh they're they're. definitely above us because they have a. bigger population and they have way more. industrials. Uh so they have uh I'll. double check. I they definitely have. more power total than us. Um more power.

generation capabilities. And um and by. the way, like it's actually not rocket. science why that is. It's if you look at. if you then break that down to sources. of that power in China, it's because. coal is like 80% of that. Yeah. They're. all They're all coal. Yeah, it's just. tons of coal. And then we've actually. like if you look in the US, renewables. have grown a lot, but a lot of it, the. reason the overall number is flat is. because we're using renewables to. replace coal, natural gas, like fossil.

fuels. Um, and so when you net it out in. the US, we're flat. And then in China, it's it's straight up. So that's the. first thing like we need we need drastic. action. You know, the administration has. the National Energy Dominance Council. Um, we've sat down with them a few times. like the we we got have to we have to. take drastic action to enable us to to. at least start matching their speed of. adding energy to the grid and ideally. surpass it. That's like that's the first. thing. The second thing like you're.

talking about is our grid is extremely. antiquated and that's a major strategic. risk. Um, you know, I don't know what. the what the cause or the source of the. the um outage across Spain was, but you. know, some people think it was a foreign. actor um or some kind of some kind of. cyber attack of some sort. Um, I guarantee you the US energy grid is. extremely susceptible to large scale. cyber attacks. Um it would be uh you.

know and the way you know the the. sophistication of these cyber attacks. sometimes is like so stupid. It's like. if you find the right like uh like power. plant login terminal to go into. sometimes people don't change the. username and password from the default. which is username and password. And so. you can just find like some power. station in like Wyoming that still has. an the username and password's username.

and password. You log in and you can. shut down the entire uh power in the. entire region. So the like the so so our. grid just because of how antiquated is. how decentralized it is every all of. that is hyper hyper susceptible to uh to. cyber attacks hyper susceptible to. foreign action foreign activity and um. that matters now like right now if you. take the energy grid in a major city. people will die so it's like it's bad. now but then let's go back to what we're.

just talking about with AI like let's. say we have large scale AI on AI warfare. with China. They just take out the power. grid, take out our data centers and the. power fueling those data centers and. then we're sitting ducks. I mean, not. only that, but it's my understanding. that China actually produces and. manufactures a lot of the major. components that go into our grid like. the transformers. If we don't even, to. my understanding, we don't even check.

those for malware, Trojan horses, [ __ ]. like that. In fact, DOE actually did an. inspection on one and never and never. even released the results of what they. found, which probably means they found. some [ __ ] And I mean, I just I don't. know. how we combat that. I mean just like the. like what what is where did that happen. elsewhere? Like look at um Salt Typhoon.

like uh this was a recent hack that was. declassified which is that Chinese. malware and cyber act activity like. basically had fully infiltrated our um. major telecom providers. I think AT&T. was like entirely uh like um entirely. compromised by this hack called Salt. Typhoon um from the CCP and uh and. that's they did that so that they could.

read all the messages like all the SMS. all the audio um they were able to to. capture as part of that as part of an. intel gathering operation. Um, but if. they're able to hack into our telco, they've sure as hell, you know, they're. clearly capable of hacking into our. energy grid, clearly h capable of. hacking to any other any of our other. critical infrastructure. And um, and it. just goes back to what we're talking. about, like the energy grid, a, if we. can't produce enough power, we're hosed,

and b, if the adversaries can take out. our power at will, we're hosed. Mhm. Um, and so we have this major major. vulnerability as a country on just like. the cyber posture of our energy grid. I. think it's like I think it's one of the. the biggest like very obvious like. flatout um uh like clear vulnerabilities. of our overall of our entire country. Um. a just like you create civil unrest. you.

can like take, you know, imagine you. took Houston's power grid out. People. would die and uh you cause like all. sorts of chaos. But then if you but then. you take out these data centers, you. take out um military bases, you take out. radar systems, um you take out, you. know, you name it, you can take out. almost any piece of homeland. infrastructure and that those create. huge strategic openings for adversaries. I mean, what M you have to run in these.

circles. I mean, you're building massive. data centers, correct? And so. when you go to DC and you're advocating, hey, we need more power and you just I I. didn't What's the association you met. with? Uh the National Energy Dominance. Council, I mean, what do they say? They. totally agree. I mean, they know we have. to build more power. And then it's about. So then you get to the next layer of. detail. It's like, okay, how can we how. do we accelerate nuclear? How do we.

accelerate the permitting process? Um. what are existing power generation. capabilities that we turned off that we. can turn back on? Um like you go through. all the natural things to do. Like it's. I mean I think I think we know what to. do. The question is if we can get out of. our own way and if and then if our grid. is so antiquated that even that. vulnerability like kind of means that we. can be taken out any time. I mean I may. have made an assumption. Are you are you. building data centers? We we ourselves. are not building data centers. We.

partner with companies that yeah that. are building you know the largest data. centers in the world. Okay. And so I've. I've also heard rumors that these major. data centers are starting to just create. their own power source. Is that is there. any validity to that? Yeah. So a lot of. designs these days involve can you just. create an SMR a small um uh like a like. a nuclear reactor per data center. can. you basically like have a nuclear. reactor colllocated with the data center.

um to uh to power that that data. center's capacity um which I think is a. good idea. The issue is like I mean. China is going to be way ahead of us on. that. The largest nuclear power plant in. the world is in China. So um you know. we're yeah you obviously we need to lean. into nuclear that needs to happen. obviously we need to to lean into all. power generation sources. when you kind. of an all the above approach to power. generation. Um uh but even that doesn't.

get us to a posture where you're. confidently exceeding China. You're just. kind of catching up to where they are. And so um I mean this is a huge a huge. issue. Yeah. Let's take a quick break. When we come back I want to I want to. dive more into China's capabilities and. and our capabilities. Smart money moves are all about getting. more out of every dollar. With Rocket. Money, you can easily find forgotten. subscriptions and have them negotiate.

bills for you, putting money back in. your pocket. And with all those savings, Rocket Money practically pays for. itself. Rocket Money is a personal. finance app that helps find and cancel. your unwanted subscriptions, monitors. your spending, and helps lower your. bills so you can grow your savings. With. Rocket Money, you get alerts if bills. increase in price, there's unusual. spending activity, or if you're close to. going over budget. The new goals feature.

automatically saves money for you, so. you don't have to think about it. Rocket. Money has over 5 million users and has. saved a total of 500 million in. cancelled subscriptions, saving members. up to $740 a year when they use all of. the apps premium features. Cancel your. unwanted subscriptions and reach your. financial goals faster with RocketMoney. Go to rocketmoney.com/srs. today. That's rocketmoney.comsrs. rocketmoney.comsrs.

When I started this podcast, it seemed. like I had to figure it out all on my. own. It was overwhelming. When you're. starting something new, it seems like. your to-do list just keeps growing and. it can overrun your entire life. Finding. the right tool can be such a gamecher. for millions of businesses. That tool is. Shopify. Shopify is the commerce. platform behind millions of businesses. around the world. and 10% of all.

e-commerce in the US from household. names to brands just getting started. I. use Shopify to power my own business so. I can keep bringing you Vigilance Elite. gummy bears. With hundreds of readytouse. templates, Shopify helps you build. online and is packed with helpful AI. tools to accelerate your content. creation. And like a marketing team, Shopify can create email and social. media campaigns wherever your customers. are. Shopify is your commerce expert. with world-class expertise in everything.

from managing inventory to international. shipping and beyond. If you're ready to. sell, you're ready for Shopify. Turn. your big business idea into with Shopify. on your side. Sign up for your one. month, $1 per month trial period and. start selling today at shopify.com/srs. Go to shopify.comsrs. shopify.com/srs.

All right, Alex, we're back from the. break. We're getting ready to discuss. some of our capabilities versus China's. capabilities. And you know, we we we just got done. kind of talking about power. Is China leading the US in any other. realms when it comes to the AI race? I. mean Xi Jinping has even has said. himself you know the the the winner of. the AI race will achieve global. domination. Yeah. I think well the first thing.

almost as you're mentioning to. understand is China has been operating. against an AI master plan since 2018. They um the CCP put out a a broad whole. of government you know civil military. fusion plan to win on AI. uh like you're. mentioning Xiinping himself has been has. spoken about how AI is going to define. the future winners of this global. competition. um in military from a.

military standpoint they say explicitly. hey we believe that AI is a leapfrog. technology which means even though our. military is worse than America's. military today if we overinvest in AI we. we have a more AI enabled military than. theirs we could leapfrog them um so. there they've been super invested uh. right now I think the best way to kind. of paint the current situation is they. are way ahead on power and power.

generation. They're behind on chips um. but catching up on chips. Um they uh are. ahead of us on data. Um China has had. again since 2018 a largecale. um operation to dominate on data. Um and. uh today in 2023 I think there were over. 2 million people in China who were. working as working inside data factories. basically as data labelers or annotators.

basically creating data to fuel into. those into AI systems. I think that. number in the US by comparison is. something like 100,000. Um uh so they're. outspending us 12 to1 on data. um they. have over seven cities, full cities in. China that are dedicated data hubs um. that are basically powering uh you know. this this like broad approach to data. dominance. Um and then on algorithms I.

think they have they are on par with us. um because of large scale espionage. So, uh, and this is, I think, one of these. open secrets in the tech industry that. Chinese intelligence basically steals. all of the IP and technological secrets. from um from the United States. Uh, there are a bunch of very concerning. reports here. So one is there was um a.

Google engineer who took the designs and. and all the IP of how Google designed. their AI chips and just took those and. and moved to China and then started a. company um on top using those using. those designs. Um, the way he got those. designs, by the way, it was this guy um. Leon Leon Ding, I think. Um, the way he. stole the data out of out of um Google's.

corporate cloud, by the way, was that he. it was so stupid. He just took all the. code, he copy pasted it into Apple notes. into like the notes app and then um. exported to a PDF and printed it and. just walked walked out with it. That's. it. That's it. Um, so, uh, that was this. was later discovered. You know, we we. found out this happened, but for months. we had, you know, we had no idea that. they had stolen all this critical IP. Um, Stanford University, this just came.

out last week. Stanford University is uh. is entirely infiltrated by CCP. operatives. Um, few crazy facts. So. first uh uh it is by law in China any. Chinese citizen must comply with Chinese. with CCP intelligence gathering. operations. So if you're a Chinese. citizen, you're living in the United. States and the um intelligence agencies. in China reach out to you, you have to. comply with them and so you have to give. them what you're seeing, what you're.

what you're finding, etc. Um uh so that. and there's tons of Chinese nationals, Chinese citizens in across. all the major elite universities, across. all the major tech companies, across all. the major AI labs, like they're. everywhere. The second thing that's. crazy is uh you know about a sixth of um. Chinese students uh so so stu like. Chinese citizens who are students in. America are on uh scholarships sponsored.

by the CCP itself and for those on these. scholarships they have to report back to. a handler basically what are the things. they find what are the things they um. they're learning otherwise their. scholarships get revoked so we There's. there's an incredibly large scale. intelligence operation running in the. against the US tech industry which is. just collecting all the information and. secrets and technological secrets from. our greatest research institutions, our.

universities, our lab AI labs, our tech. companies um at at massive scale. And. honestly, I think this is a very. underrated element of how China caught. up so quickly. So, um, you know, Deepseek came out of nowhere. Everyone. was so surprised at how capable their. model was and how they learned all these. tricks. You know, how much of that is. because they came up with all them on. their own or they managed to have a like. exquisite high-end espionage operation. to steal all of our trade secrets from.

the United States and then reimplement. them back in China? What does our espionage look like? Well, there was a uh I think nowhere. close to as good. I mean, I think um so. one thing that uh that that the CCP did. for Deepseek, the Deepseek Lab is um. after Deepseek blew up and uh and um the. CEO of DeepSeek met with the Chinese. premier uh they then locked up all the.

researchers into a um uh inside I. shouldn't say locked up, but they like. huddled all the researchers together and. they took all their passports. So none. of the AI researchers who work at. deepseek are are able to leave the. country at all and they can't they don't. come into contact with any foreigners. So they basically lock down the entire. you know research effort. Um so that it. you know that makes it very very hard to. to conduct any sort of espionage into. the into that operation. Um and then.

there's that report uh this is all in. the news but like you know a decade ago. 15 years ago um all of or many of the. CIA operatives US CIA operatives in. China um were all killed because they. were sort of um compromised because one. of the communication channels they were. using was compromised by Chinese. intelligence and you know the CCP was. able to to effectively like round a lot. of them up and kill them. So our.

comparable their espionage in us is like. extremely deep you know ex huge risk. there's incredible amounts of of you. know we're deeply deeply penetrated by. uh by Chinese intel um and comparatively. as far as I know we have like you know. much less capability and I think they've. designed it such that it's very hard to. infiltrate their AI efforts. Um. jeez. So that's how other so they're.

they're you know they're they're ahead. of us on data. They're they're able to. catch up through espionage on algorithms. pretty easily. Um uh they're ahead of us. on power. So what are we aheaded? Well, right now we're ahead in chips. Um, and. that's kind of our saving grace is that. uh the Nvidia chips and the entire stack. there are the pride of the world and you. know we're the most advanced on these. chips. Chinese chips are also catching. up. Um there's like a bunch of recent.

reports that Huawei chips are are. getting to be they're basically like one. generation behind the Nvidia chips. So. they're close. They're close. Um so all. of this is uh is pretty concerning. There was another um report that came. out of CSIS recently that there was a um. a Chinese effort called it's like the. next generation. uh brain understanding project or. something where they're basically trying. to use AI to fully um understand human.

human personality effectively and human. psych psychological behaviors. Um I. imagine that's ultimately for. effectively like information warfare. Um. as we were talking about at breakfast. like I mean China has largecale. information operations large scale. information warfare and has been has. been doing that for. decades and you know literally decades. um going back all the way to like.

in-person operations in Hong Kong like. they are so sophisticated all that and. AI is going to enable them to just move. much faster as well. How do we combat. that? Uh well, I mean, I think we need our own. information operations efforts. Like, I. think that's pretty critical. Um that's. that's specifically on that thread. And. then I think we we need to. uh we need to acknowledge that at the. end of the day um you know we are a more.

innovative country but we have to. dramatically. you know get our [ __ ] together if we. want to win longterm in AI. We need to. um we need to onore ship manufactur ship. manufacturing like we need to be. manufacturing huge numbers of chips. We. can't be dependent on Taiwan to. manufacture our high-end chips. Are we. doing that yet? At any capacity? Uh. extremely small capacity. Like there. there are a few fabs in Arizona that can. produce some chips. Um but the vast.

majority of the volume still comes out. of Taiwan. Uh we need to tighten up. security in our in our AI companies. dramatically. like we need to we need to. have proper counter intel on you know. what is the espionage risk in within. these companies. Um we need to solve the. power problem that we talked about. Um. we need to have uh we need to be. investing into you know the cyber. threats like investing into large scale. cyber defense. Um we need to invest into.

data. we need our own programs around. data dominance to ensure that you know. China doesn't just run away with uh with. higher quality and greater AI data sets. than us. So you can go through each of. the elements and build like the proper. plan for the United States to win. Um. but uh have we started any of that? Um I. mean I think some things are underway. but uh. not I mean not enough nowhere close to.

enough for for to to be sure that the US. will win. Definitely not. And they also. have a fundamental advantage. You know, uh, one of the things that that people. say a lot now is like, oh, like what we. need in the United States is an AI. Manhattan project where we like, you. know, we collect all the brilliant minds. together, we collect our resources, and. we have one large um, effort in in the. United States. Well, it turns out like. it's actually really hard to pull that. off in the United States, but China can. pull it off super easily. China can just.

say, "Hey, all the best AI people, you. now work in one company. You we're going. to pull together all of your resources. You are you all are we're going to put. you right next to the largest nuclear. power plant in the in the world. Like. we're going to build the largest data. center in the world here. All the chips. that China has are going to go towards. building this this like large scale AI. project." and they just have the ability. to collect all of their resources. together and throw it at at winning on.

the AI race. Um whereas in the United. States, we have all these companies. Um. and you know, the United States. government as of yet like it's not going. to force all these companies to combine. and merge. Like that's that's like such. an that today would be viewed as such an. overreach of government power. Um, but. because of that, we're going to have. like, you know, five fragmented AI. efforts. And maybe in aggregate, we'll. have way more chips and in aggregate. we'll have more power and in aggregate.

we'll have, you know, more great. researchers, but we're not going to be. able to focus those efforts whereas. China is easily going to be able to. focus all their efforts. Wow. You had. mentioned something downstairs about uh. nuclear weapons. Yeah, I believe. Yeah. So this is this is where stuff gets um. stuff gets really weird for for um. national security which is uh you. you could you could clearly imagine.

scenarios where. advanced very advanced cyber AI um. invalidates nuclear deterrence. What do. I mean by this? right now um you know. nobody fires nukes because we have MAD. we have mutually assured destruction and. if I do a first strike against another. country they're going to be able to. while that nuke is in the air do a. second strike and um we'll both you know. there'll be destruction on both sides.

it'll it'll be really bad. So because of. this second strike capability. um luckily we have a proper you know we. have real deterrence. Well, what if. instead. um let's say uh let's say I'm, you know, the United States and I have the most. advanced AI cyber hacking capabilities. in the world. So, I can build AI agents. that uh hack into um that can hack into. any other country, can like turn off.

their energy grid, can disable their. weapon systems, can disable everything. So, what do I do instead? I launch the. first strike and I immediat and or like. first I send in my my cyber AI agent. capabilities. I send my cyber AI. uh you know force effectively to disable. all the weapon systems of. of the of the enemy country. And because. it's uh my I have like such so much AI.

capacity, I can take out all of your I. can like disable all of your weapon. systems. and then I send my first strike. and then you don't have a second strike. capability. So if that happens basically. the combination. of AI and nuclear be you know you you. cannot deter AI plus nuclear with just. nuclear. So then it forces this um. that's what will force this like. proliferation of AI capabilities and so. even small countries are going to need. to invest in lots of AI capabilities.

because their nuclear weapons are no. longer a sufficient deterrent. Jeez. What about boweapons? Yeah, I this is. this is the the um element that is. uh really underrated right now. So, CO. leaked out of a viology lab in uh Wuhan. and basically shut the world down for. two years. And that's like le that's.

like the the level one you know biorisk. kind of stuff like this was relatively. uh a relatively. uh you know innocuous let's say um. pathogen uh but it still killed you know. probably at least 10 million people. globally and it was still you know shut. the whole world down for 2 years um well. recent models new models the new AI I. models are able to uh outperform 95% of.

MIT viologists. So the newest models. from OpenI and Google are smarter than. literally 95% of viologists at MIT uh. based on a recent study by um the center. for safety. So um so now you now whether. it's right now or whether it's in a few. years um it will be feasible to use AI. based capabilities to help you design.

powerful pathogens. And what's more than. that you're going to be able to design. in certain characteristics of these. pathogens. You know you'll be able to. tune the virality tune the um lethality. of them. You know, there's also due to. recent advancements in synthetic. biology, you now can create viruses that. specifically target certain segments of. DNA. So, um I could create a bioweapon. that just targeted, you know, um any.

individual with a certain segment of. DNA, which means I can target basically. like any population or any group or any. subsegment of the population in the. world. um which is. uh which is really really bad. And so um. the the ability so first even without AI. like biology synthetic biology is making. so much progress and that there's just. like all sorts of inherent risk of uh.

like all sorts of inherent risk of. bioweaponry or you know leaks of of. pathogens and and viruses and whatnot. And then with AI all of a sudden you. this is you know not not literally. today's models but a few models a few. generations down you're going to be able. to use these AI systems to design or. build you know uh next generation. pathogens. Um so that's that's an entire. I mean for good reason biological.

warfare is not you know one of the um is. not you know their international. treaties such that we don't engage in. biological warfare but if you imagine. these scenarios where countries you know. nuclear deterrence doesn't work they. don't have the resources to get to use. to utilize to have large scale AI data. centers um you know can you know I'm. worried that countries will will. turn to biological weaponry bioweapons.

as their deterrence mechanism which is. highly destabilizing for you know the. world. Wow, that's some scary [ __ ] The. flip side is there is new technology. that can um. that can also prevent this stuff. So. there's um there's this research coming. out of uh this lab in Seattle, David. Baker's lab, this guy who just won a. Nobel Prize on uh biological noses.

uh or uh digital noses, sorry. Um which. is basically you have these devices that. can detect. chem detect proteins or chemicals or. pathogens in the air um automatically. And so I think what this will like, you. know, the real sort of like offense. defense of of bio and bioweaponry will. end up looking like we're just going to. have large scale deployment of digital. noses effectively that in every space on.

every like shipping container on every. plane um you know they're just. constantly sensing for all existing. known pathogens any new pathogens um. that might exist and are constantly just. like you. containing effect or like detecting and. ultimately containing. Interesting. It's. sniffing real time for all of that [ __ ]. Yeah, exactly. I mean on also on the. flip side I mean I guess if AI is. developing.

a new bioweapon. CO comes out again CO 2 we'll just call. it then RAI. should also be able to. figure out the the vaccines or the. vaccine the antidote to it correct yeah. totally so there will be there will be. an offense defense um element to. just as just as in kind as we were. walking through like AI applied to.

command and control there's an offense. defense element AI applied to cyber. there's an offense defense element AI. applied to bio and bioweaponry there. will be an offense defense element so. all these thankfully there's like you. know the hope is that we end up in a in. a in a global world you know the the the. world agre agrees that basically we're. not going to go down any of these paths. like cuz there's mutual deterrence and. we just you know it's not worth it for.

anybody in the world to destabilize you. know and risk humanity like that. That's. that's basically where we need to land. Wow. How concerned are you about China. Taiwan? I mean we were chatting about. this a little bit at breakfast and I I I. can't believe they have not made a move. yet. I mean, I thought for sure it would. happen towards the end of the last. administration, but. I mean, with their chip production. capabilities, I mean, how how concerned. are you about China taking Taiwan?

I think if it's going to happen, it's. going to happen this decade and it's. probably going to happen this. administration. And um why do you say. that? Uh. I mean China at a at a macro sense they. have huge demographic issues. Those are. I mean there's not like that's just like. the of the force of gravity in their. country. They have this huge aging. population. They made the wrong bet you.

know many decades ago to have a one. child policy. Um and so they are going. to have this like huge aging population. Um over then that that plays that plays. out really like quite soon like over the. next like a decade from now it's going. to be um over time they're going to look. more and more like Japan in that way. where they have this like large aging. population and it'll paralyze a lot of. ability to make any sort of aggressive. moves. So particularly when it comes to. military industrial capacity etc. Um, so. that's like one force of gravity uh that.

they have to contend with. And then um. and so I think I think they're they're. they're going to want to move faster. sooner rather than later. And then. they've I mean they've had such an. insane military buildup um over the. course of the past few decades. Um, you. know, I don't think it's and I think, you know, we're we're currently in a. situation where China has far more. industrial capacity, far more.

manufacturing capacity than we do in the. United States. And so, um, that is set, you know, that's a window. for them. Um, so do you think they'll do. that they're pressed to do it because of. the aging population? I think a lot of. factors. I think I think Xi is aging. right. Um this will be an important. component of his legacy uh as as he. would view it. I think um they have the. Nian population which will minimize.

their political latitude over time um. naturally and then they have um I mean. they are they're in this in insane. window where they have just incredible. uh industrial manufacturing capabilities. um compared to anywhere else in the. world. you know, in 2023, uh, China deployed more industrial. robots than the rest of the world. combined. Um, that's like I mean, we. were talking a little bit about like. automated factories and automated.

industrials, like they're racing that. faster than any other country in the. world. And so um so I think that like. you can look at all these dimensions and. this window um you know there's if. they're if they're going to do it. they're going to do it soon. Yeah. Yeah. I mean what what percentage of the chips. that we use come from Taiwan? I mean 95%. of the high-end chips um are. manufactured in Taiwan. And so what.

happens if if China takes Taiwan? So yeah, war game it out. So we were. talking a little bit about this. So um. let's say China blockades or or invades. Taiwan um then then there's a qu So. these fabs are incredibly incredibly. valuable because as we were just. describing if you believe in the pace of. AI progress and AI technology then. everything boils down to how much power.

you got, how many chips you've got. And. if they own 95% of the world's. ship manufacturing capability, I mean, they're going to run away with. it. So then you look at that and you. say, will the Taiwanese people bomb the. TSMC data centers? Um, and andor will. the US bomb the TSMC data centers and or. will some other country bomb the the. data centers? Or sorry, not the the. FABS, um the TSMC chip fabs. Um I think. my personal belief I don't think uh the.

Taiwanese do it because even if they get. blockaded or invaded that those FABs are. still a huge uh component of Taiwan. survivability and um Taiwan's relevance. as a as a as an entity um even if they. get blockade or invaded by Taiwan. So I. don't think they do it. Um, China. definitely doesn't do it cuz they. obviously invading partially to get, you. know, um, to gain those capabilities. Um, and so then, uh, does the US bomb.

them? If the US bombs them, that's. probably World War II. I, it's hard to. imagine that not just resulting in. massive escalation. Um, and so you're. looking at it and there's kind of no. good options. Um, so I think it's I mean everyone's very. focused on it obviously, but it is it is. like a real powder keg of a uh damn.

of a region. How do you think this all ends? Um, we had a little discussion about this at. breakfast. Yeah. Yeah. Um I mean. I think. I think if so let's assume that in the. next handful of years next like 3 four. years um there's an invasion or blockade. of Taiwan.

and. uh you know I think it's I think given. how important AI is um it's hard for the. US to to not take any sort of action in. that scenario and then you. almost all the actions you would see. escalating into a major major conflict. So um. best case scenario is we deter the. invasion or blockade altogether and um.

and I think you know. I think it certainly is in everyone's. interest to not get into a large scale. world war that's a hugely destructive. and and kills lots of people. So I think. like fundamentally we should be able to. deter that conflict. Um, but that's uh. that's why all this matters so much. We. need to make sure our AI capabilities as. a country are the best in the world. We. need to make sure that our military AI. capabilities are the best in the world.

We need to make sure that you know um uh. the there's clear uh economic deterrence. of this kind of scenario. like we need. to um we need to be investing in in. every way to deter this conflict such. that um you know where this really will. break down is if the Chinese if the CCP. calculus uh uh you know diverges from. our own if their calculus becomes. oh no this is going to work you know we.

we can take this and then you know we're. strong enough so they'll work out for us. and then our calculus is the opposite. that's where that's where the world war. scenario happens. So um so I think it's. possible to deter and I think we have to. you know there's a lot of things we have. to do to make sure that we deter that. conflict and that should be I mean. certainly I think it already is like 80%. of the focus of the entire DoD. So, I. mean, it's it's just we can deter, but I.

mean, when you're talking about an aging. population, I mean, they're getting. desperate, and it sounds like in order. for them to to legitimately win, they. have to acquire those chip fabs, correct? And so, they already have 250 times the ship. building capacity. They have way more. people. They have they have more power. than we do. I mean, military recruitment in the US, you. know, was at an all-time low. I don't.

know what it is today, but I mean, even. if it So, I guess what I'm saying is. we can you can only deter a desperate. entity for so long before they throw a. Hail Mary play, right? Would you agree. with that? Yeah. And then it just depends on the. you would have to dedicate an entire. military to surround Taiwan. to effectively do that in my opinion.

Yeah. I mean, I think that the if if. they assess if the CCP and the PLA. assess that. Taiwan is all they're like they they. will focus their entire military. capacity on seizing Taiwan, then. that becomes a really that becomes a. really tricky calculus. I mean, why. wouldn't they? If if if if. Xi believes that the winner of the AI. race achieves global domination,

he's getting older. You just talked. about how important his legacy is to. him, which I'm sure you're right. I don't know how you deter that. And then they win the AI race. Yeah. The. only thing that we can do, I think this is a long shot, but I think. it's important, is if. um if ultimately we actually end up. collaborating on AI. And I know that.

sounds kind of crazy, but um. but if we're able as a country to. demonstrate. just we're so far ahead and there's. like, you know, the one one key element. of of how the whole AI thing plays out. um is this idea of um AI. self-improvement or uh intelligence. recursion sometimes people call it. Basically, um, once AIS get sufficiently good, then.

you can start utilizing the AIS to help. you build the next AI. You, as sci-fi as. that sounds, you utilize your current. generation AI to build the next. generation AI faster and faster and. faster and faster. And so, at some. point, um, your AI capabilities enable. you like, you know, there's some form of. like, you know, just exponential. takeoff. They just, they just, you know, your AI capabilities get good really, really quickly. And if somebody's even 3. to 6 months behind you, then they're.

they're never going to catch up to you. because you're running the. self-improvement loop got faster than. anybody else. And so this is a this is a. key idea. I mean, it's I think it's um. it's a little bit theoretical right now. Like it's not clear whether or not this. intelligence recursion um is going to be. how it plays out, but but a lot of. people in AI believe it. Um, and I. probably I probably believe it too that. that we will be able to use AIS to help. us continue training the next AIS and.

improve things more quickly. And if you. believe that, then if we're let's say. three 3 to 6 months ahead of China um, and we maintain that advantage and we. take off faster, then they're going to. be way behind. And then ultimately we're. gonna be in a great position to say, "Hey, actually, like we're way ahead and we. should just, you know, you guys should.

quit your efforts. Um we'll give you AI. for all of your economic and uh and um. humanitarian uses throughout your. society. Uh and we agree we're not going. to battle on military AI.". What would it take. to take the chip building capabilities. that Taiwan has as implement that here. in the US to protect it? So.

yeah um so the first thing is. uh there's been hundreds of billions of. dollars invested. just into like the buildout of those. fabs and the the the the call foundaries. but the buildup of these of these large. scale chip factories effectively and the. um and all the high-end equipment and. tooling inside of them. hundreds of. billions of dollars of investment. So,

first off, there needs to be hundreds of. billions of dollars investment in the. US. That's not the hard part. The second. part that's that's really the hard part. is um all it's basically a large scale. factory operated by highly highly. skilled um uh uh uh workers who. are very experienced in those processes. and the whole thing operates like a you. know like clockwork. Um, and unless you. can get those people to the US, you.

know, you're going to have to like. rebuild all that knowhow and all that. technical capability. And that's what. takes a really long time. And that's one. of the things, you know, why do you. think we haven't done that? Why do you. think we have not incentivized. these brilliant minds to come here and. do it for us? So TSMC, the Taiwan. semiconductor, um the company that you. know builds these fabs, they have stood. up a few fabs in Arizona. Um but they.

cited issues like first there were. issues around um permitting and getting. enough power and they dealt with some. EPA issues and then um and then they. just have issues where the like uh you. know the technicians working in Arizona. don't aren't as skilled or don't work as. hard as those working in Taiwan. Um. so they've built a few fabs in the. United States. So, they've tried to do. it, but our our red tape and our our.

power is not what it needs to be to be. able to do this. Red tape, power, um, workforce. And then there's another key. thing, which is. if you look at it from Taiwan. Semiconductor, from from TSMC's. perspective, they're not all that. incentivized to stand up all these. capabilities in the United States. like. if as soon as they start standing up all. these capabilities in the United States,

the United States is not incentivized to. defend Taiwan. Yeah. And it's a. Taiwanese company. Um so and it's a. critical part of their survival. strategy. Um, so, so that's that's. really where the rubber hits the road is. are they actually incentivized to do a. large scale buildout of of chip. manufacturing capacity in the United. States? Um, I think the answer is like. no. Makes sense. I mean, there would. have to be some type of a some type of a.

deal struck where they fall under our. wing. Yeah. Yeah, I mean you could. imagine some kind of deal with with. China um between the US and China. It'd. have to be like a diplomatic deal at the. highest levels, which is something along. the lines of, you know, hey, you guys can have Taiwan, but we. need large scale fabs in, you know, we. need large scale chip manufacturing in. the United States or something like. that. And like, you know, maybe there's.

worlds where that kind of deal could get. could get drawn up. I don't know. Um. uh but that would I mean that would also. mean that the United States would just. have to say hey all we care about. actually at this point is is chip. manufacturing and that we don't care. actually about the Chinese people and. the the country and all that stuff man. Man and are they working with China at. all. capacity the TSMC? Yeah. So, they're um.

I think they're technically not supposed. to, but a lot of the the um. Huawei, one of the leading companies in. China, has been able to get um. tons of chips from uh tons of dyes, it's. called, but basically tons of chips or. chip um uh uh prerequisites from Taiwan.

And they usually do it through like they. like start some cutout company that. doesn't seem associated with them in. like Singapore and then that Singaporean. company buys a bunch of um uh or. Malaysia and that or the Singaporean. Malaysian companies buy a bunch of chips. from TSMC and then they mail it back or. something. But there's clearly been uh. there's been a lot of TSMC high-end. um outputs that have gone to to the. Chinese companies. Wow. Wow.

Scary [ __ ] man. It get it gets I mean I. think this is where um. you have to believe like right now if. you look at the you know just as we were. right now like if you look at the. situation and all of the. um all the dynamics at play right now. it's it's like it's a powder cake. It's.

like very very very volatile. Um, highly. problematic in many ways. And this is. where I mean you just ultimately have to. believe that there's there's got to be. some effort towards diplomatic. solutions. Yeah. Because it is. definitely true like war will be really. bad for both sides. Yeah. Yeah. How do. we coordinate with China with the AI? Yeah. So, um, what does that look like?

So, yeah, right now, right now, we're. definitely, um, US and China, um, we're. definitely in an allout race dynamic. And, you know, we're going to race, and. I think this correct, we're going to. race to build the best AI systems. They're going to race to build the best. AI systems. Um. uh and we're both all in on this. approach and um we're both all in on on. racing towards building the most. advanced AI capabilities, the largest.

data centers, largest capacity, etc., etc. Um the uh and this is if you know. if you recall kind of how um how nuclear. was um like you know in nuclear uh. nuclear war as well as application of. nuclear towards um uh towards a power. production. It was kind of you know all. systems go like everyone racing um. towards building capacity building. capability and then uh Chernobyl and.

ThreeM island happen um and it creates. large-scale conration around the. technology um and the risks of those. technologies and um there were uh a. bunch of international treaties and. there's a large international response. towards coordinating on nuclear. technology. Now all said and done if you. really you know if you look at nuclear. like uh that set our country back set. many countries back you know many.

generations in terms of power. generation. But what it took was. effectively these like smallcale. disasters. um to take place that effectively uh. that effectively were the forcing. function for international cooperation. Um you can you can imagine a scenario. with AI where because of all the things. that we've been talking about um uh. there's some scenario where um maybe.

some terrorist group or some non-state. actor or some you know North Korea or. whomever somebody decides to use it for. um in a particularly adversarial or you. know inhumane way and creates and that. disaster has some large scale fallout. So uh it create you know you take out. the the you take out power in uh like.

one of the largest cities in the world. and tons of people die or you take out. or there's some pathogen that gets. released and like tens of millions of. people die or you know some one of these. things happens that causes the. international community and everyone in. the world to realize oh shoot we have to. be coordinating on this and you know we. should be collaborating for AI to. improve our societies and improve our. economies and improve the lives of our. people. But we shouldn't it, you know, we need to we need to coordinate on its.

use towards, for lack of a better term, scary things. like bio or cyber warfare or, you know, the list goes on. Um, so. long story short, I think the path. really is um some kind of, you know, we. sometimes we talk about like an AI oil. spill or some kind of of incident that. really causes the international. community to realize like, hey, we we. have to we have to start coordinating on. this. I mean, it's you say. China's all out, you know, gone all in.

on the race day ice and the US has gone. all out on the race day, but we're. kneecapping ourselves. I mean, you just. mentioned the red tape, the EPA, the permitting, and the power and we're not producing. more power. We're flatlined. We've. established that, as far as I know, we're not getting rid. of the red tape, you know, to to to jet. launch this. And.

I mean, it just seems like. we're cutting ourselves off at the knees. here, right? Right now, I mean, we have a lot. of work to do for sure. We have to we. have to build strategies to win to have. energy dominance to have data dominance. Um to on the algorithms I think we'll be. okay. They're gonna espionage but I. think we'll be okay on algorithms. Um we. need to ensure we have chip dominance. long term. Uh we need to make sure all.

this lends itself to military dominance. I totally agree with you. I mean we need. to. we need to today ensure that we have the. proper strategies in place so that we. stay ahead on all these areas. The worst. case scenario for the United States is. the following which is. um CCP. uh does a large scale Manhattan style. project inside their country. um realizes they can start because of.

all the factors that we've talked about. they they realize they can start. overtaking the US on AI that lends. itself to extreme hyper military. advantage and they use that to take over. the world. That's like that's like worst. case scenario for the US. If US and AI. AI US and China AI capabilities are even. just roughly on par, I think you have. deterrence. I don't think either country. will take the risk. I think if US is way.

ahead of China, I think you maintain US. leadership and that's a pretty safe. world. So the the the worst case. scenario is they get ahead of us. Are there any other players other than. the US and China involved in this? Who else do we need to be watching out. for? So yeah, right now definitely US and. China. Um the a lot of other countries. will matter. Um.

but not all of them have enough. ingredients to really properly be AI. superpowers. So um but other countries. are going to they have they have key. ingredients. So um to to name a few a uh. everything we've talked about with with. cyber warfare and information warfare, information operations, Russia has very advanced operations in. in those areas. Um and that could end up.

mattering a lot if they ally with the. with the CCP. Um there's a lot of ways. they can team up and and have uh and. that could be pretty bad. Um. there's uh you know the the countries in. the Middle East will be very important. because they have um incredible amounts. of capital and they have lots of energy. Uh and so. that's these are you know they're. critical um players in how all this.

plays out. India matters a lot. India. has a lot of high-end technical talent. Um uh I don't know if I think right now. I don't know if between India and China. which has more high-end technical talent. but there's a lot in India for sure. Um. massive population um also starting to. industrialize in a real way. Um and. right next to right next to China so. India will matter a lot. And then um you.

know there's a lot of there's a lot of. technical talent in Europe as well. I. think it's unclear exactly how this. plays out um with the European. capabilities. I mean they have to. um it seems like there's some efforts. now for Europe to try to uh build up. large scale power, build up large data. centers, you know, um. uh make a play. I think yet to be seen. how effective those efforts are going to. be, but um you can clearly see some. scenarios where if they make a hard a.

hard turn and and go all in, they could. be relevant as well. Is there a world where AI takes on a. mind of its own? So, uh, you know, obviously you can. hypothetically paint the scenario where. like, you know, you have super. intelligence or you have really powerful. AI and then, um, you know, it realizes. at some point that humans are kind of. annoying and takes us all out. But uh.

but I think I think it's a very like. that's so preventable um uh as an. outcome because. first of all all the things we just. talked about are like the very real. things that happen long before you have. you know this hyper advanced AI that. takes everyone out. That's first that's. first thing. So we have lots of things. we have to get right before then. And. then second is um you know for AI to.

actually um be capable of you know. having a mind of its own and taking all. humans out like we'd have to give it. just incredible amounts of control. Like. it would have to just basically be. running everything and we're just sort. of like along for the ride. Mhm. And. that's a choice. We have this choice of. whether or not to like give all of our. control to AI systems. And as I was. talking about before with like human. sovereignty, I my belief is we should.

not seed control of our most critical. systems. Like we should we should design. all the systems such that human. decision-m human control is really. really important. Human oversight is. really important. Um, this is one of the. things that I actually think is is um. one of the things that we're working on. as a company. So, honestly, one of like. as I think about like long-term. missions, one of the most important. things is creating human sovereignty. So. first is how do we make sure all the.

data that goes into these AI models um. increases human sovereignty such that. the models are going to do what we tell. them are aligned with humans and aligned. with um uh our objectives and two is. that we create oversight. So as AI. starts doing more and more actions, doing more planning, you know, taking. out, you know, carrying out more things. in in the in the world, in the economy, in military, etc. that humans are.

watching and supervising every one of. those actions. So that's that's how we. maintain control and that's how we. prevent, you know, the Terminator. scenarios or the, you know, AI takes us. out kind of scenarios. Interesting. Well, Alex, wrapping up the interview. here, but man, what a fascinating. discussion. Thank you. Thank you for. being here. One last question. If you. had three guests you'd like to see on. the show, who would it be?

Oh, it's a good question. Um, who would I like to see? Uh, well, I really like what you've been. doing recently, which is getting more. tech folks on the on the pod. Um, so, uh, so I go in that direction. I mean, I. think Elon would be great to see on the. show. I think, uh, I think, um, we were talking about this. Zach. would be would be cool to see on the. show. I think, uh, Sam Haltman would be.

cool to see on the show. So, definitely. like, um, more people in tech. Outside. of that, um. I think uh and we were talking about. some of this like um. international. leadership like international like. leaders of other countries is super. important because um we talk about all. these scenarios like international. cooperation is going to matter so much.

Right on. we'll we'll reach out to them. and uh you know as far as world leaders. is concerned we're we're on it but um. well Alex thanks again for coming man. fascinating discussion I'm just super. happy to see all the success that you've. amassed throughout your 28 years it's it. is. I love seeing it. So thank you for being. here. I know you're a busy guy. So yeah, thanks for having me. It was fun.

[Music]. [Applause]. No matter where you're watching Shan. Ryan Show from, if you get anything out. of this, please like, comment, subscribe, and most importantly, share. this everywhere you possibly can. And if. you're feeling extra generous, please. leave us a review on Apple and Spotify.

podcasts.