WEBVTT 00:00:00.000 --> 00:00:03.837 We're living through a historic moment right now. The next thing that's really 00:00:03.920 --> 00:00:07.637 interesting and terrifying also is recursive self-improvement, but we don't 00:00:07.720 --> 00:00:10.637 have it yet. What we do have 00:00:10.720 --> 00:00:13.277 I keep asking my friends, when does the 00:00:13.360 --> 00:00:15.637 asymptote arrive and when does the curve 00:00:15.720 --> 00:00:17.877 slow down? It is actually true that 00:00:17.960 --> 00:00:20.637 there is a limit to our craziness. 00:00:20.720 --> 00:00:23.517 We have not found it yet and that's the 00:00:23.600 --> 00:00:25.917 great thing frankly about America. 00:00:26.000 --> 00:00:28.357 The American competitor, not enemy, but 00:00:28.440 --> 00:00:30.557 competitor is China. They have lots of 00:00:30.640 --> 00:00:33.277 money. They're very, very smart. Their 00:00:33.360 --> 00:00:35.637 work ethic is equal or stronger than 00:00:35.720 --> 00:00:38.637 ours and they dominate key industries. 00:00:38.720 --> 00:00:42.957 But at the moment it sure looks to me like the robotic hardware 00:00:43.040 --> 00:00:45.517 of China is the winner. I don't want to 00:00:45.600 --> 00:00:48.837 lose the robotic revolution in my view 00:00:48.920 --> 00:00:51.077 the way we lost the electric vehicle 00:00:51.160 --> 00:00:57.160 revolution at least on the low end. It's possible, but it requires 00:00:57.680 --> 00:01:01.680 Now that's a moon shot, ladies and gentlemen. 00:01:02.640 --> 00:01:05.317 Eric, do you remember the first time we met? 00:01:05.400 --> 00:01:07.397 Yes, Larry Page introduced me to you 00:01:07.480 --> 00:01:08.677 because he was on your board. 00:01:08.760 --> 00:01:12.477 >> Yes. Yeah, so I got a call from Eric out 00:01:12.560 --> 00:01:15.197 of the blue, which was a great honor. 00:01:15.280 --> 00:01:19.117 And and said Larry says I should meet you. When are you 00:01:19.200 --> 00:01:22.437 going to be down here in or up here in San Francisco? I was in LA 00:01:22.520 --> 00:01:24.417 and I said how about tomorrow? 00:01:24.500 --> 00:01:27.037 >> [laughter] >> Typical Peter. 00:01:27.120 --> 00:01:29.677 And I remember something which was so 00:01:29.760 --> 00:01:32.477 I love the story. We sat down to lunch 00:01:32.560 --> 00:01:34.317 at Charlie's Cafe. 00:01:34.400 --> 00:01:39.717 Um and of course I'm running a nonprofit and my mission is always raising capital 00:01:39.800 --> 00:01:43.317 for nonprofit. And so we sit down to lunch 00:01:43.400 --> 00:01:47.477 and before we get started you said Peter, so what is your highest level of 00:01:47.560 --> 00:01:51.637 of giving a membership? And I said well Eric, it's our vision circle 00:01:51.720 --> 00:01:55.857 for $2.5 million and you go, okay, I'm in. Now let's have a conversation. 00:01:55.940 --> 00:02:00.437 >> [laughter] >> I'll buy them all. It was it was crazy. 00:02:00.520 --> 00:02:03.277 >> [laughter] >> Yeah. Oh, there you go. 00:02:03.360 --> 00:02:08.077 But you know, somehow you have the reason when we 00:02:08.160 --> 00:02:11.637 spoke, the reason I wanted to come here is this has become the epicenter of the 00:02:11.720 --> 00:02:16.117 abundance movement. And the abundance movement is correct. That's the 00:02:16.200 --> 00:02:18.777 important thing. Thank you. >> Yeah. 00:02:18.860 --> 00:02:20.880 >> [applause] 00:02:21.040 --> 00:02:23.597 >> Um I just want to thank you for all the 00:02:23.680 --> 00:02:26.677 support you've given myself, X Prize all 00:02:26.760 --> 00:02:29.557 these years. So grateful for that. So 00:02:29.640 --> 00:02:33.197 I'll start with a a question that I'd 00:02:33.280 --> 00:02:37.237 love to hear you expand on, which is we're living through a historic moment 00:02:37.320 --> 00:02:39.997 right now. Right? Um 00:02:40.080 --> 00:02:41.837 could you define the moment that we're 00:02:41.920 --> 00:02:44.557 in and give us sort of a a state of the 00:02:44.640 --> 00:02:48.317 union of what's going on in AI? 00:02:48.400 --> 00:02:52.437 We're 10 or 15% into the impacts of 00:02:52.520 --> 00:02:55.757 this. And you can see it. 00:02:55.840 --> 00:03:00.677 You can feel it. And some of it will happen, some of it 00:03:00.760 --> 00:03:04.557 will take longer, right? So for example, hardware takes longer than software. So 00:03:04.640 --> 00:03:09.317 that robots take longer than digital systems on traditional hardware, things 00:03:09.400 --> 00:03:13.917 like that. Um we've not um 00:03:14.000 --> 00:03:18.037 the next thing that's really interesting and terrifying also is recursive 00:03:18.120 --> 00:03:21.757 self-improvement. >> Mhm. It's not happening yet. 00:03:21.840 --> 00:03:26.277 And so it's easy to convince yourself that you're going to have human agents 00:03:26.360 --> 00:03:29.517 sorry, computer agents that are human-like completely within a year or 00:03:29.600 --> 00:03:32.037 two. We don't have the science for that 00:03:32.120 --> 00:03:34.277 yet. People are working on it. I can 00:03:34.360 --> 00:03:37.237 describe how I think it'll play out. But 00:03:37.320 --> 00:03:39.837 we don't have it yet. What we do have is 00:03:39.920 --> 00:03:42.677 reasoning systems that are perfect 00:03:42.760 --> 00:03:46.917 partners for human beings for good and bad, right? And that has a lot of 00:03:47.000 --> 00:03:51.197 implications. So if we stop today, which we're not and it's not stoppable or 00:03:51.280 --> 00:03:55.037 controllable by any government or any single individual or corporation, 00:03:55.120 --> 00:03:59.477 we would still have advanced humanity because of these reasoning agents. How 00:03:59.560 --> 00:04:03.437 fast do you imagine this is going to accelerate? 00:04:03.520 --> 00:04:07.197 Um the there's a thing which I call the San 00:04:07.280 --> 00:04:11.077 Francisco consensus and the reason I call it is cuz everyone in San Francisco 00:04:11.160 --> 00:04:12.797 believes this. 00:04:12.880 --> 00:04:15.637 Uh everyone I know anyway, which is that 00:04:15.720 --> 00:04:20.117 it it it's easy to understand. Uh this is the year of agents, which we can 00:04:20.200 --> 00:04:23.837 discuss why agents will take over everything this year. 00:04:23.920 --> 00:04:27.637 During this year the scaling of the use of agents and reasoning will sort of 00:04:27.720 --> 00:04:30.637 grow at this enormous rate. Everybody's out of 00:04:30.720 --> 00:04:32.557 hardware, everyone's out of electricity. 00:04:32.640 --> 00:04:35.917 It's a real boom, right? It's like the biggest boom I've seen and I've been 00:04:36.000 --> 00:04:39.837 through three or four of these in my career. 00:04:39.920 --> 00:04:43.677 Um the in this thinking 00:04:43.760 --> 00:04:47.397 once you have recursive self-improvement where the system can begin to improve 00:04:47.480 --> 00:04:49.837 itself, you have intelligence learning 00:04:49.920 --> 00:04:54.517 on its own and it will in this argument, it will learn faster than we can cuz 00:04:54.600 --> 00:04:58.877 we're biologically limited. And the way this is expressed in San 00:04:58.960 --> 00:05:00.557 Francisco and I'll give a simple 00:05:00.640 --> 00:05:02.237 example. You have a tech company with a 00:05:02.320 --> 00:05:07.277 thousand fantastic AI researchers. Um 00:05:07.360 --> 00:05:10.717 so one day they turn on AI research that 00:05:10.800 --> 00:05:13.437 is an AI research agent. Well, how many 00:05:13.520 --> 00:05:18.877 AI research agents do you have? Well, as many as you're limited by electricity, 00:05:18.960 --> 00:05:21.237 right? You don't have to feed them, they don't 00:05:21.320 --> 00:05:23.637 need housing, there's no more housing in San Francisco, you know, all that kind 00:05:23.720 --> 00:05:26.437 of stuff. Right? You don't have those problems. You don't have an HR 00:05:26.520 --> 00:05:29.957 department for them, if you will. Uh and you don't have to pay them, you just 00:05:30.040 --> 00:05:33.437 have to feed them electricity. So how many could you have? Well, maybe a maybe 00:05:33.520 --> 00:05:35.717 a million of these agents. 00:05:35.800 --> 00:05:38.997 Now in AI the way you determine you've 00:05:39.080 --> 00:05:42.557 made progress is you have clear metrics 00:05:42.640 --> 00:05:44.197 that the reasoning or testing or 00:05:44.280 --> 00:05:46.317 whatever the evaluation framework is 00:05:46.400 --> 00:05:50.357 better, right? So that's what happens. 00:05:50.440 --> 00:05:53.877 So in that scenario the slope goes like 00:05:53.960 --> 00:05:58.237 this because you're already at this slope, then you add more people, then 00:05:58.320 --> 00:06:02.597 you get the agents and you go like this and this is essentially 00:06:02.680 --> 00:06:04.837 a super intelligence moment. 00:06:04.920 --> 00:06:06.597 The belief in San Francisco is this 00:06:06.680 --> 00:06:09.877 occurs within two to three years. 00:06:09.960 --> 00:06:13.117 The evidence in favor 00:06:13.200 --> 00:06:17.357 goes something like this. Claude code came out a couple months 00:06:17.440 --> 00:06:20.277 ago, the the latest one, Opus whatever it is. What was it? 00:06:20.360 --> 00:06:23.037 >> 1.6, yes, thank you. And 00:06:23.120 --> 00:06:28.797 everyone I know in the Bay Area that's doing software says it was 80/20, now 00:06:28.880 --> 00:06:30.637 it's 20/80. >> Mhm. 00:06:30.720 --> 00:06:34.157 The best analysis I can come up with is 00:06:34.240 --> 00:06:36.837 it's not the Claude code part, it's that 00:06:36.920 --> 00:06:41.117 the that the underlying LLM can produce 00:06:41.200 --> 00:06:43.637 more reasoning over time, better quality 00:06:43.720 --> 00:06:46.317 tokens over time. It's a deeper thinker, 00:06:46.400 --> 00:06:50.757 Mhm. right? And all the labs now are competing for that. This is not just the 00:06:50.840 --> 00:06:53.597 size of the context window, it's actually the reasoning skill and the 00:06:53.680 --> 00:06:57.997 length of which it can think. It can just think longer and produce more 00:06:58.080 --> 00:07:01.957 stuff, right? I watched this stuff when I was I 00:07:02.040 --> 00:07:05.717 moved to the the Bay Area when I was 21 00:07:05.800 --> 00:07:09.037 and I was a programmer in high school way back when. 00:07:09.120 --> 00:07:10.837 And I was pretty good programmer. 00:07:10.920 --> 00:07:13.037 And I watch what it does and I go, my 00:07:13.120 --> 00:07:16.197 god, I'm over, you know? There's not a 00:07:16.280 --> 00:07:19.157 thing that I could do that it cannot do. 00:07:19.240 --> 00:07:22.637 So when they wrote a C compiler 00:07:22.720 --> 00:07:26.077 in rust I got it's over, you know, like 00:07:26.160 --> 00:07:29.837 declare suc So I think [laughter] part of this part of this is because the 00:07:29.920 --> 00:07:33.917 people who are building it are also seeing the diminution of their own 00:07:34.000 --> 00:07:38.197 skill. They're being forced to go from programmers, which is what I'm very 00:07:38.280 --> 00:07:42.957 proud to have been, to being the the director of a programming system, 00:07:43.040 --> 00:07:46.997 Mhm. >> right? And the most likely scenario, by 00:07:47.080 --> 00:07:49.197 the way, there's a lot of implications for this. 00:07:49.280 --> 00:07:53.197 One is that it's always been true, speaking as your local arrogant 00:07:53.280 --> 00:07:57.917 programmer, that the very top programmers were worth 10 times more 00:07:58.000 --> 00:07:59.957 than the ones right below. There's something 00:08:00.040 --> 00:08:03.597 >> special about the mathematical reasoning skills of programmers. 00:08:03.680 --> 00:08:06.397 Those people will become more valuable, 00:08:06.480 --> 00:08:10.717 not less valuable, because these systems need to be controlled by humans at the 00:08:10.800 --> 00:08:14.517 moment. Those people will be capable of grasping the parallelization and 00:08:14.600 --> 00:08:17.557 activities of this. It also means that 00:08:17.640 --> 00:08:21.797 you're going to have, in my view, a relatively small number of very large 00:08:21.880 --> 00:08:24.597 companies. >> Yeah. Yeah. And this is a big deal. 00:08:24.680 --> 00:08:28.357 >> Yeah. Yeah. And a very large number of very small companies cuz you don't need 00:08:28.440 --> 00:08:30.637 as many people. And you're watching that 00:08:30.720 --> 00:08:35.717 play out this month. Mhm. I mean this all happened in the last three I got I 00:08:35.800 --> 00:08:38.317 one I was in one startup I'm involved with. 00:08:38.400 --> 00:08:41.637 I was talking to the programmer who was, you know, perfectly perfectly brilliant 00:08:41.720 --> 00:08:44.157 young man. And I said, well, what's the 00:08:44.240 --> 00:08:46.397 truth? He said, well, here's what I do. 00:08:46.480 --> 00:08:50.757 Um he's working on UIs of various kinds and I said, I write the spec of what I 00:08:50.840 --> 00:08:53.037 want and then I write a test function, 00:08:53.120 --> 00:08:55.877 an evaluation function Mhm. and then I 00:08:55.960 --> 00:09:00.397 turn it on. I said, what time? And he goes, 7:00 00:09:00.480 --> 00:09:03.397 in the evening. And I go, okay, what do you then do? 00:09:03.480 --> 00:09:06.957 Well, he has dinner with his wife and he goes to sleep. And I said, do you wake 00:09:07.040 --> 00:09:09.467 up? He said, no, I sleep very well. 00:09:09.550 --> 00:09:11.957 >> [laughter] >> When does it finish? Oh, 4:00 in the 00:09:12.040 --> 00:09:16.557 morning. Mhm. And then he gets up, has breakfast, 00:09:16.640 --> 00:09:20.117 you know, does whatever he does and then he sees what's been invented. I mean 00:09:20.200 --> 00:09:23.237 it's mind-boggling. And and the stupid 00:09:23.320 --> 00:09:27.597 example I used with this young man, this is what the power of these systems 00:09:27.680 --> 00:09:32.677 are. If you can define the evaluation function and you can let it run and if 00:09:32.760 --> 00:09:36.717 you have enough hardware, you're inventing worlds. I mean this stuff 00:09:36.800 --> 00:09:39.797 would have taken me 6 months and 10 programmers at Google to do the same 00:09:39.880 --> 00:09:42.677 thing and this poor guy's sleeping. It's so funny you say that cuz I was 00:09:42.760 --> 00:09:46.877 literally backstage, they said Eric Schmidt's coming now and I have my lid 00:09:46.960 --> 00:09:51.037 open on my Mac and I'm trying to get the jobs onto the 00:09:51.120 --> 00:09:54.877 cloud so I can close the lid cuz if you close the lid it'll break the jobs. So 00:09:54.960 --> 00:09:58.477 I've got these six concurrent Claude 4.6 >> open. 00:09:58.560 --> 00:10:01.237 >> can you know, it's like important what you're doing. 00:10:01.320 --> 00:10:05.037 Tony interrupt for me. You're important, too, you know. 00:10:05.120 --> 00:10:09.917 No, it it's it's crazy cuz when we got together in Davos just what 2 months ago, 00:10:10.000 --> 00:10:13.797 uh it was in this kind of autocomplete mode. You'd write the code and then it 00:10:13.880 --> 00:10:16.357 would help you get it done. You're about 10 times more efficient, but you're 00:10:16.440 --> 00:10:21.077 still babysitting it. Now, literally it's working right now. When I 00:10:21.160 --> 00:10:25.397 get off stage, it will have solved six problems that I launched. And And and I 00:10:25.480 --> 00:10:28.877 appreciate the excitement in the industry, but I can tell you when I was 00:10:28.960 --> 00:10:32.557 I used to work on BSD. I basically worked at Berkeley on Unix at Bell Labs 00:10:32.640 --> 00:10:34.157 and at BSD Unix. 00:10:34.240 --> 00:10:37.197 And we programmers invent what they 00:10:37.280 --> 00:10:42.357 need. And so we invented the first email system and the first messaging system. 00:10:42.440 --> 00:10:45.077 And nobody thought about it. It was like, well, we just need this thing. 00:10:45.160 --> 00:10:49.517 Yeah. So one key thing to understand about digital intelligence is the first 00:10:49.600 --> 00:10:52.757 inventors are the people who are solving problems of themselves who are 00:10:52.840 --> 00:10:56.517 programmers. Mhm. Right? You shouldn't be surprised by this. You should have 00:10:56.600 --> 00:10:59.917 expected this. The other thing that's interesting about 00:11:00.000 --> 00:11:03.677 programming is it's um it's both scale free, which means there's no no 00:11:03.760 --> 00:11:07.277 particular limitations except electricity. You don't need a lot of 00:11:07.360 --> 00:11:11.437 data and you already have GitHub and the equivalents. And it's also a fairly 00:11:11.520 --> 00:11:15.637 limited language set. So the number of language components, if you will, 00:11:15.720 --> 00:11:17.437 compared to human language is less. 00:11:17.520 --> 00:11:21.357 Smaller language, clear objective function, all you need is electricity. 00:11:21.440 --> 00:11:25.877 Yep. Now, how far can this go? It'll get to the point where you don't have the 00:11:25.960 --> 00:11:27.677 ability to do completely new things. 00:11:27.760 --> 00:11:31.637 Yeah. Isn't it Isn't it really quaint and crazy to think that we can sit here and 00:11:31.720 --> 00:11:34.277 say, yeah, I wrote a ton of code when I was younger. 00:11:34.360 --> 00:11:37.877 No one will ever do that again after the end of this year. It'll be like riding a 00:11:37.960 --> 00:11:41.437 horse, you know, be like quaint skills that we all used to have. No, but I do 00:11:41.520 --> 00:11:44.077 have a proposal for universities. Those of you who are associated with 00:11:44.160 --> 00:11:46.517 universities, you should stop everything else you're doing in the university 00:11:46.600 --> 00:11:51.237 right now and design a course for freshman men and women 00:11:51.320 --> 00:11:54.997 uh uh who starting in September, 00:11:55.080 --> 00:11:57.997 which is a prompt engineering class. 00:11:58.080 --> 00:12:01.437 Why Why Why university? Why not high school? 00:12:01.520 --> 00:12:03.697 God, you're so aggressive, Peter. 00:12:03.780 --> 00:12:06.477 >> [laughter] >> Let's start with universities. You can 00:12:06.560 --> 00:12:10.037 improve my idea. I I thought 18-year-olds would be would be young 00:12:10.120 --> 00:12:12.357 enough. Maybe you think it's younger. 00:12:12.440 --> 00:12:16.997 Here's the most important thing. Spend Spend Spend a quarter or a semester. The 00:12:17.080 --> 00:12:21.277 first thing they learn in university is how to use these tools. 00:12:21.360 --> 00:12:24.197 Universities are completely opposed to my idea, as usual. 00:12:24.280 --> 00:12:28.277 >> Yeah. Because it violates every one of their tenets. But if you think about the 00:12:28.360 --> 00:12:30.517 student, and I mean every student, 00:12:30.600 --> 00:12:33.037 liberal arts, you know, math, whatever, 00:12:33.120 --> 00:12:35.757 they're going this platform will be the 00:12:35.840 --> 00:12:38.517 expression platform for their art, their 00:12:38.600 --> 00:12:41.117 music, their writing, and so forth. Why 00:12:41.200 --> 00:12:43.037 wouldn't you teach them immediately? 00:12:43.120 --> 00:12:46.037 Peter, improve my proposal. No, I I just 00:12:46.120 --> 00:12:49.117 I just feel like we're that AI is going 00:12:49.200 --> 00:12:52.997 to impact every student in high school 00:12:53.080 --> 00:12:56.757 today. Yeah. And that they're living an 00:12:56.840 --> 00:12:59.917 unnatural life by not engaging with it. 00:13:00.000 --> 00:13:04.517 And when they hit universities, for those that still exist, um 00:13:04.600 --> 00:13:08.037 Well, plus your kids are that age, and so they're literally right now doing 00:13:08.120 --> 00:13:11.237 exactly what you're describing. So >> Peo- People here who have teenagers, you 00:13:11.320 --> 00:13:13.797 know what I'm talking about cuz they're all in it already. So So I think you're 00:13:13.880 --> 00:13:15.517 that's an improvement to my argument. 00:13:15.600 --> 00:13:19.557 The- There's a problem of age restriction. Uh you really have to think 00:13:19.640 --> 00:13:23.237 about vulnerable teenagers with this technology. Um >> [clears throat] 00:13:23.320 --> 00:13:25.077 >> I did some some analysis of where the 00:13:25.160 --> 00:13:27.317 real problems are with this stuff. 00:13:27.400 --> 00:13:30.797 Um a simple summary is that at some 00:13:30.880 --> 00:13:35.917 point there will be jobs impact from this stuff. We're seeing it in software 00:13:36.000 --> 00:13:39.077 and we're seeing it in certain customer service industries, not across the 00:13:39.160 --> 00:13:40.837 board. At some point that will happen. 00:13:40.920 --> 00:13:42.277 That's an issue. 00:13:42.360 --> 00:13:47.197 Another one is how do we as a country 00:13:47.280 --> 00:13:49.237 maintain our moral values while we're 00:13:49.320 --> 00:13:51.717 also racing against China? Another one 00:13:51.800 --> 00:13:55.037 is the impact on um 00:13:55.120 --> 00:13:59.597 uh young people. It is not okay for 13-year-olds to be committing suicide 00:13:59.680 --> 00:14:02.557 because of an LLM. It's just not okay. It should 00:14:02.640 --> 00:14:05.997 It's It's It needs to be addressed. It needs to be addressed right now. For 00:14:06.080 --> 00:14:09.597 sure. Uh and there's all sorts of other issues. The other one I came up with was 00:14:09.680 --> 00:14:13.197 in agent orchestration. Agents can be combined. 00:14:13.280 --> 00:14:16.557 I've always been worried that when you put the agents together, 00:14:16.640 --> 00:14:20.677 especially if they're from non uh non-compatible vendors, you get 00:14:20.760 --> 00:14:26.037 unpredictable effects. Yeah. So So these are problems to be solved. So we herald 00:14:26.120 --> 00:14:28.877 the future and we solve the problems that it brought. So we're we're going to 00:14:28.960 --> 00:14:32.397 talk about China and government and jobs. 00:14:32.480 --> 00:14:36.397 But before we do that, um I want to say I'm I'm in this savor the moment's kind 00:14:36.480 --> 00:14:39.397 of mode right now because I feel like the world to a year from today will be 00:14:39.480 --> 00:14:41.957 nothing like the world today and all 00:14:42.040 --> 00:14:43.797 everything we're doing right now, 00:14:43.880 --> 00:14:46.637 I've enjoyed so much for so long and I 00:14:46.720 --> 00:14:51.117 just want to savor the moment, but reminisce for 1 minute about the fact 00:14:51.200 --> 00:14:55.037 that while you were running Google, the transformer got invented there. 00:14:55.120 --> 00:14:59.957 The TPU got invented there. Demis Hassabis solved protein folding, 00:15:00.040 --> 00:15:03.197 which is now universally used. You know, do Does the 00:15:03.280 --> 00:15:04.917 work in I think it's Does the work in an 00:15:05.000 --> 00:15:10.637 hour that used to take a PhD student 4 years 4 years. 00:15:10.720 --> 00:15:14.597 >> It's like 300 million times more efficient. Um all of that and all the 00:15:14.680 --> 00:15:17.437 diaspora from that, all the people working in the field in San Francisco, 00:15:17.520 --> 00:15:21.677 as you mentioned, they all were your people. Yeah. And so you were there at 00:15:21.760 --> 00:15:24.877 the creation of everything we're experiencing right now. Do you think 00:15:24.960 --> 00:15:28.117 anything like that profoundly strikes you about that moment? I mean, did you 00:15:28.200 --> 00:15:30.637 even realize at the time that it was still I think I think when you're making 00:15:30.720 --> 00:15:32.757 history, you typically don't know it. 00:15:32.840 --> 00:15:36.397 Um I give a lot of credit to Larry and Sergey. 00:15:36.480 --> 00:15:38.117 Because they were ahead of me. I'm I'm 00:15:38.200 --> 00:15:41.597 an operating CEO and they pushed pushed 00:15:41.680 --> 00:15:45.837 and pushed for excellence. And I'll give you an example. In the 00:15:45.920 --> 00:15:50.557 early years of Google, Larry would My favorite interaction was one day I 00:15:50.640 --> 00:15:54.237 said, we need to hire some people doing Java. 00:15:54.320 --> 00:15:58.837 And Larry and Sergey said, this is the stupidest idea we have ever heard. And 00:15:58.920 --> 00:16:01.517 And I could never tell with them whether they were being serious or not or they 00:16:01.600 --> 00:16:05.317 were just joking with me. But their argument was that real programmers were 00:16:05.400 --> 00:16:06.957 programming one level lower. Today 00:16:07.040 --> 00:16:09.117 Google has many thousands of of it. 00:16:09.200 --> 00:16:12.477 But they But they were so precise and so 00:16:12.560 --> 00:16:17.357 um driven to excellence in technology, Yeah. right? That I could not uh fool 00:16:17.440 --> 00:16:21.637 them. I couldn't market around them. I needed to have the technical expert. And 00:16:21.720 --> 00:16:25.077 they say, oh, that's boring. Don't do that. That's another one of your ideas. 00:16:25.160 --> 00:16:29.637 Right? We want a new idea. Wow. And I give them a lot of credit for it. 00:16:29.720 --> 00:16:31.077 >> But what about the TPU in particular? 00:16:31.160 --> 00:16:35.557 Like that to me cuz I I didn't even hear about it until much later. 00:16:35.640 --> 00:16:39.837 And it takes years to to build design and build your own internal chips. And 00:16:39.920 --> 00:16:44.157 now it's it's about to explode. I don't know how much is public or not, but it's 00:16:44.240 --> 00:16:48.597 it's just Well, so the TPU version one was essentially a matrix multiplier of a 00:16:48.680 --> 00:16:51.437 particular kind. When they went to version two, they changed the algorithm 00:16:51.520 --> 00:16:52.997 in a complicated way. And it's 00:16:53.080 --> 00:16:56.037 particularly good for inference. 00:16:56.120 --> 00:16:59.877 Whether it's brilliance or just luck, 00:16:59.960 --> 00:17:02.037 those decisions made 10 years ago set up 00:17:02.120 --> 00:17:04.477 the TPU as the perfect inference engine. 00:17:04.560 --> 00:17:09.717 And for everybody's benefit, inference is what the reasoning tech steps that 00:17:09.800 --> 00:17:12.797 I'm describing on. So Google is particularly well positioned. As you 00:17:12.880 --> 00:17:17.277 know, Nvidia purchased Groq um for the reason of getting that inner 00:17:17.360 --> 00:17:19.237 >> Yeah, trying to catch up to what you thought of 10 years ago. 00:17:19.320 --> 00:17:21.637 >> interesting about Nvidia, if you look at them, I was looking at the Rubin 00:17:21.720 --> 00:17:25.957 architecture. They managed to do Nvidia managed to do 00:17:26.040 --> 00:17:30.397 what Intel could never do. Intel could never get control of the complete server 00:17:30.480 --> 00:17:34.637 architecture. And they tried. Nvidia has managed to build real 00:17:34.720 --> 00:17:38.957 supercomputers that you can really buy with enough time and money and so forth. 00:17:39.040 --> 00:17:41.997 And it will really be delivered to your to your And And it just do the whole 00:17:42.080 --> 00:17:46.357 thing. These are major industrial achievements. And that's why both 00:17:46.440 --> 00:17:48.957 companies will do incredibly well. 00:17:49.040 --> 00:17:54.077 Right, for that reason. Eric, in the in the AI exponential growth right now, 00:17:54.160 --> 00:17:56.917 talk [clears throat] to me about where the constraints are. You were in 00:17:57.000 --> 00:18:00.317 Congress talking about energy, uh chips, 00:18:00.400 --> 00:18:04.197 um people, capital. Where are the constraints right now? Well, it's It's 00:18:04.280 --> 00:18:05.517 interesting. I started a data center 00:18:05.600 --> 00:18:11.720 company with my friends. Um there's a uh the 00:18:11.880 --> 00:18:13.637 In my testimony, I said there was an 00:18:13.720 --> 00:18:17.597 estimated 92 gigawatts shortage of power 00:18:17.680 --> 00:18:20.797 in America in the next between now and 2030. 00:18:20.880 --> 00:18:23.397 And uh by reference, a nuclear power 00:18:23.480 --> 00:18:27.917 plant is about 1.5 gigawatts. So it's about 60 nuclear plants and we're doing 00:18:28.000 --> 00:18:29.517 essentially zero or one, right? 00:18:29.600 --> 00:18:32.677 Depending on how you count. Um 00:18:32.760 --> 00:18:35.117 So I got interested in the question of 00:18:35.200 --> 00:18:40.397 what's the real resource constraint in in America? And it's electricity. Mhm. 00:18:40.480 --> 00:18:44.157 We have the universities. We have the smart people. We have the economics. And 00:18:44.240 --> 00:18:47.997 we have these amazing finance people who will give all of us billions and 00:18:48.080 --> 00:18:51.877 billions of dollars on a wing and a prayer. I mean, there's no country where 00:18:51.960 --> 00:18:55.557 the finance people are sufficiently crazy to do that. 00:18:55.640 --> 00:18:58.557 It's not true in China. It's not It's certainly not true in Europe. And these 00:18:58.640 --> 00:19:02.717 guys are incredibly jealous of the American financial system. So I always 00:19:02.800 --> 00:19:07.237 start Thank you to the finance people for funding our dreams whether they work 00:19:07.320 --> 00:19:09.317 or not, right? Thank [laughter] you. 00:19:09.400 --> 00:19:13.437 Uh >> [applause] >> So 00:19:13.520 --> 00:19:16.797 So the There There's usually a retort at this 00:19:16.880 --> 00:19:20.677 point where people say, well, the algorithms will ultimately require less 00:19:20.760 --> 00:19:23.917 energy. I am sure that that is true. 00:19:24.000 --> 00:19:28.477 There is this property that is the as the power as the power of the hardware 00:19:28.560 --> 00:19:30.517 goes up, as the algorithms 00:19:30.600 --> 00:19:35.557 become more efficient, you don't need less power, you need even more power and 00:19:35.640 --> 00:19:39.197 even more computers because we discover new uses. Yeah. Jevons paradox. 00:19:39.280 --> 00:19:40.917 >> It's called Jevons paradox. Yeah. 00:19:41.000 --> 00:19:44.757 And so I think that uh 00:19:44.840 --> 00:19:48.797 be- because humans have trouble with exponentials, everyone says, oh, well, 00:19:48.880 --> 00:19:51.877 in 6 to 9 months, it'll will the bubble and you know, so forth and so on. 00:19:51.960 --> 00:19:55.437 There's no sign of this. We've been I I I and a team have been 00:19:55.520 --> 00:20:00.117 working on this for years. The the ultimate law the ultimate 00:20:00.200 --> 00:20:04.197 essentially scaling laws are not done yet. 00:20:04.280 --> 00:20:06.757 I keep asking my friends, when does the 00:20:06.840 --> 00:20:08.637 asymptote arrive, and when does the 00:20:08.720 --> 00:20:11.637 curve slow down? We've not seen it yes 00:20:11.720 --> 00:20:14.397 yet. There will be one, right? 00:20:14.480 --> 00:20:18.677 It is actually true that there is a limit to our craziness. 00:20:18.760 --> 00:20:23.397 We have not found it yet. And we're running to the wall. And 00:20:23.480 --> 00:20:25.717 that's the great thing, frankly, about America. 00:20:25.800 --> 00:20:28.557 >> You think you think it's a limit to the capital, or a limit to if you just add 00:20:28.640 --> 00:20:32.837 more and more and more scale and parameters, something just doesn't work? 00:20:32.920 --> 00:20:35.437 Um Well, the first question is is there a 00:20:35.520 --> 00:20:38.797 limit to the capital available? 00:20:38.880 --> 00:20:42.997 Um a gigawatt of power corresponds to 00:20:43.080 --> 00:20:47.757 about 50 billion dollars of hardware, software, data centers. It's on the 00:20:47.840 --> 00:20:49.197 order of, depending on what numbers you 00:20:49.280 --> 00:20:53.357 use, okay? So, 100 gigawatts is do the 00:20:53.440 --> 00:20:56.957 math. Yeah. Um can we raise 5 trillion 00:20:57.040 --> 00:21:00.557 dollars over 5 years? Yeah. 00:21:00.640 --> 00:21:02.717 That's the strength of America. 00:21:02.800 --> 00:21:04.717 Could we double that? Mm, 00:21:04.800 --> 00:21:06.917 you know, we're we're we're getting the 00:21:07.000 --> 00:21:11.957 data center build out is 1% of the GDP of America growth right 00:21:12.040 --> 00:21:13.317 >> we're back to a power program. 00:21:13.400 --> 00:21:17.597 >> Right. Well, thank you. And the current estimate of electricity use 00:21:17.680 --> 00:21:21.877 um in America is that electricity the 10% of the electricity in the United 00:21:21.960 --> 00:21:23.837 States will be used in the data centers. 00:21:23.920 --> 00:21:26.837 And these data centers These are not the data centers I used to build at Google, 00:21:26.920 --> 00:21:30.677 which seemed tiny by comparison. They were immense at the time. Yeah. The the 00:21:30.760 --> 00:21:35.077 standard data center that's being built is on the order of 400 megawatts. These 00:21:35.160 --> 00:21:39.837 things are plus or minus, and they're about um a half a mile long and about 00:21:39.920 --> 00:21:43.557 500 ft wide, right? And they're essentially airflow machines. Take the 00:21:43.640 --> 00:21:48.437 air, send the air out, uh cool it in the middle uh using typically air cooling, 00:21:48.520 --> 00:21:51.757 and then they have a water system inside to keep the chips 00:21:51.840 --> 00:21:54.037 using Nvidia's an example, the um the 00:21:54.120 --> 00:21:59.197 chips are water-cooled, and also the HBM3E and now the four memories put out 00:21:59.280 --> 00:22:02.597 so much heat that they have to be water-cooled. The chips are 2 kilowatts. 00:22:02.680 --> 00:22:05.557 I mean, this is insane. These things will kill you. You want to hear 00:22:05.640 --> 00:22:10.677 something truly astounding and funny in hindsight? When you bought DeepMind, Yeah. 00:22:10.760 --> 00:22:12.837 everybody thought it was like 800 million bucks or something. 00:22:12.920 --> 00:22:14.917 >> 600 million. 600 million. Bargain. 00:22:15.000 --> 00:22:16.837 Everyone thought, why on earth would you 00:22:16.920 --> 00:22:22.077 waste 600 million dollars on this zero revenue AI? All it does is play Go. 00:22:22.160 --> 00:22:25.197 Yeah. And then years later it came out that 00:22:25.280 --> 00:22:29.517 the acquisition paid for itself just by controlling the air conditioning more 00:22:29.600 --> 00:22:33.237 efficiently in the data centers. The entire acquisition price was paid off, 00:22:33.320 --> 00:22:35.597 and that became the AI that's changing the world today. 00:22:35.680 --> 00:22:38.757 >> And that one go The credit of that one actually goes to Larry Page. Larry had 00:22:38.840 --> 00:22:42.077 studied AI when he was a Stanford graduate student, and he We always 00:22:42.160 --> 00:22:43.997 deferred to him in this thing. And he 00:22:44.080 --> 00:22:47.357 said, this is the best team. Um and I 00:22:47.440 --> 00:22:49.837 think Elon and Larry competed over it. 00:22:49.920 --> 00:22:51.637 There was some complicated kerfuffle 00:22:51.720 --> 00:22:56.037 there. Yeah. And so um Jeff Dean, who's 00:22:56.120 --> 00:22:59.997 the the chief scientist, went over, and then he and I basically, you know, 00:23:00.080 --> 00:23:03.517 finished the deal. And I still remember, you know, it there 00:23:03.600 --> 00:23:06.837 in one floor, you know, these sort of British people, 00:23:06.920 --> 00:23:09.517 and uh led by a sort of Greek British 00:23:09.600 --> 00:23:14.157 person, Demis. Yeah. And they were smart, but Google's full of other smart 00:23:14.240 --> 00:23:18.317 people. To give you an example, in 2016 00:23:18.400 --> 00:23:22.477 um so Demis announces that we're going to win the game of Go. I figured, well, 00:23:22.560 --> 00:23:25.637 And by the way, they're at this point they're a separate group. We've We've 00:23:25.720 --> 00:23:28.357 let them alone cuz they have to grow and figure out what they're doing and all 00:23:28.440 --> 00:23:31.717 that. Okay. And this is the patience of capital. We could let them do that. We 00:23:31.800 --> 00:23:34.157 didn't require that they do anything. 00:23:34.240 --> 00:23:36.997 And so he goes, um I'm going to go, and I said, well, 00:23:37.080 --> 00:23:38.757 I'm going to come, too. 00:23:38.840 --> 00:23:44.237 And I said, okay. So, I fly to Korea, and it's all one floor, and I go and I 00:23:44.320 --> 00:23:48.157 meet the team that's been winning the game. And of course, these all of these 00:23:48.240 --> 00:23:50.797 Koreans They're all very excited about this cuz they know they're going to beat 00:23:50.880 --> 00:23:55.437 the computer. >> Mhm. And so, the the Koreans are in one room, 00:23:55.520 --> 00:23:58.397 I'm in another. I go to the Korean room, and they're all saying, you know, we're 00:23:58.480 --> 00:24:02.037 going to beat beat the crap out of this Google Google Google group. Then I go 00:24:02.120 --> 00:24:06.717 into the Google room, and it's very quiet, and there's a monitor. 00:24:06.800 --> 00:24:10.997 And there's an basically what I now understand is an RL prediction mechanism 00:24:11.080 --> 00:24:13.117 of whether we're winning or not. Yeah, 00:24:13.200 --> 00:24:17.037 cool. Okay? And it starts at 50/50. 00:24:17.120 --> 00:24:18.917 So, I watch I go listen to the Koreans 00:24:19.000 --> 00:24:24.397 talk for a while, and then I go watch the screen, and it goes to 51%. 00:24:24.480 --> 00:24:27.957 Okay? And then it goes to 52%. 00:24:28.040 --> 00:24:32.237 And then David, who is the guy who's the architect, says, 00:24:32.320 --> 00:24:35.647 well, we just planned for it to get to infinity. 00:24:35.730 --> 00:24:41.517 >> [laughter] >> Okay. So, basically, it's a it's the abundance theory. So, it's just 00:24:41.600 --> 00:24:44.357 And >> [laughter] >> And everyone is All the humans are crushed. 00:24:44.440 --> 00:24:47.437 >> Yeah, they're all crying. The DeepMind people say, Yeah, yeah. 00:24:47.520 --> 00:24:50.837 They were They were supposed to. Yeah, yeah. [laughter] Welcome. And And then I 00:24:50.920 --> 00:24:54.517 understood the genius of the DeepMind people. And you can see this today with 00:24:54.600 --> 00:24:57.157 Gemini. Gemini 3 00:24:57.240 --> 00:25:00.357 is probably the broadest of the um of of 00:25:00.440 --> 00:25:04.757 the non-Chinese systems in terms of its depth. And because it's multilingual, 00:25:04.840 --> 00:25:07.717 multimodal, and so forth. >> so much so many moments in your life are 00:25:07.800 --> 00:25:11.597 just turning points in history, and I don't know if you realize them in in the 00:25:11.680 --> 00:25:15.517 moment, but that was one of the last moments where, you know, we humans used 00:25:15.600 --> 00:25:18.517 to look for challenges where the computer could try to catch up, like 00:25:18.600 --> 00:25:20.357 chess. And then I think Go was the end 00:25:20.440 --> 00:25:22.917 point. Go And And we knew that, by the 00:25:23.000 --> 00:25:28.957 way. We understood that Go the game of Go was sort of incomputable by normal 00:25:29.040 --> 00:25:31.317 algorithms. >> Yeah. There was lots of math that said 00:25:31.400 --> 00:25:34.677 you couldn't solve it. And so it was the combina- They They came up with a 00:25:34.760 --> 00:25:39.237 two-tree model with two different RL trees. So, one of these other thing I 00:25:39.320 --> 00:25:43.277 learned about these these things is it's not just write me a Go program that will 00:25:43.360 --> 00:25:46.157 win the game. You actually have to understand the game 00:25:46.240 --> 00:25:50.277 and so forth. So, they took the same team. They They got bored with Go having won. 00:25:50.360 --> 00:25:53.037 So, then they took the same team and had them work on protein folding. 00:25:53.120 --> 00:25:56.757 >> Yeah. And in protein folding, they took a protein whole bunch of protein 00:25:56.840 --> 00:25:59.557 scientists, which I know Can we just think about the genius of that? Like 00:25:59.640 --> 00:26:03.677 nobody would ever connect the game of Go >> Demis. solving all of biology. But But 00:26:03.760 --> 00:26:06.637 Demis Demis had always wanted to work on this. Larry and Sergey were very 00:26:06.720 --> 00:26:10.677 interested in this, and protein folding is the perfect problem because you had 00:26:10.760 --> 00:26:13.797 um you got a constant >> end point. You got a defined end point. 00:26:13.880 --> 00:26:15.437 So, what happens is people get excited 00:26:15.520 --> 00:26:18.717 about AI, but you need to have a 00:26:18.800 --> 00:26:22.637 validation function because these things don't have common sense yet. Yeah. 00:26:22.720 --> 00:26:25.557 Right? You have to show them what it's got. Ultimately, they produced this 00:26:25.640 --> 00:26:27.077 thing called AlphaZero, which 00:26:27.160 --> 00:26:32.797 essentially self-learns. Let's talk about data centers in space. Um I'm in 00:26:32.880 --> 00:26:36.677 favor of it. >> Eight Eight, nine months ago, no one was discussing this. 00:26:36.760 --> 00:26:40.717 >> I mean, all of a sudden >> know why I'm in favor of them? I do, but you [laughter] 00:26:40.800 --> 00:26:42.997 you can mention it as you wish. 00:26:43.080 --> 00:26:46.757 Um but all of a sudden, everybody's talking about them. 00:26:46.840 --> 00:26:52.277 What are your thoughts? Um I'm part owner of a rocket company, and we 00:26:52.360 --> 00:26:55.597 need >> Which I love. I love having you come into the space community. It's 00:26:55.680 --> 00:26:57.117 >> You understand this far, far better than I. 00:26:57.200 --> 00:27:01.077 >> It's It's uh And I've been Rocket science is named that for a reason. Um 00:27:01.160 --> 00:27:03.197 rocket science is really, really hard. 00:27:03.280 --> 00:27:06.117 Um what I've And I don't know that much about rockets, although I certainly know 00:27:06.200 --> 00:27:09.517 how to manage tech people. Um but But I 00:27:09.600 --> 00:27:13.997 I I think that the opportunity is is large and interesting. There are 00:27:14.080 --> 00:27:17.677 challenges. There's an issue of getting heat off of Again, you know this much 00:27:17.760 --> 00:27:21.077 better than I do. Getting heat off of it because you don't have oxygen, and you 00:27:21.160 --> 00:27:24.317 also have radiation issues. Yeah. Those have to get addressed. 00:27:24.400 --> 00:27:28.797 >> But it makes the business plan for every rocket company that's large enough, 00:27:28.880 --> 00:27:29.957 right? The small guys aren't going to 00:27:30.040 --> 00:27:34.077 launch it, but Relativity Space and uh I 00:27:34.160 --> 00:27:37.357 and you know, Blue Origin and SpaceX, I mean, 00:27:37.440 --> 00:27:40.517 I you know, Elon's predictions were, you 00:27:40.600 --> 00:27:44.877 know, I think a launch per hour to populate the constellation he wanted. 00:27:44.960 --> 00:27:49.797 Um but do you think technically we're going to get there? 00:27:49.880 --> 00:27:51.597 Well, the technology is understood. 00:27:51.680 --> 00:27:54.597 What's interesting about Technically for the for the data centers in space for 00:27:54.680 --> 00:27:57.957 heat dissipation Yeah, that That technology is understood. Uh to me, it's 00:27:58.040 --> 00:28:01.637 a business question. Um and the question is what where where 00:28:01.720 --> 00:28:04.517 should the data center be? Should it be in space with these other issues, but it 00:28:04.600 --> 00:28:08.237 has other benefits, including infinite power and so forth, Yeah. versus on the 00:28:08.320 --> 00:28:12.397 ground where you have fiber, and you know, it's not shaking too much. Yeah. I 00:28:12.480 --> 00:28:17.677 mean, the energy argument says space wins by far, and I think the the cooling 00:28:17.760 --> 00:28:21.237 is a very big challenge, but I think it's largely figured out now. 00:28:21.320 --> 00:28:24.917 But then the politics of space You know, one of the turning points in 00:28:25.000 --> 00:28:27.677 AI history also is you getting in front of Congress and saying, hey, we need to 00:28:27.760 --> 00:28:32.877 find almost 100 gigawatts. And at the time, it seemed outrageous. 00:28:32.960 --> 00:28:35.957 And now, of course, it's mainstream, and it looks like, you know, the crazy 00:28:36.040 --> 00:28:39.197 investors are solving the problem. You They're unleashing of the money is 00:28:39.280 --> 00:28:42.477 happening. >> American capitalism. Tech industry, I 00:28:42.560 --> 00:28:44.277 mean, we have another set of problems. 00:28:44.360 --> 00:28:46.757 Well, if the next frontier is space, then but there's no there's no 00:28:46.840 --> 00:28:50.277 investment community in space, but there's also no military 00:28:50.360 --> 00:28:53.797 jurisdiction in space, or maybe there is. I I would have never thought my 00:28:53.880 --> 00:28:57.797 childhood dreams of going to the moon and Mars and would be fueled by data 00:28:57.880 --> 00:29:02.557 centers. Um Never. Well, mine can't carry you at the 00:29:02.640 --> 00:29:04.597 moment, but it can in the future, maybe. 00:29:04.680 --> 00:29:09.597 Yeah. Yeah, all the way. I I read an a Time op-ed piece you wrote 00:29:09.680 --> 00:29:11.357 last night. Um 00:29:11.440 --> 00:29:16.717 China can dominate the physical AI future, or uh What did you Can you 00:29:16.800 --> 00:29:19.117 summarize that for us? It was an important conversation. 00:29:19.200 --> 00:29:24.037 >> the geopolitical context, the And I've said this many times, I'll 00:29:24.120 --> 00:29:27.797 say it again. The American competitor, not enemy, but 00:29:27.880 --> 00:29:31.517 competitor, is China. I I think it's By the way, I think it's 00:29:31.600 --> 00:29:33.397 an important distinction for you to make, so thank you. 00:29:33.480 --> 00:29:39.117 >> Not Not enemy, competitor. Um and how to understand them as a 00:29:39.200 --> 00:29:42.437 competitor. They have lots of money. They're very, 00:29:42.520 --> 00:29:45.317 very smart. Their work ethic is equal or 00:29:45.400 --> 00:29:47.917 stronger than ours, and they dominate 00:29:48.000 --> 00:29:50.757 key industries. And I don't know Right? 00:29:50.840 --> 00:29:54.077 With respect to robotics, we somehow 00:29:54.160 --> 00:29:56.917 decided it was okay for them to dominate 00:29:57.000 --> 00:30:01.317 the electric vehicle industry. This was an error. To be very clear, it's an 00:30:01.400 --> 00:30:05.197 error. Why do you not understand it's an error? Because we don't allow their cars 00:30:05.280 --> 00:30:10.237 in. Spend some time outside of this country in Chinese cars, trust me. 00:30:10.320 --> 00:30:11.797 They are real competitors. They've done 00:30:11.880 --> 00:30:14.997 a great job. As I understand it, 00:30:15.080 --> 00:30:19.797 China is capable of vertical integration and building these gigafactories at a 00:30:19.880 --> 00:30:24.277 scale that we can't for all sorts of reasons. That's got to get addressed. 00:30:24.360 --> 00:30:27.997 So, if you want to compete and I want to compete and win with China and the and 00:30:28.080 --> 00:30:31.557 the and I compete not enemy. I want us to have the same kind of 00:30:31.640 --> 00:30:36.317 system. So, in robotics, it turns out robotics, 00:30:36.400 --> 00:30:39.597 you can understand robots as essentially actuators. These little stepper motors, 00:30:39.680 --> 00:30:44.077 click click click click click click and a brain. Ignoring the appearance and the 00:30:44.160 --> 00:30:46.797 Google, you know, eyes and all that kind of stuff. 00:30:46.880 --> 00:30:49.197 It turns out that the industry of the 00:30:49.280 --> 00:30:51.557 electric vehicle produces the same kind 00:30:51.640 --> 00:30:54.957 of motors and the same kind of systems. 00:30:55.040 --> 00:30:57.717 They have an expertise that we don't. 00:30:57.800 --> 00:31:02.197 My own view is that at least for very low cost, 00:31:02.280 --> 00:31:06.237 China is going to win that. And that was what I was trying to say in that piece. 00:31:06.320 --> 00:31:10.477 And I worry about that. Now, today these are not particularly useful. You know, 00:31:10.560 --> 00:31:13.277 they're they're fun toys. They're a replacement for the dog if you get mad 00:31:13.360 --> 00:31:15.277 at your dog. Sorry, I love I love dogs. 00:31:15.360 --> 00:31:18.597 But you get the idea. So, 00:31:18.680 --> 00:31:21.277 so we we we need to address this. 00:31:21.360 --> 00:31:25.597 But at the moment, it sure looks to me like the robotic hardware 00:31:25.680 --> 00:31:28.277 of China is the winner at the low end. 00:31:28.360 --> 00:31:30.797 I'm not talking about the high end. I'm not talking about the expensive stuff. 00:31:30.880 --> 00:31:32.757 I'm not talking about industrial robots. 00:31:32.840 --> 00:31:34.877 And if you're confused, watch the 00:31:34.960 --> 00:31:39.837 Unitree robot dance with the humans. 00:31:39.920 --> 00:31:41.437 Yeah. That came out about a month ago. 00:31:41.520 --> 00:31:44.637 >> Unitree here in the tech hub and the co-founder will be on stage with us 00:31:44.720 --> 00:31:46.717 later today. Pay Pay attention to them. 00:31:46.800 --> 00:31:48.757 They're they're very very impressive. 00:31:48.840 --> 00:31:51.917 And I spent some time with them last time I was in China. 00:31:52.000 --> 00:31:53.997 And they're one of many. And the way 00:31:54.080 --> 00:31:56.837 China works is that they have brutal 00:31:56.920 --> 00:32:01.357 competition. Brutal brutal It's like unbelievable. I was talking to my 00:32:01.440 --> 00:32:05.677 friend, we teach at Stanford, and he said, you know, in China, we don't have 00:32:05.760 --> 00:32:08.437 the board dinner. We have a 2-hour meeting. We get back to work. And 00:32:08.520 --> 00:32:11.117 there's no preamble. We're not, you know, we don't say hello, how are you? 00:32:11.200 --> 00:32:12.317 How's the family? That kind of stuff. 00:32:12.400 --> 00:32:17.877 We're boom boom. Right? It's just cultural. Yeah. And the 00:32:17.960 --> 00:32:21.237 work the the work ethic, the precision, and 00:32:21.320 --> 00:32:25.277 the scale that is possible in China is a real competitor. 00:32:25.360 --> 00:32:28.237 I don't want to lose the robotic 00:32:28.320 --> 00:32:31.077 revolution in my view the way we lost 00:32:31.160 --> 00:32:35.757 the electric vehicle revolution at least on the low end. Interesting. Cuz I had 00:32:35.840 --> 00:32:39.077 the Chinese model very much has a well-built-out supply chain with many 00:32:39.160 --> 00:32:43.077 vendors in the loop. But we we've been on a worldwide tour of all of the 00:32:43.160 --> 00:32:47.037 humanoid robotics companies. And uh just like coincidence, I guess. But when you 00:32:47.120 --> 00:32:50.157 look at the gigafactory and look at Elon's vertical integration and also 00:32:50.240 --> 00:32:53.517 Brad Adcock, it figures same thing. It's all vertically integrated. Why? Well, 00:32:53.600 --> 00:32:58.357 cuz there's no vendor. Yeah. I I have no choice. I have So, so it appears that to 00:32:58.440 --> 00:33:01.997 get to again, we're in this is the abundance group. This is the abundance 00:33:02.080 --> 00:33:06.117 club. The way you get to abundance is you drive prices down and you get 00:33:06.200 --> 00:33:10.077 vertically integrated. And Elon in our country pioneered that to his credit. 00:33:10.160 --> 00:33:13.797 Yeah. Right? You know, the old joke about Google was we would build anything 00:33:13.880 --> 00:33:18.237 including the buildings. Well, Elon is actually doing that. Yeah. You 00:33:18.320 --> 00:33:20.597 know, he And why? Not because he's 00:33:20.680 --> 00:33:25.917 insane, but because he actually That's how you drive cost down. Yeah. He He 00:33:26.000 --> 00:33:27.517 truly believes, and I'd love to get your 00:33:27.600 --> 00:33:29.637 your take on this. He truly believes 00:33:29.720 --> 00:33:32.957 that the the robot building the robot is 00:33:33.040 --> 00:33:37.157 imminent. And I didn't get it until we toured the gigafactory and I realized 00:33:37.240 --> 00:33:40.637 that almost all of it's automated already. It's just the last piece is the 00:33:40.720 --> 00:33:44.677 human controlling a few knobs. And that, you know, the humanoid robot can 00:33:44.760 --> 00:33:46.717 actually do. >> Let me define the boundary cuz it's 00:33:46.800 --> 00:33:51.437 important. Let's use batteries, for example. Batteries are predictable, 00:33:51.520 --> 00:33:56.237 straightforward manufacturing processes at huge scale. Right? Things like that 00:33:56.320 --> 00:33:59.357 will have gigafactories. One of the questions and I of course 00:33:59.440 --> 00:34:04.117 used LLMs to do my deep research as a new person in the rocket company was how 00:34:04.200 --> 00:34:08.517 much of the human labor to build a rocket could be replaced by robots. 00:34:08.600 --> 00:34:13.557 The current limit, which of course will change, is in our company, we have these 00:34:13.640 --> 00:34:15.117 extraordinarily 00:34:15.200 --> 00:34:18.917 talented essentially assembly people. 00:34:19.000 --> 00:34:22.637 And they're they're they're more than welders and they're more than, you know, 00:34:22.720 --> 00:34:28.277 mechanics. They understand precisely how the little the tubes and so forth and so 00:34:28.360 --> 00:34:30.917 on go together and they use precise 00:34:31.000 --> 00:34:33.637 tolerances. That kind of assembly is 00:34:33.720 --> 00:34:39.397 beyond current robots. I'm sure it will eventually show up, but 00:34:39.480 --> 00:34:42.477 not for a long time. >> People don't realize the majority cost 00:34:42.560 --> 00:34:46.397 of a rocket is labor. Exactly. It's not material. You'll listen to this person. 00:34:46.480 --> 00:34:49.717 >> when they get inside the rocket, they understand what they're doing and they 00:34:49.800 --> 00:34:53.677 see what's wrong and they use human judgment. We don't have those systems 00:34:53.760 --> 00:34:57.517 yet. Yeah. Now, perhaps we will in the future or perhaps this will be one of 00:34:57.600 --> 00:34:59.637 the last things to go. 00:34:59.720 --> 00:35:02.557 Right? But at the moment, high-skilled 00:35:02.640 --> 00:35:05.637 mechanical labor is very important. 00:35:05.720 --> 00:35:11.077 Low-skilled labor of any kind gets swept up. Well, so both of those, there's AI 00:35:11.160 --> 00:35:14.237 self-improvement and then there's robotics building robots building robots 00:35:14.320 --> 00:35:16.237 self-improvement. Both of those loops. 00:35:16.320 --> 00:35:19.957 And I I we we talk a lot about closed loops being 00:35:20.040 --> 00:35:21.437 If I can interrupt you. Yeah, please. 00:35:21.520 --> 00:35:24.357 The term I like to use is learning loops. Learning loops. In a business, 00:35:24.440 --> 00:35:27.437 try to figure out all the different learning loops and then try to 00:35:27.520 --> 00:35:30.677 accelerate the learning. Fastest learner wins. 00:35:30.760 --> 00:35:33.037 Sorry. Well, I'm going to lead the witness here a little bit. But if you if 00:35:33.120 --> 00:35:37.157 you asked Daniela Rus over at CSAIL a year ago, Erik Brynjolfsson at Stanford 00:35:37.240 --> 00:35:38.437 a year ago, 00:35:38.520 --> 00:35:40.797 do we need one more big breakthrough in 00:35:40.880 --> 00:35:44.437 AI core science or will scaling what 00:35:44.520 --> 00:35:46.277 we've already got lead to 00:35:46.360 --> 00:35:48.797 self-improvement and then that will be 00:35:48.880 --> 00:35:51.957 all we need to get to AGI 00:35:52.040 --> 00:35:55.957 >> and then self-improvement. That that I spent the last week doing RSI reviews, 00:35:56.040 --> 00:35:58.157 recursive self-improvement 00:35:58.240 --> 00:36:02.517 reviews. The scientists do not agree on 00:36:02.600 --> 00:36:06.717 the exact approach to work yet. So, I think it's too early to know that 00:36:06.800 --> 00:36:09.637 question. There's evidence that it will work. 00:36:09.720 --> 00:36:12.077 There are tests in the lab that show it. 00:36:12.160 --> 00:36:15.797 But they show it in limited cases that are kind of demos. 00:36:15.880 --> 00:36:17.677 Right? Real recursive self-improvement 00:36:17.760 --> 00:36:22.997 is the following. Start now, learn everything, discover things, and tell me 00:36:23.080 --> 00:36:24.597 what you learned. Yeah. 00:36:24.680 --> 00:36:27.837 That query doesn't work yet. 00:36:27.920 --> 00:36:32.037 We're seeing all of the frontier labs sort of constantly leapfrog each other, 00:36:32.120 --> 00:36:34.397 right? I mean, literally every week it's the new model. 00:36:34.480 --> 00:36:36.797 >> Unbelievable. And it's it's extraordinary. 00:36:36.880 --> 00:36:38.717 And do you imagine they're all 00:36:38.800 --> 00:36:44.680 converging towards the same endpoint or is anyone going to pull ahead? 00:36:45.200 --> 00:36:46.757 So, if you go back to this question of 00:36:46.840 --> 00:36:49.477 capital, how many how much room is there 00:36:49.560 --> 00:36:54.277 in the world for these companies? How many can there be? 00:36:54.360 --> 00:36:56.317 I'm going to make some numbers up. 00:36:56.400 --> 00:37:00.597 And these are made up. I think there's at least 10 in the world 00:37:00.680 --> 00:37:04.157 at this scale. I think there'll be a few in in China. I 00:37:04.240 --> 00:37:08.437 think the majority will be in the United States, the usual suspects most likely. 00:37:08.520 --> 00:37:12.517 I think there'll be a They They might be one or two in Europe. Mhm. Depending 00:37:12.600 --> 00:37:14.517 their electricity costs are a problem. 00:37:14.600 --> 00:37:16.997 There might be one in India, right? 00:37:17.080 --> 00:37:20.997 There's not going to be one in Russia because of the the war and so forth and 00:37:21.080 --> 00:37:22.117 so on. 00:37:22.200 --> 00:37:26.277 So, can the world accommodate 10? Yes. 00:37:26.360 --> 00:37:30.037 Do they track together? I don't think so. 00:37:30.120 --> 00:37:33.397 One of the key things to understand about China is China's approach, which 00:37:33.480 --> 00:37:36.637 has produced DCV4, Quinn, Kimmy 2, Kimmy 00:37:36.720 --> 00:37:41.117 version 3, etc. and more coming, is it's all open 00:37:41.200 --> 00:37:45.677 source open weights. They've managed to do this with our chip 00:37:45.760 --> 00:37:49.757 limitations against them, which annoy them no end. Shows you how clever they 00:37:49.840 --> 00:37:54.517 are. They're also the Chinese strategy is a bit different. It's less central 00:37:54.600 --> 00:37:58.117 computing and much more edge computing, which has to do with enveloping their 00:37:58.200 --> 00:38:02.917 Chinese customers with AI around them all all the time. We're much more AGI 00:38:03.000 --> 00:38:06.117 ASI centered, which is fine. 00:38:06.200 --> 00:38:09.357 So, the the patterns are diverging. 00:38:09.440 --> 00:38:14.277 Within the companies, it's it's it's a jumble now. But 00:38:14.360 --> 00:38:18.037 fundamentally, Microsoft and Google have these large cash flow streams from 00:38:18.120 --> 00:38:20.677 enterprise, so they can fund that. Yeah. 00:38:20.760 --> 00:38:24.437 Anthropic has done a fantastic job of raising money from those other companies 00:38:24.520 --> 00:38:26.157 to and they use, as you know, Google 00:38:26.240 --> 00:38:29.237 TPUs. And they've become the sort of 00:38:29.320 --> 00:38:33.797 leading player in this sort of Claude API within the enterprise agent 00:38:33.880 --> 00:38:38.917 system. And and OpenAI is now shifting a bit of its strategy to include the the new 00:38:39.000 --> 00:38:42.397 things it's doing. I don't think we can predict. 00:38:42.480 --> 00:38:46.597 But the key thing to understand is that they need so much money. 00:38:46.680 --> 00:38:50.397 Right? I mean, you look at what Sam is trying to raise. They need so much money 00:38:50.480 --> 00:38:54.357 that they're forced into these situations where they have to win those 00:38:54.440 --> 00:38:55.677 battles. And they're busy winning them. 00:38:55.760 --> 00:38:59.877 I mean, this is all good. I think it's the it's We In a year, we'll know better 00:38:59.960 --> 00:39:03.517 the answer to your question. I two questions I want to close this out with 00:39:03.600 --> 00:39:05.797 that I think are important. Um 00:39:05.880 --> 00:39:08.117 You made a a statement a couple of 00:39:08.200 --> 00:39:11.237 times, once in our podcast, once uh 00:39:11.320 --> 00:39:13.157 elsewhere that 00:39:13.240 --> 00:39:16.237 regarding AI safety, the world may need 00:39:16.320 --> 00:39:19.517 to have a modest Chernobyl-like death 00:39:19.600 --> 00:39:23.397 event in order for us to wake up. 00:39:23.480 --> 00:39:26.037 Uh do you still believe that's the case? 00:39:26.120 --> 00:39:27.677 Yeah, and by the way, I'm not endorsing 00:39:27.760 --> 00:39:33.760 that. I'm I'm doing it as a descriptive, not as a as a proscriptive. 00:39:35.080 --> 00:39:37.437 What are the real dangers of this? There 00:39:37.520 --> 00:39:40.437 are biological dangers. I mean, there's 00:39:40.520 --> 00:39:44.557 obviously the dangers of of kids and democracies and so forth. But 00:39:44.640 --> 00:39:46.957 like let's think about like a biological 00:39:47.040 --> 00:39:49.917 attack, a nuclear attack that's spawned 00:39:50.000 --> 00:39:52.117 by these things. 00:39:52.200 --> 00:39:55.757 It may take such a tragedy, hopefully a 00:39:55.840 --> 00:39:59.357 small one, to awaken the world to understand that 00:39:59.440 --> 00:40:03.517 these things are they do have negative power. 00:40:03.600 --> 00:40:06.877 And so I can imagine, I'm making this up, that there's some bad thing that 00:40:06.960 --> 00:40:10.277 happened and then all of the leaders, 00:40:10.360 --> 00:40:14.797 China, the US, we all have a meeting and we basically say like what are we 00:40:14.880 --> 00:40:18.597 going to do? You know, we're in brutal competition, we hate 00:40:18.680 --> 00:40:20.957 each other, you know, I don't like you, you know, you don't speak the same 00:40:21.040 --> 00:40:22.877 language, blah blah blah, but we are all 00:40:22.960 --> 00:40:26.237 in it together, right? Over this issue. 00:40:26.320 --> 00:40:30.920 My sense is that will happen, but I don't know when. 00:40:31.320 --> 00:40:34.997 We had we had a congressperson on this stage last year and one of the crowd 00:40:35.080 --> 00:40:38.717 asked, how much time do you spend talking about AI in Congress? 00:40:38.800 --> 00:40:42.557 And he said, well, it's definitely way less than 1%. Yeah. And so without that 00:40:42.640 --> 00:40:45.997 wake-up call, I don't see how you have >> I mean governments, I spend lots of time 00:40:46.080 --> 00:40:49.037 with governments. Governments are super busy, right? And they're and they're 00:40:49.120 --> 00:40:52.717 driven by political things, they're driven by by 00:40:52.800 --> 00:40:56.477 in at least in democracies by by political sentiment. 00:40:56.560 --> 00:40:59.237 I'd like us as a nation to focus on the 00:40:59.320 --> 00:41:02.517 following. I want to win the AI race. I 00:41:02.600 --> 00:41:06.517 want us to do whatever it takes to do that. This government is doing a very 00:41:06.600 --> 00:41:10.437 good job of making energy permitting more accessible. 00:41:10.520 --> 00:41:14.877 The rate at which data centers are getting built is now accelerated, 00:41:14.960 --> 00:41:19.557 solving the grid problems. I also want lots of immigrants in our country 00:41:19.640 --> 00:41:23.437 because those immigrants, at least the high stakes high skills immigration, is 00:41:23.520 --> 00:41:25.877 what we need because we need the the 00:41:25.960 --> 00:41:28.157 smartest people in the world on our side 00:41:28.240 --> 00:41:30.797 to build these systems. This is a unique 00:41:30.880 --> 00:41:36.940 moment in history, right? >> [applause] 00:41:37.600 --> 00:41:40.317 >> I would take us home on a positive note. 00:41:40.400 --> 00:41:43.477 So, you know, you said we're going to get to 00:41:43.560 --> 00:41:48.597 ASI at some point, whether it's 2 years out, 5 years out, some place in this 00:41:48.680 --> 00:41:52.637 next decade. So, the question is, what steps can we 00:41:52.720 --> 00:41:56.917 take to steer artificial superintelligence towards 00:41:57.000 --> 00:41:58.237 abundance, 00:41:58.320 --> 00:42:02.437 towards uplifting and in alignment with 00:42:02.520 --> 00:42:05.717 humanity? You know, to make this abundance thesis 00:42:05.800 --> 00:42:09.997 materialize, what's your advice to us, 00:42:10.080 --> 00:42:12.637 companies, governments? 00:42:12.720 --> 00:42:15.037 There's an over-reliance in our society 00:42:15.120 --> 00:42:17.557 on people like me 00:42:17.640 --> 00:42:20.477 to work on this. 00:42:20.560 --> 00:42:23.877 Why don't we have the smartest people in 00:42:23.960 --> 00:42:26.077 politics, history, 00:42:26.160 --> 00:42:28.957 human psychology, governance, ethics 00:42:29.040 --> 00:42:33.277 working together to make sure this stuff stays in human values and human 00:42:33.360 --> 00:42:37.597 alignment? I want the system that we build in 00:42:37.680 --> 00:42:42.037 America to reflect American values. The values of freedom and freedom of speech 00:42:42.120 --> 00:42:45.517 freedom of association, all those things you learned in college and excuse me, in 00:42:45.600 --> 00:42:47.477 elementary school and and high school. 00:42:47.560 --> 00:42:49.597 They're still important to our nation. 00:42:49.680 --> 00:42:52.997 They're the enablers for the next generation of our children and 00:42:53.080 --> 00:42:56.437 grandchildren. I I desperately want that 00:42:56.520 --> 00:43:00.157 and I don't want America to ever get on the wrong side of that battle. 00:43:00.240 --> 00:43:02.597 There's lots of people working on this. 00:43:02.680 --> 00:43:06.117 Lots of people understand the technical details. I happen to run an informal 00:43:06.200 --> 00:43:08.317 group that discusses this every week. 00:43:08.400 --> 00:43:12.677 So, it's possible, but it requires political 00:43:12.760 --> 00:43:15.397 will and it requires an understanding that 00:43:15.480 --> 00:43:19.917 this can be done without screwing up the genius of America, right? In other 00:43:20.000 --> 00:43:24.317 words, I'm not suggesting slowing anything down. I'm you said it so well, 00:43:24.400 --> 00:43:28.517 shaping it. Making sure we don't cross lines. Like I 00:43:28.600 --> 00:43:32.597 already mentioned the teenage sorry, the underage kids problem. That's a line we 00:43:32.680 --> 00:43:37.520 can't cross. We got to solve that problem. There are others.