WEBVTT 00:00:35.840 --> 00:00:37.997 Please welcome Andrew Ross Sorkin and 00:00:38.080 --> 00:00:40.317 his guest, CEO and co-founder of 00:00:40.400 --> 00:00:44.197 Anthropic, Dario Amodei. 00:00:44.280 --> 00:00:47.757 Good afternoon, everybody. I hope you guys all had a great lunch. 00:00:47.840 --> 00:00:49.997 We have a huge afternoon starting with 00:00:50.080 --> 00:00:55.477 Dario Amodei here. He is one of the most consequential people here in the world 00:00:55.560 --> 00:00:59.357 of artificial intelligence. He's the co-founder and CEO of Anthropic, of 00:00:59.440 --> 00:01:02.397 course, known for its Claude model. Uh it's one of the fastest-growing 00:01:02.480 --> 00:01:03.797 technology companies in history and 00:01:03.880 --> 00:01:07.517 uniquely backed now by all three giants, 00:01:07.600 --> 00:01:12.277 uh tech giants, Amazon, Microsoft, and Google. That's new, at least one of them. 00:01:12.360 --> 00:01:16.797 Uh and by the way, he has been at this uh really longer than most. Uh he worked 00:01:16.880 --> 00:01:18.797 at Baidu, then Google, was an early 00:01:18.880 --> 00:01:20.757 employee at OpenAI where he led the 00:01:20.840 --> 00:01:25.037 development of uh ChatGPT-2 and 3. Uh 00:01:25.120 --> 00:01:28.037 and the reason that we wanted to speak with him this year more than anything 00:01:28.120 --> 00:01:32.197 else is because he has singularly been perhaps the most outspoken and candid 00:01:32.280 --> 00:01:36.557 person about AI when it comes to the way he's been thinking about jobs and job 00:01:36.640 --> 00:01:38.797 losses and selling chips to China and 00:01:38.880 --> 00:01:43.597 politics in our country and where all of this goes. So, welcome to you. Thank you 00:01:43.680 --> 00:01:46.237 for being here. >> Thank you for having me. Um we got a lot 00:01:46.320 --> 00:01:50.957 to talk about, um including, by the way, are we in an AI bubble? But I promise 00:01:51.040 --> 00:01:55.917 you we will get there. I I I'll start here, though, um which is 00:01:56.000 --> 00:01:56.997 I mentioned you were a research 00:01:57.080 --> 00:02:00.677 scientist uh back at Baidu uh 2014. 00:02:00.760 --> 00:02:03.237 And if I had sat with you then 00:02:03.320 --> 00:02:05.837 and said, "We're going to sit together 00:02:05.920 --> 00:02:08.597 in 2025 00:02:08.680 --> 00:02:13.517 talking about AI." You would have told me what? What would have been your 00:02:13.600 --> 00:02:17.597 expectation for what would have happened? So, I'll tell you what I am 00:02:17.680 --> 00:02:19.197 surprised by and what what and what I'm 00:02:19.280 --> 00:02:23.077 not. Um I'm not surprised by the 00:02:23.160 --> 00:02:26.357 economic impacts of the technology, the 00:02:26.440 --> 00:02:30.837 the value that it's creating, you know, the fact that, you know, I walk by any 00:02:30.920 --> 00:02:35.517 billboard in New York and, you know, it's it's it's kind of everything about AI. 00:02:35.600 --> 00:02:38.397 >> that this would this would be this would be real by now. 00:02:38.480 --> 00:02:41.957 In in some form that this would be real, that it would be central to the economy, 00:02:42.040 --> 00:02:45.037 that it would be central to national security. That it would be central to 00:02:45.120 --> 00:02:48.157 scientific research. I you know, I I I I 00:02:48.240 --> 00:02:52.117 don't think I imagined that I would be leading one of the companies in the 00:02:52.200 --> 00:02:55.357 space, right? I think that I think that would have been, 00:02:55.440 --> 00:02:58.637 you know, very surprising to me. I didn't think of that as as kind of as 00:02:58.720 --> 00:03:02.837 kind of my role at the time. And the exact way in which things happened, all 00:03:02.920 --> 00:03:07.317 of the, you know, all of the kind of strange lingo we've developed around 00:03:07.400 --> 00:03:12.277 language models, all of the kind of financialization of it, you know, if you 00:03:12.360 --> 00:03:16.317 think about it, if you think about the implications of the models becoming as 00:03:16.400 --> 00:03:20.477 smart and as powerful as they are and scaling in the way that they are, in the 00:03:20.560 --> 00:03:24.877 way that me and some of my colleagues had predicted, it all makes sense. But I 00:03:24.960 --> 00:03:28.277 I don't think I would have derived it from first principles. Okay, well, then 00:03:28.360 --> 00:03:31.797 let's go straight to the question I said I'd ask at the beginning. Um 00:03:31.880 --> 00:03:34.837 because maybe this is the place thinking about where this goes and the fact that 00:03:34.920 --> 00:03:37.917 I didn't think you would say, by the way, that you thought that this is where 00:03:38.000 --> 00:03:41.557 we would be in in 2025 because I think even people back then 00:03:41.640 --> 00:03:45.437 thought this would be a much longer road. But if you're right, 00:03:45.520 --> 00:03:49.077 do you look at the amount of economic uh muscle that's being put into this 00:03:49.160 --> 00:03:53.157 industry right now? I mean, it really does represent potentially almost all of 00:03:53.240 --> 00:03:55.997 the growth in the United States GDP right now, literally. 00:03:56.080 --> 00:03:59.637 >> Yes. That we are in some form of a bubble. 00:03:59.720 --> 00:04:02.277 Are we overspending? Does the math of 00:04:02.360 --> 00:04:05.677 this make sense? So, this is really 00:04:05.760 --> 00:04:10.317 complicated and I want to separate out the technological side of it from the 00:04:10.400 --> 00:04:14.997 economic side of it. On the technological side of it, I feel really 00:04:15.080 --> 00:04:18.477 solid. I think I'm one of the most bullish people around and I think it 00:04:18.560 --> 00:04:21.637 pencils out. On the economic side, you 00:04:21.720 --> 00:04:26.637 know, I I I have my concerns where even if the technology is is, you know, 00:04:26.720 --> 00:04:30.437 really powerful and fulfills all its promises, I think there may be players 00:04:30.520 --> 00:04:34.357 in the ecosystem who, if they just make a timing error, if they just get it off 00:04:34.440 --> 00:04:37.237 by a little bit, bad things could happen. So, let me go through both of 00:04:37.320 --> 00:04:40.477 them. On the technological side, the the 00:04:40.560 --> 00:04:45.877 reason that I'm not in honestly, by the pure technology, not that surprised is 00:04:45.960 --> 00:04:49.757 myself and some of the people who eventually became my my my co-founders, 00:04:49.840 --> 00:04:54.277 we were the first to document the scaling laws of AI, which is you put 00:04:54.360 --> 00:04:56.757 more compute, you put more data into AI. 00:04:56.840 --> 00:05:00.757 With small modifications, we've seen these things like reasoning models and 00:05:00.840 --> 00:05:02.797 test time compute. They're all tiny 00:05:02.880 --> 00:05:05.037 little tweaks. And I've been watching 00:05:05.120 --> 00:05:08.077 that trend for the last 12 years or so 00:05:08.160 --> 00:05:09.957 since I joined the field. And the thing 00:05:10.040 --> 00:05:13.117 that is most striking about all of it is 00:05:13.200 --> 00:05:17.877 as you train these models in this very simple way, you know, with a few simple 00:05:17.960 --> 00:05:21.517 modifications, they get better and better at every task under the sun. They 00:05:21.600 --> 00:05:25.277 get better at coding. They get better at doing science. They get better at 00:05:25.360 --> 00:05:27.117 biomedicine. They get better at the law. 00:05:27.200 --> 00:05:31.077 They get better at finance. They get better at at, you know, materials and 00:05:31.160 --> 00:05:35.077 manufacturing. And and that's just that's just a listing of all the sources 00:05:35.160 --> 00:05:37.557 of of of of value of value in our 00:05:37.640 --> 00:05:40.077 economy. If I just take Anthropic 00:05:40.160 --> 00:05:42.997 itself, which, because we work so much 00:05:43.080 --> 00:05:47.197 in the enterprise side, I think we're a good barometer, maybe a purer barometer 00:05:47.280 --> 00:05:50.717 than the others which kind of filter through consumers, which kind of have 00:05:50.800 --> 00:05:53.037 their habits and their use cases. We 00:05:53.120 --> 00:05:55.557 look at our revenue. It's grown 10x a 00:05:55.640 --> 00:05:58.597 year every year for the last 3 years. 0 00:05:58.680 --> 00:06:01.197 to 100 million 2023, 100 million to 00:06:01.280 --> 00:06:06.397 billion 2024, 1 billion to it's going to end somewhere between 8 and 10 at at the 00:06:06.480 --> 00:06:10.957 end of this year. Will it continue? I don't know, but the technology is 00:06:11.040 --> 00:06:15.277 driving there and the economic value is coming with it. I it will, you know, 00:06:15.360 --> 00:06:18.997 that that trend is going to slow down for sure, but it's still going to be 00:06:19.080 --> 00:06:21.317 really fast. And so, I have this 00:06:21.400 --> 00:06:25.357 confidence that the the ult- eventually 00:06:25.440 --> 00:06:28.037 the economic value is the eventually the 00:06:28.120 --> 00:06:32.877 economic value is going to be there. Um When you but let's just go to this 00:06:32.960 --> 00:06:36.557 because there are companies that are spending 100 billion dollars a year 00:06:36.640 --> 00:06:38.917 more. You're going to be spending 50. 00:06:39.000 --> 00:06:42.397 You look at what Sam Altman, who was here last year, plans to be spending. 00:06:42.480 --> 00:06:44.237 These are extraordinary numbers and this 00:06:44.320 --> 00:06:47.877 is all a bet, a big bet, that this is 00:06:47.960 --> 00:06:51.997 going to scale in this way. And and my question is, is there a real way to 00:06:52.080 --> 00:06:56.277 pencil this out or is this more of a 00:06:56.360 --> 00:06:58.837 a gut feeling at this point? So, let me 00:06:58.920 --> 00:07:00.517 let Yeah, so that really gets to the 00:07:00.600 --> 00:07:03.517 second part of it. And and I I I I will 00:07:03.600 --> 00:07:06.597 describe as transparently as I can, I 00:07:06.680 --> 00:07:08.677 think there's a real dilemma 00:07:08.760 --> 00:07:13.917 deriving from uncertainty in how quickly the economic value is going to grow and 00:07:14.000 --> 00:07:17.837 the lag times on building the data centers that that drives it. So, I think 00:07:17.920 --> 00:07:21.437 there's genuine uncertainty. There's genuine dilemma, which we as a company 00:07:21.520 --> 00:07:24.237 try to manage as responsibly as we can. 00:07:24.320 --> 00:07:28.437 And then I think there are some players who, you know, who who are YOLOing, who 00:07:28.520 --> 00:07:31.997 who pull pull the risk dial too far and I'm very concerned. 00:07:32.080 --> 00:07:35.197 >> Who is YOLOing? >> So, I That's a question I'm not going to 00:07:35.280 --> 00:07:36.237 answer. 00:07:36.320 --> 00:07:40.877 Um uh uh So, on the first one, 00:07:40.960 --> 00:07:43.357 put yourself in the position of of Anthropic. 00:07:43.440 --> 00:07:47.117 >> yourself >> Put put yourself in in the position of 00:07:47.200 --> 00:07:50.397 of Anthropic. Put yourself in my position. 00:07:50.480 --> 00:07:54.917 You you you've seen this revenue curve that goes up 10x a year for 3 years. 00:07:55.000 --> 00:07:57.957 You're like, "Okay, what's going to happen next year?" If I'm really dumb 00:07:58.040 --> 00:08:01.877 and I extrapolate the pattern 10 to 100 billion. I don't believe that, just to 00:08:01.960 --> 00:08:04.277 be clear. I don't I don't believe that at all. Even though it's happened in the 00:08:04.360 --> 00:08:08.237 last 3 years, just at this scale, I don't believe it. But that's one of the 00:08:08.320 --> 00:08:12.757 outer bounds of, you know, the outer limits of possibility. If I go in and 00:08:12.840 --> 00:08:16.077 I'm like, "This enterprise and that enterprise and this use case and this is 00:08:16.160 --> 00:08:20.157 our go-to-market motion." If I try and do it, you know, bottom-up, then, you 00:08:20.240 --> 00:08:24.957 know, maybe it's maybe it's 20 or 30 or something like that. So, there is well, 00:08:25.040 --> 00:08:26.877 what I've been calling internally this 00:08:26.960 --> 00:08:30.037 cone of uncertainty where I don't know 00:08:30.120 --> 00:08:34.237 if a year from now it's going to be 20 billion or, you know, it's it's going to 00:08:34.320 --> 00:08:36.517 be 50 or or like, you know, it's it's 00:08:36.600 --> 00:08:39.557 it's very uncertain. I try to plan in a 00:08:39.640 --> 00:08:41.357 conservative way, so I plan for the 00:08:41.440 --> 00:08:44.437 lower side of it. But but that is very 00:08:44.520 --> 00:08:47.037 disconcerting and you add to that the 00:08:47.120 --> 00:08:51.557 idea that building the data centers has a long lag 00:08:51.640 --> 00:08:53.677 time. It's like a year or two. So, I 00:08:53.760 --> 00:08:55.997 have to decide now, literally now, or in 00:08:56.080 --> 00:08:58.717 some cases a few months ago, how how how 00:08:58.800 --> 00:09:01.797 much compute I need to buy in you know, 00:09:01.880 --> 00:09:04.397 early 2024 to serve the models in early 00:09:04.480 --> 00:09:07.197 2027 when I get to that revenue amount. 00:09:07.280 --> 00:09:12.157 And there's two couple dangers. One is that if I if I don't buy enough compute, 00:09:12.240 --> 00:09:15.157 I won't be able to serve all the customers I want. I'll have to turn them 00:09:15.240 --> 00:09:19.237 away and send them to to to my competitors. If I buy too much compute, 00:09:19.320 --> 00:09:23.157 of course, I might not get enough revenue to pay for that compute. And and 00:09:23.240 --> 00:09:26.397 and, you know, and and, you know, in the extreme case, there's kind of the risk 00:09:26.480 --> 00:09:29.077 of going bankrupt. And how how much 00:09:29.160 --> 00:09:33.717 buffer there is in that in that cone, um is basically determined by my margins. 00:09:33.800 --> 00:09:36.957 If I have 80% margins, I can buy 20 billion dollars of compute and it could 00:09:37.040 --> 00:09:39.237 serve a 100 billion dollar a 100 billion 00:09:39.320 --> 00:09:41.437 dollars of revenue. But because the cone 00:09:41.520 --> 00:09:44.637 is so wide, it's hard to avoid, you 00:09:44.720 --> 00:09:46.797 know, making a mistake on on 00:09:46.880 --> 00:09:49.437 on on one side on one side or the other. 00:09:49.520 --> 00:09:52.877 Now, we've been a relatively responsible 00:09:52.960 --> 00:09:57.957 company, um and I think because we focus on enterprise, I think we have a better 00:09:58.040 --> 00:10:01.117 business model. I think we have better margins. I think we're being responsible 00:10:01.200 --> 00:10:05.157 about it. But again, let's say you have a different business model. Let's say 00:10:05.240 --> 00:10:09.477 you have a consumer business model. You know, your your your your your your kind 00:10:09.560 --> 00:10:14.677 of the source of your revenue isn't as good. Your margins aren't certain. And 00:10:14.760 --> 00:10:18.597 let's say you're a person who just kind of like constitutionally just wants to 00:10:18.680 --> 00:10:21.157 YOLO things or just likes big numbers. 00:10:21.240 --> 00:10:25.397 Um then then you may turn that dial pretty far. And so I think there's a 00:10:25.480 --> 00:10:29.237 real underlying risk. Whenever there's uncertainty, there's a risk of 00:10:29.320 --> 00:10:31.997 overextension. We all face it. I face 00:10:32.080 --> 00:10:34.037 it. All the other companies face it. 00:10:34.120 --> 00:10:36.397 There's there's an inherent risk when 00:10:36.480 --> 00:10:38.677 when the timing of the economic value is 00:10:38.760 --> 00:10:43.997 is uncertain. There's inherent risk of of under-reacting or overextension. And 00:10:44.080 --> 00:10:47.997 because the companies are competing with each other and frankly we genuinely need 00:10:48.080 --> 00:10:52.517 to compete with you know our authoritarian adversaries. Um 00:10:52.600 --> 00:10:56.197 there there's there's kind of a lot of pressure to push things. So I think 00:10:56.280 --> 00:10:58.117 there's some amount of irreducible risk 00:10:58.200 --> 00:11:01.237 here and I absolutely don't want to deny 00:11:01.320 --> 00:11:05.237 this. But at the same time as that I think there are some players who are not 00:11:05.320 --> 00:11:08.597 managing that risk well, who are taking unwise risks. 00:11:08.680 --> 00:11:11.917 >> All right, let me let me ask you about that with maybe you'll mention who that 00:11:12.000 --> 00:11:14.557 is. I think we all know who that is. 00:11:14.640 --> 00:11:18.037 Um You have said that you're going to break even. 00:11:18.120 --> 00:11:19.917 Uh this is privately at least to your 00:11:20.000 --> 00:11:22.877 investors by 2028 even with the spending 00:11:22.960 --> 00:11:25.277 plans, I think. Uh Sam Altman who you 00:11:25.360 --> 00:11:30.117 worked with and for says that he's going to do it by 2030. 00:11:30.200 --> 00:11:33.117 Uh I use his math, not yours. He would have 00:11:33.200 --> 00:11:38.877 to go from a $74 billion loss in the course of 2 years to be profitable 2 00:11:38.960 --> 00:11:43.677 years later. Does that make sense to you? So look, I don't I don't know the internal 00:11:43.760 --> 00:11:47.437 financials of any other company. I can't I can't say anything about what the 00:11:47.520 --> 00:11:50.397 economics of any other of of of of of 00:11:50.480 --> 00:11:52.557 any other company is. I will just go 00:11:52.640 --> 00:11:55.717 back to our own calculation and the cone 00:11:55.800 --> 00:11:59.837 of uncertainty where where where where where where we basically say we want to 00:11:59.920 --> 00:12:04.557 buy enough compute that we're confident, you know, even in the 10th percentile, 00:12:04.640 --> 00:12:07.637 you know, scenario like might be in a bad position, but like we think we can 00:12:07.720 --> 00:12:10.997 pay for it. There's there's some end of the curve where you know, things go so 00:12:11.080 --> 00:12:14.917 badly that you know, we can't pay that that that there's all there's always a 00:12:15.000 --> 00:12:19.917 tail risk. There's not zero, but we're trying to manage that risk well while 00:12:20.000 --> 00:12:23.557 also buying an amount an amount of compute that allows us to be competitive 00:12:23.640 --> 00:12:26.797 with the other players. We're very efficient training. We're very efficient 00:12:26.880 --> 00:12:30.717 in inference. We have good margins. I think I you know, I think I think we can 00:12:30.800 --> 00:12:35.157 manage it. I think the odds are on our side. What are we supposed to think of 00:12:35.240 --> 00:12:38.997 what I think people now describe as circular deals. Back in the day we 00:12:39.080 --> 00:12:43.277 called this vendor financing. But in this context, you have a situation where 00:12:43.360 --> 00:12:47.557 Nvidia in particular, but others as well, effectively have 00:12:47.640 --> 00:12:53.077 been taking stakes in companies and invariably those companies are using 00:12:53.160 --> 00:12:56.157 some of that money one way or the other considering money's fungible and going 00:12:56.240 --> 00:12:59.157 to buy Nvidia chips. Yes. So I mean, 00:12:59.240 --> 00:13:03.437 we've done some of these deals, not not at the same scale as as as some other 00:13:03.520 --> 00:13:07.277 players. But we've done some of these deals and I 00:13:07.360 --> 00:13:09.877 can just I can just I can just I can just I can just I can just kind of walk 00:13:09.960 --> 00:13:13.077 you through not a specific deal cuz I'm not going to go into the details, but 00:13:13.160 --> 00:13:17.077 but but kind of like a stylized what these deals often look like and kind of 00:13:17.160 --> 00:13:21.597 why they can make sense. So if you want to buy a gigawatt of compute, right? 00:13:21.680 --> 00:13:23.797 That buying the chips and building the 00:13:23.880 --> 00:13:26.397 chips, building everything, that costs, 00:13:26.480 --> 00:13:28.837 you know, roughly let's say $50 billion 00:13:28.920 --> 00:13:31.517 of of capital expense to to kind of to 00:13:31.600 --> 00:13:35.997 kind of fund that. And you can think of that as useful lifetime as people argue 00:13:36.080 --> 00:13:40.477 about it, but maybe it's 5 years. So that's 10 10 billion dollars for basic 00:13:40.560 --> 00:13:44.357 basically for 5 years. And and so if you're a company, you know, you're 00:13:44.440 --> 00:13:47.357 you're you're you're a company that's making, you know, 8 10 billion dollars 00:13:47.440 --> 00:13:48.877 of revenue. You think that's growing. 00:13:48.960 --> 00:13:50.437 You don't know how fast it's growing. 00:13:50.520 --> 00:13:53.517 You have to make the decision right now and you don't have $50 billion. You 00:13:53.600 --> 00:13:57.597 don't have $50 billion on you. So you know, a thing you can do, a deal you can 00:13:57.680 --> 00:14:01.237 make with a large player who has an incentive to to to to to do this because 00:14:01.320 --> 00:14:04.637 they're the one selling the chips or providing the cloud is they'll say, 00:14:04.720 --> 00:14:08.637 "Okay, you know, I'll give you I don't know, 20% of it. I'll invest $10 00:14:08.720 --> 00:14:12.237 billion." So that lets you pay for the first year and then for and then for the 00:14:12.320 --> 00:14:16.037 other years you can kind of pay as you go because I know you don't have $50 00:14:16.120 --> 00:14:20.157 billion now, but but you know, looking at how things are are are are are 00:14:20.240 --> 00:14:24.237 growing, that isn't a crazy bet. We're already almost we're already almost at 00:14:24.320 --> 00:14:28.797 at at we're already almost at the $10 billion of revenue. So it it kind of it 00:14:28.880 --> 00:14:31.917 you know, it takes a year to build a data center. It's financed for a year. 00:14:32.000 --> 00:14:34.357 So you're you're you know, you're basically saying I need to get $10 00:14:34.440 --> 00:14:37.357 billion of of revenue per year 2 years 00:14:37.440 --> 00:14:41.717 from now. Um so I don't think there's anything wrong with that. One player has 00:14:41.800 --> 00:14:45.197 capital and has an interest because they're selling the because they're 00:14:45.280 --> 00:14:49.477 selling the you know, they're selling the chips and the other player is pretty 00:14:49.560 --> 00:14:51.877 confident they'll have they'll have the revenue at the right time, but they 00:14:51.960 --> 00:14:55.197 don't have $50 billion at hand. So I don't think there's anything 00:14:55.280 --> 00:14:57.037 inappropriate about that in principle. 00:14:57.120 --> 00:15:00.957 Now if you start stacking these where they get to huge amounts of money and 00:15:01.040 --> 00:15:05.637 you're saying, you know, by by 2027 or 2028 I need to make $200 billion a year, 00:15:05.720 --> 00:15:09.477 then yeah, you can you you can you can overextend yourself, of course. It's all 00:15:09.560 --> 00:15:12.117 a matter of the size. >> But I think is one of the key questions 00:15:12.200 --> 00:15:15.917 behind the math of this entire industry is what's called the depreciation 00:15:16.000 --> 00:15:18.517 schedule, if you will, for these chips. 00:15:18.600 --> 00:15:21.437 And there seems to be a big debate about it. Meaning 00:15:21.520 --> 00:15:25.597 when you buy a new chip, is that chip going to work for you 00:15:25.680 --> 00:15:29.317 effectively for three or four years or is it going to work for you for six or 00:15:29.400 --> 00:15:31.597 seven or eight years or even 10 years? 00:15:31.680 --> 00:15:35.157 And depending on where you think the math really lands, 00:15:35.240 --> 00:15:38.277 all of this pencils out or really doesn't. 00:15:38.360 --> 00:15:39.957 What do you think the schedule is? 00:15:40.040 --> 00:15:43.397 >> from from from from our point of view, we make very conservative assumptions 00:15:43.480 --> 00:15:46.037 here. Um I don't think there's a particular 00:15:46.120 --> 00:15:49.837 depreciation schedule, right? When new chips come out, the issue isn't the 00:15:49.920 --> 00:15:53.437 lifetime of the chips. Chips chips keep working for a long time. The issue is 00:15:53.520 --> 00:15:57.317 new chips come out that are faster and cheaper and and and and and 00:15:57.400 --> 00:16:01.437 >> if your competitors have them. Yeah, yeah. And so and so kind of the value of 00:16:01.520 --> 00:16:05.237 old chips goes down someone. In fact, that that can happen you know, a year 00:16:05.320 --> 00:16:08.117 after you buy the chips because you know, now there are multiple companies, 00:16:08.200 --> 00:16:12.837 TPUs, GPUs coming out with coming out with new chips. So I think the way we 00:16:12.920 --> 00:16:15.997 think about it is we take into account that you know, the old chips are going 00:16:16.080 --> 00:16:18.997 to be less valuable as as as time goes 00:16:19.080 --> 00:16:23.317 on. And you know, we assume very aggressive, you know, 00:16:23.400 --> 00:16:27.157 kind of continuation of the of the chip efficiency curve. And again, I can only 00:16:27.240 --> 00:16:30.877 speak for Anthropic. Like we make conservative assumptions here and and we 00:16:30.960 --> 00:16:34.757 think we're going to be we think we're going to be okay in basically almost all 00:16:34.840 --> 00:16:37.677 worlds. Can't be literally all worlds, but we think we're going to be okay in 00:16:37.760 --> 00:16:41.877 almost all worlds. I can't speak for other companies. Again, I can imagine 00:16:41.960 --> 00:16:44.957 that there may be other players out there who are, you know, who are 00:16:45.040 --> 00:16:48.517 diluting themselves and and you know, making making assumptions that are very 00:16:48.600 --> 00:16:52.717 far inflected on the optimistic So we're clear, there's only two of you who are 00:16:52.800 --> 00:16:55.477 who are not >> I look, I I I just don't know who you're 00:16:55.560 --> 00:16:58.357 talking about, okay? I I just have no idea. 00:16:58.440 --> 00:17:02.957 Um Let me ask you this about the models themselves and how you 00:17:03.040 --> 00:17:05.477 see the competition. So one of the things that's happened literally in the 00:17:05.560 --> 00:17:10.557 last week and there has been a complete sort of meltdown in the valley over 00:17:10.640 --> 00:17:15.077 what's happening here. And Sundar Pichai was also here last year and it appears 00:17:15.160 --> 00:17:16.877 at least that his new model has gotten a 00:17:16.960 --> 00:17:22.157 lot of people excited about what he's doing. And that Google, which I used to 00:17:22.240 --> 00:17:25.877 think from the beginning given all of the data they have, should have been 00:17:25.960 --> 00:17:30.557 sort of the the winner by default. And you have a memo that went out from Sam Altman 00:17:30.640 --> 00:17:34.117 saying that code red, everyone's got to get back to their desks to figure out 00:17:34.200 --> 00:17:37.757 what the what the next thing is to break the to get to the next place. How do you 00:17:37.840 --> 00:17:42.277 stack rank right now where these models are and how important do you think it is 00:17:42.360 --> 00:17:46.997 in any given moment? Yeah. So this is one of the cases where I'm just very 00:17:47.080 --> 00:17:51.357 grateful that Anthropic is taking a different path. Right? On one hand 00:17:51.440 --> 00:17:54.917 >> being the enterprise doing The the path being the enterprise, right? Both of the 00:17:55.000 --> 00:17:58.517 players that you that you mentioned, right? Both of these other two players 00:17:58.600 --> 00:18:02.157 are, you know, primarily focused on the consumer. They try and do some 00:18:02.240 --> 00:18:05.197 enterprise work, but they're they're they're and and they're fighting in 00:18:05.280 --> 00:18:08.917 consumer. That is, you know, that is that is the reason for kind of the code 00:18:09.000 --> 00:18:13.077 red, the intense fighting, right? It's, you know, Google has a search monopoly 00:18:13.160 --> 00:18:16.557 that they're trying to defend. And the center of what OpenAI is doing is in is 00:18:16.640 --> 00:18:20.517 in consumer. So those those two are fighting it out. For both of them, 00:18:20.600 --> 00:18:24.997 serving businesses is secondary. And so what we found is over time we've 00:18:25.080 --> 00:18:29.157 optimized our models more and more for the needs of businesses. The one that's 00:18:29.240 --> 00:18:33.117 gone the fastest has been coding. You know, I think that has really, you know, 00:18:33.200 --> 00:18:36.557 moved forward the quickest, but we're starting to go beyond that to finance, 00:18:36.640 --> 00:18:38.997 biomedical, retail, you know, energy, 00:18:39.080 --> 00:18:41.957 manufac- all kind of all of that. 00:18:42.040 --> 00:18:46.597 And so and so and so what we find is that these model wars, as much as our 00:18:46.680 --> 00:18:48.437 models are like really good, like, you 00:18:48.520 --> 00:18:53.717 know, the one released last week, Opus 4.5, is hands down, I think almost 00:18:53.800 --> 00:18:56.477 everyone thinks, the best model for coding. So I think that's it's very 00:18:56.560 --> 00:19:00.397 important that we continue to have this this model superiority, but there's a 00:19:00.480 --> 00:19:03.677 way in which we're kind of going in a different direction or or on a different 00:19:03.760 --> 00:19:07.877 dimension. And so we we kind of have to worry less about this back and forth. We 00:19:07.960 --> 00:19:11.277 have a little bit of a privileged position where we can just keep growing 00:19:11.360 --> 00:19:14.117 and just keep developing our models and we don't have to do any code red. 00:19:14.200 --> 00:19:18.277 >> But what is the the moat around any of these businesses? 00:19:18.360 --> 00:19:22.917 And and when I say that, I assume if Google is success is as successful as it 00:19:23.000 --> 00:19:26.397 wants to be or OpenAI or any or or Meta, right? Anybody else who's involved in 00:19:26.480 --> 00:19:29.077 this, that they think that one day if we 00:19:29.160 --> 00:19:34.357 ever get to AGI, that all these models effectively will be able to do what 00:19:34.440 --> 00:19:37.757 either, you know, any of them do. And whether it's, you know, is there a moat? 00:19:37.840 --> 00:19:39.757 Is it the persistent memory? So I'm I 00:19:39.840 --> 00:19:42.797 use ChatGPT for certain things. It knows 00:19:42.880 --> 00:19:46.997 me now because it's I've been, you know, asking it different questions. 00:19:47.080 --> 00:19:50.837 Is Or do you think people just switch back and forth, whoever's got the the 00:19:50.920 --> 00:19:54.917 latest thing? Yeah. So I you look, I can only speak to the enterprise side. What 00:19:55.000 --> 00:19:57.677 I will say is is it is surprising how 00:19:57.760 --> 00:20:02.037 different the personality and capabilities of the models are if you're 00:20:02.120 --> 00:20:04.997 building for businesses versus if you're building for if you're building for 00:20:05.080 --> 00:20:08.557 consumers. Um, you just focus on different things. You focus less on 00:20:08.640 --> 00:20:11.717 engagement, you focus more on coding, 00:20:11.800 --> 00:20:16.797 high intellectual activities, scientific ability. Um, and you know, I don't think 00:20:16.880 --> 00:20:20.597 it's true that if we got AGI they would all converge to the same place. Is 00:20:20.680 --> 00:20:23.357 everyone in this audience converge to the same place? Is everyone in this 00:20:23.440 --> 00:20:27.397 audience a copy of everyone else because we're all agent? No, we're we're all 00:20:27.480 --> 00:20:33.037 specialized. Specialization exists, you know, in in in it exists alongside general 00:20:33.120 --> 00:20:35.597 intelligence. And then I think there's all the standard enterprise stuff as 00:20:35.680 --> 00:20:39.677 well, which is that um, you know, companies build relationships with you, 00:20:39.760 --> 00:20:42.237 they get used to using certain models. 00:20:42.320 --> 00:20:43.837 Uh, and and we're starting to see that. 00:20:43.920 --> 00:20:47.517 Like even our even our API business, which is basically just selling the raw 00:20:47.600 --> 00:20:51.197 model, you wouldn't think that would be very sticky. Companies have great 00:20:51.280 --> 00:20:54.997 difficulty switching from one model to another because they have downstream 00:20:55.080 --> 00:20:58.317 customers who use the model and they like the current model. And you prompt 00:20:58.400 --> 00:21:00.597 and interact with the models in different ways and they have different 00:21:00.680 --> 00:21:04.677 personalities. It's actually quite hard to switch. So so I think there really is 00:21:04.760 --> 00:21:08.237 a durable business here. Um, one quick AGI question and it's a science 00:21:08.320 --> 00:21:12.557 question, which is do you think just the way transformers work today and just 00:21:12.640 --> 00:21:17.317 compute power alone from a scalability sense that that is what would get to AGI 00:21:17.400 --> 00:21:19.917 or do you think there's some other ingredient and maybe there's a technical 00:21:20.000 --> 00:21:24.757 question, but I'm trying to keep it very very easy that has that be included in 00:21:24.840 --> 00:21:28.197 this that gets you to some place where this stuff is actually going to really 00:21:28.280 --> 00:21:30.837 think on its own? >> No, I think I think scaling is going to 00:21:30.920 --> 00:21:34.077 get us there. Again, with small every once in a while there'll be a small 00:21:34.160 --> 00:21:37.437 modification, you know, so small you may not even read about it. It's just 00:21:37.520 --> 00:21:41.157 something going on in the lab. I have been watching these scaling laws for for 00:21:41.240 --> 00:21:44.077 10 years. So what's your what's your what's your timeline now? 00:21:44.160 --> 00:21:46.077 There's no one particular point, right? 00:21:46.160 --> 00:21:49.877 That this is what I've said over I've never liked these terms AGI, artificial 00:21:49.960 --> 00:21:53.237 superintelligence. I don't know what it means. There's just an exponential. Just 00:21:53.320 --> 00:21:57.477 like we had an exponential with Moore's law, chips getting faster and faster 00:21:57.560 --> 00:22:01.317 until they could, you know, do any, you know, simple calculation, you know, 00:22:01.400 --> 00:22:04.997 faster than faster faster than any human. I think the models are just going 00:22:05.080 --> 00:22:07.717 to get more and more capable at everything. Every few months we release 00:22:07.800 --> 00:22:12.117 a new model, gets better at coding, it gets better at science, you know, now 00:22:12.200 --> 00:22:15.317 models are routinely winning, you know, math high school math olympiads, they're 00:22:15.400 --> 00:22:18.757 moving on to college math olympiads, they're starting to do new new new 00:22:18.840 --> 00:22:23.637 mathematics. For the first time I've had internal people at Anthropic say, I 00:22:23.720 --> 00:22:26.757 don't write any code anymore. I don't write I don't open up an editor and and 00:22:26.840 --> 00:22:28.837 and and write code. I just let Claude 00:22:28.920 --> 00:22:30.757 code write the first draft and and all I 00:22:30.840 --> 00:22:34.157 do is edit it. Um, we had never reached 00:22:34.240 --> 00:22:38.037 that point before and the drumbeat is just going to continue. And and I I I I 00:22:38.120 --> 00:22:41.477 I I don't think there's any privileged point around there's no point at which 00:22:41.560 --> 00:22:45.397 the models start to do something different. What what we're going to see 00:22:45.480 --> 00:22:48.717 in the future is just like we've going to we've seen in the past except more 00:22:48.800 --> 00:22:52.317 so. The models are just going to get more and more intellectually capable 00:22:52.400 --> 00:22:55.957 and, you know, the the revenue is going to keep adding zeros. 00:22:56.040 --> 00:23:00.477 Last couple policy questions. Um, you have been outspoken. We we spoke to uh 00:23:00.560 --> 00:23:04.037 the president of Taiwan Yes. >> Um, 00:23:04.120 --> 00:23:07.517 you have been outspoken about the idea that we should not be selling Nvidia 00:23:07.600 --> 00:23:11.317 chips, for example, the the most advanced chips to China. By the way, 00:23:11.400 --> 00:23:14.397 it's interesting that you now have a partnership with Nvidia. Uh, Jensen 00:23:14.480 --> 00:23:17.397 Huang, who's also been here, was not so happy with you when you made those 00:23:17.480 --> 00:23:20.837 comments. Do you have a new view on that? My my my 00:23:20.920 --> 00:23:24.277 view hasn't changed. So I I definitely will say, and this has this has always 00:23:24.360 --> 00:23:27.877 been the case, you know, I have an enormous amount of respect for Jensen 00:23:27.960 --> 00:23:31.597 and for Nvidia. You know, Jensen is an immigrant who came to the the US with 00:23:31.680 --> 00:23:34.837 nothing. He built the most, you know, the the most valuable company in the 00:23:34.920 --> 00:23:37.117 world. This this isn't personal. This is 00:23:37.200 --> 00:23:39.317 a policy question. This is a question of 00:23:39.400 --> 00:23:44.197 how to def how best to defend our national security. And there my view 00:23:44.280 --> 00:23:47.877 hasn't changed. It's it's it's the following, which is if we go back to my 00:23:47.960 --> 00:23:52.437 picture of the models getting smarter and smarter as we continue to improve 00:23:52.520 --> 00:23:57.237 them. A phrase I've used in an essay I wrote a year and a half ago was, 00:23:57.320 --> 00:24:00.197 eventually the models are going to get to the point where they look like a 00:24:00.280 --> 00:24:02.557 country of geniuses in a data center. 00:24:02.640 --> 00:24:05.837 And so once we get to that point, think 00:24:05.920 --> 00:24:07.557 about what that country of geniuses in a 00:24:07.640 --> 00:24:10.597 data center can do and which existing 00:24:10.680 --> 00:24:13.077 country on earth it's plopped down in. 00:24:13.160 --> 00:24:17.877 Um, if it's plopped down in an authoritarian country, I feel like they 00:24:17.960 --> 00:24:19.637 can outsmart us in every way. 00:24:19.720 --> 00:24:23.317 Intelligence, defense, economic value, 00:24:23.400 --> 00:24:27.317 R&D, you know, and I worry that they'll be able to 00:24:27.400 --> 00:24:30.837 oppress their own people, that they'll be able to have a perfect surveillance 00:24:30.920 --> 00:24:33.517 state. And so I have always felt that we 00:24:33.600 --> 00:24:37.957 need to have the advantage here. And this is a national security issue. 00:24:38.040 --> 00:24:40.477 Right? Some people are saying this is an 00:24:40.560 --> 00:24:45.237 they they they they they say this is an economic issue, that it's an analogy to 00:24:45.320 --> 00:24:49.357 like the internet or 5G. We need to diffuse our stack like we needed to beat 00:24:49.440 --> 00:24:53.037 Huawei in in, you know, in telecommunications. 00:24:53.120 --> 00:24:54.877 You know, I don't I don't see it that 00:24:54.960 --> 00:24:57.997 way. I think we're building a 00:24:58.080 --> 00:25:00.557 growing and singular capability that has 00:25:00.640 --> 00:25:03.357 singular national security implications 00:25:03.440 --> 00:25:06.237 and democracies need to get there first. 00:25:06.320 --> 00:25:09.237 It is absolutely it is absolutely an imperative. 00:25:09.320 --> 00:25:09.757 >> Do you think it could happen? 00:25:09.840 --> 00:25:12.357 >> we if we sell these chips to China, that 00:25:12.440 --> 00:25:16.037 just makes it more likely they will get there first. It's common sense. 00:25:16.120 --> 00:25:17.477 >> Okay, but do you think that could happen 00:25:17.560 --> 00:25:20.637 here? So we had Alex Karp here earlier 00:25:20.720 --> 00:25:23.717 and there has been lots of worries about 00:25:23.800 --> 00:25:25.397 surveillance here. Talk about it in a 00:25:25.480 --> 00:25:30.877 democracy, right? What what is your concern there? Um, I should say by the 00:25:30.960 --> 00:25:33.597 way, there was a period of time where you called the president, this was 00:25:33.680 --> 00:25:38.477 before he was the president, a feudal warlord at one point. Um, 00:25:38.560 --> 00:25:42.637 so how do you think about the president today, America today and this idea that 00:25:42.720 --> 00:25:44.957 AI and surveillance could come together? 00:25:45.040 --> 00:25:48.757 Yeah, so so look, I I want to I want to say over and over again, the you know, 00:25:48.840 --> 00:25:53.157 that I I you know, I think that the the tendency to drag this down into being 00:25:53.240 --> 00:25:57.397 about specific personalities and and, you know, and and and and specific 00:25:57.480 --> 00:26:00.637 fights I think is not helpful here. We should really think we should really 00:26:00.720 --> 00:26:05.037 think at a at a policy level here. And it's not about one administration, it's 00:26:05.120 --> 00:26:08.997 not about another administration. We should have principles here. And and I 00:26:09.080 --> 00:26:13.117 think that the principle I would give that that I think is is is very 00:26:13.200 --> 00:26:14.757 important is actually it can happen 00:26:14.840 --> 00:26:18.077 anywhere, right? You know, a a we should 00:26:18.160 --> 00:26:22.597 we should worry about concentration of power in democracies, not as much as we 00:26:22.680 --> 00:26:25.077 worry about it in authoritarian um, uh 00:26:25.160 --> 00:26:26.877 states, but you know, we we need to make 00:26:26.960 --> 00:26:30.037 sure that the technology is governed in 00:26:30.120 --> 00:26:34.637 in, you know, in a way that that allows people to participate, that gives people 00:26:34.720 --> 00:26:38.357 basic rights. And so the formulation I've always given when I think about how 00:26:38.440 --> 00:26:41.917 to apply these models for national security is I think we should 00:26:42.000 --> 00:26:44.517 aggressively use them in in every 00:26:44.600 --> 00:26:47.637 possible way except in the ways that 00:26:47.720 --> 00:26:51.597 would make us more like our authoritarian adversaries, right? We 00:26:51.680 --> 00:26:55.757 need to beat them, but we need to not do the things that would cause us to become 00:26:55.840 --> 00:26:58.837 them. Um, that is the one constraint we should observe. 00:26:58.920 --> 00:27:00.077 >> Okay, let me ask you a separate question 00:27:00.160 --> 00:27:03.397 and maybe you'll say it's a fight, but you can take it out of out of the the 00:27:03.480 --> 00:27:07.557 the person if you if you want, which is you have been very vocal about your 00:27:07.640 --> 00:27:11.197 concerns about the chip issue, but also what could 00:27:11.280 --> 00:27:15.877 happen to jobs, uh regulating reg- regulating this technology so it doesn't 00:27:15.960 --> 00:27:17.877 do bad things or other things like that. 00:27:17.960 --> 00:27:20.957 Uh, David Sacks, uh who works as the AI 00:27:21.040 --> 00:27:23.117 czar at the White House, uh said this 00:27:23.200 --> 00:27:26.157 about you. He says that Anthropic is 00:27:26.240 --> 00:27:31.397 running a sophisticated regulatory capture strategy based on fearmongering. 00:27:31.480 --> 00:27:32.997 It is principally responsible for the 00:27:33.080 --> 00:27:35.757 state regulatory frenzy that is damaging 00:27:35.840 --> 00:27:40.357 the startup ecosystem. Again, I don't think this should be about specific 00:27:40.440 --> 00:27:44.397 individuals, right? This isn't about any particular administration. This is about 00:27:44.480 --> 00:27:48.717 This is about policy questions. I mean, you know, going all the way back to 20 00:27:48.800 --> 00:27:52.957 2016 I've written papers about AI right before I even had a company, right? 00:27:53.040 --> 00:27:56.677 Before there there there even, you know, could have been a plan around anything 00:27:56.760 --> 00:27:59.357 like regulatory capture. And and by the 00:27:59.440 --> 00:28:01.517 way, almost all the AI regulation that 00:28:01.600 --> 00:28:03.957 we've supported has has exemptions for 00:28:04.040 --> 00:28:06.677 small players, right? The main um, AI 00:28:06.760 --> 00:28:10.357 bill we supported, SB 53, um, you know, 00:28:10.440 --> 00:28:14.517 doesn't even apply at all to startups with under $500 million in revenue. So 00:28:14.600 --> 00:28:18.717 we've been very careful about this. And you know, if there's one point again, I 00:28:18.800 --> 00:28:22.357 want to say again, I think people should focus on the policy. You can throw out 00:28:22.440 --> 00:28:26.117 these accusations and they don't match reality at all. They don't match the 00:28:26.200 --> 00:28:29.997 reality of the bills we've actually supported. They don't match the reality 00:28:30.080 --> 00:28:33.117 >> these two worlds right now, which is by the way, you know, Andreessen Horowitz 00:28:33.200 --> 00:28:36.997 and and others are are have a have one super PAC. You guys are building another 00:28:37.080 --> 00:28:40.557 super PAC to approach regulation of this industry 00:28:40.640 --> 00:28:44.557 completely differently. And the question is why? What do you see that they don't? 00:28:44.640 --> 00:28:47.317 >> So so I, you know, again, I I want to 00:28:47.400 --> 00:28:49.997 keep this at the policy level. What what 00:28:50.080 --> 00:28:55.477 how I see this technology, I I I am concerned and I can understand where 00:28:55.560 --> 00:28:58.477 folks are coming from, but I am concerned that there are some who see 00:28:58.560 --> 00:29:01.797 this technology as analogous to previous 00:29:01.880 --> 00:29:06.077 technological revolutions, as being like the internet, as being like 00:29:06.160 --> 00:29:09.837 telecommunications where yes, there are some issues, but, you know, the the 00:29:09.920 --> 00:29:13.677 market will figure it out, which I think was maybe a more reasonable view in in 00:29:13.760 --> 00:29:17.597 these previous technological revolutions. I think those who are 00:29:17.680 --> 00:29:20.557 closest to AI don't feel this way. If 00:29:20.640 --> 00:29:22.837 you pull the actual researchers who who 00:29:22.920 --> 00:29:26.397 work on AI, not investors who invest in 00:29:26.480 --> 00:29:31.717 some AI application companies, not general tech commentators who, you know, 00:29:31.800 --> 00:29:35.037 think they know something about AI, but the actual people who are building the 00:29:35.120 --> 00:29:38.717 technology, they're excited about the potential, but 00:29:38.800 --> 00:29:42.037 they're also worried. They're worried about the national security risks. 00:29:42.120 --> 00:29:45.477 They're worried about alignment of the models. They're worried about the 00:29:45.560 --> 00:29:47.797 economic impacts of the models. And for 00:29:47.880 --> 00:29:52.717 example, the idea that we would put a moratorium on all all all kind of 00:29:52.800 --> 00:29:56.837 regulation or all state regulation without a federal, you know, with with 00:29:56.920 --> 00:30:02.157 that without without a federal framework for 10 years, which, you know, was 00:30:02.240 --> 00:30:05.517 attempted in the summer and I think it was just attempted this last week again 00:30:05.600 --> 00:30:09.237 and it failed because it was very unpopular because even the average 00:30:09.320 --> 00:30:11.557 person understands that this is a new 00:30:11.640 --> 00:30:16.677 and and powerful technology. And so, you know, I think we I I am more than any 00:30:16.760 --> 00:30:19.797 you know, I I am maybe the most optimistic about the 00:30:19.880 --> 00:30:24.397 upsides, right? I wrote this whole essay Machines of Loving Grace where I said AI 00:30:24.480 --> 00:30:26.357 is going to, you know, extend might even 00:30:26.440 --> 00:30:31.477 extend the human lifespan to 150 10 years after we get the the country of 00:30:31.560 --> 00:30:35.117 geniuses in the data center because we'll have a virtual biologist that can 00:30:35.200 --> 00:30:38.717 make discoveries much faster than we can. That that, you know, it could 00:30:38.800 --> 00:30:43.117 drive, you know, economic growth to, you know, five or five or 10%. I'm 00:30:43.200 --> 00:30:46.477 incredibly optimistic about the technology. Frankly, much more 00:30:46.560 --> 00:30:50.037 optimistic than some of people who describe themselves as boosters of the 00:30:50.120 --> 00:30:53.317 technology. Um, but but nothing that 00:30:53.400 --> 00:30:55.997 powerful doesn't have a significant 00:30:56.080 --> 00:30:58.357 number of downsides. And and we as a 00:30:58.440 --> 00:31:01.397 society, as a polity, need to think 00:31:01.480 --> 00:31:05.837 ahead about those downsides. Saying that for 10 years we won't regulate that 00:31:05.920 --> 00:31:09.277 technology, it's like it's like saying I'm driving a car, I'm going to rip out 00:31:09.360 --> 00:31:12.837 the steering wheel because I don't need to steer for 10 years. Okay, so here's 00:31:12.920 --> 00:31:14.677 the the question about the downside then. 00:31:14.760 --> 00:31:17.557 >> One of the downsides, beyond hacking and everything else that I know you worry 00:31:17.640 --> 00:31:21.637 about, is jobs. You spoke about it on 60 Minutes recently. But I want to know not 00:31:21.720 --> 00:31:24.837 just that you you think that there's a good chance 00:31:24.920 --> 00:31:27.757 and I don't want to put words in your mouth that it could be, you know, half 00:31:27.840 --> 00:31:31.037 of all entry-level jobs get lost. I want to know what you think should be done 00:31:31.120 --> 00:31:35.197 about it. Absolutely. So, you know, I I I think at the end of the day I warn 00:31:35.280 --> 00:31:40.157 about these things not to be a prophet of doom, but because warning about them 00:31:40.240 --> 00:31:42.037 is the first step towards solving them. 00:31:42.120 --> 00:31:45.797 And if we don't warn about them, then we'll just uh, you know, we'll we'll 00:31:45.880 --> 00:31:49.877 we'll just kind of blindly walk into a landmine and blow us up. Um, if we warn 00:31:49.960 --> 00:31:53.517 about them, if we see the landmine, we can walk around it and we can avoid it. 00:31:53.600 --> 00:31:56.517 So, I have been thinking a lot about these ideas. I've been thinking about 00:31:56.600 --> 00:31:59.917 them inside Anthropic where we where, you know, Claude is starting to write a 00:32:00.000 --> 00:32:03.397 lot of our code and we're thinking about how the jobs change. So, I think there's 00:32:03.480 --> 00:32:07.757 several levels of it that maybe go from short-term to long-term or or just kind 00:32:07.840 --> 00:32:11.877 of requiring more and more of the resources of society to happen. I think 00:32:11.960 --> 00:32:15.677 some of it can happen in the private sector and even in our relationships 00:32:15.760 --> 00:32:17.997 with customers. Every customer we work 00:32:18.080 --> 00:32:19.877 with has the following trade-off and 00:32:19.960 --> 00:32:23.037 it's not either-or. They can, um, you 00:32:23.120 --> 00:32:28.117 know, they can increase efficiency by basically having AIs do what what humans 00:32:28.200 --> 00:32:29.437 used to do. And there's plenty of that. 00:32:29.520 --> 00:32:33.517 Things like, you know, insurance claims processing or know your customer, whole 00:32:33.600 --> 00:32:37.357 workflows that can just be done end-to-end via AI and I think we'll need 00:32:37.440 --> 00:32:41.317 a lot less humans for them. It it will increase efficiency, it'll save costs, 00:32:41.400 --> 00:32:45.717 do the same thing for lower cost and much less people needed. But you can 00:32:45.800 --> 00:32:49.437 also do things where you can create a lot of new value. And even in cases 00:32:49.520 --> 00:32:54.357 where AI does 90% of the job, not 100% but 90%, the humans can be 10 times more 00:32:54.440 --> 00:32:57.917 leverage and sometimes you need 10 times more of them to do 100 times what you 00:32:58.000 --> 00:33:02.317 did before because it's so efficient and valuable. And so encouraging companies 00:33:02.400 --> 00:33:05.797 to do as much of the second relative to the first. We know they're going to do 00:33:05.880 --> 00:33:08.037 the first. We're not trying to stop them from doing the first, but if they can do 00:33:08.120 --> 00:33:11.917 more of the second than the first, maybe more jobs can be created than than get 00:33:12.000 --> 00:33:13.997 lost. >> mean we need government incentives? Is that a policy 00:33:14.080 --> 00:33:18.117 >> So so uh again, that's that's that's level one. Level two is the involvement 00:33:18.200 --> 00:33:21.917 of the government. I don't see retraining programs as a panacea, but I 00:33:22.000 --> 00:33:25.117 think we're going to need to do some form of that. Companies are going to do 00:33:25.200 --> 00:33:28.917 it, companies are going to have to work with governments to do it. And I but I I 00:33:29.000 --> 00:33:33.157 I do think fiscally at some point the government is going to need to step in. 00:33:33.240 --> 00:33:35.637 I don't know if that's tax policy, but 00:33:35.720 --> 00:33:40.317 but this world of fast growth, right? We did this report where we said even 00:33:40.400 --> 00:33:45.557 current models it looks like they will increase productivity by 1.6% 00:33:45.640 --> 00:33:48.837 a year. That's almost, you know, almost a doubling of productivity. And the 00:33:48.920 --> 00:33:52.077 models are getting better and better. So I think we're going to get up to five 00:33:52.160 --> 00:33:54.717 five percent a year, maybe 10% a year. 00:33:54.800 --> 00:33:57.397 That's a big pie. That's a big pie that 00:33:57.480 --> 00:34:01.757 we can we can give out to the people who are who are not such fortunate 00:34:01.840 --> 00:34:05.597 beneficiaries, right? If the wealth concentrates, there there there there 00:34:05.680 --> 00:34:08.677 there really is a big pie here. So I think the government is going to need to 00:34:08.760 --> 00:34:11.237 have some role here. That's level two 00:34:11.320 --> 00:34:13.757 and I think level three is over the long 00:34:13.840 --> 00:34:16.637 run the structure of a society that has 00:34:16.720 --> 00:34:21.597 built powerful AI is just going to have to be different. If we if we go back to 00:34:21.680 --> 00:34:25.317 John Maynard Keynes, right? Economic possibilities for our grandchildren, 00:34:25.400 --> 00:34:28.997 right? He invented this idea of technological unemployment. He suggested 00:34:29.080 --> 00:34:33.397 that maybe his grandchildren would only have to work 15 or 20 hours hours a 00:34:33.480 --> 00:34:36.917 week, right? That's like a different way of structuring the society. Some people 00:34:37.000 --> 00:34:41.517 will always want to work, you know, as hard as possible. Um, you know, there 00:34:41.600 --> 00:34:45.517 there always be segments of society who who want to do that. But, you know, can 00:34:45.600 --> 00:34:50.117 can can we have a world where work doesn't for many people doesn't need to 00:34:50.200 --> 00:34:53.757 have the centrality that it does that that people find their their locus of 00:34:53.840 --> 00:34:56.797 meaning elsewhere or work is about is 00:34:56.880 --> 00:34:58.997 about different things. It's more about 00:34:59.080 --> 00:35:01.837 fulfillment than it is about economic 00:35:01.920 --> 00:35:04.717 economic survival. Um, there there's so 00:35:04.800 --> 00:35:06.997 many possibilities here. I think society 00:35:07.080 --> 00:35:10.317 is flexible and and society can I'm not 00:35:10.400 --> 00:35:14.837 suggesting anything top-down. I think society needs to restructure itself. We 00:35:14.920 --> 00:35:19.237 all need to figure out how to operate in the in in the post in the post-AGI age. 00:35:19.320 --> 00:35:23.597 So I think those three levels will go from fast and and easy for it for, you 00:35:23.680 --> 00:35:27.437 know, individual companies to do to requiring a lot of consensus and and and 00:35:27.520 --> 00:35:31.077 very slow to do. But over the years we're we're going to need to do all 00:35:31.160 --> 00:35:34.357 three of these things. Uh, Dario, I hope you come back so we can have a 00:35:34.440 --> 00:35:38.197 conversation as we have to do all of those things to figure out what comes 00:35:38.280 --> 00:35:41.557 next. Want to thank you for a fantastic conversation. Thank you, Andrew. Thank 00:35:41.640 --> 00:35:44.840 you. Thank you so much. Appreciate it.