1 00:00:05,000 --> 00:00:08,917 Good afternoon, everyone, and welcome to the OpenAI forum. I'm Chris Nicholson, 2 00:00:09,000 --> 00:00:11,477 and I'm glad to be here with all of you today. 3 00:00:11,560 --> 00:00:16,157 The forum is a place for serious conversation about how AI is being used 4 00:00:16,240 --> 00:00:20,437 in the world, what we're learning from that, and how more people can help shape 5 00:00:20,520 --> 00:00:22,837 its trajectory. Today's conversation 6 00:00:22,920 --> 00:00:24,917 focuses on one of the biggest questions 7 00:00:25,000 --> 00:00:30,237 in technology, what it will mean as AI systems grow dramatically more capable, 8 00:00:30,320 --> 00:00:31,837 and how we should think about their 9 00:00:31,920 --> 00:00:34,917 implications for science, work, our life 10 00:00:35,000 --> 00:00:39,237 together, and governance. To discuss that, I'm joined by Sam 11 00:00:39,320 --> 00:00:43,517 Altman, co-founder and CEO of OpenAI, Josh Acklin, 12 00:00:43,600 --> 00:00:48,797 OpenAI's chief futurist, and Adrian Akyol, a long-time researcher here. So, let's 13 00:00:48,880 --> 00:00:51,477 get started. Sam, 14 00:00:51,560 --> 00:00:56,037 the blueprint we released this morning talks a lot about superintelligence. Um, 15 00:00:56,120 --> 00:01:00,237 a big question on my mind is, why are we doing that now, and what are 16 00:01:00,320 --> 00:01:04,317 some things that you can see from the inside that you wish everybody knew? 17 00:01:04,400 --> 00:01:08,197 >> The The biggest reason is simply that the rate of progress is continuing to 18 00:01:08,280 --> 00:01:12,357 accelerate, and we believe we are very close now. 19 00:01:12,440 --> 00:01:16,037 And this won't be a one-time thing. This will be a you know, 20 00:01:16,120 --> 00:01:19,677 over the next few years to powerful models that will impact the world in 21 00:01:19,760 --> 00:01:24,877 important ways. The researchers that are working on these models that did and 22 00:01:24,960 --> 00:01:28,277 I think an incredible job with this set of ideas, and these are meant to be 23 00:01:28,360 --> 00:01:30,997 early ideas to start a discussion. 24 00:01:31,080 --> 00:01:33,637 You know, I'm sure we'll get to much better ideas as the world debates all of 25 00:01:33,720 --> 00:01:36,397 these. Are staring down the models that are 26 00:01:36,480 --> 00:01:39,517 coming, the pipeline in front of us. 27 00:01:39,600 --> 00:01:42,877 And you know, we may be wrong. We may hit 28 00:01:42,960 --> 00:01:45,397 some wall. We We are imperfect, but our 29 00:01:45,480 --> 00:01:47,437 But given what we see, 30 00:01:47,520 --> 00:01:50,677 we expect to be in a world of extremely 31 00:01:50,760 --> 00:01:53,397 capable models quite soon, and then for 32 00:01:53,480 --> 00:01:56,197 the the ramp of the capability to 33 00:01:56,280 --> 00:01:58,117 continue to increase. I think this will 34 00:01:58,200 --> 00:02:03,597 have huge impact on the economy, on the way we live, on what we can do. And 35 00:02:03,680 --> 00:02:05,037 one thing I've observed from watching 36 00:02:05,120 --> 00:02:06,997 the world go through some number of 37 00:02:07,080 --> 00:02:11,197 transitions is that the more time the 38 00:02:11,280 --> 00:02:15,517 the public, our leaders, the political system has to debate ideas before you 39 00:02:15,600 --> 00:02:19,597 really have to make a decision, the more likely you are to make a good decision. 40 00:02:19,680 --> 00:02:23,877 So, starting this now, given what we see coming, so that as this becomes 41 00:02:23,960 --> 00:02:26,637 a very large issue of public debate, I think it's important. 42 00:02:26,720 --> 00:02:31,237 >> For sure. Um and speaking of debate, we brought in a lot of researchers in 43 00:02:31,320 --> 00:02:34,997 during very early in this process. I think it was a 44 00:02:35,080 --> 00:02:38,717 maybe a unique exercise here in how many researchers were working 45 00:02:38,800 --> 00:02:42,037 with the folks who also think about policy a lot. 46 00:02:42,120 --> 00:02:46,117 It's closely tied. What was that like for you and for the research group as a 47 00:02:46,200 --> 00:02:49,597 whole? >> Yeah, you know, I think it was Well, it 48 00:02:49,680 --> 00:02:52,757 was a very interesting experience. Like it was my first time 49 00:02:52,840 --> 00:02:56,997 working like actively on a on a policy doc. I think it was a little bit like 50 00:02:57,080 --> 00:03:01,357 humbling in some cases, you know, uh uh sometimes 51 00:03:01,440 --> 00:03:05,437 as researchers, we can have these abstract ideas of oh, we should really 52 00:03:05,520 --> 00:03:09,837 be thinking about the economic impact of this or or about like policy for for 53 00:03:09,920 --> 00:03:12,597 safety, but you know, it's it's one thing to think about this and another 54 00:03:12,680 --> 00:03:17,277 thing to like actually put, you know, pen to paper and um and think of 55 00:03:17,360 --> 00:03:22,197 concrete uh policy ideas that are going to be debated by by your your peer 56 00:03:22,280 --> 00:03:23,997 uh your your peer researchers. Um so, it 57 00:03:24,080 --> 00:03:25,717 was an interesting experience for me. 58 00:03:25,800 --> 00:03:29,557 Um I I hope there was 59 00:03:29,640 --> 00:03:31,717 uh you know, very helpful for the final 60 00:03:31,800 --> 00:03:36,877 product uh that we had the researchers involved so early and so and so deeply 61 00:03:36,960 --> 00:03:40,597 like for for something like this, uh especially since it's so 62 00:03:40,680 --> 00:03:44,437 forward-looking. Uh you kind of need to to Sam's point, 63 00:03:44,520 --> 00:03:48,677 like you need people who are um who are dealing with this technology 64 00:03:48,760 --> 00:03:52,237 every day, who know how to build it, know how the safety stack works, 65 00:03:52,320 --> 00:03:54,637 and also are seeing like 66 00:03:54,720 --> 00:03:58,077 the speed of progress. Um and one thing 67 00:03:58,160 --> 00:04:01,997 that, you know, that I remember as part of this process in the in the past few 68 00:04:02,080 --> 00:04:07,157 months that we were were working on it, like a lot of researchers went through a a 69 00:04:07,240 --> 00:04:10,957 transition uh from, you know, writing most of their 70 00:04:11,040 --> 00:04:13,677 own code to having AI most write most of 71 00:04:13,760 --> 00:04:17,957 their code. And I think that I think to some extent led them to bring a lot of 72 00:04:18,040 --> 00:04:19,557 the urgency of like 73 00:04:19,640 --> 00:04:23,997 this technology is is real and important 74 00:04:24,080 --> 00:04:26,997 moving fast in a way that maybe um 75 00:04:27,080 --> 00:04:30,397 not everyone can can see. Uh and and 76 00:04:30,480 --> 00:04:34,397 that's part of also kind of your your earlier question about why now, like 77 00:04:34,480 --> 00:04:36,837 because we are seeing uh this urgency. 78 00:04:36,920 --> 00:04:40,717 >> Can I tell a quick story that reminds me of? Um 79 00:04:40,800 --> 00:04:45,557 There was a night in 80 00:04:45,640 --> 00:04:49,797 I guess it would've been late January, early February of 2020, 81 00:04:49,880 --> 00:04:54,997 when uh the OpenAI researchers kind of got obsessed with COVID before the rest 82 00:04:55,080 --> 00:04:57,277 of the world did. And we were talking about it all the time, and we were 83 00:04:57,360 --> 00:04:59,677 watching the numbers every day, and we're like, "This is going to happen." 84 00:04:59,760 --> 00:05:04,157 >> Yeah. >> And, you know, we were like making plans to go uh 85 00:05:04,240 --> 00:05:07,397 work from home, and there was this like some article that came out like mocking 86 00:05:07,480 --> 00:05:10,557 us because they're like these crazy people at OpenAI. We had put like some 87 00:05:10,640 --> 00:05:14,157 copper or something on some of the door handles because people >> I remember that. 88 00:05:14,240 --> 00:05:16,477 >> You remember that? And some journalist wrote about this, 89 00:05:16,560 --> 00:05:21,560 and there's all all these things going on. And I 90 00:05:21,720 --> 00:05:26,197 And you know, we we kind of like made our plans, and we assumed a 91 00:05:26,280 --> 00:05:28,117 shutdown was going to happen. We're like, "There's this thing coming. The 92 00:05:28,200 --> 00:05:32,037 world's not paying attention." And for whatever reason, uh something about like 93 00:05:32,120 --> 00:05:34,517 working on exponential makes you understand these things better. So, I 94 00:05:34,600 --> 00:05:38,717 think we were like a group of people that were primed to do it. Um 95 00:05:38,800 --> 00:05:41,517 And then there was this one night, it was like a very cold night. I lived in 96 00:05:41,600 --> 00:05:45,397 the mission at the time. And I was like, "I'm about to get locked in my house for 97 00:05:45,480 --> 00:05:46,757 a while, and I'm going to go for a walk. 98 00:05:46,840 --> 00:05:49,357 I want to one more time I want to like, you know go for a walk cuz who knows 99 00:05:49,440 --> 00:05:52,277 what what's going to happen. And I went through this long walk 100 00:05:52,360 --> 00:05:55,797 through the city, hours, cold cold night. And I was like watching people, 101 00:05:55,880 --> 00:05:58,277 you know, breathing in each other's faces in restaurants and bars through 102 00:05:58,360 --> 00:06:01,557 the windows. And I was like wearing my mask looking all looking crazy. And 103 00:06:01,640 --> 00:06:04,237 there was one other dude out wearing a mask and kind of we nodded at each 104 00:06:04,320 --> 00:06:06,757 other. And that was But other than that it was just like 105 00:06:06,840 --> 00:06:11,797 life felt totally normal. I have not felt that so acutely as I do 106 00:06:11,880 --> 00:06:13,637 again in this moment. >> Yeah. 107 00:06:13,720 --> 00:06:17,957 >> Um where it's like there is this crazy change. The change 108 00:06:18,040 --> 00:06:21,157 has already happened. Like the models have already hit some level. Society has 109 00:06:21,240 --> 00:06:23,397 not digested them yet. >> Yeah. 110 00:06:23,480 --> 00:06:27,317 >> We feel like we see it clearly. We are trying to tell the world that it's 111 00:06:27,400 --> 00:06:31,517 going to happen. It is hard to get this across. But it feels like that night in 112 00:06:31,600 --> 00:06:33,397 the very beginning of COVID walking through the streets again. 113 00:06:33,480 --> 00:06:37,397 >> That's really interesting. And and you've talked a bit about the upsides to 114 00:06:37,480 --> 00:06:39,877 unlock and a lot about science as a 115 00:06:39,960 --> 00:06:43,077 means to do that. Um so so if we're 116 00:06:43,160 --> 00:06:45,877 going to like contrast this with COVID, 117 00:06:45,960 --> 00:06:51,677 what are some of the hugely positive things in the pipeline for us? 118 00:06:51,760 --> 00:06:54,517 >> I will answer that. I think the positives are so positive we should talk 119 00:06:54,600 --> 00:06:58,597 more about the other things that we're thinking about here. But like it it you 120 00:06:58,680 --> 00:07:01,717 mentioned science. If we can really go make a 121 00:07:01,800 --> 00:07:05,237 decades worth of scientific progress in a year, if we can go cure a ton of 122 00:07:05,320 --> 00:07:08,597 diseases, if we can come up with personalized medicine for people, find 123 00:07:08,680 --> 00:07:13,277 new materials to sort of make cheap safe energy 124 00:07:13,360 --> 00:07:16,157 there's if we can make it such that anybody who 125 00:07:16,240 --> 00:07:19,397 can come up with an idea for a startup can have the AI implement it, write the 126 00:07:19,480 --> 00:07:22,557 piece of software they want, uh you know, have a custom video game 127 00:07:22,640 --> 00:07:28,277 that's like the most fun for you to play. Uh this stuff is all wonderful. Now, 128 00:07:28,360 --> 00:07:30,757 you know, part of the reason for putting this out with urgency is there are going 129 00:07:30,840 --> 00:07:34,557 to come there are a lot of things coming that we'll need to mitigate. 130 00:07:34,640 --> 00:07:37,837 I assume we'll figure it out. I I'm always an optimistic person by nature. 131 00:07:37,920 --> 00:07:42,677 But also the benefits of this this has change the 132 00:07:42,760 --> 00:07:44,037 option space in front of us and what we 133 00:07:44,120 --> 00:07:47,517 can do that one of 134 00:07:47,600 --> 00:07:51,877 my first reaction to reading the blueprint after the researchers wrote it 135 00:07:51,960 --> 00:07:55,877 was like it is awesome but also a little crazy that we can credibly be talking 136 00:07:55,960 --> 00:08:00,717 about these kinds of things. Um so we do have like if 137 00:08:00,800 --> 00:08:02,917 the AI is as good as we think >> Yeah. 138 00:08:03,000 --> 00:08:06,677 >> and all these wonderful things happen, we also have an incredible new tool at 139 00:08:06,760 --> 00:08:09,077 our disposal to help us mitigate the potential downsides. 140 00:08:09,160 --> 00:08:13,397 >> Yeah. And it's a tool for everyone. Uh Josh, I'd like to ask you 141 00:08:13,480 --> 00:08:17,277 So So I I think we've talked about this as social infrastructure that changes 142 00:08:17,360 --> 00:08:19,637 the way people work and learn and 143 00:08:19,720 --> 00:08:24,477 participate in society. Um what 144 00:08:24,560 --> 00:08:28,997 what responsibilities do we have and do institutions have to help society get 145 00:08:29,080 --> 00:08:31,397 ready for that and how how do you think about it? 146 00:08:31,480 --> 00:08:34,237 >> Yeah. Um you know, one of the things that I think about here, this does kind 147 00:08:34,320 --> 00:08:37,037 of come back to the broad benefits for everyone thing. 148 00:08:37,120 --> 00:08:39,317 Uh for a long time in society, we've had 149 00:08:39,400 --> 00:08:44,357 this great aspiration that everyone could have, you know, food, shelter, 150 00:08:44,440 --> 00:08:48,837 electricity, uh health care and we've we've always 151 00:08:48,920 --> 00:08:53,197 wanted to see there be some kind of 152 00:08:53,280 --> 00:08:55,877 new step in the direction of providing these sorts of things for everyone so 153 00:08:55,960 --> 00:08:59,437 that everyone can focus on the things that are most important in their lives. 154 00:08:59,520 --> 00:09:03,357 Um and we've often been told over and over again like, you know, actually we 155 00:09:03,440 --> 00:09:05,037 can't have that, it's too expensive. 156 00:09:05,120 --> 00:09:09,437 There's no way to pay for it. Um like it's it's nice but it would be too 157 00:09:09,520 --> 00:09:11,917 burdensome to society to do all of that. 158 00:09:12,000 --> 00:09:14,117 And I think what AI and 159 00:09:14,200 --> 00:09:16,877 superintelligence will unlock is the 160 00:09:16,960 --> 00:09:21,197 freedom to do all of it at a much lower cost than has ever been possible. And 161 00:09:21,280 --> 00:09:24,397 correspondingly for the folks of us who are sort of the stewards of the 162 00:09:24,480 --> 00:09:28,357 technology, we have a special responsibility to make sure that we 163 00:09:28,440 --> 00:09:30,837 actually do fully realize those benefits 164 00:09:30,920 --> 00:09:36,357 and be a part of building policies and systems that help working people, middle 165 00:09:36,440 --> 00:09:39,397 class people, people in low-income countries, really make sure that it 166 00:09:39,480 --> 00:09:43,677 benefits everyone and not just the very wealthy. So, I'm those are the things 167 00:09:43,760 --> 00:09:47,197 that I think of as key responsibilities here, and I'm very excited about it. 168 00:09:47,280 --> 00:09:50,397 Plus, the downside risks are also quite 169 00:09:50,480 --> 00:09:54,557 serious, and there are systemic shocks that could happen. We have to prepare. 170 00:09:54,640 --> 00:09:56,517 We have to be thoughtful. We have to be honest about them. 171 00:09:56,600 --> 00:10:00,397 >> Yeah. Yeah, so that sounds like a resilience question. Um 172 00:10:00,480 --> 00:10:04,077 and and when I look at the document and and speak with 173 00:10:04,160 --> 00:10:08,917 you folks, it sounds like you think of resilience in layers, right? There's um 174 00:10:09,000 --> 00:10:12,397 kind of and and a lot of it is not before the AI goes out, but it's also 175 00:10:12,480 --> 00:10:17,197 after the AI goes out in terms of um our responses to AI and how people are are 176 00:10:17,280 --> 00:10:20,317 prepared for it. I'd actually like to ask each of you how you think about 177 00:10:20,400 --> 00:10:23,717 resilience. Um Adrian, why don't we why don't we start with you? 178 00:10:23,800 --> 00:10:28,037 >> Yeah. You know, I I think maybe you want one distinction 179 00:10:28,120 --> 00:10:31,477 that I would draw with uh you know, classically we've thought 180 00:10:31,560 --> 00:10:33,677 about about safety and about making sure 181 00:10:33,760 --> 00:10:38,517 that we that we run, you know, safety evals, that we red team our models, um 182 00:10:38,600 --> 00:10:41,397 that we implement mitigations. And I think like that's, you know, to your 183 00:10:41,480 --> 00:10:45,677 point of resilience is a layer. This is like a very important layer that we 184 00:10:45,760 --> 00:10:50,117 should, you know, still keep doing and keep expanding, but um 185 00:10:50,200 --> 00:10:53,357 at the same time uh 186 00:10:53,440 --> 00:10:55,997 you want society to 187 00:10:56,080 --> 00:11:00,517 uh be prepared for the possibility that well, maybe there will be some actors 188 00:11:00,600 --> 00:11:02,917 who do less safety testing, and like 189 00:11:03,000 --> 00:11:07,597 what what happens what happens then? How is society resilient to risks from AIs 190 00:11:07,680 --> 00:11:11,197 uh in these cases? Um maybe there will be 191 00:11:11,280 --> 00:11:15,837 uh incidents in spite of our safety testing or near misses uh in the 192 00:11:15,920 --> 00:11:20,077 in the uh blueprint, we talk, for instance, about um 193 00:11:20,160 --> 00:11:23,677 incident reporting that's modeled a little bit of after um 194 00:11:23,760 --> 00:11:26,557 how the uh aviation industry uh does 195 00:11:26,640 --> 00:11:30,757 things when whenever there's kind of like a near miss or any incidents, like 196 00:11:30,840 --> 00:11:35,717 however minor, that kind of like gets reported to um to a database so that, 197 00:11:35,800 --> 00:11:39,277 you know, all the companies can kind of know, okay, well, this is a risk and 198 00:11:39,360 --> 00:11:42,597 perhaps uh you know, here are uh mitigations that that you could 199 00:11:42,680 --> 00:11:47,357 implement. And so, there's a lot of things that could happen at a society-wide uh 200 00:11:47,440 --> 00:11:51,037 level. Um another thing would be um 201 00:11:51,120 --> 00:11:55,077 you know, defending against uh against risks. Uh 202 00:11:55,160 --> 00:11:57,517 we're talking about models that that can 203 00:11:57,600 --> 00:11:58,997 code um 204 00:11:59,080 --> 00:12:02,637 a lot better now. Uh that also implies 205 00:12:02,720 --> 00:12:04,917 uh cyber capabilities. Like, could they 206 00:12:05,000 --> 00:12:08,637 help uh bad actors uh run cyber attacks? 207 00:12:08,720 --> 00:12:12,397 Uh and I think part of resilience is ensuring 208 00:12:12,480 --> 00:12:14,317 that we uh 209 00:12:14,400 --> 00:12:19,477 that we make our software systems uh more secure uh and use AI to do these 210 00:12:19,560 --> 00:12:22,277 things. So, so again, there's as you said, all these layers. So, that's kind 211 00:12:22,360 --> 00:12:25,277 of how I take the the resilience question. 212 00:12:25,360 --> 00:12:29,037 >> Sam, before the show, we were talking about how prosperity can be emergent 213 00:12:29,120 --> 00:12:32,237 when everybody has access to AI. It also strikes me that resilience can be 214 00:12:32,320 --> 00:12:34,717 emergent. How How do you think about it? 215 00:12:34,800 --> 00:12:39,597 >> Yeah, I I think our original AI safety thinking 216 00:12:39,680 --> 00:12:42,757 and the field as in general, like I'll call it classical AI safety thinking, 217 00:12:42,840 --> 00:12:47,437 was that there are going to be a very tiny number of AIs in the world. The 218 00:12:47,520 --> 00:12:51,317 only thing that matters is making sure those AIs do the right thing and that as 219 00:12:51,400 --> 00:12:52,957 long as you align them and they don't do 220 00:12:53,040 --> 00:12:56,397 unsafe things, the world will be okay. 221 00:12:56,480 --> 00:13:00,797 I think the picture now is actually more stable but more complex 222 00:13:00,880 --> 00:13:05,957 and there are going to be many AIs in the world uh and the 223 00:13:06,040 --> 00:13:09,517 it will not be enough to just say like, you know, 224 00:13:09,600 --> 00:13:12,517 this one company is going to make sure the AI never does something it shouldn't 225 00:13:12,600 --> 00:13:14,717 do. Um but there will need to be an 226 00:13:14,800 --> 00:13:19,917 emergent response across society. Uh you know, 227 00:13:20,000 --> 00:13:23,117 Adrian talked a little bit about some of this, but if we just take a few examples 228 00:13:23,200 --> 00:13:25,277 of threats that we expect to be coming. 229 00:13:25,360 --> 00:13:29,037 Um cybersecurity is definitely going to become a huge issue. AI will be 230 00:13:29,120 --> 00:13:33,357 incredibly good at finding vulnerabilities in software, and I think 231 00:13:33,440 --> 00:13:36,517 the world will find that their software is much more brittle and much less 232 00:13:36,600 --> 00:13:39,677 secure than we thought. And you know, humans just have limited 233 00:13:39,760 --> 00:13:45,037 capacity to find the exploits. Um, it is not enough to say that, you know, 234 00:13:45,120 --> 00:13:48,117 one or two or three model providers are just going to make sure that their 235 00:13:48,200 --> 00:13:52,397 systems won't do this because code is like, you know, the same thing that 236 00:13:52,480 --> 00:13:55,237 code is very useful to be good at, and being good at writing code can also help 237 00:13:55,320 --> 00:13:58,277 find security problems. And even if all 238 00:13:58,360 --> 00:14:02,637 of us somehow could prevent our models from ever being used for this, there 239 00:14:02,720 --> 00:14:05,477 will be open-source models coming soon that are that are good at code and thus 240 00:14:05,560 --> 00:14:08,957 good at security exploits. So, what has to happen is 241 00:14:09,040 --> 00:14:11,597 the world has to use these models, and there can be, you know, differential 242 00:14:11,680 --> 00:14:14,797 access. You can give it to good known trusted defenders first. We have a 243 00:14:14,880 --> 00:14:18,677 program for that. Other companies will do similar things. Um, 244 00:14:18,760 --> 00:14:22,197 and you have to empower the companies that defend software because there will 245 00:14:22,280 --> 00:14:26,277 be some power plant that no one has to the software for 20 years, and no one 246 00:14:26,360 --> 00:14:28,317 can patch it, and there's a big problem with it, and you have to do something 247 00:14:28,400 --> 00:14:30,917 about that. Um, but 248 00:14:31,000 --> 00:14:35,677 a resilience approach here is, okay, there's this new thing in the world. 249 00:14:35,760 --> 00:14:39,597 There's AI that is really good at exploiting computer systems. Um, let's 250 00:14:39,680 --> 00:14:42,437 use AI to defend it, and that is not a one-company thing. That's going to 251 00:14:42,520 --> 00:14:47,237 require this huge effort. Um, if we go a little bit further, I I think 252 00:14:47,320 --> 00:14:51,517 there will be a uh bio version of this where, 253 00:14:51,600 --> 00:14:54,277 you know, classically people have said, well, we're just going to restrict our 254 00:14:54,360 --> 00:14:57,557 models from being able to develop pathogens. Someone at some point is 255 00:14:57,640 --> 00:15:01,877 going to use some model to develop a pathogen. And the world needs defense 256 00:15:01,960 --> 00:15:05,277 shields against that, detection systems, rapid response treatments, a whole bunch 257 00:15:05,360 --> 00:15:08,957 of other things. And this is not 258 00:15:09,040 --> 00:15:12,397 This doesn't get us off the hook in any way of aligning our systems and building 259 00:15:12,480 --> 00:15:14,277 safe systems. We still have to do that. 260 00:15:14,360 --> 00:15:16,557 Like, we get a time advantage there as 261 00:15:16,640 --> 00:15:18,517 long as we stay at the frontier. 262 00:15:18,600 --> 00:15:23,517 But, we do need the world to like do its thing, society to have this emergent 263 00:15:23,600 --> 00:15:27,197 magic and build these layers of defensive shields. Um there are many 264 00:15:27,280 --> 00:15:30,237 threats besides those two, but that's enough given we have short time. 265 00:15:30,320 --> 00:15:34,317 >> For sure. Um Josh, you have shared some interesting 266 00:15:34,400 --> 00:15:38,957 thoughts with me about how each huge technological shift has produced new 267 00:15:39,040 --> 00:15:41,557 institutions and new democratic mechanisms. 268 00:15:41,640 --> 00:15:43,757 >> Mhm. >> And also you've uh been thinking a lot 269 00:15:43,840 --> 00:15:45,597 about new institutions that might emerge 270 00:15:45,680 --> 00:15:48,437 now. Um how are you 271 00:15:48,520 --> 00:15:51,077 What are What are your kind of 272 00:15:51,160 --> 00:15:55,517 What are your most exciting ideas and what what do you really like to think 273 00:15:55,600 --> 00:15:59,037 about in terms of the collective response to superintelligence? 274 00:15:59,120 --> 00:16:01,357 >> Yeah, certainly. Um so so one thing I'll 275 00:16:01,440 --> 00:16:05,277 say first on the subject of resilience just as grounding, a lot of the problems 276 00:16:05,360 --> 00:16:09,797 that we're concerned about AI creating new externalities for are problems and 277 00:16:09,880 --> 00:16:13,677 vulnerabilities that exist in the world regardless of whether AI is present and 278 00:16:13,760 --> 00:16:16,237 AI just increases the urgency of action. 279 00:16:16,320 --> 00:16:20,757 But coming back to COVID, we found back then that everyone had a much deeper 280 00:16:20,840 --> 00:16:25,117 dependency on the functioning of supply chains than most people were previously 281 00:16:25,200 --> 00:16:28,437 conscious of. Um supply chains are super important, 282 00:16:28,520 --> 00:16:31,197 supply chains for food, for goods, for for everything that sustains 283 00:16:31,280 --> 00:16:36,157 civilization. Um and also of course uh you know, for for other types of 284 00:16:36,240 --> 00:16:39,837 vulnerabilities like democracy. We've been debating for years how um there are 285 00:16:39,920 --> 00:16:44,117 real risks when people are influencing society sort of inappropriately. 286 00:16:44,200 --> 00:16:48,397 And we're we're worried that AI is going to make these things potentially easier 287 00:16:48,480 --> 00:16:52,117 to attack in the near term because there will be tools at people's disposal that 288 00:16:52,200 --> 00:16:55,037 they haven't had before. Um I'm excited 289 00:16:55,120 --> 00:16:59,477 about the possibility that we can build new institutions and state capacities to 290 00:16:59,560 --> 00:17:02,997 use AI to rectify some of these vulnerabilities. Um we can 291 00:17:03,080 --> 00:17:06,957 systematically identify them with AI in ways we couldn't in the past. We can 292 00:17:07,040 --> 00:17:09,957 systematically close them in ways we couldn't in the past and we can use AI 293 00:17:10,040 --> 00:17:14,357 to scale up efforts to combat certain types of issues uh in in ways where we 294 00:17:14,440 --> 00:17:16,517 can potentially make it too expensive 295 00:17:16,600 --> 00:17:18,117 for attackers to really do something. 296 00:17:18,200 --> 00:17:21,397 So, uh you know, on on cyber and bio, I 297 00:17:21,480 --> 00:17:23,917 am optimistic that maybe we can build an 298 00:17:24,000 --> 00:17:27,117 ecosystem of defenders that all together 299 00:17:27,200 --> 00:17:31,157 can make it so expensive for attackers to try to, you know, run a cyber attack 300 00:17:31,240 --> 00:17:35,437 that they there just won't be that much of an incentive to do it. And if we can 301 00:17:35,520 --> 00:17:39,517 fully implement the the bio resilient side of things, um not just for 302 00:17:39,600 --> 00:17:42,637 pathogens that might impact humans, but uh especially for the food supply chain. 303 00:17:42,720 --> 00:17:44,757 This is one where I have like a hobby horse on this and I'm going to talk 304 00:17:44,840 --> 00:17:47,677 about it every chance I get. I think people under attend the food supply 305 00:17:47,760 --> 00:17:52,077 chain bio risks. Um but we can use AI to make that resilient at scale in a way 306 00:17:52,160 --> 00:17:55,797 that today is cost prohibitive. Um so I'm very excited about, you know, the 307 00:17:55,880 --> 00:18:00,437 things we can build there. >> Yeah. Neat. Um one more question. 308 00:18:00,520 --> 00:18:04,797 When we talk about kind of the individual transition for many people, um 309 00:18:04,880 --> 00:18:08,157 what work looks like, where value shifts to. I know you've been thinking about 310 00:18:08,240 --> 00:18:09,597 that a lot. Um 311 00:18:09,680 --> 00:18:12,797 how how what do you see happening as 312 00:18:12,880 --> 00:18:15,677 folks kind of transition to other ways 313 00:18:15,760 --> 00:18:18,597 of creating value in an AI economy? 314 00:18:18,680 --> 00:18:21,797 >> Oh. Oh goodness. That's very broad. Um 315 00:18:21,880 --> 00:18:24,837 I I think people will have 316 00:18:24,920 --> 00:18:29,197 a lot more uh opportunity to exercise agency. Um 317 00:18:29,280 --> 00:18:33,917 you know, if you can uh start a new business and have a team 318 00:18:34,000 --> 00:18:37,117 of AIs that handle all of the functions of putting the business together that 319 00:18:37,200 --> 00:18:40,437 you have no expertise in yourself. Um you can get something off the ground an 320 00:18:40,520 --> 00:18:43,037 awful lot easier. And so, you know, there there are a lot of ways that the 321 00:18:43,120 --> 00:18:46,997 economy just fundamentally changes when you get people access and tools to help 322 00:18:47,080 --> 00:18:48,997 them do more things than they could have before. 323 00:18:49,080 --> 00:18:53,077 >> Yeah, for sure. Um Sam, similar question. You have so much 324 00:18:53,160 --> 00:18:56,877 experience with startups. Running them, managing Y Combinator, or 325 00:18:56,960 --> 00:18:59,317 just being in the ecosystem for so long. 326 00:18:59,400 --> 00:19:04,597 What um how do you see startups changing and like our potential to realize new 327 00:19:04,680 --> 00:19:07,477 ideas changing with AI? >> I'm obsessed with trying to explore the 328 00:19:07,560 --> 00:19:11,557 space. I don't know exactly what it's going to look like, but I this idea of 329 00:19:11,640 --> 00:19:16,477 one person or a very small team being able to create an entire startup 330 00:19:16,560 --> 00:19:18,757 as Josh was talking about pretty quickly. 331 00:19:18,840 --> 00:19:23,717 Um all my instincts are there's something 332 00:19:23,800 --> 00:19:25,637 deep and important to figure out here. 333 00:19:25,720 --> 00:19:30,957 Every time in our industry that the 334 00:19:31,040 --> 00:19:33,877 friction, cost, whatever you want to call it of starting the startup has come 335 00:19:33,960 --> 00:19:37,717 down a lot. Amazing new things have happened. Um you 336 00:19:37,800 --> 00:19:42,077 know, I remember the transition The one of these transitions that I was doing uh 337 00:19:42,160 --> 00:19:43,477 a startup during 338 00:19:43,560 --> 00:19:47,717 uh was when like basically AWS came out 339 00:19:47,800 --> 00:19:51,037 and all of a sudden there was like an idea of a cloud and a small startup 340 00:19:51,120 --> 00:19:53,677 didn't have to go do all the crazy things you used to have to do. 341 00:19:53,760 --> 00:19:55,797 >> Manage his racks in the closet. Yeah. 342 00:19:55,880 --> 00:20:01,077 >> And that was like an amazing change to what you could do as a small startup 343 00:20:01,160 --> 00:20:03,877 with a few people. This one that's coming is much bigger and there have 344 00:20:03,960 --> 00:20:07,077 been several in between. But uh 345 00:20:07,160 --> 00:20:10,917 I really want to find out what it looks like when a startup is 346 00:20:11,000 --> 00:20:14,157 you know, two or three people and a ton of GPUs and you can just >> Yeah. 347 00:20:14,240 --> 00:20:17,557 >> you can really democratize who can start a startup. 348 00:20:17,640 --> 00:20:19,477 >> Yeah. Yeah. Yeah, it's that 349 00:20:19,560 --> 00:20:21,317 democratization aspect and it gets down 350 00:20:21,400 --> 00:20:25,517 to the widespread availability of AI. Um 351 00:20:25,600 --> 00:20:27,517 how do you What's What's the best frame 352 00:20:27,600 --> 00:20:34,360 for thinking about bringing more people in, democratizing AI access? 353 00:20:35,360 --> 00:20:37,477 >> I think when people talk about democratization of AI, they they mean 354 00:20:37,560 --> 00:20:41,437 two different things. One is share the access 355 00:20:41,520 --> 00:20:45,797 and making sure that everybody gets to use sufficient AI to 356 00:20:45,880 --> 00:20:48,157 improve their own lives, build things for other people, all that. And the 357 00:20:48,240 --> 00:20:51,357 other is a sort of a voice in where it's all going to go. 358 00:20:51,440 --> 00:20:55,917 Uh I think both are very important. Um part of why we do things like this 359 00:20:56,000 --> 00:21:00,397 blueprint are if we're not debating the issues as a 360 00:21:00,480 --> 00:21:02,917 society. Also part of the reason we actually release products in the first 361 00:21:03,000 --> 00:21:06,557 place. People don't have a feel for this if we're not talking about this. 362 00:21:06,640 --> 00:21:10,597 Um that is kind of a prerequisite to people being able to have input, um, but 363 00:21:10,680 --> 00:21:13,757 it's not enough. You also have to have a way that people's input that we listen 364 00:21:13,840 --> 00:21:16,477 and the input is captured back into the into the system. 365 00:21:16,560 --> 00:21:20,997 Um, so that's one that I think is really important and the other is 366 00:21:21,080 --> 00:21:23,237 we need to put 367 00:21:23,320 --> 00:21:25,957 not just services like ChatGPT, but the 368 00:21:26,040 --> 00:21:28,437 real deal high compute valuable services 369 00:21:28,520 --> 00:21:33,237 where people can start a startup or make a scientific discovery or whatever in 370 00:21:33,320 --> 00:21:34,717 broadly into many people's hands. 371 00:21:34,800 --> 00:21:37,717 >> Yeah. Yeah, and that's going to take new 372 00:21:37,800 --> 00:21:42,837 economic models or much cheaper uh, inference to to get it 373 00:21:42,920 --> 00:21:45,757 wider spread, right? And that's an infrastructure problem among many other 374 00:21:45,840 --> 00:21:49,317 problems to solve. >> You know, we we used to talk for years 375 00:21:49,400 --> 00:21:51,677 in OpenAI about when we were going to get through the compute crunch, when we 376 00:21:51,760 --> 00:21:54,517 were going to build like enough compute that we wouldn't be so strapped. I don't 377 00:21:54,600 --> 00:21:58,717 think we ever get out of it. If we do our job, if we keep driving the cost of 378 00:21:58,800 --> 00:22:02,957 intelligence down and the capabilities of intelligence up, I think uh, you 379 00:22:03,040 --> 00:22:06,637 know, effectively if that happens, the demand is uncapped. 380 00:22:06,720 --> 00:22:08,277 And 381 00:22:08,360 --> 00:22:11,397 the worlds where 382 00:22:11,480 --> 00:22:15,597 we don't build enough infrastructure, 383 00:22:15,680 --> 00:22:20,197 I think you get a crazy concentration of power and concentration of compute 384 00:22:20,280 --> 00:22:23,717 because people will just bid the price up and up and up. So, the only thing 385 00:22:23,800 --> 00:22:28,277 that I really believe in as a long-term democratization strategy is to just make 386 00:22:28,360 --> 00:22:32,997 so much AI infrastructure available and make the models so good and so capable 387 00:22:33,080 --> 00:22:35,877 um, that we hope to get to a world where people are like, 388 00:22:35,960 --> 00:22:38,357 "I need help coming up with ideas for what to use all this compute for." I 389 00:22:38,440 --> 00:22:39,557 don't think we will in practice. 390 00:22:39,640 --> 00:22:44,797 >> Yeah. >> Um, but I certainly think that if compute is very limited, 391 00:22:44,880 --> 00:22:47,517 you know, the richest people and the richest companies in the world will just 392 00:22:47,600 --> 00:22:50,277 sort of bid up the price to a kind of extreme degree. 393 00:22:50,360 --> 00:22:52,557 >> It'll be another kind of scarcity that 394 00:22:52,640 --> 00:22:55,437 that is um, monopolized. Where So, this 395 00:22:55,520 --> 00:22:59,717 is a more data centers is actually a very egalitarian 396 00:22:59,800 --> 00:23:04,837 um, initiative in the sense that they can make AI access more widespread. 397 00:23:04,920 --> 00:23:08,277 >> I I would look at many examples throughout history. You know, one of the 398 00:23:08,360 --> 00:23:12,557 best things that we ever did for really increasing people's quality of life was 399 00:23:12,640 --> 00:23:14,997 to drive the price of electricity way down. 400 00:23:15,080 --> 00:23:17,117 >> Mhm. >> Price of energy broadly way down. 401 00:23:17,200 --> 00:23:20,037 >> Mhm. >> Um energy correlates incredibly well 402 00:23:20,120 --> 00:23:22,557 with quality of life, or at least it has for a long time. Maybe now it'll be more 403 00:23:22,640 --> 00:23:26,037 about AI. Um and 404 00:23:26,120 --> 00:23:31,597 by making energy abundant and shockingly cheap relative to what it cost 50, 200 405 00:23:31,680 --> 00:23:35,637 years ago, uh that has done like quite a bit for 406 00:23:35,720 --> 00:23:38,317 lifting the entire world up. I think we need to do the same thing with AI. 407 00:23:38,400 --> 00:23:40,277 >> Mhm. >> And I think that means you need a lot of 408 00:23:40,360 --> 00:23:43,237 it, and just like with energy, you need to innovate new ways to make it much 409 00:23:43,320 --> 00:23:48,797 more affordable. >> Yeah. Can I give give a thought on on this whole 410 00:23:48,880 --> 00:23:51,357 issue as well? I think we've talked a little bit about 411 00:23:51,440 --> 00:23:55,557 uh you know, the broad access to AI, which I think is very important and and 412 00:23:55,640 --> 00:23:58,197 can create like you know, potentially a lot of new 413 00:23:58,280 --> 00:24:01,077 products that will be um very helpful 414 00:24:01,160 --> 00:24:02,997 for the world, very useful for people. 415 00:24:03,080 --> 00:24:05,437 Um I think one thing that, you know, we 416 00:24:05,520 --> 00:24:07,397 try to think about as well 417 00:24:07,480 --> 00:24:12,157 in in writing this blueprint is 418 00:24:12,240 --> 00:24:15,717 you know, ensuring that, you know, ordinary people who maybe, you know, 419 00:24:15,800 --> 00:24:19,837 aren't going to uh start start start up necessarily um all of them like aren't 420 00:24:19,920 --> 00:24:22,197 left behind by this technology. Um I 421 00:24:22,280 --> 00:24:26,957 think this is related to to uh something that that we might talk about, which is 422 00:24:27,040 --> 00:24:28,197 kind of 423 00:24:28,280 --> 00:24:31,437 how does AI change the composition of 424 00:24:31,520 --> 00:24:35,437 the economy? Does it uh move it more towards 425 00:24:35,520 --> 00:24:37,917 uh capital or towards like 426 00:24:38,000 --> 00:24:40,397 labor, but labor that that is done by by 427 00:24:40,480 --> 00:24:43,117 AI really. Um and and one of the things 428 00:24:43,200 --> 00:24:48,077 that we talk about in the blueprint is uh how do you monitor modernize the the 429 00:24:48,160 --> 00:24:52,997 the tax base for an economy that is like this uh uh and how do you distribute 430 00:24:53,080 --> 00:24:56,357 kind of uh this prosperity that, you know, will 431 00:24:56,440 --> 00:24:59,877 be created by this technology? Uh how do you make sure that this is prosperity 432 00:24:59,960 --> 00:25:02,637 for everyone and not like wealth for, 433 00:25:02,720 --> 00:25:05,477 you know, a relatively few few people. 434 00:25:05,560 --> 00:25:09,397 And so, this is something that we try to address in in the blueprint, but I'm 435 00:25:09,480 --> 00:25:12,597 curious if we can talk about it here as well. 436 00:25:12,680 --> 00:25:16,797 >> we totally should. A couple of the big ideas that I saw were 437 00:25:16,880 --> 00:25:20,837 have workers co-authoring how AI is deployed in their workspaces. I'd like 438 00:25:20,920 --> 00:25:24,397 to to ask you about that, Josh, and I'd also ask I'd like to ask all you about 439 00:25:24,480 --> 00:25:29,037 more broadly how society can capture the upside. What are the institutional forms 440 00:25:29,120 --> 00:25:31,917 that'll that'll take, but let's start with you, Josh. 441 00:25:32,000 --> 00:25:34,877 >> Sure. Just on the on this compute question for 1 second, I want to say the 442 00:25:34,960 --> 00:25:37,757 compute allocation problem, figuring out 443 00:25:37,840 --> 00:25:42,077 what things we use compute to help people do with AI will probably one of 444 00:25:42,160 --> 00:25:45,597 the most important society-wide questions to navigate over the next few 445 00:25:45,680 --> 00:25:49,117 years while compute is relatively scarce, and we should try to boost the 446 00:25:49,200 --> 00:25:52,997 amount of compute in the world as much and as quickly as we possibly can so we 447 00:25:53,080 --> 00:25:55,917 don't have to have painful trade-off questions where there's some 448 00:25:56,000 --> 00:25:59,357 extraordinary good we could provide to everyone, and we're stuck with a hard 449 00:25:59,440 --> 00:26:01,677 question where someone says, "Well, how are you going to pay for that?" because 450 00:26:01,760 --> 00:26:05,997 the cost of compute is so high. Um on getting workers involved in AI, 451 00:26:06,080 --> 00:26:09,757 um I I actually I kind of want to back up and just acknowledge an elephant in 452 00:26:09,840 --> 00:26:13,197 the room, which is that a lot of workers are concerned about AI. They're worried 453 00:26:13,280 --> 00:26:17,077 about what AI means for them. They are not immediately excited at the prospect 454 00:26:17,160 --> 00:26:19,717 of of figuring out, all right, how are we going to use AI in our workplace? And 455 00:26:19,800 --> 00:26:25,037 they're thinking, "Oh my gosh, is the AI going to replace me?" Um and what I what 456 00:26:25,120 --> 00:26:27,797 I think is sort of the important first step here is that those of us who are 457 00:26:27,880 --> 00:26:30,637 working on AI and who are kind of the stewards for this 458 00:26:30,720 --> 00:26:34,037 have to be putting out things like this this blueprint document where we say, 459 00:26:34,120 --> 00:26:36,997 "Well, here's how we're going to advocate for policies to make sure that 460 00:26:37,080 --> 00:26:41,517 the economy is fair and that you are supported, no matter what." And then, 461 00:26:41,600 --> 00:26:46,637 given that we've made this level of safety net, now we can talk about, you know, 462 00:26:46,720 --> 00:26:49,477 something where where you have confidence in in us, we can talk 463 00:26:49,560 --> 00:26:53,837 together, have a good conversation, Um, we should figure out how do we empower 464 00:26:53,920 --> 00:26:58,117 unions to make wise choices about where and how to use AI. Um, how do we empower 465 00:26:58,200 --> 00:27:01,317 workers to participate in conversations about the acceptable use of AI in the 466 00:27:01,400 --> 00:27:04,957 workplace. I think a lot of folks are rightly concerned about AI surveillance 467 00:27:05,040 --> 00:27:07,637 in the workplace, making sure that workers are a part of the decisions 468 00:27:07,720 --> 00:27:08,917 about those types of things feels very 469 00:27:09,000 --> 00:27:11,877 important. And um, a big push on AI 470 00:27:11,960 --> 00:27:15,397 literacy to ensure that folks um, 471 00:27:15,480 --> 00:27:19,077 you know, get the tools they need to use AI to make their lives better, uh, to 472 00:27:19,160 --> 00:27:22,677 start small businesses, to to do all the kinds of things that, you know, will 473 00:27:22,760 --> 00:27:24,117 help them realize their potential. 474 00:27:24,200 --> 00:27:28,077 >> For sure. Um, what are some institutions that you've 475 00:27:28,160 --> 00:27:33,237 considered that allow everyone to capture some of the upside, Josh? 476 00:27:33,320 --> 00:27:36,117 >> Um, so 477 00:27:36,200 --> 00:27:40,357 let's see. For for new kinds of institutions, I think state capacity to 478 00:27:40,440 --> 00:27:43,957 measure pieces of the economy in, you know, greater granular depth so that 479 00:27:44,040 --> 00:27:46,637 there can be responses if there's, you know, like an economic shift in one 480 00:27:46,720 --> 00:27:49,477 place or another. >> yeah. >> Um, I think AI's actually a very 481 00:27:49,560 --> 00:27:52,357 exciting tool for making that more scalable and less expensive than it 482 00:27:52,440 --> 00:27:53,837 would have been in the past. >> Yeah. 483 00:27:53,920 --> 00:27:57,637 >> Uh, I I also think that there can be more institutions that are kind of in 484 00:27:57,720 --> 00:28:02,397 between corporations and governments, which have very very different levels of 485 00:28:02,480 --> 00:28:05,437 accountability governance-wise. There maybe is like a need for something with 486 00:28:05,520 --> 00:28:09,317 like more in between level of accountability. Um, 487 00:28:09,400 --> 00:28:14,677 that can provide uh, you know, like social safety net type 488 00:28:14,760 --> 00:28:18,557 services or >> Something between a corporate board and the regulator. 489 00:28:18,640 --> 00:28:22,637 >> Yeah, yeah, yeah. Like there's um, 490 00:28:22,720 --> 00:28:25,757 like this can't all just happen in private companies that have very minimal 491 00:28:25,840 --> 00:28:29,717 governance. Uh, and we also don't expect that government, which moves fairly 492 00:28:29,800 --> 00:28:32,597 slowly, is going to do all of it quite quickly. And so we sort of maybe need 493 00:28:32,680 --> 00:28:36,157 some in-between institutions that can help us prototype things. Um, this is 494 00:28:36,240 --> 00:28:39,637 like a little bit spitballing. Uh, and I I I don't think this is like quite 495 00:28:39,720 --> 00:28:42,797 covered in the blueprint, but uh, you know, you asked and so that's I think in 496 00:28:42,880 --> 00:28:44,917 the innovative new institutions that I think we could do. 497 00:28:45,000 --> 00:28:48,197 >> Cool. Um, Sam, institutionally, how are 498 00:28:48,280 --> 00:28:53,920 you envisioning that people might broadly participate in the upside? 499 00:28:56,000 --> 00:28:59,597 >> I think we talked earlier about very broad 500 00:28:59,680 --> 00:29:04,557 access and giving a lot of people a lot of compute. Um, I 501 00:29:04,640 --> 00:29:08,357 you you hear these ideas like universal basic compute or other things with nice 502 00:29:08,440 --> 00:29:13,477 branding, but really what they mean is just like uh 503 00:29:13,560 --> 00:29:16,557 instead of the traditional thinking of we're going to give people, you know, a 504 00:29:16,640 --> 00:29:19,797 monthly stipend or money or whatever when AI does all the jobs, I think it's 505 00:29:19,880 --> 00:29:23,157 way better to say, "Actually, people are pretty good about knowing what they need 506 00:29:23,240 --> 00:29:26,197 and pretty creative about figuring out how to use things." But if people are 507 00:29:26,280 --> 00:29:30,237 boxed out of access to this resource, uh that will be 508 00:29:30,320 --> 00:29:32,717 a a challenge. I do suspect that we're 509 00:29:32,800 --> 00:29:37,477 going to have to make changes to how we tax like in a world where AI is doing 510 00:29:37,560 --> 00:29:40,917 most of the intellectual work in the world or at least of the work of today. 511 00:29:41,000 --> 00:29:43,077 Um, you know, we probably are going to need 512 00:29:43,160 --> 00:29:46,757 to explore some way to tax that instead of taxing human income in the 513 00:29:46,840 --> 00:29:50,197 traditional sense. Um, I suspect that we will need to 514 00:29:50,280 --> 00:29:53,997 provide new kinds of transition assistance, unemployment insurance, 515 00:29:54,080 --> 00:29:57,997 things like that. Um, and I suspect that eventually we will need to think about 516 00:29:58,080 --> 00:30:02,717 how people get to be an owner in the upside of all of this 517 00:30:02,800 --> 00:30:06,317 in new ways. Um you know, capitalism is dependent on a 518 00:30:06,400 --> 00:30:10,077 certain balance between labor and capital and if that gets totally out of 519 00:30:10,160 --> 00:30:13,037 whack, then the current system is not going to work and there'll have to be 520 00:30:13,120 --> 00:30:15,557 some sort of evolution. What that is I 521 00:30:15,640 --> 00:30:19,397 think is a very open question and again 522 00:30:19,480 --> 00:30:22,717 part of the goal here is to throw out some ideas, but there's many more. 523 00:30:22,800 --> 00:30:27,557 Um and I will always leave some room and say maybe we're wrong and maybe no 524 00:30:27,640 --> 00:30:30,877 change at all is required and somehow this just works differently than we think. 525 00:30:30,960 --> 00:30:34,517 But again, in a spirit of trying to use 526 00:30:34,600 --> 00:30:38,757 the time we have to think and debate, it seems like a good time to start putting 527 00:30:38,840 --> 00:30:41,077 ideas here. >> Can I say something on this maybe we're 528 00:30:41,160 --> 00:30:43,237 wrong aspect? Like I I think one thing 529 00:30:43,320 --> 00:30:45,757 that you know in the in the blueprint we 530 00:30:45,840 --> 00:30:50,677 we have you know proposals around like modernizing the the tax base and around 531 00:30:50,760 --> 00:30:54,597 like uh we talk about maybe even a 32-hour work 532 00:30:54,680 --> 00:30:56,677 week and and these types of things. I 533 00:30:56,760 --> 00:31:01,717 think there's there's something um important here about 534 00:31:01,800 --> 00:31:04,757 uh trying to create counter-cyclical 535 00:31:04,840 --> 00:31:10,717 measures where you know conditional on disruption from uh from AI we have kind 536 00:31:10,800 --> 00:31:15,237 of uh additional like unemployment insurance uh we have these measures like 537 00:31:15,320 --> 00:31:19,917 the um 32-hour work week but that we um 538 00:31:20,000 --> 00:31:24,877 it's I think fairly important to me that you know some of these measures uh 539 00:31:24,960 --> 00:31:27,797 maybe are maybe some of these measures are good in the current world but I 540 00:31:27,880 --> 00:31:30,677 think many of them would be quite disruptive and we're really talking 541 00:31:30,760 --> 00:31:35,877 about a world uh that uh that that changes a lot and so like to me 542 00:31:35,960 --> 00:31:37,397 institutionally something that we need 543 00:31:37,480 --> 00:31:41,557 is kind of um some thinking about 544 00:31:41,640 --> 00:31:45,757 what are potential disruptions that could occur from AI and 545 00:31:45,840 --> 00:31:50,277 what are things that we can implement as we as we see those coming 546 00:31:50,360 --> 00:31:54,037 uh to kind of uh counter the disruptions and uh 547 00:31:54,120 --> 00:31:58,637 distribute benefits uh broadly uh at that time. Um 548 00:31:58,720 --> 00:32:01,357 >> Yeah and I saw one of the ideas in the report was portable benefits since 549 00:32:01,440 --> 00:32:04,957 benefits are so linked to employers in America now. It sounded like there were 550 00:32:05,040 --> 00:32:07,197 a lot of >> Correct. Yeah yeah. And this was this 551 00:32:07,280 --> 00:32:11,757 one I think an example of the one of the more kind of uh US-focused uh proposals 552 00:32:11,840 --> 00:32:16,157 of course uh but um uh but yeah >> it's a great idea. I think it's insane 553 00:32:16,240 --> 00:32:20,597 we don't already have that and that like the way that the US benefits world has 554 00:32:20,680 --> 00:32:22,957 evolved is really bad but I think it's a great idea. 555 00:32:23,040 --> 00:32:26,037 >> No no one should lose their health care if they lose their job. Like that just 556 00:32:26,120 --> 00:32:30,477 shouldn't happen. >> Agreed. Um so Adrian from inside the 557 00:32:30,560 --> 00:32:34,437 research organization you're seeing this since acceleration it's real for you you 558 00:32:34,520 --> 00:32:39,157 can see some some um scientific um kind of 559 00:32:39,240 --> 00:32:41,957 progress that's being made with these models. 560 00:32:42,040 --> 00:32:45,517 Um what's what's our We want institutions. We want 561 00:32:45,600 --> 00:32:47,317 society to keep pace with technology. 562 00:32:47,400 --> 00:32:50,397 What what do you think the window is for adaptation? 563 00:32:50,480 --> 00:32:54,797 >> So, you know, it's it's a Well, I was going to say it's hard to 564 00:32:54,880 --> 00:32:58,877 put a number. I would say that there's a lot of uncertainty about these numbers. 565 00:32:58,960 --> 00:33:01,757 Uh we've talked uh I think about 566 00:33:01,840 --> 00:33:06,917 uh having an automated researcher in 2028 or late 2028. Uh and I I want 567 00:33:07,000 --> 00:33:08,637 >> 2028 is the official goal. >> What's that? 568 00:33:08,720 --> 00:33:12,997 >> March of 2028 is the >> March, thank you. Um uh and 569 00:33:13,080 --> 00:33:17,757 I I think one useful thing to to think about here is once you have this 570 00:33:17,840 --> 00:33:20,797 automated researcher, which is an automated like AI researcher capable of 571 00:33:20,880 --> 00:33:23,557 doing AI research, you potentially have kind of like a 572 00:33:23,640 --> 00:33:27,397 double whammy of disruption, I would say. Like, first of all, you have a 573 00:33:27,480 --> 00:33:30,437 model that's capable of advanced 574 00:33:30,520 --> 00:33:34,517 cognitive work, clearly, which which AI research is. And so, that in itself is a 575 00:33:34,600 --> 00:33:37,037 disruption. It may accelerate 576 00:33:37,120 --> 00:33:40,517 uh further AI progress. And so, um 577 00:33:40,600 --> 00:33:44,517 you know, I I can't tell you, you know, after that point exactly how much 578 00:33:44,600 --> 00:33:48,477 progress we'll have made like a year from then, but it's probably, you know, 579 00:33:48,560 --> 00:33:52,557 more than the the pace of progress that we've been making so far. And so, uh 580 00:33:52,640 --> 00:33:55,477 this is kind of the the type of window that uh that we're talking about, I 581 00:33:55,560 --> 00:33:58,517 mean, you. >> Yeah, thank you. Okay, so we are at the 582 00:33:58,600 --> 00:34:02,437 point in the conversation where we open up questions. It's not just me anymore. 583 00:34:02,520 --> 00:34:05,117 It's uh members of the community. So, 584 00:34:05,200 --> 00:34:08,757 I've got one here. Um it's from Svetlana 585 00:34:08,840 --> 00:34:11,677 Romanova. As AI becomes more capable, 586 00:34:11,760 --> 00:34:15,797 what which human qualities do you think will matter most in the future? I'd like 587 00:34:15,880 --> 00:34:18,477 to ask each of you one by one, Josh. 588 00:34:18,560 --> 00:34:22,117 >> Um you know, I think there are human qualities that are timeless and that 589 00:34:22,200 --> 00:34:27,797 will always matter. Uh character, commitment, effort, um compassion. 590 00:34:27,880 --> 00:34:29,117 I I think they're going to matter a lot. 591 00:34:29,200 --> 00:34:33,437 >> Mhm. Yeah. Sam. >> All of those, creativity, understanding 592 00:34:33,520 --> 00:34:36,117 what other people want, but I will share a recent anecdote that really struck 593 00:34:36,200 --> 00:34:40,637 home for me that things don't quite go the same way. I went to my first robot cafe 594 00:34:40,720 --> 00:34:43,437 for the first like I was so excited to try. I thought I was going to love it. 595 00:34:43,520 --> 00:34:46,357 >> Mhm. >> And it was the most underwhelming 596 00:34:46,440 --> 00:34:49,957 experience. And I thought I was someone that did not need like the barista at 597 00:34:50,040 --> 00:34:52,957 Starbucks to smile at me and say hi and ask how my day was going. I really 598 00:34:53,040 --> 00:34:57,117 thought I was like didn't care about that. It turns out that I really want 599 00:34:57,200 --> 00:34:59,997 that and walking in to like push on the screen >> Mhm. 600 00:35:00,080 --> 00:35:02,917 >> and have the robot do the thing and give you a delicious cup of coffee 601 00:35:03,000 --> 00:35:07,317 >> Yeah. >> was like a deeply unfulfilling I don't want this experience. 602 00:35:07,400 --> 00:35:09,357 >> Yeah. >> And I thought I wouldn't have cared. 603 00:35:09,440 --> 00:35:12,837 >> I totally just those small interactions throughout the day. I 604 00:35:12,920 --> 00:35:15,437 I really appreciate them, too. Okay. 605 00:35:15,520 --> 00:35:18,957 Here Here's one. Should those >> is >> Oh, that's fine. That's fine. 606 00:35:19,040 --> 00:35:20,757 >> No, go for it. >> Well, I I mean I think what I was going 607 00:35:20,840 --> 00:35:23,797 to say is a little bit along the lines of of what Sam said. And And I believe 608 00:35:23,880 --> 00:35:27,917 it's in the blueprint like uh humans 609 00:35:28,000 --> 00:35:29,997 need each other. Like I think we care 610 00:35:30,080 --> 00:35:35,877 about other humans. Um in fact, you know, to some extent uh one of the most 611 00:35:35,960 --> 00:35:41,357 uh uh scary things with the development of of technology and and social media, 612 00:35:41,440 --> 00:35:46,237 video games, and stuff like that is like maybe uh that is gotten us to lose a 613 00:35:46,320 --> 00:35:48,917 little bit of the connection that that we used to have. But I I I still think 614 00:35:49,000 --> 00:35:52,477 that it's something that matters tremendously to people and that they 615 00:35:52,560 --> 00:35:55,517 will recognize this more and more in fact uh 616 00:35:55,600 --> 00:36:00,437 as as AI becomes uh becomes more advanced and can do some of some of 617 00:36:00,520 --> 00:36:04,277 these other tasks that don't require human connection. And so uh that's like 618 00:36:04,360 --> 00:36:07,277 one big thing that I believe will um 619 00:36:07,360 --> 00:36:09,517 will expand. It seems like a good thing 620 00:36:09,600 --> 00:36:14,677 to me, right? That like this is um this can be of course like a type of work, 621 00:36:14,760 --> 00:36:18,877 right? You know, nursing and and uh and all 622 00:36:18,960 --> 00:36:23,197 these these types of works in the care economy, teaching. Um 623 00:36:23,280 --> 00:36:27,157 and but you know, it's also just important to to our lives, right? And I 624 00:36:27,240 --> 00:36:31,717 think that's to me like going to be the the big quality, like how good you are 625 00:36:31,800 --> 00:36:35,957 as a person to other people. >> Yes, I agree. Um okay, so in America 626 00:36:36,040 --> 00:36:37,517 things like health care, child care, and 627 00:36:37,600 --> 00:36:40,677 elder care are very expensive. Um here's 628 00:36:40,760 --> 00:36:43,397 a question. How can AI expand access to 629 00:36:43,480 --> 00:36:47,237 those for everyday people? Josh? 630 00:36:47,320 --> 00:36:50,837 >> Um one thing I am so excited about is 631 00:36:50,920 --> 00:36:55,597 the way that AI can help provide the best uh health care in the world to 632 00:36:55,680 --> 00:36:58,557 everybody. Um I've heard a lot of stories from 633 00:36:58,640 --> 00:37:02,397 folks navigating the health care system that they didn't know where to go, um 634 00:37:02,480 --> 00:37:04,557 how to navigate the insurance, 635 00:37:04,640 --> 00:37:09,437 uh what specialist to talk to, and you hear stories of people bouncing around 636 00:37:09,520 --> 00:37:12,517 for a diagnosis for years and years and not getting anywhere. You hear about 637 00:37:12,600 --> 00:37:16,117 folks who are who are stuck in a health care system where even if you have the 638 00:37:16,200 --> 00:37:20,437 most caring, compassionate nurses and doctors, there's not enough time to give 639 00:37:20,520 --> 00:37:23,717 everyone the best quality care. And I think that AI is going to make it 640 00:37:23,800 --> 00:37:27,637 possible to deliver the best quality care at scale. I don't think it's going 641 00:37:27,720 --> 00:37:31,037 to replace doctors. I think it's going to make their workloads manageable, and 642 00:37:31,120 --> 00:37:33,557 I think it's going to make it possible for patients to get the best experience 643 00:37:33,640 --> 00:37:35,557 possible. >> Yeah. I agree with that. A lot of 644 00:37:35,640 --> 00:37:39,157 patient empowerment out there. So, yeah. 645 00:37:39,240 --> 00:37:43,877 >> Uh we have all told stories many times of things we've seen on uh social media 646 00:37:43,960 --> 00:37:47,117 about people having this like amazing health care experience. Uh 647 00:37:47,200 --> 00:37:49,637 I don't have anything that amazing, but I'll tell my own because at least it 648 00:37:49,720 --> 00:37:53,757 happened to me. Uh I recently got a blood test. Uh there were like nothing 649 00:37:53,840 --> 00:37:57,317 seriously wrong, but a few markers are just like kind of out of their range, 650 00:37:57,400 --> 00:37:59,037 and you know, you kind of scan down. 651 00:37:59,120 --> 00:38:01,917 There's like 100 things, and you just look at the list of new tests and the 652 00:38:02,000 --> 00:38:04,877 ones that are like a little bit out of range. I asked my doctor, he was like, 653 00:38:04,960 --> 00:38:07,637 uh you know, probably those are all close enough, it's fine. I put it in 654 00:38:07,720 --> 00:38:10,557 ChatGPT, it said, yeah, you're fine, but like here's what's going on, take this 655 00:38:10,640 --> 00:38:12,957 one supplement, get your blood test again in a month. 656 00:38:13,040 --> 00:38:15,877 >> Mhm. >> You should be okay. And it did. Again, I 657 00:38:15,960 --> 00:38:20,397 wasn't like that sick, I wasn't but like the fact that I could just like upload 658 00:38:20,480 --> 00:38:24,197 my blood test and instantly get the right answer. For like a kind of complex thing. 659 00:38:24,280 --> 00:38:27,837 >> Yeah. >> Was an amazing experience. Uh and I think there will be many things like 660 00:38:27,920 --> 00:38:31,757 that across health care education and all these other areas, elder care. You 661 00:38:31,840 --> 00:38:34,397 know, that's one where I think we want people doing that. 662 00:38:34,480 --> 00:38:37,197 >> Very much. Yeah. >> But there will be a lot of ways we can 663 00:38:37,280 --> 00:38:38,997 really drive down the cost of >> Yeah. 664 00:38:39,080 --> 00:38:40,797 >> um health care and education and things like that. 665 00:38:40,880 --> 00:38:43,077 >> For sure. >> And even personalized learning like it 666 00:38:43,160 --> 00:38:47,557 can still be humans but you can figure out how to teach individuals, right? Um 667 00:38:47,640 --> 00:38:48,837 you know, how do you think about it? 668 00:38:48,920 --> 00:38:52,837 >> Yeah, I mean, you know, I would say similar things of course. I mean, 669 00:38:52,920 --> 00:38:56,517 another basic thing in terms of health care, you know, that I hope at least is 670 00:38:56,600 --> 00:39:01,517 is simply that, you know, AI will be able to help medical research and that, 671 00:39:01,600 --> 00:39:04,957 you know, that that's like a basic thing that that would make 672 00:39:05,040 --> 00:39:09,637 health care better for people. But also, you know, I just talked about 673 00:39:09,720 --> 00:39:13,637 the care economy and and I think to some extent, you know, to the extent that AI 674 00:39:13,720 --> 00:39:15,717 can um 675 00:39:15,800 --> 00:39:18,597 facilitate some of the of the more, you 676 00:39:18,680 --> 00:39:20,877 know, bureaucratic, frankly, aspects of 677 00:39:20,960 --> 00:39:24,437 of health care and and help us have more 678 00:39:24,520 --> 00:39:27,637 people actually, you know, providing the 679 00:39:27,720 --> 00:39:31,597 the actual the actual health care 680 00:39:31,680 --> 00:39:34,757 to to individuals. That that seems like 681 00:39:34,840 --> 00:39:38,957 like a a positive thing. Like it's not AI would be providing 682 00:39:39,040 --> 00:39:44,397 would be doing this. We would be freeing up people to to actually do this work. 683 00:39:44,480 --> 00:39:46,797 >> Yeah. >> We can hope. >> We we've talked a lot about the 684 00:39:46,880 --> 00:39:50,797 capability overhang this year. How it AI has 685 00:39:50,880 --> 00:39:54,917 capable of so many things that most folks are not leaning into it for. And I 686 00:39:55,000 --> 00:39:58,237 sometimes suspect that it's because they're resigned to the world like it 687 00:39:58,320 --> 00:40:02,277 is, right? I think PG calls it schlepp blindness, right? So they're they're 688 00:40:02,360 --> 00:40:06,797 they have ceased to consider that something better is possible. Um 689 00:40:06,880 --> 00:40:08,637 so I think they're going to start 690 00:40:08,720 --> 00:40:14,077 leaning in more, right? Um and and I think when they lean in that 691 00:40:14,160 --> 00:40:17,197 their behavior is actually what will change society as much as any 692 00:40:17,280 --> 00:40:22,117 technological breakthrough. Just that moment of adoption. Um as you in your 693 00:40:22,200 --> 00:40:24,917 lives what are the moments where you've seen 694 00:40:25,000 --> 00:40:26,677 somebody kind of light up and realize, 695 00:40:26,760 --> 00:40:33,477 oh I I can do this. I don't have to live resigned anymore to the old ways? 696 00:40:33,560 --> 00:40:35,957 >> Um wait, I've taken a lot of questions first. Adrian, do you want to take a 697 00:40:36,040 --> 00:40:39,237 crack at this? >> Now you get time to think about it. 698 00:40:39,320 --> 00:40:42,797 >> Oh my god. Wow. Well, >> Yeah, putting you on the spot. 699 00:40:42,880 --> 00:40:46,557 >> Yeah, maybe I maybe I maybe I do want time to think about this, but 700 00:40:46,640 --> 00:40:50,480 you know, I mean to your point, I think it 701 00:40:50,840 --> 00:40:54,797 I think it's definitely the case that uh that people take a while to adapt to 702 00:40:54,880 --> 00:40:56,037 new technologies. I think to some 703 00:40:56,120 --> 00:40:59,197 extent, you know, the the capability 704 00:40:59,280 --> 00:41:04,157 overhang might be large in terms of capabil- capabilities versus how much 705 00:41:04,240 --> 00:41:05,757 people are actually using them. 706 00:41:05,840 --> 00:41:08,757 Um I think there is an extent to which 707 00:41:08,840 --> 00:41:10,517 that's a function 708 00:41:10,600 --> 00:41:13,517 of how fast the capabilities are 709 00:41:13,600 --> 00:41:18,477 improving versus how fast people are used to, you know, things getting uh 710 00:41:18,560 --> 00:41:21,077 things getting better. >> I have a favorite to mention. 711 00:41:21,160 --> 00:41:24,117 >> Yeah. >> My favorite There are many options here, 712 00:41:24,200 --> 00:41:25,797 but my favorite of all is watching 713 00:41:25,880 --> 00:41:31,157 parents who are coders by training watch watching the parent watch their kids use 714 00:41:31,240 --> 00:41:33,357 Codex >> Mhm. >> for the first time. 715 00:41:33,440 --> 00:41:38,277 >> Mhm. >> And uh a kid who has a bunch of ideas and no idea about like what the 716 00:41:38,360 --> 00:41:41,757 traditional limits are or what would be hard or easy, just start describing a 717 00:41:41,840 --> 00:41:44,757 video game and having Codex make it. 718 00:41:44,840 --> 00:41:49,117 Uh And the the kind of like creative journey the kid goes through. I mean, 719 00:41:49,200 --> 00:41:51,237 often you see the kid doing this mostly by voice. 720 00:41:51,320 --> 00:41:52,957 >> Yeah. >> And the parent is just like, that's not 721 00:41:53,040 --> 00:41:55,757 going to work, and then it works, and then they're like, wow, my kid is going 722 00:41:55,840 --> 00:42:00,037 to grow up in a world where he or she just like expects this this happens. 723 00:42:00,120 --> 00:42:03,197 Like and I kind of still like I wouldn't even thought to try that cuz I would've 724 00:42:03,280 --> 00:42:04,597 been so certain it didn't work. 725 00:42:04,680 --> 00:42:07,477 >> Yeah. >> So like watching watching it through the parent's eyes 726 00:42:07,560 --> 00:42:10,117 the kid do it for the first time, especially if the parent is a software 727 00:42:10,200 --> 00:42:12,037 engineer by training, is awesome. 728 00:42:12,120 --> 00:42:15,197 >> Yeah, especially. I mean, this is a tale as old as time, right? Like the kids 729 00:42:15,280 --> 00:42:18,957 always know how to use the the VCR in the '80s or whatever, right? 730 00:42:19,040 --> 00:42:23,037 Uh and yeah. Interesting. >> That's That's funny. 731 00:42:23,120 --> 00:42:25,877 >> Um I just on the capability overhang and 732 00:42:25,960 --> 00:42:30,077 how fast people notice when a capability has arrived, there's an interesting time 733 00:42:30,160 --> 00:42:34,797 scale mismatch where people have like a who who aren't super in the know on AI 734 00:42:34,880 --> 00:42:37,357 have this like distant awareness that something is happening. They know 735 00:42:37,440 --> 00:42:40,797 there's a product out there. Once every few months, they might check it out. 736 00:42:40,880 --> 00:42:44,157 They don't immediately and instinctively probe it to the maximal extent of its 737 00:42:44,240 --> 00:42:47,237 capabilities. Uh and they often don't put it on the 738 00:42:47,320 --> 00:42:49,757 thinking setting. Like they don't know that reasoning models have happened. 739 00:42:49,840 --> 00:42:53,517 They stay on the default chat model that's that's right out there. And so 740 00:42:53,600 --> 00:42:55,917 they wind up with this misperception that things aren't moving as fast as 741 00:42:56,000 --> 00:42:58,997 they are. And you hear people talk about, well, there's hallucinations, 742 00:42:59,080 --> 00:43:02,637 it's slop, it's making mistakes, it's inaccurate. Why would they ever tell us 743 00:43:02,720 --> 00:43:03,957 that it's going to do, you know, these 744 00:43:04,040 --> 00:43:06,917 great things? And uh this like visceral 745 00:43:07,000 --> 00:43:11,397 belief gap is I think an issue that will get overcome when they start to see 746 00:43:11,480 --> 00:43:15,357 other folks and institutions very successfully use AI at sort of the 747 00:43:15,440 --> 00:43:20,197 maximal reasoning settings, at the most capable settings, in ways that are 748 00:43:20,280 --> 00:43:23,877 shocking to them. Um like this video game example, but sort of like at scale 749 00:43:23,960 --> 00:43:28,317 for society as a whole. Uh they're going to see a lot of people get diagnoses 750 00:43:28,400 --> 00:43:32,037 that, you know, they wouldn't have expected that someone could get quickly. 751 00:43:32,120 --> 00:43:34,557 And it's going to update them. And I think I think that's just like an 752 00:43:34,640 --> 00:43:38,317 interesting phenomenon that the the time scale for AI progress is weeks and 753 00:43:38,400 --> 00:43:41,757 months. And the time scale for people to currently checking back is like every 754 00:43:41,840 --> 00:43:45,677 half year or something. And uh yeah, some big change will happen when 755 00:43:45,760 --> 00:43:48,717 people um realize the maximal extent of capabilities today. 756 00:43:48,800 --> 00:43:52,717 >> Yeah. Um I agree. The uh the point you brought up, Sam, 757 00:43:52,800 --> 00:43:57,317 about the kids really illustrates for me what an advantage 758 00:43:57,400 --> 00:44:01,237 creative people have. Like there are some folks that are just kind of a font 759 00:44:01,320 --> 00:44:04,597 of ideas. Many of those ideas have never been realized. Some are scientists, some 760 00:44:04,680 --> 00:44:07,917 are artists, many are children. Um and 761 00:44:08,000 --> 00:44:11,557 it feels like the floodgates are opening 762 00:44:11,640 --> 00:44:14,317 for them to realize more things. 763 00:44:14,400 --> 00:44:18,437 I think you mentioned that you would actually burn through your Codex list, 764 00:44:18,520 --> 00:44:21,157 and you're not having it run all night anymore. 765 00:44:21,240 --> 00:44:24,437 >> We just need to make a model that helps you come up with good new ideas. I 766 00:44:24,520 --> 00:44:28,437 actually think this will be one of the most exciting things to do. I don't 767 00:44:28,520 --> 00:44:31,077 think we're that far away from a model where you can say, "Go look through all 768 00:44:31,160 --> 00:44:34,997 my text messages, all my email, look at my entire computer, 769 00:44:35,080 --> 00:44:39,317 anything you can find about me, and just suggest ideas that I've like gestured at 770 00:44:39,400 --> 00:44:40,997 as fragments or that might be interesting to me." 771 00:44:41,080 --> 00:44:42,357 >> Yeah. >> And then I'll build those. 772 00:44:42,440 --> 00:44:45,917 >> Yeah. Yeah, agreed. A thought partner, I see a lot of people using it like that. 773 00:44:46,000 --> 00:44:47,637 Well, I think we're wrapping up here. 774 00:44:47,720 --> 00:44:50,797 So, thank you all for joining us today, 775 00:44:50,880 --> 00:44:55,557 and thank you, Sam, Josh, Adrian. This has been pretty cool. 776 00:44:55,640 --> 00:44:56,517 >> This is a lot of fun. Thank you. 777 00:44:56,600 --> 00:45:00,437 >> Yeah. So, the ideas discussed may sound 778 00:45:00,520 --> 00:45:04,797 ambitious to you, and they're meant to be. 779 00:45:04,880 --> 00:45:08,837 But, we know that they're also early and exploratory. We're offering them 780 00:45:08,920 --> 00:45:11,237 not as a final plan, but as a starting 781 00:45:11,320 --> 00:45:14,677 point in a very public conversation 782 00:45:14,760 --> 00:45:16,837 with policy makers and everyone in 783 00:45:16,920 --> 00:45:19,637 society to encourage more discussion and 784 00:45:19,720 --> 00:45:23,717 research and debate. OpenAI wants this 785 00:45:23,800 --> 00:45:28,637 conversation to continue. The company, we are inviting feedback 786 00:45:28,720 --> 00:45:34,680 through a new email address. It's newindustrialpolicy.openai.com. 787 00:45:36,040 --> 00:45:38,597 Please send us your best ideas. 788 00:45:38,680 --> 00:45:40,917 We're launching a pilot program of 789 00:45:41,000 --> 00:45:43,997 fellowships and focused research grants 790 00:45:44,080 --> 00:45:46,437 for up to $100,000 in funding and up to 791 00:45:46,520 --> 00:45:48,477 a million in API credits. And we're 792 00:45:48,560 --> 00:45:51,477 convening further discussions at the new 793 00:45:51,560 --> 00:45:56,277 OpenAI workshop opening in Washington, D.C. in May. So, thank you again for 794 00:45:56,360 --> 00:45:59,957 being part of this forum. We appreciate the time and thought that everyone is 795 00:46:00,040 --> 00:46:04,760 bringing to this conversation, and we look forward to continuing it.