1 00:00:08,320 --> 00:00:11,720 Hello everyone. 2 00:00:13,120 --> 00:00:14,877 >> Well, welcome to lunch. Not for you and 3 00:00:14,960 --> 00:00:19,517 me, but welcome to lunch. Um, 4 00:00:19,600 --> 00:00:21,677 uh, I think we've had a, uh, a great day 5 00:00:21,760 --> 00:00:25,117 so far. and uh and I'm honored to have 6 00:00:25,200 --> 00:00:29,517 with me uh Sam Alman uh joining us for 7 00:00:29,600 --> 00:00:31,997 our discussion about 8 00:00:32,080 --> 00:00:34,957 uh AI and and where we're going from 9 00:00:35,040 --> 00:00:37,597 here. So um 10 00:00:37,680 --> 00:00:39,677 so thanks for thanks for joining us. You 11 00:00:39,760 --> 00:00:42,397 have really the greatest countries in 12 00:00:42,480 --> 00:00:44,717 the world all around you. So would you 13 00:00:44,800 --> 00:00:47,757 mind giving us a little history like how 14 00:00:47,840 --> 00:00:50,317 do how do you go from being Sam Alman to 15 00:00:50,400 --> 00:00:54,957 being the head of AI and really at the frontier like sort of walk us through 16 00:00:55,040 --> 00:00:57,037 how you got from there to here? 17 00:00:57,120 --> 00:01:00,077 >> First of all thank you very much for having me. Um as you said this is 18 00:01:00,160 --> 00:01:03,357 greatest countries in the world and it's it's a great honor to get to address all 19 00:01:03,440 --> 00:01:06,717 of you at the same time. Um 20 00:01:06,800 --> 00:01:11,597 I I was always an AI nerd. I was like a real sci-fi nerd as a kid. I thought AI 21 00:01:11,680 --> 00:01:15,517 was the coolest thing. I always wanted to work on it. Um, I never like really 22 00:01:15,600 --> 00:01:19,437 thought I'd actually get to do it. I kind of can't believe this happened to 23 00:01:19,520 --> 00:01:23,277 me, but I I always I always thought it was awesome. I went 24 00:01:23,360 --> 00:01:25,037 to school to study it at the time. 25 00:01:25,120 --> 00:01:28,797 Nothing was working and I kind of gave up on it and I went on this side quest 26 00:01:28,880 --> 00:01:30,397 of entrepreneurship, which was also 27 00:01:30,480 --> 00:01:35,437 great. Um, and then in 2012, 28 00:01:35,520 --> 00:01:38,397 um, everything changed. None of us paid 29 00:01:38,480 --> 00:01:42,717 enough attention, but there was a a real watershed moment where all of a sudden 30 00:01:42,800 --> 00:01:47,037 deep learning started to work and it got better with more compute. And I paid a 31 00:01:47,120 --> 00:01:50,877 lot of attention to that for the next couple of years. And by the time 2015 32 00:01:50,960 --> 00:01:55,117 rolled around, I was like, hey, this is really this is going to happen. Like we 33 00:01:55,200 --> 00:01:58,557 got to take we got to try this could be like the most important thing ever. Uh 34 00:01:58,640 --> 00:01:59,997 and so we thought for a while about what 35 00:02:00,080 --> 00:02:03,597 to do and started OpenAI. Uh and 36 00:02:03,680 --> 00:02:09,117 >> so what year did you start OpenAI? uh the very end of 2015 um we announced it 37 00:02:09,200 --> 00:02:10,557 and then the first day of work was like 38 00:02:10,640 --> 00:02:13,757 January of 2016. 39 00:02:13,840 --> 00:02:17,037 >> So all right so you start in uh in in 40 00:02:17,120 --> 00:02:19,757 2016 and and what are your like what's 41 00:02:19,840 --> 00:02:24,477 the big goal that you start with and then how does that evolve? 42 00:02:24,560 --> 00:02:26,077 So we knew that there was this magic 43 00:02:26,160 --> 00:02:28,157 piece of technology. We knew that we 44 00:02:28,240 --> 00:02:31,997 could apply compute 45 00:02:32,080 --> 00:02:34,397 to a problem and to learn it. And we 46 00:02:34,480 --> 00:02:39,277 knew that the more compute we used, the smarter and more capable the system got. 47 00:02:39,360 --> 00:02:45,037 We didn't really know anything else. We didn't know how we were going to um 48 00:02:45,120 --> 00:02:47,437 what kind of system we were going to build. This is way before the idea of 49 00:02:47,520 --> 00:02:49,277 language models. We were trying to train 50 00:02:49,360 --> 00:02:54,637 a robot hand to do a Rubik's cube. Um we were trying to, you know, show that we 51 00:02:54,720 --> 00:02:57,997 could play video games. And we were really developing the algorithms and 52 00:02:58,080 --> 00:03:00,157 trying to understand how this amazing 53 00:03:00,240 --> 00:03:03,197 property of the universe worked. And and 54 00:03:03,280 --> 00:03:06,317 then not until about 2018 55 00:03:06,400 --> 00:03:08,957 did we start making progress on 56 00:03:09,040 --> 00:03:10,797 unsupervised learning. And then the 57 00:03:10,880 --> 00:03:15,437 first GPT1 model and not until 2020 did 58 00:03:15,520 --> 00:03:17,997 we train GPT3 which was the first model 59 00:03:18,080 --> 00:03:22,637 that I think actually was over some threshold of of usability. Even then, 60 00:03:22,720 --> 00:03:26,477 most people in the world looked at this and said, you know, okay, the model can 61 00:03:26,560 --> 00:03:29,357 like generate a co coherent sentence. 62 00:03:29,440 --> 00:03:31,037 That was really the limit at the time. 63 00:03:31,120 --> 00:03:33,837 Kind of impressive, but like what is this going to what is this going to 64 00:03:33,920 --> 00:03:36,557 mean? And why is why is this going to 65 00:03:36,640 --> 00:03:41,997 like matter to the economy or society or anything else? Um, but we had discovered 66 00:03:42,080 --> 00:03:45,597 by this point these scaling laws which said, well, if we could, you know, apply 67 00:03:45,680 --> 00:03:47,757 like a trillion dollars of compute to 68 00:03:47,840 --> 00:03:52,797 this idea, something quite amazing would happen. And people said, "Well, you 69 00:03:52,880 --> 00:03:55,277 can't apply a trillion dollars of pizza, so it doesn't matter." And we sort of 70 00:03:55,360 --> 00:03:59,277 said, "Why not?" Like, let's try. 71 00:03:59,360 --> 00:04:01,117 So, 72 00:04:01,200 --> 00:04:04,237 you've got the idea and and it's moving 73 00:04:04,320 --> 00:04:07,917 forward, but when when does it come 74 00:04:08,000 --> 00:04:10,957 together that it's really bottling 75 00:04:11,040 --> 00:04:15,677 knowledge? like how how does it 76 00:04:15,760 --> 00:04:19,757 >> different people at OpenAI would give you different answers to this but I 77 00:04:19,840 --> 00:04:22,557 would say mo the kind of consensus to 78 00:04:22,640 --> 00:04:28,920 the degree there is one was the time of GPT4 this was like 79 00:04:29,680 --> 00:04:32,157 I believe this was like March of 2023 80 00:04:32,240 --> 00:04:37,037 but I may be wrong on the timeline there um we had that model for maybe eight 81 00:04:37,120 --> 00:04:40,877 months before it launched so we had had time internally to really get to know it 82 00:04:40,960 --> 00:04:44,957 and that was the time where people even some of the people internally had been 83 00:04:45,040 --> 00:04:47,757 skeptics of this approach would looked 84 00:04:47,840 --> 00:04:51,037 at it and said this is going to go very 85 00:04:51,120 --> 00:04:54,637 far. Um and it hasn't been that long 86 00:04:54,720 --> 00:04:56,157 since that moment you know three and a 87 00:04:56,240 --> 00:04:59,597 half years now. Uh and 88 00:04:59,680 --> 00:05:04,717 and the fact that we now have a system 89 00:05:04,800 --> 00:05:07,517 uh and we're launching our new model soon which is another step forward and 90 00:05:07,600 --> 00:05:12,157 there be many more step forwards coming soon after that. um but that it is so 91 00:05:12,240 --> 00:05:13,837 capable that it is discovering new 92 00:05:13,920 --> 00:05:16,557 knowledge, doing science, able to add 93 00:05:16,640 --> 00:05:19,357 huge economic value, create entire comp 94 00:05:19,440 --> 00:05:24,397 pieces of complex software. Um this is 95 00:05:24,480 --> 00:05:28,557 this was like a very crazy moment. I think it hit us. 96 00:05:28,640 --> 00:05:30,557 Yeah. Over a period of time but centered 97 00:05:30,640 --> 00:05:34,637 around this GPT4 period. 98 00:05:34,720 --> 00:05:38,157 >> So you understand that 99 00:05:38,240 --> 00:05:41,037 you can sort of capture education right? 100 00:05:41,120 --> 00:05:45,677 You capture knowledge. Um, how how 101 00:05:45,760 --> 00:05:52,440 should the the G20 economies think about this? 102 00:05:54,080 --> 00:05:57,837 I I don't want to overstate things, but I'm like very excited about our new 103 00:05:57,920 --> 00:05:59,917 model, so forgive me if I get a little 104 00:06:00,000 --> 00:06:05,480 bit too enthusiastic here. Um I 105 00:06:06,240 --> 00:06:10,557 I think this for example will be the greatest boom in entrepreneurship and 106 00:06:10,640 --> 00:06:11,997 the creation and development of small 107 00:06:12,080 --> 00:06:15,117 businesses um the world has ever seen. 108 00:06:15,200 --> 00:06:17,837 If you have a great idea but you didn't 109 00:06:17,920 --> 00:06:20,797 have the resources or the ability to get 110 00:06:20,880 --> 00:06:25,357 enough capital together or hire enough experts to work on it or to figure out 111 00:06:25,440 --> 00:06:29,037 what it's going to take to invent a new piece of science or manage a complex 112 00:06:29,120 --> 00:06:32,077 supply chain. You can do that with AI 113 00:06:32,160 --> 00:06:36,077 now. Um, and I remember after ChateBT 114 00:06:36,160 --> 00:06:40,477 launched, one of the stories that has stuck with me the most from that moment 115 00:06:40,560 --> 00:06:42,797 was a guy that managed a laundromat. 116 00:06:42,880 --> 00:06:45,757 Apparently, laundromats are usually good businesses. Wouldn't have been obvious 117 00:06:45,840 --> 00:06:49,357 to me. Apparently, they are. Um, but this one was not going well. And he was 118 00:06:49,440 --> 00:06:52,397 using Chat GBT for everything. um to 119 00:06:52,480 --> 00:06:54,637 make his marketing materials to you know 120 00:06:54,720 --> 00:06:56,717 manage give him advice on legal 121 00:06:56,800 --> 00:07:01,757 contracts to manage like relationships with vendors this long list of stuff he 122 00:07:01,840 --> 00:07:03,437 he was really the first person I met 123 00:07:03,520 --> 00:07:07,037 that had figured out how to use AI to 124 00:07:07,120 --> 00:07:11,517 effectively run run a business and this was amazing to me at the time now I know 125 00:07:11,600 --> 00:07:14,957 you all have heard stories about this a bunch and it's no longer surprising but 126 00:07:15,040 --> 00:07:17,837 in 2023 the fact that someone was using 127 00:07:17,920 --> 00:07:22,477 chat GBT broken and embarrassing though it was at the time to let them manage a 128 00:07:22,560 --> 00:07:23,757 business that otherwise they couldn't 129 00:07:23,840 --> 00:07:27,037 have done was was like quite remarkable. 130 00:07:27,120 --> 00:07:31,037 Um in 2025 we saw a real acceleration of 131 00:07:31,120 --> 00:07:36,477 this with coding agents and and white collar work agents. Um I think we'll see 132 00:07:36,560 --> 00:07:39,437 a third thing soon where we'll have these long-term persistent agents that 133 00:07:39,520 --> 00:07:40,877 can work like a real virtual 134 00:07:40,960 --> 00:07:46,157 collaborator constantly helping. But um 135 00:07:46,240 --> 00:07:49,197 it it's it's it's amazing to me what is 136 00:07:49,280 --> 00:07:52,797 happening with the boom in 137 00:07:52,880 --> 00:07:54,637 entrepreneurship and business creation 138 00:07:54,720 --> 00:07:58,557 because of AI. If I were a country um 139 00:07:58,640 --> 00:08:02,077 you know many of you are going to take very different approaches to how you 140 00:08:02,160 --> 00:08:06,237 regulate AI, how you welcome it into your country, how you use it. But for 141 00:08:06,320 --> 00:08:09,837 sure I think it is non-negotiable that you have to use it. the economic growth 142 00:08:09,920 --> 00:08:15,117 and benefit to people that can come from this um the value to a country is too 143 00:08:15,200 --> 00:08:17,997 high to ignore. Uh there will be different ways people try to do this but 144 00:08:18,080 --> 00:08:20,557 this is like you know the smartest 145 00:08:20,640 --> 00:08:24,077 people in the world uh decided to move 146 00:08:24,160 --> 00:08:27,437 to your country to learn your language 147 00:08:27,520 --> 00:08:32,317 um to work very hard on whatever problem you'd like um to go discover new things 148 00:08:32,400 --> 00:08:36,317 that you need and you can put as much of this to work as you want. Some of you 149 00:08:36,400 --> 00:08:39,117 will choose to build data centers. Some of you will choose to rent data centers 150 00:08:39,200 --> 00:08:41,517 from other people because you don't want them in your country. I think all that's 151 00:08:41,600 --> 00:08:44,317 fine. Um, but we want to help. We want 152 00:08:44,400 --> 00:08:47,037 to support not just our company, our 153 00:08:47,120 --> 00:08:49,597 whole industry. Like we want to bring 154 00:08:49,680 --> 00:08:53,597 this incredible magic of, 155 00:08:53,680 --> 00:08:57,997 you know, intelligence in a bottle, education in a bottle um to all of you. 156 00:08:58,080 --> 00:09:00,237 I think this is like this is an 157 00:09:00,320 --> 00:09:02,957 incredible moment for the world. what 158 00:09:03,040 --> 00:09:09,197 people can do with this and the economic 159 00:09:09,280 --> 00:09:11,597 boom that will come with it. The sort of 160 00:09:11,680 --> 00:09:14,157 individual increased quality of life. 161 00:09:14,240 --> 00:09:18,717 People talk about, you know, medical care and what that means, education, 162 00:09:18,800 --> 00:09:20,797 what that means, services that only very 163 00:09:20,880 --> 00:09:25,997 rich people used to have access to, now anybody can have with AI. Um, and the 164 00:09:26,080 --> 00:09:29,757 ability for people to just come up with ideas and get them to fruition so 165 00:09:29,840 --> 00:09:32,637 quickly, uh, is going to be incredible. 166 00:09:32,720 --> 00:09:37,117 Do you do you think that um 167 00:09:37,200 --> 00:09:41,677 your company can create the context 168 00:09:41,760 --> 00:09:45,277 um that people can use to create uh 169 00:09:45,360 --> 00:09:47,117 their outcomes or do you think there'll 170 00:09:47,200 --> 00:09:50,557 be an industry sort of surrounding you 171 00:09:50,640 --> 00:09:54,237 that will contextualize it? Because if you think about it, you say the the 172 00:09:54,320 --> 00:09:57,437 smartest people in the world move in to my neighborhood and they're willing to 173 00:09:57,520 --> 00:10:01,037 work for me. But if I don't know you, that's not really a fun dinner party 174 00:10:01,120 --> 00:10:03,917 having the smartest people in the world sitting with you and they can't really 175 00:10:04,000 --> 00:10:08,237 have a conversation, right? So, how do we how do we think about context that 176 00:10:08,320 --> 00:10:11,757 that's not going to come from us and I don't think that should. Um, we are we 177 00:10:11,840 --> 00:10:14,477 will provide this this engine, you know, 178 00:10:14,560 --> 00:10:19,357 we will provide this incredible 179 00:10:19,440 --> 00:10:24,477 commodity of AI that can you can use for whatever you want. But the people of the 180 00:10:24,560 --> 00:10:27,517 world, and I have complete trust in the people of the world's creativity and 181 00:10:27,600 --> 00:10:29,997 ambition, um will have to figure out 182 00:10:30,080 --> 00:10:32,477 what to ask it to do, what ideas to to 183 00:10:32,560 --> 00:10:34,957 to throw this at, what what problems and 184 00:10:35,040 --> 00:10:37,517 what context in a particular society or 185 00:10:37,600 --> 00:10:42,077 company is important to understand what to do. Um so that won't be our role. I 186 00:10:42,160 --> 00:10:45,917 don't think we'd be good at it even if it were. Um but we will be able to 187 00:10:46,000 --> 00:10:48,717 enable everyone around the world to bring that context and those questions 188 00:10:48,800 --> 00:10:52,477 and those ideas. So 189 00:10:52,560 --> 00:10:55,837 should should the governments of the world 190 00:10:55,920 --> 00:10:59,437 think of AI 191 00:10:59,520 --> 00:11:03,357 and companies your company differently 192 00:11:03,440 --> 00:11:06,237 than they thought about prior technology 193 00:11:06,320 --> 00:11:09,517 meaning the if if what you're bringing 194 00:11:09,600 --> 00:11:12,397 them is you know the smartest people in 195 00:11:12,480 --> 00:11:14,877 the world an educated 196 00:11:14,960 --> 00:11:17,597 capacity then if they look at that as 197 00:11:17,680 --> 00:11:22,477 technology and they uh keep it out of their country or they 198 00:11:22,560 --> 00:11:24,557 constrain it. Are they are they 199 00:11:24,640 --> 00:11:30,840 constraining their capacity to think and grow and build? 200 00:11:31,600 --> 00:11:35,677 I am always tempted to say this time is different. This is really special. You 201 00:11:35,760 --> 00:11:40,637 know this is and I suspect 202 00:11:40,720 --> 00:11:42,477 well to zoom out even further than that 203 00:11:42,560 --> 00:11:46,957 as a kid my understanding of 204 00:11:47,040 --> 00:11:50,877 the world was that there were these few punctuated moments in history each of 205 00:11:50,960 --> 00:11:54,957 which was a very different thing. You had um the agricultural revolution and 206 00:11:55,040 --> 00:11:58,477 then you had the industrial revolution and then you had the computer revolution 207 00:11:58,560 --> 00:12:02,637 and these were all completely different unrelated things and there were not that 208 00:12:02,720 --> 00:12:06,797 many lessons to learn from them and they were best understood in isolation and 209 00:12:06,880 --> 00:12:08,557 even if you zoomed into one pick the 210 00:12:08,640 --> 00:12:10,877 industrial revolution um the right way 211 00:12:10,960 --> 00:12:15,037 to understand that was um 20 or 30 212 00:12:15,120 --> 00:12:18,317 important pieces of technology that were all developed over a period of a couple 213 00:12:18,400 --> 00:12:19,837 hundred years that came together in this 214 00:12:19,920 --> 00:12:23,117 important way. uh 215 00:12:23,200 --> 00:12:26,237 as an adult I look at it as you know it 216 00:12:26,320 --> 00:12:30,237 has been a single revolution a single exponential of technology. Each 217 00:12:30,320 --> 00:12:34,317 generation has built on the scaffolding of the generations before put a new 218 00:12:34,400 --> 00:12:37,917 brick in place. People have been able to see or layer of scaffolding to stick 219 00:12:38,000 --> 00:12:40,877 with the analogy. People have been able to climb and see a little higher and do 220 00:12:40,960 --> 00:12:45,277 the new thing. Um, if you think about what it took to get us to this point 221 00:12:45,360 --> 00:12:49,517 where we can build AI, um, it was all of those previous revolutions uh, stacked 222 00:12:49,600 --> 00:12:54,397 together. And it was the collective discovery of science throughout society 223 00:12:54,480 --> 00:12:56,077 and the global economy that we all 224 00:12:56,160 --> 00:12:59,117 contribute to that made this incredible 225 00:12:59,200 --> 00:13:04,237 thing possible and now happen. And it is tempting whenever you're in the 226 00:13:04,320 --> 00:13:06,637 moment to say this is the last revolution. This is the biggest 227 00:13:06,720 --> 00:13:10,157 revolution. There will be more after this. There will be uh bigger things 228 00:13:10,240 --> 00:13:13,517 after this. people will use AI to invent whatever thing that comes next. It's 229 00:13:13,600 --> 00:13:15,037 probably very difficult for us to 230 00:13:15,120 --> 00:13:19,517 imagine right now. Um and 231 00:13:19,600 --> 00:13:24,157 and I think the right answer is to look at the history of technology as one 232 00:13:24,240 --> 00:13:27,437 continuous exponential. The history of the economy and society as one 233 00:13:27,520 --> 00:13:31,677 continuous exponential. Um and I really mean that. It's not just the technology. 234 00:13:31,760 --> 00:13:35,597 It's this social fabric and the kind of complex structure 235 00:13:35,680 --> 00:13:38,477 of the world that allows this technology to flourish and people to figure out 236 00:13:38,560 --> 00:13:43,037 what to do with it. And you have to embrace it continuously all the way 237 00:13:43,120 --> 00:13:46,237 through. If you miss out on any part of it, um you're not ready for the next 238 00:13:46,320 --> 00:13:49,517 thing that will come. If you if you 239 00:13:49,600 --> 00:13:53,597 don't enable your people and your businesses with AI, uh they will not 240 00:13:53,680 --> 00:13:57,037 invent the next level of the scaffolding. But there will be more 241 00:13:57,120 --> 00:14:01,117 things and I think it is tempting to say this one is different and it clearly is 242 00:14:01,200 --> 00:14:05,597 really important. Um but I would view it as a continuum. 243 00:14:05,680 --> 00:14:07,517 So 244 00:14:07,600 --> 00:14:10,557 we all read about the the various 245 00:14:10,640 --> 00:14:13,677 companies at the frontier. Can you can 246 00:14:13,760 --> 00:14:15,597 you sort of differentiate them for us? 247 00:14:15,680 --> 00:14:18,157 What what do you what do you view open 248 00:14:18,240 --> 00:14:21,517 AI as best at? What what's the you know 249 00:14:21,600 --> 00:14:24,477 your DNA if you will that separates you 250 00:14:24,560 --> 00:14:28,877 from the others and what are you great at? And just give us that sort of from 251 00:14:28,960 --> 00:14:34,237 your perspective. Um 252 00:14:34,320 --> 00:14:36,957 I think from a from what matters to this 253 00:14:37,040 --> 00:14:39,917 room um we are the pragmatic centrists. 254 00:14:40,000 --> 00:14:45,757 We we realize like we want to be we want to be accurate in how we talk 255 00:14:45,840 --> 00:14:47,917 about what we see in the future. We don't want to fall into the trap of 256 00:14:48,000 --> 00:14:51,357 blind optimism. We don't want to fall into the trap of dumerism. This is 257 00:14:51,440 --> 00:14:55,117 clearly complex. There's clearly a combination of both excitement and 258 00:14:55,200 --> 00:14:57,757 anxiety of transformation and risks that 259 00:14:57,840 --> 00:15:02,717 the world has to navigate. Um but 260 00:15:02,800 --> 00:15:05,437 by getting pulled into either extreme we 261 00:15:05,520 --> 00:15:06,957 are not going to successfully figure out 262 00:15:07,040 --> 00:15:09,757 the challenges in front of us. Um we 263 00:15:09,840 --> 00:15:14,717 want to be a reliable partner. Uh we want like we really do view what we are 264 00:15:14,800 --> 00:15:18,397 doing as a platform as a service to the world. We realize that different people 265 00:15:18,480 --> 00:15:23,037 around the world are going to use it very differently and we want to put 266 00:15:23,120 --> 00:15:27,917 sufficient constraints on our system to avoid catastrophic risks. But we really 267 00:15:28,000 --> 00:15:30,557 do want to respect all of your sovereignity and that you're going to 268 00:15:30,640 --> 00:15:35,037 use it in very different ways. And we personally may not always like it. Um, 269 00:15:35,120 --> 00:15:39,357 but I don't like everything that people do with electricity either. And I still 270 00:15:39,440 --> 00:15:40,877 think everybody should get to have it. 271 00:15:40,960 --> 00:15:44,920 Um, so, 272 00:15:45,280 --> 00:15:49,677 oh, and then also I would say like we want the whole global economy to 273 00:15:49,760 --> 00:15:53,517 succeed. We do not want to be the only company. Um, we do not want to suck up 274 00:15:53,600 --> 00:15:56,877 all the value. We do not think that is good for global stability. nor do we 275 00:15:56,960 --> 00:16:00,077 think that's possible for the way that people need to flourish and people need 276 00:16:00,160 --> 00:16:03,197 to stay at the center of this. Oh, I'll get to that one more thing after this. 277 00:16:03,280 --> 00:16:07,437 Um, and we want to like enable every 278 00:16:07,520 --> 00:16:11,037 entrepreneur, every government, every big company in the world to thrive with 279 00:16:11,120 --> 00:16:15,117 this technology. Uh, the last thing I'll say that I think differentiates us from 280 00:16:15,200 --> 00:16:18,717 some of the other companies is we are very firmly and very proudly on team 281 00:16:18,800 --> 00:16:21,277 humanity. Um, we would like to build 282 00:16:21,360 --> 00:16:23,277 tools for people. We would like people's 283 00:16:23,360 --> 00:16:26,317 lives to be better. Um, we think that 284 00:16:26,400 --> 00:16:29,757 people need to be at the center of the 285 00:16:29,840 --> 00:16:31,917 economy and society and global 286 00:16:32,000 --> 00:16:34,877 decision-m um, and that people should 287 00:16:34,960 --> 00:16:37,277 run the future in AI. 288 00:16:37,360 --> 00:16:42,237 >> So, it it seems that entrepreneurship 289 00:16:42,320 --> 00:16:44,637 should be really the fire starter of all 290 00:16:44,720 --> 00:16:47,517 this, right? You're are you the you know 291 00:16:47,600 --> 00:16:49,997 the the kindling of it? I mean maybe 292 00:16:50,080 --> 00:16:53,117 sort of tell me how entrepreneurship and 293 00:16:53,200 --> 00:16:57,677 and uh open AAI sort of work together. 294 00:16:57,760 --> 00:16:59,917 >> Before OpenAI I used to run a startup 295 00:17:00,000 --> 00:17:05,597 accelerator and I had always been interested not always after I came to 296 00:17:05,680 --> 00:17:09,037 college I'd always been interested in entrepreneurship and then having had 297 00:17:09,120 --> 00:17:11,197 this incredible front row seat I really 298 00:17:11,280 --> 00:17:14,957 became convinced that entrepreneurship 299 00:17:15,040 --> 00:17:19,037 was maybe the most important 300 00:17:19,120 --> 00:17:21,837 novel force in all of capitalism. Um, 301 00:17:21,920 --> 00:17:25,757 and I fell in love with it and 302 00:17:25,840 --> 00:17:28,477 watching what new companies were able to 303 00:17:28,560 --> 00:17:32,637 do and watching how 304 00:17:32,720 --> 00:17:37,037 large of a percentage of the new ideas that mattered in the tech industry over 305 00:17:37,120 --> 00:17:40,557 the last, you know, 20 years or whatever came from startups and not big 306 00:17:40,640 --> 00:17:43,597 companies. Um, now having seen us in 307 00:17:43,680 --> 00:17:45,437 other industries, I am a huge believer 308 00:17:45,520 --> 00:17:50,840 in entrepreneurship. I also think that, 309 00:17:51,040 --> 00:17:53,677 you know, like I talked to a lot of people around the world and they would 310 00:17:53,760 --> 00:17:56,717 much rather run a great lifestyle business than go work as like a 311 00:17:56,800 --> 00:18:00,237 corporate cog. And I think that's great, too. Like I think that's just we should 312 00:18:00,320 --> 00:18:03,357 enable that. Um, one of the things I got 313 00:18:03,440 --> 00:18:07,277 excited about early with AI, of course AI is going to transform big companies 314 00:18:07,360 --> 00:18:08,717 and of course AI is going to transform 315 00:18:08,800 --> 00:18:12,717 governments, but what AI can do 316 00:18:12,800 --> 00:18:15,757 for entrepreneurs and for people that 317 00:18:15,840 --> 00:18:18,237 want to take an idea and bring it into 318 00:18:18,320 --> 00:18:23,037 the world quickly um is really quite amazing. When I was running the startup 319 00:18:23,120 --> 00:18:26,317 accelerator, it lasted for three months and the work that 320 00:18:26,400 --> 00:18:30,237 >> it lasted for three months. You were in it for three months and the work that we 321 00:18:30,320 --> 00:18:32,157 expected a startup to accomplish in 322 00:18:32,240 --> 00:18:34,637 three months is now probably doable in 323 00:18:34,720 --> 00:18:38,557 like 17 minutes with codeex. This is 324 00:18:38,640 --> 00:18:42,637 just amazing. The world is not caught up with what this is going to mean. Not 325 00:18:42,720 --> 00:18:47,197 just for the economic value that gets created from that, but how quickly 326 00:18:47,280 --> 00:18:50,637 people can test ideas, build things, get feedback from real customers. We're all 327 00:18:50,720 --> 00:18:53,597 just going to get much better stuff. 328 00:18:53,680 --> 00:18:57,197 So, you use the term uh I want to sort 329 00:18:57,280 --> 00:19:01,357 of flush it out a bit a bit non-negotiable. 330 00:19:01,440 --> 00:19:04,077 Can you maybe uh help everybody 331 00:19:04,160 --> 00:19:09,037 understand what you mean about that and and what that means for each of uh our 332 00:19:09,120 --> 00:19:14,120 partner ministers who are here today with them? 333 00:19:14,800 --> 00:19:17,357 >> Uh again, I'm biased. I'm trying to talk 334 00:19:17,440 --> 00:19:19,277 my book here. Forgive me for this 335 00:19:19,360 --> 00:19:22,077 analogy. Um, I think it would be 336 00:19:22,160 --> 00:19:26,797 approximately as bad of an idea to say we're not going to have AI in our 337 00:19:26,880 --> 00:19:30,397 country as it was to say we're not going to have electricity in our country, you 338 00:19:30,480 --> 00:19:34,797 know, back 100 plus years ago. I think this is something at that level. Um, 339 00:19:34,880 --> 00:19:36,397 this is something that every person and 340 00:19:36,480 --> 00:19:40,237 every business and really the entire 341 00:19:40,320 --> 00:19:43,837 machine of society is going to need to 342 00:19:43,920 --> 00:19:47,037 deliver the quality of life that your 343 00:19:47,120 --> 00:19:51,677 citizens should demand. Now, electricity also came with some 344 00:19:51,760 --> 00:19:55,037 complexities and it took a little while for us to figure out how to make it 345 00:19:55,120 --> 00:19:58,717 safe, but we made fairly rapid progress as a society safe even though it can do 346 00:19:58,800 --> 00:20:02,957 a lot of bad things. Um, and at this point, we barely think about 347 00:20:03,040 --> 00:20:06,957 electricity. You know, we turn these lights on, we expect them to work. You 348 00:20:07,040 --> 00:20:09,997 know, if this the power shut off and I had to scream because this microphone 349 00:20:10,080 --> 00:20:14,477 was not working, like I would be annoyed about that. You I won't go through all 350 00:20:14,560 --> 00:20:16,957 the examples. I see all the phones on the table. Like you just it would be 351 00:20:17,040 --> 00:20:20,477 hard for society to function well without electricity at this point. But 352 00:20:20,560 --> 00:20:24,077 we don't think about it much. We think about you know there's light at night. 353 00:20:24,160 --> 00:20:27,677 That's great. We can hear these people speak in the room without them having to 354 00:20:27,760 --> 00:20:29,997 yell. That's nice. Our phones can do these amazing things for us. We care 355 00:20:30,080 --> 00:20:32,957 about our phones. We don't think too much about the electricity that gets 356 00:20:33,040 --> 00:20:35,677 generated to power them. Um and I think 357 00:20:35,760 --> 00:20:36,877 the same thing is going to happen with 358 00:20:36,960 --> 00:20:40,397 AI. We won't, my prediction is we won't 359 00:20:40,480 --> 00:20:43,197 be talking about AI as much as we do in 360 00:20:43,280 --> 00:20:48,397 a decade from now because we'll just expect it everywhere. You know, like a 361 00:20:48,480 --> 00:20:53,677 kid growing up today will never be smarter than AI, but he or she will also 362 00:20:53,760 --> 00:20:57,997 never have understood a world where every 363 00:20:58,080 --> 00:21:01,757 product and service that they interact with is not really smart and really 364 00:21:01,840 --> 00:21:05,997 capable and really helpful. And because we'll just be so used to that, we won't 365 00:21:06,080 --> 00:21:09,277 think about the AI. will just be like, "Yeah, I want my products to be good." 366 00:21:09,360 --> 00:21:12,477 You know, if I have an idea, I want to be able to like make it right away. I 367 00:21:12,560 --> 00:21:16,077 want this software to be created instantly for me. Um, if I have a 368 00:21:16,160 --> 00:21:17,837 disease, like I expect a cure to get 369 00:21:17,920 --> 00:21:23,277 discovered very quickly. Uh, so I think countries need to need to embrace this. 370 00:21:23,360 --> 00:21:24,477 Again, there's many ways to do it. 371 00:21:24,560 --> 00:21:28,077 People will set different rules. People will decide on what they want to build 372 00:21:28,160 --> 00:21:30,397 versus rent, but I think everyone will 373 00:21:30,480 --> 00:21:33,597 need the this new commodity. 374 00:21:33,680 --> 00:21:38,237 If um if we look forward five years and 375 00:21:38,320 --> 00:21:43,037 and we come back to North Carolina alto together um 376 00:21:43,120 --> 00:21:48,840 what what will be holding us back do you think in your opinion? 377 00:21:50,160 --> 00:21:53,597 Well, there are clearly challenges that 378 00:21:53,680 --> 00:21:55,837 we have to get right along the way. 379 00:21:55,920 --> 00:22:00,317 There will be specifics. For example, I'm sure cyber security is a top-of- 380 00:22:00,400 --> 00:22:03,437 mind issue for many of you. Uh we work with many of the governments in the 381 00:22:03,520 --> 00:22:05,837 room. Uh we work with the state of North 382 00:22:05,920 --> 00:22:08,157 Carolina. Uh we work with companies big 383 00:22:08,240 --> 00:22:12,637 and small and we are 384 00:22:12,720 --> 00:22:16,957 I think we have a big challenge in front of us like to not to not try to sidestep 385 00:22:17,040 --> 00:22:20,877 this one. I think some things are going to go very wrong with cyber security 386 00:22:20,960 --> 00:22:25,197 unless people act quite urgently. There will be other challenges in the next 387 00:22:25,280 --> 00:22:28,397 five years. People talk about uh biocurity and the the things we're going 388 00:22:28,480 --> 00:22:31,997 to face there. um 389 00:22:32,080 --> 00:22:33,837 there will be bigger ones yet to come 390 00:22:33,920 --> 00:22:35,757 and I think if we don't successfully 391 00:22:35,840 --> 00:22:39,037 navigate those um 392 00:22:39,120 --> 00:22:41,037 society will not be able to adopt AI to 393 00:22:41,120 --> 00:22:44,477 the degree or to the speed with which 394 00:22:44,560 --> 00:22:47,677 people deserve. So getting 395 00:22:47,760 --> 00:22:51,837 successfully navigating the risks and downsides in front of us is something 396 00:22:51,920 --> 00:22:55,517 that could go very wrong and I think will set this technology back could set 397 00:22:55,600 --> 00:22:58,717 this technology back a great deal. Um, 398 00:22:58,800 --> 00:23:00,157 another thing that could go wrong is too 399 00:23:00,240 --> 00:23:05,037 much concentration of power. Um, 400 00:23:05,120 --> 00:23:10,317 AI should be in many ways AI should be an equalizing force in the world. You 401 00:23:10,400 --> 00:23:13,437 talked about what it means to have like a reset on the educational capacity 402 00:23:13,520 --> 00:23:16,877 available to everybody. Um, you can also 403 00:23:16,960 --> 00:23:21,437 see worlds where AI concentrates because 404 00:23:21,520 --> 00:23:24,957 some people make early investments and others don't and there's, you know, bad 405 00:23:25,040 --> 00:23:28,877 inequities with comput or whatever. uh that'd be bad. So I think if we fail to 406 00:23:28,960 --> 00:23:31,677 make AI abundant, it ends up being 407 00:23:31,760 --> 00:23:35,917 something that is very hotly competed over, rich people spend a huge amount of 408 00:23:36,000 --> 00:23:40,717 money on and um 409 00:23:40,800 --> 00:23:44,957 that would be a bad outcome. So I think we need to make it abundant so that we 410 00:23:45,040 --> 00:23:48,877 get the the benefits of lifting everybody up and not much worsening 411 00:23:48,960 --> 00:23:52,157 inequality. >> Right. As you said, if if the smartest 412 00:23:52,240 --> 00:23:54,397 people in the world learned your 413 00:23:54,480 --> 00:23:56,717 language and all agreed to move to your 414 00:23:56,800 --> 00:23:59,357 country and work on whatever you wanted 415 00:23:59,440 --> 00:24:02,157 them to work on, that that has to be the 416 00:24:02,240 --> 00:24:07,277 most incredible thing. Do you think that 417 00:24:07,360 --> 00:24:10,957 since you'll have all the smartest people speaking all those languages, 418 00:24:11,040 --> 00:24:12,717 can't they figure out a way do you think 419 00:24:12,800 --> 00:24:15,597 over time to deliver the same amount of 420 00:24:15,680 --> 00:24:19,197 compute more inexpensively without the 421 00:24:19,280 --> 00:24:24,317 same use of power without the same I mean aren't these the kind of things 422 00:24:24,400 --> 00:24:28,957 >> that are going to happen that will democratize it by sort of by itself in a 423 00:24:29,040 --> 00:24:32,717 way >> it it will still require huge investment 424 00:24:32,800 --> 00:24:37,037 but yes we will continue to make things vastly more efficient and we'll figure 425 00:24:37,120 --> 00:24:40,557 out how to make more and better chips and we'll figure out how to make smarter 426 00:24:40,640 --> 00:24:44,797 algorithms. All of that will happen. But to put some numbers on the magnitude of 427 00:24:44,880 --> 00:24:46,797 how much we we need this to happen. 428 00:24:46,880 --> 00:24:49,357 Again, I know these numbers in front of me. I'm not going to get this exactly 429 00:24:49,440 --> 00:24:53,037 right. Um but forgive me for the approximation. 430 00:24:53,120 --> 00:24:57,837 At the beginning of 2020, um the token leader in the world was an OpenAI 431 00:24:57,920 --> 00:24:59,997 employee using roughly a 100,000 tokens 432 00:25:00,080 --> 00:25:02,157 a month. 433 00:25:02,240 --> 00:25:05,437 Um In the middle of 2026, 434 00:25:05,520 --> 00:25:07,117 the token leader that I know of, there 435 00:25:07,200 --> 00:25:09,837 may be somebody using more than this at 436 00:25:09,920 --> 00:25:12,717 outside of OpenAI, um was using hundreds 437 00:25:12,800 --> 00:25:16,077 of billions of tokens a month. So, you 438 00:25:16,160 --> 00:25:20,317 know, a multi-millionx increase in six and a half years. And the average person 439 00:25:20,400 --> 00:25:22,557 on Earth had gone from using effectively 440 00:25:22,640 --> 00:25:24,637 zero tokens to 100,000 tokens a month. 441 00:25:24,720 --> 00:25:27,357 That was the global per capita thing. 442 00:25:27,440 --> 00:25:30,477 If we just naively project this forward again, which seems like a reasonable 443 00:25:30,560 --> 00:25:35,997 thing to do to me. Um, and I hate tokens as a unit here. It's a dumb one. No one 444 00:25:36,080 --> 00:25:39,357 should care, but like let's just take that as shorthand for amount of 445 00:25:39,440 --> 00:25:42,557 intelligence. Then 446 00:25:42,640 --> 00:25:46,717 in another six and a half years, the average per capita use of tokens will go 447 00:25:46,800 --> 00:25:51,437 up to, let's round it down to 100 billion tokens a month. And the person 448 00:25:51,520 --> 00:25:55,837 using the most in the world will be using 449 00:25:55,920 --> 00:25:58,397 you know 100 quadrillion tokens a month. 450 00:25:58,480 --> 00:26:02,557 Uh or one quadrillion 100 trillion like 451 00:26:02,640 --> 00:26:05,997 >> no I was right 100 trillion tokens a month. 100 quadrillion tokens a month. 452 00:26:06,080 --> 00:26:11,517 Um even with great gains on efficiency we 453 00:26:11,600 --> 00:26:14,637 are going to need to build much more infrastructure 454 00:26:14,720 --> 00:26:19,277 unless we want this to be a highly priced commodity which we don't. We want 455 00:26:19,360 --> 00:26:21,597 this to be abundant. We want this to be inexpensive. We want people to just be 456 00:26:21,680 --> 00:26:23,997 able to use this for whatever they need. 457 00:26:24,080 --> 00:26:27,437 >> So that's the driving force. If we if we 458 00:26:27,520 --> 00:26:32,077 globally can build enough then it will 459 00:26:32,160 --> 00:26:35,437 intelligence will be broadly distributed 460 00:26:35,520 --> 00:26:38,557 uh more democratized across the world. 461 00:26:38,640 --> 00:26:42,237 Uh the world will be educated or they'll 462 00:26:42,320 --> 00:26:46,237 have the access to education. Is that 463 00:26:46,320 --> 00:26:48,237 >> to to go back to the analogy of 464 00:26:48,320 --> 00:26:51,117 electricity? Um there's this amazing 465 00:26:51,200 --> 00:26:54,557 chart of what it cost to have an hour of 466 00:26:54,640 --> 00:26:59,597 light at night. And there was a time, one of the 467 00:26:59,680 --> 00:27:01,517 earliest data points you can find is 468 00:27:01,600 --> 00:27:04,557 that it it took an average of 5 hours of 469 00:27:04,640 --> 00:27:06,637 labor at the wage at the time to be able 470 00:27:06,720 --> 00:27:10,157 to pay for one hour of light at night. 471 00:27:10,240 --> 00:27:14,237 Electricity came along. It fell. We figured out how to make more 472 00:27:14,320 --> 00:27:17,357 electricity. So there was like, you know, the supply and demand change 473 00:27:17,440 --> 00:27:22,317 curve. It fell again. We figured out how to make vastly more efficient light 474 00:27:22,400 --> 00:27:26,237 bulbs. We went from incandescent lights to LEDs. A whole bunch of other things 475 00:27:26,320 --> 00:27:29,117 happened. And now an hour of light at 476 00:27:29,200 --> 00:27:33,277 night is not something that people think of at all about the cost. I don't even 477 00:27:33,360 --> 00:27:36,077 know what the number is, but someone in here can do it. It's it's like very 478 00:27:36,160 --> 00:27:38,077 cheap to run, you know, a five watt bulb 479 00:27:38,160 --> 00:27:42,477 for an hour. Um the 480 00:27:42,560 --> 00:27:45,997 if that hadn't happened if we and all of those things together had to happen lots 481 00:27:46,080 --> 00:27:48,877 of electricity generation huge innovation on the efficiency all of 482 00:27:48,960 --> 00:27:53,917 these things. If that hadn't happened then rich people get light at night and 483 00:27:54,000 --> 00:27:56,477 they can study more they have a compounding effect they can learn more 484 00:27:56,560 --> 00:27:59,197 whatever and and you know poor people 485 00:27:59,280 --> 00:28:03,597 don't. So I think it's been very good that energy has become abundant and that 486 00:28:03,680 --> 00:28:05,837 light at night has become relatively 487 00:28:05,920 --> 00:28:09,437 like shockingly inexpensive. Um, if that 488 00:28:09,520 --> 00:28:11,997 same thing happens with AI and anybody 489 00:28:12,080 --> 00:28:13,917 on earth, rich, poor, whatever, can use 490 00:28:14,000 --> 00:28:19,197 AI to get the abundant services that they need and to express their ideas and 491 00:28:19,280 --> 00:28:23,357 to start their businesses and whatever else. And we fulfill our mission of 492 00:28:23,440 --> 00:28:28,157 making AI so inexpensive and so smart that people are just like they think 493 00:28:28,240 --> 00:28:31,597 about it like they think of the cost of an hour at night of light at night. I 494 00:28:31,680 --> 00:28:35,117 think that'd be really wonderful. And then this huge reset and democratization 495 00:28:35,200 --> 00:28:37,597 of education you're talking about can happen. 496 00:28:37,680 --> 00:28:41,997 So are you you know there are look there 497 00:28:42,080 --> 00:28:44,557 are doomers out there who worry about 498 00:28:44,640 --> 00:28:47,277 everything but we know that if you look 499 00:28:47,360 --> 00:28:49,117 back through the industrial re as you 500 00:28:49,200 --> 00:28:51,597 said it it always seems to work out 501 00:28:51,680 --> 00:28:54,557 fine. Are you uh fundamentally 502 00:28:54,640 --> 00:28:57,277 optimistic to what your products will do 503 00:28:57,360 --> 00:29:00,797 to the world and will serve the world? 504 00:29:00,880 --> 00:29:02,557 I I think part of the reason it tends to 505 00:29:02,640 --> 00:29:06,477 work out fine is people worry and they 506 00:29:06,560 --> 00:29:09,597 stress and they look at the downsides and they try to address those and they 507 00:29:09,680 --> 00:29:12,477 try to learn how we avoid accidents. So 508 00:29:12,560 --> 00:29:15,117 if we go back to an early example even 509 00:29:15,200 --> 00:29:17,597 before electricity of a technology fire 510 00:29:17,680 --> 00:29:22,477 was incredible incredible for human evolution incredible for letting us cook 511 00:29:22,560 --> 00:29:25,757 our food and heat our homes at night and whatever else. It also burnt down whole 512 00:29:25,840 --> 00:29:30,317 cities a few times and people really worried about that because we don't want 513 00:29:30,400 --> 00:29:32,717 cities to burn down and we figured out 514 00:29:32,800 --> 00:29:37,277 fire safety and through a lot of human 515 00:29:37,360 --> 00:29:39,277 ingenuity um through a lot of good 516 00:29:39,360 --> 00:29:41,597 policy definitely through learning from 517 00:29:41,680 --> 00:29:46,317 some very bad accidents we figured out how to make it safer. Now had we just 518 00:29:46,400 --> 00:29:49,837 said like yeah you know some cities are going to burn down whatever we got other 519 00:29:49,920 --> 00:29:52,637 problems to work on probably wouldn't have figured that out and that wouldn't 520 00:29:52,720 --> 00:29:56,637 have been as good. Um, so I think worry 521 00:29:56,720 --> 00:29:59,437 is worry is how we anticipate problems 522 00:29:59,520 --> 00:30:03,917 and how we from a matter of policy and a matter of technology figure out how to 523 00:30:04,000 --> 00:30:07,837 address them. But I am optimistic that we can mitigate the downsides of this 524 00:30:07,920 --> 00:30:12,157 technology. And if you look at what's happened, you know, if you look at what 525 00:30:12,240 --> 00:30:15,837 the doomers were saying 5 years ago about the chances of us being able to 526 00:30:15,920 --> 00:30:20,397 make AI of this level, of this sort of near human, sometimes superhuman 527 00:30:20,480 --> 00:30:25,037 capacity level, you know, broadly considered safe and reliable. Not 528 00:30:25,120 --> 00:30:26,237 perfect. There have been accidents. 529 00:30:26,320 --> 00:30:29,437 There will be accidents, of course. I don't think most people would have 530 00:30:29,520 --> 00:30:31,357 thought it was going to go this well as 531 00:30:31,440 --> 00:30:35,037 it has so far. And I I believe in human 532 00:30:35,120 --> 00:30:39,757 ingenuity and the ability for to solve very difficult, very complex 533 00:30:39,840 --> 00:30:42,877 problems. And I think I think we'll keep doing that. 534 00:30:42,960 --> 00:30:46,077 And I think the economic value and the 535 00:30:46,160 --> 00:30:51,197 personal value is so huge. Um I met someone just this morning who told and 536 00:30:51,280 --> 00:30:54,317 again I'm sure you've all heard stories like this that they wouldn't be alive 537 00:30:54,400 --> 00:30:57,357 without CHPT. Um and that they had a 538 00:30:57,440 --> 00:31:01,517 very difficult disease and you know got a diagnosis that doctors weren't able to 539 00:31:01,600 --> 00:31:03,197 >> give them. We shouldn't take that away. 540 00:31:03,280 --> 00:31:06,317 >> No. But we need to figure out how to make the technology safe so that people 541 00:31:06,400 --> 00:31:08,157 can have more of that. 542 00:31:08,240 --> 00:31:10,797 >> Great. Sam, thank you for joining us. It 543 00:31:10,880 --> 00:31:13,357 was really an incredible conversation. 544 00:31:13,440 --> 00:31:17,917 Um 2:00, so 2 p.m. in the ministerial 545 00:31:18,000 --> 00:31:21,437 room where we will have uh Alex Karp 546 00:31:21,520 --> 00:31:24,957 will be our next guest uh speaking to us. 547 00:31:25,040 --> 00:31:28,157 >> He's a good one. >> He's a good one. But uh 548 00:31:28,240 --> 00:31:31,577 >> thank you Sam for joining us. We we really appreciate it. Thank you. 549 00:31:31,660 --> 00:31:36,120 [applause] Thanks.