WEBVTT 00:00:00.480 --> 00:00:03.677 All right, everyone. Um, so how many of 00:00:03.760 --> 00:00:06.317 you uh are Stanford students? Raise your 00:00:06.400 --> 00:00:08.957 hand. Okay, pretty good. We got a lot. 00:00:09.040 --> 00:00:14.157 Um, how many of you in your like years at Stanford lived in Donner? 00:00:14.240 --> 00:00:17.917 >> We also got a few. >> I think we got [laughter] a few. 00:00:18.000 --> 00:00:20.637 >> Well, Sam was actually a Donner resident 00:00:20.720 --> 00:00:24.157 and uh yeah, so why don't we start there? Do you remember moving in on your 00:00:24.240 --> 00:00:25.597 first day at Stanford over here? 00:00:25.680 --> 00:00:28.717 >> I do. I actually I haven't been back to campus in so long. I'm feeling inspired 00:00:28.800 --> 00:00:30.717 to like go walk by after this cuz I have 00:00:30.800 --> 00:00:35.997 like such fond memories of that first day. Um it was like, you know, I'm sure 00:00:36.080 --> 00:00:39.277 like for all of you it was a very strange experience, but it was like 00:00:39.360 --> 00:00:41.037 awesome as soon as I got here. 00:00:41.120 --> 00:00:45.197 >> Do you have any favorite memories? Any building climbing, tunnel diving? 00:00:45.280 --> 00:00:50.157 >> Uh yeah, I I was mentioning this backstage. I like it's sort of, you 00:00:50.240 --> 00:00:52.477 know, when you go to a place you haven't been in a while, all these memories that 00:00:52.560 --> 00:00:55.917 you forgot about come come back. Uh, and 00:00:56.000 --> 00:01:00.077 very near here, uh, like early in freshman year, a bunch of us went steam 00:01:00.160 --> 00:01:01.197 tunneling, which I don't know if people 00:01:01.280 --> 00:01:03.197 still do, but was like a cool right of 00:01:03.280 --> 00:01:07.277 passage at the time, uh, one of the 00:01:07.360 --> 00:01:11.357 people that we went with was like not told you had to put the cover back on. 00:01:11.440 --> 00:01:14.797 So, they kind of left the cover off. We went down and looked around and whatever 00:01:14.880 --> 00:01:16.957 and came back and there was a car, 00:01:17.040 --> 00:01:22.317 professor's car that had like fallen into the open manhole. Uh, I thought I 00:01:22.400 --> 00:01:24.957 was going to get like, you know, kicked out. it was like first few weeks of 00:01:25.040 --> 00:01:27.117 school. Um, but I had totally forgotten 00:01:27.200 --> 00:01:29.357 about that and it's fun to see. Um, my 00:01:29.440 --> 00:01:32.637 memories are like Stanford is awesome. 00:01:32.720 --> 00:01:34.877 Uh, and I just have like very happy 00:01:34.960 --> 00:01:39.917 memories of that time. Uh, and kind of 00:01:40.000 --> 00:01:44.157 even the parts that I didn't think I was going to like at the time like staying 00:01:44.240 --> 00:01:48.317 up all night working in like the basement of Gates are very happy memories now. 00:01:48.400 --> 00:01:51.437 >> I think that's like a core CS student type of thing. I have also pulled all 00:01:51.520 --> 00:01:54.717 nighters in Gates. It's >> there. It's a good memory in retrospect. 00:01:54.800 --> 00:01:59.037 >> Yeah. And every time I walk by Gates, I just think back to that all nighter and 00:01:59.120 --> 00:02:04.077 uh you know, Gates Gates comes with certain memories now. [laughter] >> Yep. 00:02:04.160 --> 00:02:07.757 >> Did you have any specific clubs that you were a part of here at Stanford? 00:02:07.840 --> 00:02:12.477 >> Um I did a few, but the honestly the most 00:02:12.560 --> 00:02:16.477 the best thing I did was just like hacking on projects with friends. Like 00:02:16.560 --> 00:02:19.837 that was if I could go back and do it, I would have done like less clubs and more 00:02:19.920 --> 00:02:22.477 just building stuff. Yeah. All right. 00:02:22.560 --> 00:02:25.277 Um, well, we went through the archives 00:02:25.360 --> 00:02:28.077 uh of Sam's time here at Stanford, and I 00:02:28.160 --> 00:02:32.877 don't know if you guys know the, uh, club faces. It's the student 00:02:32.960 --> 00:02:34.877 entrepreneurship club here on campus. 00:02:34.960 --> 00:02:40.637 And they found this document, the business symposium. Um, whoa. And it was 00:02:40.720 --> 00:02:43.517 for the next [laughter] generation of business leaders. So, this is from 00:02:43.600 --> 00:02:45.837 spring 2005. This is like right before 00:02:45.920 --> 00:02:50.637 you dropped out. Uh and in this document 00:02:50.720 --> 00:02:54.077 there's this one entry uh and it says 00:02:54.160 --> 00:02:58.557 Vienno and Viendo is a service for cell phones that provides personalized 00:02:58.640 --> 00:03:02.717 information about hot venues, a map of locations of friends nearby and 00:03:02.800 --> 00:03:07.197 compatible new friends and dates in the area. And keep in mind this is 2005 so 00:03:07.280 --> 00:03:08.797 this is like before the iPhone came out. 00:03:08.880 --> 00:03:11.357 So this is kind of like a crazy idea at 00:03:11.440 --> 00:03:14.877 the time. Uh, and it's co-founded by 00:03:14.960 --> 00:03:16.957 four students as you can see here. Um, 00:03:17.040 --> 00:03:22.957 Peter, Alec, Nick, and, uh, this guy named Sam up there as well. Um, is this 00:03:23.040 --> 00:03:23.517 looped? 00:03:23.600 --> 00:03:27.677 >> Yeah. Uh, I forgot about this also, but 00:03:27.760 --> 00:03:31.517 the the important thing here is not 00:03:31.600 --> 00:03:33.437 about building stuff, but it's about how 00:03:33.520 --> 00:03:37.037 much Y Combinator did to change what it 00:03:37.120 --> 00:03:41.437 took to get a project funded. Um, I was like, you know, I came here, I was not 00:03:41.520 --> 00:03:45.037 that interested in startups and then it kind of like I was like it was in the 00:03:45.120 --> 00:03:49.437 water and I got excited about startups, but it was a super different time then. 00:03:49.520 --> 00:03:52.717 And you would like talk to people and they'd be like, "Oh, you need like a 00:03:52.800 --> 00:03:56.797 business person. You can't just you got to like get these connections to VCs. It 00:03:56.880 --> 00:04:00.077 was like, you know, you got to like get serious. You need like a bunch of MBAs. 00:04:00.160 --> 00:04:03.997 You got to write a business plan. And, you know, it's like you need to like 00:04:04.080 --> 00:04:06.237 raise this big round and you're going to have these VCs. They're going to tell 00:04:06.320 --> 00:04:10.237 you what to do and whatever." And I was like, "Okay, I guess I don't know any 00:04:10.320 --> 00:04:12.797 better." And these smart people are saying that's what you have to do, so 00:04:12.880 --> 00:04:16.397 like I'll believe it. Um, this was right 00:04:16.480 --> 00:04:19.037 around this time is when Y Combinator 00:04:19.120 --> 00:04:22.637 launched. Uh, and I'm sure you all 00:04:22.720 --> 00:04:26.797 already think this from just hearing from Gary, but like if you want to start 00:04:26.880 --> 00:04:28.157 a startup, you should definitely do Y 00:04:28.240 --> 00:04:32.317 Combinator. Uh, but and it's an amazing 00:04:32.400 --> 00:04:35.357 thing. Uh but before YC like in the dark 00:04:35.440 --> 00:04:40.157 ages, this is what you had to do. Like you had to go do business plan 00:04:40.240 --> 00:04:43.277 competitions which are a business plans are a waste of time. Business plan 00:04:43.360 --> 00:04:44.957 competitions even worse waste of time. 00:04:45.040 --> 00:04:48.157 Um but this is kind of what you were stuck with. Like this was how you could 00:04:48.240 --> 00:04:51.677 get things out in the world. And in the 00:04:51.760 --> 00:04:56.317 20 years since uh things have changed like unbelievably for the better. 00:04:56.400 --> 00:04:59.677 >> Yeah. So how long were you working on this idea before like you discovered Y 00:04:59.760 --> 00:05:03.517 Combinator? Uh I was like hacking on like a project. That was another thing 00:05:03.600 --> 00:05:07.517 like it didn't this like many other things did not start intending to be a 00:05:07.600 --> 00:05:10.877 company in any way. This was like a sort of late night dorm project. 00:05:10.960 --> 00:05:14.237 >> Oh wow. >> But over like a while and then it got serious when YC 00:05:14.320 --> 00:05:16.237 >> you remember if you won this competition. 00:05:16.320 --> 00:05:19.117 >> We did. Yeah. >> That's pretty good. 00:05:19.200 --> 00:05:23.117 >> Um so then how did you end up getting in contact with like YC? You were in the 00:05:23.200 --> 00:05:26.237 first batch, right? >> Um 00:05:26.320 --> 00:05:27.917 you just like applied online. I actually 00:05:28.000 --> 00:05:30.637 I think it was maybe it was like you 00:05:30.720 --> 00:05:35.197 filled out this weird form that PG had that you had to like 00:05:35.280 --> 00:05:37.037 paste into an email and not change any 00:05:37.120 --> 00:05:43.560 formatting because he had some weird parser for it. I think it was like that. 00:05:44.000 --> 00:05:46.397 >> So all three of us are sophomores right 00:05:46.480 --> 00:05:48.397 now. Um could you walk us through a day 00:05:48.480 --> 00:05:51.597 in your life back then? 00:05:51.680 --> 00:05:56.897 >> Um I mean it was really boring like there like 00:05:56.980 --> 00:05:59.437 >> [laughter] >> I don't know. I like went to class or 00:05:59.520 --> 00:06:01.757 didn't and I like hung out with my 00:06:01.840 --> 00:06:06.557 friends and I built stuff >> like 00:06:06.640 --> 00:06:11.517 Yeah. Again, very fun memories, but it was like very like simple, lovely, 00:06:11.600 --> 00:06:15.277 boring time. >> Yeah. >> So, when you were considering dropping 00:06:15.360 --> 00:06:18.397 out, did you feel like it was it was risky? I mean, were you excited? I mean, 00:06:18.480 --> 00:06:22.717 it sounds like school maybe wasn't the whole uh environment that you were 00:06:22.800 --> 00:06:27.037 looking for. What was kind of like your your process behind that? 00:06:27.120 --> 00:06:31.357 Uh, look, I feel a little bad saying this 00:06:31.440 --> 00:06:35.437 because obviously it worked out for me and I don't, you know, survivorship 00:06:35.520 --> 00:06:37.517 survivorship bias is a real thing. 00:06:37.600 --> 00:06:41.917 >> Uh, I didn't think at the time and I don't think now that dropping out is 00:06:42.000 --> 00:06:44.317 like a particularly risky thing to do. 00:06:44.400 --> 00:06:46.877 >> Uh, I don't know if Stanford still has this, but at the time it was like you 00:06:46.960 --> 00:06:51.037 could stop out for eight years and come back kind of no questions asked. um 00:06:51.120 --> 00:06:53.117 which I think is a great a great policy 00:06:53.200 --> 00:06:55.357 and it certainly made it easier to get 00:06:55.440 --> 00:06:58.157 my parents slightly on board with the 00:06:58.240 --> 00:07:01.597 idea. Um 00:07:01.680 --> 00:07:04.637 I think you should just work on whatever 00:07:04.720 --> 00:07:07.357 the sort of most interesting highest 00:07:07.440 --> 00:07:12.317 rate of learning highest impact thing you can is. And if that's being in 00:07:12.400 --> 00:07:15.117 school and learning a ton of stuff and being around interesting people and 00:07:15.200 --> 00:07:18.637 working on interesting stuff, great. If it's doing a startup, great. if it's 00:07:18.720 --> 00:07:20.797 dropping out to do AI research or 00:07:20.880 --> 00:07:23.677 whatever. Also great. Um 00:07:23.760 --> 00:07:26.077 I think one of the trends of the last 00:07:26.160 --> 00:07:28.237 few decades, couple decades at least, 00:07:28.320 --> 00:07:31.117 has been that um 00:07:31.200 --> 00:07:35.837 the default path has gotten 00:07:35.920 --> 00:07:39.757 relatively less good. And the option space of what you can do and still be 00:07:39.840 --> 00:07:43.597 really successful and happy and have a great impact on the world has increased 00:07:43.680 --> 00:07:45.357 and increased and increased. And as the 00:07:45.440 --> 00:07:48.557 society gets richer and freer and more 00:07:48.640 --> 00:07:51.597 capability with a better technology tree 00:07:51.680 --> 00:07:53.197 and 00:07:53.280 --> 00:07:56.077 like I think that will just keep going. 00:07:56.160 --> 00:07:59.597 So uh it didn't feel like a crazy or 00:07:59.680 --> 00:08:04.077 risky thing to me at the time. Uh I think if I were a student today it would 00:08:04.160 --> 00:08:07.117 feel like even more of a that's totally something I could consider. 00:08:07.200 --> 00:08:09.997 >> Yeah. >> My parents didn't like it. 00:08:10.080 --> 00:08:14.477 >> Yeah, that makes sense. That makes sense. Wow. So you raised over like $30 00:08:14.560 --> 00:08:17.917 million for this idea which you know is like kind of considered like seed round 00:08:18.000 --> 00:08:19.997 today. How >> I mean I was going to say that's like a 00:08:20.080 --> 00:08:23.197 pre pre [laughter] like it was a lot of money at the time. 00:08:23.280 --> 00:08:26.557 >> Yeah. Um how how did you do this? I mean what what did 00:08:26.640 --> 00:08:30.157 >> 17 GPUs now or something? >> Wait. No exactly right. 00:08:30.240 --> 00:08:34.717 >> Well one thing that was is cool about 00:08:34.800 --> 00:08:38.077 Stanford and particularly so at the time is it had like a good on-ramp. It was 00:08:38.160 --> 00:08:41.277 like very well connected to the whole like VC machinery. 00:08:41.360 --> 00:08:45.037 >> Yeah. and Y cominator also was helpful there. 00:08:45.120 --> 00:08:47.997 >> Yeah. >> Um 00:08:48.080 --> 00:08:50.317 it was maybe there were less VC firms 00:08:50.400 --> 00:08:53.357 and less money at the time but they were 00:08:53.440 --> 00:08:55.437 extremely focused on Stanford as like a 00:08:55.520 --> 00:08:57.997 source of ideas and people. 00:08:58.080 --> 00:09:00.637 >> Do you remember any like stories uh from 00:09:00.720 --> 00:09:02.877 that YC batch or from founding? Like did 00:09:02.960 --> 00:09:09.917 it go really well all at first or like what was that process like? Um, 00:09:10.000 --> 00:09:11.197 actually it felt like still being in 00:09:11.280 --> 00:09:13.757 college. Everybody was like pretty young 00:09:13.840 --> 00:09:17.357 at the time. Um, we kind of like would 00:09:17.440 --> 00:09:19.757 stay up late talking or working on 00:09:19.840 --> 00:09:24.877 computers and it it it felt like it felt shockingly not that different. 00:09:24.960 --> 00:09:28.157 And I've heard a lot of people say this that have done YC or not that have 00:09:28.240 --> 00:09:30.157 dropped out to do startups. Like if 00:09:30.240 --> 00:09:32.637 you're a college student kind of like if 00:09:32.720 --> 00:09:37.837 you're like a CSish college student and then you do a startup the fir like the 00:09:37.920 --> 00:09:40.477 last year that you did school and the first year of doing a startup eventually 00:09:40.560 --> 00:09:43.917 it gets very different. They're like shockingly the same. 00:09:44.000 --> 00:09:45.517 >> So I mean we have a lot of students here 00:09:45.600 --> 00:09:48.637 from Stanford but we also have a lot of non-stamford students and I agree with 00:09:48.720 --> 00:09:52.237 you. I do think Stanford has a pipeline into like this PC culture and all this 00:09:52.320 --> 00:09:55.277 money, right? I mean what would you recommend to students coming from other 00:09:55.360 --> 00:09:59.117 schools if they were interested in going into this the same process? That was the 00:09:59.200 --> 00:10:02.317 case at the time. I think that's no longer the case. I think the sort of 00:10:02.400 --> 00:10:06.317 like Stanford special access I mean maybe there's still some of it but I 00:10:06.400 --> 00:10:09.757 think it's like mostly over maybe totally over maybe even slight negative 00:10:09.840 --> 00:10:11.277 selection for Stanford students at this 00:10:11.360 --> 00:10:15.757 point. Um the I think YC did a lot for 00:10:15.840 --> 00:10:19.197 this but also like VC just matured as an 00:10:19.280 --> 00:10:22.797 industry and there's so much money in the world that wants to fund startups 00:10:22.880 --> 00:10:26.717 now. Um that I think it's no longer the case at all that it's like a very 00:10:26.800 --> 00:10:30.477 Stanfordy thing. Okay. So, fast forward a few years and 00:10:30.560 --> 00:10:32.877 you're now the president of YC and then 00:10:32.960 --> 00:10:35.837 all of a sudden, boom, open AI is born. 00:10:35.920 --> 00:10:38.077 Um, what happened? How did you guys come 00:10:38.160 --> 00:10:39.197 up with the idea? 00:10:39.280 --> 00:10:42.877 >> Uh, so I was studying AI when I was here 00:10:42.960 --> 00:10:47.437 and it was not working at the time at all. Like I thought AI would be the 00:10:47.520 --> 00:10:51.917 coolest, most important thing, but it was I worked in the AI lab the summer 00:10:52.000 --> 00:10:53.917 between uh my freshman and sophomore 00:10:54.000 --> 00:10:59.277 year and I was like, okay, these are this is not it. Um, and I got distracted 00:10:59.360 --> 00:11:01.837 and did a startup with something else and then I became an investor for a 00:11:01.920 --> 00:11:05.757 while. But I always thought that uh AI 00:11:05.840 --> 00:11:08.157 was at least one of the two or three 00:11:08.240 --> 00:11:10.317 most important things that could happen. 00:11:10.400 --> 00:11:13.757 Um, and 00:11:13.840 --> 00:11:17.357 you know, I was like paying attention to it. I This is like a a thing I recommend 00:11:17.440 --> 00:11:21.277 and something I have heard many people describe over the course of your career, 00:11:21.360 --> 00:11:25.757 which is you get conviction on the things that you care about early, a 00:11:25.840 --> 00:11:28.157 super set of them. Some you'll lose 00:11:28.240 --> 00:11:30.557 interest in, some will develop more than 00:11:30.640 --> 00:11:33.917 you thought, but the the landscape of 00:11:34.000 --> 00:11:35.757 the world just is going to keep changing 00:11:35.840 --> 00:11:41.037 as you get more experience. And continuing to focus and like stick your 00:11:41.120 --> 00:11:45.597 head up and look and not get into tunnel vision on one thing seems like it's 00:11:45.680 --> 00:11:47.677 really important and really correlates 00:11:47.760 --> 00:11:50.317 with success over a long period of time. 00:11:50.400 --> 00:11:52.797 And you know, so I was like paying 00:11:52.880 --> 00:11:53.997 attention to all the areas I was 00:11:54.080 --> 00:11:57.677 interested in. In 2012, 00:11:57.760 --> 00:12:01.197 uh, the Alex Net paper happened and I, like everybody else, was like, "Oh, 00:12:01.280 --> 00:12:04.797 that's kind of cool or very cool, but it didn't update me as much as it should 00:12:04.880 --> 00:12:07.517 have." Like, you know, strong priors are 00:12:07.600 --> 00:12:11.517 a real factor. I I then watched over the 00:12:11.600 --> 00:12:15.117 next couple of years as 00:12:15.200 --> 00:12:20.397 it deep learning models kept getting better with scale and I still didn't 00:12:20.480 --> 00:12:25.437 update enough but now I was at least like this is like an asteroid coming and 00:12:25.520 --> 00:12:30.077 a crazy thing that people are not paying more attention to and so in 2014 we 00:12:30.160 --> 00:12:34.717 started saying you know we should really do something about this. Um it was 00:12:34.800 --> 00:12:38.397 incredibly unpopular at the time. Like we had said we want to make an AGI lab 00:12:38.480 --> 00:12:41.517 and all the like elders of the field were like you're insane. You're a 00:12:41.600 --> 00:12:45.437 scammer. This is like you know AGI is 100 years away. None of these approaches 00:12:45.520 --> 00:12:48.397 are going to work. And we really said 00:12:48.480 --> 00:12:52.557 let's just push on this one idea that scaling deep learning seems to matter. 00:12:52.640 --> 00:12:56.077 We didn't know at the time how beautifully predictable the scaling laws 00:12:56.160 --> 00:13:00.077 were, but it was at least clear back in those days that if you threw more 00:13:00.160 --> 00:13:03.037 compute at something, you got better results most of the time. 00:13:03.120 --> 00:13:05.917 Um, and we kind of just decided we were 00:13:06.000 --> 00:13:10.237 going to push on it as far as we could and see what happened. Uh, we were also 00:13:10.320 --> 00:13:13.357 very worried about what it would mean for like how we were going to solve the 00:13:13.440 --> 00:13:17.517 alignment problem, what it would mean for society. We didn't know that we were 00:13:17.600 --> 00:13:19.757 going to make a product. We just thought we were going to be a research lab. So, 00:13:19.840 --> 00:13:22.477 we kind of had a weird start. Um, but it 00:13:22.560 --> 00:13:25.597 was really this 00:13:25.680 --> 00:13:27.757 it was this mindset of if AI works, it 00:13:27.840 --> 00:13:29.917 will be unbelievably important and we 00:13:30.000 --> 00:13:32.637 finally have an attack vector that maybe 00:13:32.720 --> 00:13:35.517 can go very far. It felt and still feels 00:13:35.600 --> 00:13:37.437 kind of crazy to me that it can go as 00:13:37.520 --> 00:13:41.197 far as it's turned out to go. Um, deep 00:13:41.280 --> 00:13:43.917 learning, 00:13:44.000 --> 00:13:48.557 the fact that these models can sort of do unsupervised learning in particular 00:13:48.640 --> 00:13:50.557 still seems sort of magical to me. The 00:13:50.640 --> 00:13:53.277 fact that next word prediction 00:13:53.360 --> 00:13:57.757 can be used basically to discover new 00:13:57.840 --> 00:14:01.757 scientific ideas. It makes like intellectual sense, but to 00:14:01.840 --> 00:14:06.077 see it work is still like a very crazy thing. Um, 00:14:06.160 --> 00:14:08.477 but that was it. It was we have this one idea, let's push on it. 00:14:08.560 --> 00:14:11.837 >> So, you see all these ideas now, but as you mentioned, it was incredibly 00:14:11.920 --> 00:14:15.037 unpopular at the time. I'm really curious to know what the first pitch for 00:14:15.120 --> 00:14:16.637 OpenAI looked like. 00:14:16.720 --> 00:14:19.997 >> Um, I love the unpopular ideas. I I I 00:14:20.080 --> 00:14:23.117 have always liked ideas that are big if 00:14:23.200 --> 00:14:26.397 they work, difficult to get to work, and 00:14:26.480 --> 00:14:29.677 unpopular. Um, my career as an investor 00:14:29.760 --> 00:14:34.397 was basically betting on those. Uh, for whatever like reason that people think 00:14:34.480 --> 00:14:37.037 one thing is fun and not another, this is something that has always seemed 00:14:37.120 --> 00:14:40.957 particularly fun to me. So, even if it weren't that I loved AI so much, I would 00:14:41.040 --> 00:14:43.037 have thought the fact that this seems 00:14:43.120 --> 00:14:47.117 really undervalued and promising uh was 00:14:47.200 --> 00:14:51.917 was cool. And that was basically the pitch. The pitch was uh something 00:14:52.000 --> 00:14:56.557 important is happening with deep learning and scale. Uh we don't know 00:14:56.640 --> 00:14:59.037 what we're going to do with it. We don't know where it's going to go. We had a 00:14:59.120 --> 00:15:03.117 bunch of ideas that turned out to be wrong on the hops along the way, but 00:15:03.200 --> 00:15:07.117 we're going to push on this and something good is going to come out of 00:15:07.200 --> 00:15:09.917 it and other people are undervaluing 00:15:10.000 --> 00:15:14.717 this. So it was a it was like that was really the pitch. It was not a 00:15:14.800 --> 00:15:18.397 great pitch. [laughter] Well, it worked. Um, how did you meet 00:15:18.480 --> 00:15:20.157 your co-founders? 00:15:20.240 --> 00:15:25.277 >> Uh, I had known Greg forever. Um, 00:15:25.360 --> 00:15:28.477 he I was an early investor in Stripe. I think he was the first employee and I 00:15:28.560 --> 00:15:30.717 was like brought in to help close him. 00:15:30.800 --> 00:15:32.397 Um, and we had stayed in touch for the 00:15:32.480 --> 00:15:34.957 sort of decade or whatever in between. 00:15:35.040 --> 00:15:39.517 Um, Ilia is the sort of genius 00:15:39.600 --> 00:15:41.757 and godfather of the field and I stalked 00:15:41.840 --> 00:15:44.877 him at a conference. Uh and then later 00:15:44.960 --> 00:15:47.757 we started talking about um doing a 00:15:47.840 --> 00:15:51.917 startup. Uh Voytech I met through kind 00:15:52.000 --> 00:15:55.517 of the like weird AGI nerds network of 00:15:55.600 --> 00:15:59.037 the Bay Area at the time and John 00:15:59.120 --> 00:16:01.197 one of the others connected me to and 00:16:01.280 --> 00:16:06.850 Elon uh I guess yeah. [laughter] 00:16:08.080 --> 00:16:12.157 So, so how did founding feel on this time with OpenAI compared to your 00:16:12.240 --> 00:16:14.717 experience with Looped before? 00:16:14.800 --> 00:16:17.677 >> Uh, I mean this was really a weird one. 00:16:17.760 --> 00:16:22.957 Like I the degree to which OpenAI was not meant 00:16:23.040 --> 00:16:27.277 to be a company is like very hard to overstate. We had no idea that we were 00:16:27.360 --> 00:16:29.837 going to ever do a product. >> Yeah, >> we thought we were just going to do 00:16:29.920 --> 00:16:32.957 research papers. Um, 00:16:33.040 --> 00:16:37.677 as we got going, it became clear that a there was going to be a lot more 00:16:37.760 --> 00:16:40.957 economic value along the way than we thought. We kind of had this conception 00:16:41.040 --> 00:16:43.837 that you were going to build this super intelligence and you're going to have 00:16:43.920 --> 00:16:47.357 this like crazy thing happen all at once. And we learned that was not quite 00:16:47.440 --> 00:16:50.477 the right picture. We also realized that instead of needing the few billion 00:16:50.560 --> 00:16:52.797 dollars we thought we might need, you're going to need like hundreds of billions 00:16:52.880 --> 00:16:57.917 of dollars. >> And so it evolved, but at the start it 00:16:58.000 --> 00:17:00.797 was like we're going to be a research lab. actually one of my most vivid 00:17:00.880 --> 00:17:03.357 memories of OpenAI. 00:17:03.440 --> 00:17:06.317 Very first day been all this drama to 00:17:06.400 --> 00:17:11.517 get it started. Uh very first day we're together in Greg Brockman's apartment 00:17:11.600 --> 00:17:13.037 which was where we worked until we got 00:17:13.120 --> 00:17:14.797 our first office a few weeks or maybe a 00:17:14.880 --> 00:17:20.157 month later. And it's like, you know, 9:30, 10 in the 00:17:20.240 --> 00:17:23.117 morning. Everybody rolls in. We're sitting on Greg's couch. Maybe there's 00:17:23.200 --> 00:17:26.477 10 or 12 of us. Maybe not even that many. Maybe eight or 10. And we look 00:17:26.560 --> 00:17:30.157 around and say like, "Okay, what are we going to do?" 00:17:30.240 --> 00:17:32.557 >> Yeah. >> And someone said, "We should write some 00:17:32.640 --> 00:17:37.117 papers." And someone said, "Okay, we need a whiteboard to start talking." 00:17:37.200 --> 00:17:40.717 >> And like someone orders like a whiteboard on, you know, Amazon. 00:17:40.800 --> 00:17:42.477 >> Yeah. >> Instant or something. 00:17:42.560 --> 00:17:47.997 >> And and I had this real moment of like, what? This is not this is not good. Like 00:17:48.080 --> 00:17:50.717 I don't know what this is, but this is not a startup or any kind of thing 00:17:50.800 --> 00:17:54.077 that's going to be effective. Um, but 00:17:54.160 --> 00:17:56.877 you know, I like I am a big believer 00:17:56.960 --> 00:18:02.077 that in moments like that, you just like breathe, trust that if it's if you have 00:18:02.160 --> 00:18:04.557 good people around, it's like going to work out. And we just kind of went with 00:18:04.640 --> 00:18:08.077 it. Sometime in that first week, most of 00:18:08.160 --> 00:18:13.117 the ideas that turned out to be the core ideas for the um first four years of 00:18:13.200 --> 00:18:16.637 OpenAI were written down on that whiteboard. Even though at the time we 00:18:16.720 --> 00:18:19.837 didn't realize that and we're kind of just like, eh, this is probably not. We 00:18:19.920 --> 00:18:21.757 went in some other directions. 00:18:21.840 --> 00:18:25.517 And you know, we said we need to get some 00:18:25.600 --> 00:18:28.877 GPUs, we need to do this, we need to do that. Uh we need to like pick some 00:18:28.960 --> 00:18:32.477 projects to see if this is really working. 00:18:32.560 --> 00:18:34.557 >> And stuff just kind of kept going. 00:18:34.640 --> 00:18:38.637 >> Wow. >> Yeah. So you're uh you were in this 00:18:38.720 --> 00:18:41.437 place where you're like, "Okay, what do we do? Let's start doing some research 00:18:41.520 --> 00:18:45.037 papers." like when was the moment after that where things started to click for 00:18:45.120 --> 00:18:49.197 the first time and you're like uh things started to feel like uh you guys really 00:18:49.280 --> 00:18:55.800 had discovered something or something was like big was about to happen. Um 00:19:01.120 --> 00:19:02.637 there were a few moments I think it was 00:19:02.720 --> 00:19:07.597 not just one but the the felt sense was 00:19:07.680 --> 00:19:10.637 it was like miracle after miracle and so 00:19:10.720 --> 00:19:14.717 at some point more than any one thing that worked. It was like, man, something 00:19:14.800 --> 00:19:19.357 about the underlying approach here feels like we've discovered like a new law of 00:19:19.440 --> 00:19:24.077 physics or something. And you know, it was like great to get Dota working or 00:19:24.160 --> 00:19:27.997 the robot hand working and then eventually the the first language model. 00:19:28.080 --> 00:19:32.157 But the the biggest takeaway was just like there is something about this 00:19:32.240 --> 00:19:34.077 underlying approach that really feels 00:19:34.160 --> 00:19:37.917 like we're on a trajectory to the degree 00:19:38.000 --> 00:19:40.797 that I had like a single moment. It was 00:19:40.880 --> 00:19:44.797 the GPT series. Um like by GPT2 it was 00:19:44.880 --> 00:19:49.517 clear to me like man this is gonna this is something important is about to 00:19:49.600 --> 00:19:52.877 happen. >> Do you remember that day the GP G2 launch? 00:19:52.960 --> 00:19:55.597 >> I do. Uh I don't remember the launch day 00:19:55.680 --> 00:19:57.037 but I remember the day that like I got 00:19:57.120 --> 00:19:59.997 to first talk to the model and I was 00:20:00.080 --> 00:20:03.197 just like wow this is 00:20:03.280 --> 00:20:07.517 this is great. And actually I think it was technically a model that was like a 00:20:07.600 --> 00:20:11.597 little bit beyond what we released as GPT2. Um, 00:20:11.680 --> 00:20:16.157 but like I knew GPT3 would be amazing and GPT4 would be amazing and they were 00:20:16.240 --> 00:20:19.757 and they were amazing in new ways. But that first night that I got to play with 00:20:19.840 --> 00:20:22.957 the model and it was like doing 00:20:23.040 --> 00:20:26.797 something I never had seen a computer do before. I was like, "Okay, this is and 00:20:26.880 --> 00:20:31.517 and we had the builtup like confidence of deep learning working." 00:20:31.600 --> 00:20:36.237 >> Yeah. And you initially withheld that model GBT2, right? What at what point 00:20:36.320 --> 00:20:40.557 did you feel like we were ready or or like what made you decide that the world 00:20:40.640 --> 00:20:43.997 was ready for these models? >> Uh 00:20:44.080 --> 00:20:48.157 look, clearly that looked like silly in retrospect. I think the principle of 00:20:48.240 --> 00:20:50.477 precaution with each new level of AI 00:20:50.560 --> 00:20:53.277 capability is reasonable. Alignment has 00:20:53.360 --> 00:20:55.757 been easier to make progress on than 00:20:55.840 --> 00:21:00.157 many of us in the field thought. Uh 00:21:00.240 --> 00:21:04.877 but the societal impacts have been 00:21:04.960 --> 00:21:08.957 or are getting big. Um, and 00:21:09.040 --> 00:21:13.837 you know, if we bias like slightly too much towards the 00:21:13.920 --> 00:21:15.917 cautionary side, I think that's good. 00:21:16.000 --> 00:21:20.477 Uh, too much would be bad. I I'm also worried about like a mega AI capability 00:21:20.560 --> 00:21:22.157 overhang building up. Like the way I 00:21:22.240 --> 00:21:24.717 would explain this is if companies don't 00:21:24.800 --> 00:21:27.677 adopt AI fast enough then they will lose 00:21:27.760 --> 00:21:32.797 to fully autonomous completely AI run and started companies and that will be a 00:21:32.880 --> 00:21:34.477 crazy destabilizing thing for society. 00:21:34.560 --> 00:21:36.877 So you can't be that cautious either. Um 00:21:36.960 --> 00:21:42.840 but you know like we'll go a little bit on that side of the line. 00:21:43.600 --> 00:21:45.597 >> So what do you think the next chat GPT 00:21:45.680 --> 00:21:47.757 moment will be? 00:21:47.840 --> 00:21:50.877 Uh well I think the next JBT moment 00:21:50.960 --> 00:21:53.757 already was coding agents. Um and I 00:21:53.840 --> 00:21:55.517 think the next one after this that has 00:21:55.600 --> 00:22:00.077 not come yet will be that same level of 00:22:00.160 --> 00:22:03.357 ability to get stuff done for all knowledge work which I don't think is 00:22:03.440 --> 00:22:05.037 that far away. 00:22:05.120 --> 00:22:10.637 >> Wow. So I mean we're all sophomores here. Um there's a lot that's going to 00:22:10.720 --> 00:22:13.837 change in the next few years. I mean before we graduate I think. Do I mean do 00:22:13.920 --> 00:22:16.717 you think AGI will be >> Yeah, I think if you are a sophomore 00:22:16.800 --> 00:22:19.197 now, you will graduate to a world with 00:22:19.280 --> 00:22:24.237 AGI in it. Uh and it will be much, you 00:22:24.320 --> 00:22:28.877 know, in some ways it'll like be the same. You'll go move and get a job and 00:22:28.960 --> 00:22:31.917 think about having a family and whatever else like the human, you never bet 00:22:32.000 --> 00:22:36.477 against like sort of the human drives and what we care about staying the same. 00:22:36.560 --> 00:22:38.477 But in some other sense, it's just going 00:22:38.560 --> 00:22:40.797 to be wildly different. uh you know I 00:22:40.880 --> 00:22:44.637 think we'll have AI uh improving at an 00:22:44.720 --> 00:22:47.197 incredibly rapid clip. Um society will 00:22:47.280 --> 00:22:50.077 be coming along uh at a slower clip but 00:22:50.160 --> 00:22:55.837 still very fast. Science will be getting automated. Uh what it means to start a 00:22:55.920 --> 00:22:58.397 startup will be totally different. What it means to go work at a company will be 00:22:58.480 --> 00:23:02.200 totally different. Uh 00:23:02.400 --> 00:23:06.077 there's going to be a lot of change in the next couple of years. Uh you are 00:23:06.160 --> 00:23:09.597 lucky to be a student right now because you can go do kind of whatever. uh and 00:23:09.680 --> 00:23:12.237 you can try a lot of things quickly. Um 00:23:12.320 --> 00:23:14.557 but and you're also lucky in that this 00:23:14.640 --> 00:23:17.837 is probably like 00:23:17.920 --> 00:23:20.637 the most interesting time to be starting 00:23:20.720 --> 00:23:26.077 off like adult life or a career. Um 00:23:26.160 --> 00:23:28.637 but I think a lot of the traditional 00:23:28.720 --> 00:23:30.477 advice is not quite going to work. 00:23:30.560 --> 00:23:34.717 >> Yeah. So speaking of execution, um in 00:23:34.800 --> 00:23:39.197 your first ever blog post on blog.samalttman.com, sam alman.com. You 00:23:39.280 --> 00:23:43.597 say that knowing is easy and it's the doing that's difficult. Um, is there a 00:23:43.680 --> 00:23:46.717 truth that you think you know now about the future where the missing piece is 00:23:46.800 --> 00:23:52.200 execution? >> Um, 00:23:55.360 --> 00:23:57.197 well, I think that's just generally 00:23:57.280 --> 00:24:01.837 going to continue to be true. Uh, I 00:24:01.920 --> 00:24:05.357 mean, knowing knowing is easier and easier like you can you get the help of 00:24:05.440 --> 00:24:10.077 these AI tools. Um, getting stuff done is easier too, but it it's easier for 00:24:10.160 --> 00:24:12.717 everybody. And so you have to like compete with everybody else trying to 00:24:12.800 --> 00:24:16.717 get stuff done in the world. Um, the 00:24:16.800 --> 00:24:18.877 it is for sure true that what one 00:24:18.960 --> 00:24:23.117 programmer can do now uh is like 00:24:23.200 --> 00:24:26.637 mindbendingly different than what you could do a year 00:24:26.720 --> 00:24:28.797 or two years ago, a year ago, let's say. 00:24:28.880 --> 00:24:31.917 Um, it is also true that the people that 00:24:32.000 --> 00:24:34.637 I know that are using these tools the 00:24:34.720 --> 00:24:39.517 most effectively say uh it has never been harder to do their work. And I 00:24:39.600 --> 00:24:43.677 suspect this trend is going to keep going. But like man, watching these 00:24:43.760 --> 00:24:48.157 people who are really good at using AI coding tools have like 12 agents running 00:24:48.240 --> 00:24:50.317 all the time and like these complicated 00:24:50.400 --> 00:24:51.837 custom harnesses that they're constantly 00:24:51.920 --> 00:24:55.597 evolving like the the yeah, the tools 00:24:55.680 --> 00:25:01.437 have gotten unbelievably good. Um, and the ability to use them to be at the top 00:25:01.520 --> 00:25:03.197 of the game I think has never been harder. 00:25:03.280 --> 00:25:06.157 >> And you think this will apply across like all verticals, not just coding? 00:25:06.240 --> 00:25:09.677 >> Uh, I mean, look, eventually you will just 00:25:09.760 --> 00:25:13.437 say like, "Hey, Mr. AI, please like make me my whole startup and do everything 00:25:13.520 --> 00:25:18.397 and do a great job. You know, I'll help you with whatever you need." But 00:25:18.480 --> 00:25:22.157 between now and then, yeah, I think it'll apply to all all verticals. 00:25:22.240 --> 00:25:26.477 Given that uh these models are becoming more and more powerful then and you you 00:25:26.560 --> 00:25:29.277 we have people that are running this many coding agents. There's definitely 00:25:29.360 --> 00:25:33.677 some of y'all in the audience here. Um what should people be working on and 00:25:33.760 --> 00:25:36.637 focusing on then? Like what do you think is the most important problem in the 00:25:36.720 --> 00:25:41.720 world right now? >> Uh 00:25:45.200 --> 00:25:49.437 the the degree to which it feels like 00:25:49.520 --> 00:25:53.117 everything is up for a rethink. I'm not like that interested. People are like, 00:25:53.200 --> 00:25:55.117 "Oh, all SAS is dead. I'm gonna like, 00:25:55.200 --> 00:25:58.237 you know, make a new startup to make 00:25:58.320 --> 00:26:03.117 SAS company X better." Like, you know what? That will probably work. But I 00:26:03.200 --> 00:26:04.477 think that's missing the point of what's 00:26:04.560 --> 00:26:08.717 possible. Now, the degree to which 00:26:08.800 --> 00:26:12.477 things are just completely fundamentally 00:26:12.560 --> 00:26:16.557 reimaginable, uh, 00:26:16.640 --> 00:26:18.717 and the space feels super open on that. 00:26:18.800 --> 00:26:21.277 like you know if you like just to pick a 00:26:21.360 --> 00:26:26.557 random example uh social products have not changed that 00:26:26.640 --> 00:26:30.237 much in the last and I'm not even counting like video scrolling apps just 00:26:30.320 --> 00:26:33.117 like an actual connect to people and 00:26:33.200 --> 00:26:35.277 like look at information about them 00:26:35.360 --> 00:26:38.397 style apps have not changed that much. I 00:26:38.480 --> 00:26:41.597 think uh moldbook points to the first 00:26:41.680 --> 00:26:45.437 interesting new thing where you can imagine a bunch of agents on behalf of 00:26:45.520 --> 00:26:48.877 their users off in a virtual space talking to each other like exchanging 00:26:48.960 --> 00:26:52.877 new information completely changing what it means to 00:26:52.960 --> 00:26:56.557 interact with other people on the internet like that was just not possible 00:26:56.640 --> 00:27:00.317 at all until very recently and now it feels like the space of social for the 00:27:00.400 --> 00:27:04.477 first time is totally open for some startup to do something completely new. 00:27:04.560 --> 00:27:07.677 Um, you know, a lot of people are like 00:27:07.760 --> 00:27:12.637 bolting AI into some productivity software and you know, like I don't 00:27:12.720 --> 00:27:16.477 really need something in Google Docs trying to like summarize it or write a 00:27:16.560 --> 00:27:19.277 sentence for me. I mean, that's like fine, but probably the whole thing of 00:27:19.360 --> 00:27:23.117 what it means to write a document is 00:27:23.200 --> 00:27:26.797 going to completely change. And there's a whole new kind of thing to imagine 00:27:26.880 --> 00:27:30.557 there. And this will apply not just traditional 00:27:30.640 --> 00:27:33.597 software startups, but most companies in 00:27:33.680 --> 00:27:39.757 the world pretty soon. You know, robots won't be that far off, whatever. Uh, 00:27:39.840 --> 00:27:41.837 I love times like this. They're rare. 00:27:41.920 --> 00:27:45.277 The iPhone when iPhone launched was one of them. I don't think we've really had 00:27:45.360 --> 00:27:48.637 one since. And the fact that this time, 00:27:48.720 --> 00:27:52.637 not only can you use the technology to do these things that you could never do 00:27:52.720 --> 00:27:56.477 before, but the fact that you can use technology to like make the product or 00:27:56.560 --> 00:28:01.037 make the company so quickly and with so few people, 00:28:01.120 --> 00:28:02.477 I think it's going to mean a lot more 00:28:02.560 --> 00:28:08.557 startups getting super successful really fast. And 00:28:08.640 --> 00:28:10.797 a lot of startups that have like one 00:28:10.880 --> 00:28:12.477 person or six people or something like 00:28:12.560 --> 00:28:15.837 that that get as impactful and as much 00:28:15.920 --> 00:28:18.157 revenue as some of the you know a 00:28:18.240 --> 00:28:21.837 medium-sized company does today. 00:28:21.920 --> 00:28:24.637 Do you think then that uh given you were 00:28:24.720 --> 00:28:29.037 talking about uh like Mbook these agents that like once AGI happens it will then 00:28:29.120 --> 00:28:32.237 surprise us and just all of a sudden like all of everything we've done all 00:28:32.320 --> 00:28:35.197 these new companies are popping up and creating themselves and integrating into 00:28:35.280 --> 00:28:39.517 our world and competing with things in a way like that or like how will it be 00:28:39.600 --> 00:28:44.600 introduced into our world then >> uh 00:28:45.440 --> 00:28:46.557 so I think I think that what it's going 00:28:46.640 --> 00:28:50.157 to feel like in the next few years let's 00:28:50.240 --> 00:28:55.037 say two years is stuff's just going to happen faster. You know, startups are 00:28:55.120 --> 00:28:57.597 going to do new things faster. Existing companies are going to ramp their 00:28:57.680 --> 00:29:00.317 revenue faster. It will feel like we've 00:29:00.400 --> 00:29:04.957 broken the laws of traditional speed and product development and 00:29:05.040 --> 00:29:08.077 business growth rates and and things like that. And, you know, companies will 00:29:08.160 --> 00:29:11.677 start to hire AI co-workers um and do 00:29:11.760 --> 00:29:13.997 amazing things with fewer people. Uh, I 00:29:14.080 --> 00:29:15.437 I think we'll continue to see AI 00:29:15.520 --> 00:29:19.757 research go much faster. Um, and we'll 00:29:19.840 --> 00:29:22.477 see scientific research happen much faster, but I don't think it'll feel 00:29:22.560 --> 00:29:25.837 like totally autonomous companies 00:29:25.920 --> 00:29:27.277 transacting with each other in an 00:29:27.360 --> 00:29:31.837 environment sort of moldbook style. Uh, 00:29:31.920 --> 00:29:33.997 eventually that probably does happen. 00:29:34.080 --> 00:29:37.837 Uh, and you know, one of one of the sort of 00:29:37.920 --> 00:29:42.237 like central observations I've had in life is that 00:29:42.320 --> 00:29:44.637 people are unbelievably adaptable. 00:29:44.720 --> 00:29:48.557 Societyy's unbelievably adaptable. So that sounds like a totally crazy 00:29:48.640 --> 00:29:52.397 destabilizing thing. And I bet it's not going to be as weird 00:29:52.480 --> 00:29:55.597 to live through as it sounds or only for a day. 00:29:55.680 --> 00:29:57.997 >> So I kind of wanted to go back to that thing that you'd mentioned about 00:29:58.080 --> 00:30:01.197 societal impacts. I mean, how do you think this is going to impact like 00:30:01.280 --> 00:30:04.877 politics like religion? like just expanding more just outside of like the 00:30:04.960 --> 00:30:06.557 startup space. How's society going to be 00:30:06.640 --> 00:30:09.517 impacted by this? Do you feel 00:30:09.600 --> 00:30:13.597 >> one of the um everyone's got a different definition 00:30:13.680 --> 00:30:17.197 for AGI, different definition for super intelligence. Uh you know, I kind of 00:30:17.280 --> 00:30:20.877 think like the most important definitions are something about the 00:30:20.960 --> 00:30:23.197 ability to self-improve. But one of the 00:30:23.280 --> 00:30:25.197 ones I like as a sort of example for a 00:30:25.280 --> 00:30:28.797 way to think about this is if 00:30:28.880 --> 00:30:32.637 if we had an AI system that could do a 00:30:32.720 --> 00:30:35.197 better job at making decisions 00:30:35.280 --> 00:30:37.117 than anyone we could possibly have be 00:30:37.200 --> 00:30:40.877 say president of the United States. Uh 00:30:40.960 --> 00:30:44.157 would we and like confidently much better. 00:30:44.240 --> 00:30:48.077 >> Um would we politically or society want that? 00:30:48.160 --> 00:30:51.517 >> It's very unclear. uh you know most people I think today at least would say 00:30:51.600 --> 00:30:54.157 probably not. Um maybe as things evolve 00:30:54.240 --> 00:30:56.637 more they do or you know like an AI CEO 00:30:56.720 --> 00:30:58.557 of a big company would would you rather 00:30:58.640 --> 00:31:02.077 have uh I think it'd be awesome for open 00:31:02.160 --> 00:31:04.557 AI to have an AI CEO but I think a lot 00:31:04.640 --> 00:31:10.077 of people be like ah that's a little that's a little scary. Um, 00:31:10.160 --> 00:31:13.517 if though AI is better at doing some of 00:31:13.600 --> 00:31:17.917 these things, I think there will be like many things that people are better at 00:31:18.000 --> 00:31:19.677 than AI long term, or at least people 00:31:19.760 --> 00:31:21.917 really care about other people doing, 00:31:22.000 --> 00:31:25.277 but I have no delusions that an AI will 00:31:25.360 --> 00:31:27.517 not be a better CEO of OpenAI than me at 00:31:27.600 --> 00:31:31.757 some reasonably soon time. Um, if 00:31:31.840 --> 00:31:34.477 if that's true and if some companies or 00:31:34.560 --> 00:31:39.197 countries don't do that and others do and AI is much better like that will 00:31:39.280 --> 00:31:41.997 have a real impact in economic competitiveness, national 00:31:42.080 --> 00:31:45.917 competitiveness, things like that. And and so I think one of the things that 00:31:46.000 --> 00:31:48.077 will happen about how this is going to 00:31:48.160 --> 00:31:54.120 impact us economically, society, politically is 00:31:54.560 --> 00:31:56.557 if the AI is just much better, I think 00:31:56.640 --> 00:31:58.477 people will feel increasingly like we 00:31:58.560 --> 00:32:01.917 either do worse or we put the AI in more 00:32:02.000 --> 00:32:06.157 and more influential positions. I think people will always like, you know, if 00:32:06.240 --> 00:32:09.197 you think of like an AI CEO of a company, I think people will always want 00:32:09.280 --> 00:32:10.557 human board members and that's probably 00:32:10.640 --> 00:32:14.717 a really great idea. Um, but 00:32:14.800 --> 00:32:17.837 I kind of think that 00:32:17.920 --> 00:32:21.197 people may have not quite 00:32:21.280 --> 00:32:23.997 I certainly have not really wrestled 00:32:24.080 --> 00:32:28.237 with like is there a way that this 00:32:28.320 --> 00:32:29.997 doesn't happen and what all of the 00:32:30.080 --> 00:32:32.557 political, economic, societal impacts 00:32:32.640 --> 00:32:36.477 are. Uh, I I still believe that although 00:32:36.560 --> 00:32:40.557 it sounds like a completely crazy thing to say, 00:32:40.640 --> 00:32:43.837 we're very adaptable. We really care about other people. You know, maybe 00:32:43.920 --> 00:32:47.917 there's like a AI CEO, but you just care about like the 00:32:48.000 --> 00:32:51.197 company's spokesperson speaking to you in these 00:32:51.280 --> 00:32:53.597 like 8second video clips or whatever. 00:32:53.680 --> 00:32:56.680 >> Um, 00:32:59.360 --> 00:33:02.637 >> I think I'm not a jobs doomer at all. I mean a lot of the current jobs are going 00:33:02.720 --> 00:33:05.917 to go away or be heavily changed but 00:33:06.000 --> 00:33:08.717 human desire for 00:33:08.800 --> 00:33:13.117 being useful to each other to compete with each other uh to like create 00:33:13.200 --> 00:33:15.517 differential status to do something 00:33:15.600 --> 00:33:18.637 fulfilling to express creativity that is 00:33:18.720 --> 00:33:21.917 not going to go anywhere. And maybe 00:33:22.000 --> 00:33:25.677 maybe the jobs of 100 years from now look nothing like the jobs of today. 00:33:25.760 --> 00:33:28.397 >> Yeah. nor do that many of the jobs of today 00:33:28.480 --> 00:33:32.397 look much like the jobs of a few hundred years ago. Um, 00:33:32.480 --> 00:33:36.477 but I'm confident we'll have stuff to do. I'm confident we'll really care 00:33:36.560 --> 00:33:38.317 about other people and less about the 00:33:38.400 --> 00:33:42.957 machines. And then beyond that, uh, 00:33:43.040 --> 00:33:46.957 yeah, I think we're just like AI is going to get ever more competent and 00:33:47.040 --> 00:33:50.397 we're going to have we're gonna want to use it for more and more things. 00:33:50.480 --> 00:33:54.237 >> Awesome. All right, so we're gonna go into a quick Q&A segment now uh, with 00:33:54.320 --> 00:33:56.957 questions from the audience. I would love like hard questions that I've never 00:33:57.040 --> 00:34:00.557 heard before. We have a Slack channel, Sam Alman Q&A. 00:34:00.640 --> 00:34:05.597 >> Sam Alman Q&A, guys, and a lot of you have put in questions. Um, 00:34:05.680 --> 00:34:08.317 >> so we're going to we're going to start off by reading some of the questions 00:34:08.400 --> 00:34:12.157 that were already submitted, I think, since we posted it yesterday. But we 00:34:12.240 --> 00:34:15.757 encourage you guys to submit more questions and then if you really really 00:34:15.840 --> 00:34:17.997 like a certain question, we want you to 00:34:18.080 --> 00:34:22.877 just uh reply with some sort of emoji so that we can see it and we can ask Sam. 00:34:22.960 --> 00:34:24.237 Awesome. All right. You want to start off 00:34:24.320 --> 00:34:25.837 >> to get started? Uh, you're talking about 00:34:25.920 --> 00:34:29.037 like OpenAI potentially having a AI CEO. 00:34:29.120 --> 00:34:32.797 So, if you ask a question that's kind of related to this about like say OpenAI 00:34:32.880 --> 00:34:34.877 becomes this like end- all beall company 00:34:34.960 --> 00:34:37.597 that can do anything because it's uh CEO 00:34:37.680 --> 00:34:40.557 is an AI. How do you compete with OpenAI 00:34:40.640 --> 00:34:45.517 then in in the future? Um, 00:34:45.600 --> 00:34:48.237 when we started OpenAI, everyone was like, you can't do this. You can't 00:34:48.320 --> 00:34:50.557 compete with Google. It's impossible. 00:34:50.640 --> 00:34:54.477 And there will someday be much bigger and more successful companies than 00:34:54.560 --> 00:34:58.557 OpenAI. They will not do exactly what OpenAI does. Uh you may steal our users. 00:34:58.640 --> 00:35:01.277 You may do some other thing. You may like have a replacement product. It will 00:35:01.360 --> 00:35:07.400 not very unlikely to be exactly what Open AAI does. Uh 00:35:08.320 --> 00:35:12.397 Google screwed up, didn't react enough to our approach early enough. They're, 00:35:12.480 --> 00:35:15.757 you know, doing a very nice nice job now, but had Google had their act 00:35:15.840 --> 00:35:19.597 together, we would not have been able to get off the ground at all. Um and they 00:35:19.680 --> 00:35:24.557 had very smart people. It's just big companies have big company problems. Uh 00:35:24.640 --> 00:35:26.237 someone in this room I hope will do the 00:35:26.320 --> 00:35:29.597 same thing to OpenAI. 00:35:29.680 --> 00:35:34.397 We are in we sell intelligence for what 00:35:34.480 --> 00:35:37.677 I think of as a very low price. Um you 00:35:37.760 --> 00:35:39.277 have 00:35:39.360 --> 00:35:42.637 probably the biggest option space of any 00:35:42.720 --> 00:35:45.837 startup of any of startups that have at 00:35:45.920 --> 00:35:48.877 any time in history. If if you try to 00:35:48.960 --> 00:35:52.317 make like an exact copy of chatbt or 00:35:52.400 --> 00:35:55.357 codecs or you know frontier models in an 00:35:55.440 --> 00:35:59.277 API probably not going to work. There's 00:35:59.360 --> 00:36:03.437 so much other stuff to do. Uh and the 00:36:03.520 --> 00:36:08.877 best thing of all is to figure out you know we talked about this earlier 00:36:08.960 --> 00:36:12.157 like things that are just going to totally change now. Take your pick. 00:36:12.240 --> 00:36:16.317 We're not going to be able to go do all those things. Uh, and neither is any 00:36:16.400 --> 00:36:20.077 other company that is not a startup and that has the sort of like freedom to be 00:36:20.160 --> 00:36:23.517 a little bit weird and decisive and pull together a band of rebels. Just go do 00:36:23.600 --> 00:36:28.317 that. It always sounds really scary. I remember how many like very wise people 00:36:28.400 --> 00:36:30.477 said you can't start an AI company. 00:36:30.560 --> 00:36:32.397 Google's just going to crush you. Uh, 00:36:32.480 --> 00:36:34.237 maybe they still do. I don't know. Um, 00:36:34.320 --> 00:36:39.117 but just just like go at it. 00:36:39.200 --> 00:36:42.877 >> Um, okay. Well, I can ask the next question. Um, this might be a burning 00:36:42.960 --> 00:36:47.357 question. Let me see. All right. News reports say OpenAI is burning cash very 00:36:47.440 --> 00:36:51.117 fast and could face liquid liquidity pressure in the future. How do you plan 00:36:51.200 --> 00:36:55.117 to handle this? And is the situation really as serious as you think the media 00:36:55.200 --> 00:36:56.317 reports it to be? 00:36:56.400 --> 00:36:58.557 >> Uh we are burning cash very fast. It is 00:36:58.640 --> 00:37:02.237 not a serious situation like the you 00:37:02.320 --> 00:37:06.637 know if we can spend a billion dollars this year to make $3 00:37:06.720 --> 00:37:10.317 billion next year there's a lot of capital in the world that wants to do 00:37:10.400 --> 00:37:12.397 that. So we will raise a lot of money 00:37:12.480 --> 00:37:18.920 equity and debt. we will spend a lot of money. We'll make a lot of money. Uh the 00:37:19.040 --> 00:37:21.677 it's weird. The economy hasn't seen 00:37:21.760 --> 00:37:26.237 something quite like this before, but given what we see about revenue growth 00:37:26.320 --> 00:37:29.357 and model growth and how much model growth correlates with future revenue 00:37:29.440 --> 00:37:32.877 growth, we're like, 00:37:32.960 --> 00:37:36.797 yeah, super confident in where things are going to go. 00:37:36.880 --> 00:37:37.837 >> Yeah. 00:37:37.920 --> 00:37:39.437 >> So, we've got another question here. 00:37:39.520 --> 00:37:44.480 It's um Sam, are you really happy 00:37:45.010 --> 00:37:48.077 >> [laughter] >> I I am actually one of the happiest 00:37:48.160 --> 00:37:50.477 people I know. Uh but I didn't used to 00:37:50.560 --> 00:37:52.957 be. I used to be a very anxious person. 00:37:53.040 --> 00:37:57.117 Um the [snorts] 00:37:57.200 --> 00:38:01.437 a thing people say to me all the time is like you have a miserable job. You have 00:38:01.520 --> 00:38:03.917 all the stress. You have all these people coming after you. You have like 00:38:04.000 --> 00:38:06.077 crazy bad You know, so many things 00:38:06.160 --> 00:38:07.997 happen to you a day. Like how do you not 00:38:08.080 --> 00:38:12.397 have a mental breakdown? Um, and 00:38:12.480 --> 00:38:15.997 my answer to that is like I just figured out what it was going to take for me 00:38:16.080 --> 00:38:19.197 like in my 20s when I realized I was not particularly happy and certainly not 00:38:19.280 --> 00:38:22.717 particularly calm. I figured out what it was going to take for me to get happy 00:38:22.800 --> 00:38:25.837 and calm. Um, I think people find their 00:38:25.920 --> 00:38:28.397 own paths there. But, 00:38:28.480 --> 00:38:30.877 uh, meditation was a big part of it for 00:38:30.960 --> 00:38:33.917 me. Uh, and it's kind of like a onetime 00:38:34.000 --> 00:38:38.317 thing. And now like even when stuff is 00:38:38.400 --> 00:38:42.717 really hard, like really painful, um, 00:38:42.800 --> 00:38:46.157 one of a thing I kind of 00:38:46.240 --> 00:38:48.317 learned in meditation that always stuck 00:38:48.400 --> 00:38:53.277 with me is that everybody thinks the opposite of a bad experience is a good 00:38:53.360 --> 00:38:56.877 experience. So if I'm having a bad experience, then I'm not happy because I 00:38:56.960 --> 00:38:58.397 wish I were having a good experience. 00:38:58.480 --> 00:38:59.997 And the kind of like a big mental shift 00:39:00.080 --> 00:39:02.637 for me was to reframe it as the opposite 00:39:02.720 --> 00:39:05.917 of a bad experience is no experience. 00:39:06.000 --> 00:39:09.757 And someday that'll happen to you and you'll miss the bad experiences too. And 00:39:09.840 --> 00:39:12.717 you know like I have a lot of days where it's very stressful and very hard and a 00:39:12.800 --> 00:39:16.557 lot of things go wrong. Uh I'm still grateful for them. 00:39:16.640 --> 00:39:19.357 >> Adding on to this um someone asks what 00:39:19.440 --> 00:39:22.637 does a day in your life look like then? 00:39:22.720 --> 00:39:28.317 >> Um absolute chaos. Uh I I like wake up 00:39:28.400 --> 00:39:30.717 early. I work for a few hours. I can I 00:39:30.800 --> 00:39:32.957 kind of have control of my life until 00:39:33.040 --> 00:39:37.277 like 8 o'clock in the morning. Uh 00:39:37.360 --> 00:39:40.557 and I can like get something done. I can try to drive whatever I'm want to get 00:39:40.640 --> 00:39:44.317 done. Then I play with my kid for an hour. Then I go into the office. And 00:39:44.400 --> 00:39:47.197 then it's just like insane. 00:39:47.280 --> 00:39:49.117 Whatever is going to happen happens like 00:39:49.200 --> 00:39:55.160 crazy. I don't think any company has been as 00:39:55.760 --> 00:39:58.157 fastm moving, chaotic in everybody's 00:39:58.240 --> 00:40:02.317 crosshairs as us. And so it's just yeah, 00:40:02.400 --> 00:40:05.837 unpredictable chaos all day. >> Yeah, a lot of us definitely don't wake 00:40:05.920 --> 00:40:08.077 up at uh before 8 in the morning. 00:40:08.160 --> 00:40:12.637 >> I did not used to wake up early. This this this job is the thing that made me 00:40:12.720 --> 00:40:16.077 start doing it. >> Awesome. >> Should we do two more questions and then 00:40:16.160 --> 00:40:18.317 >> let's do two more questions and then we'll wrap up. 00:40:18.400 --> 00:40:21.037 >> We are at time. 00:40:21.120 --> 00:40:23.037 I I have another question from someone. 00:40:23.120 --> 00:40:25.517 Um, what AI sub field today feels like 00:40:25.600 --> 00:40:30.077 open AI in 2016 a little undervalued or underestimated but could shoot out of 00:40:30.160 --> 00:40:33.597 nowhere? >> Uh, that's a good that's a great 00:40:33.680 --> 00:40:37.277 question there. This is the kind of question that I would like spend a lot 00:40:37.360 --> 00:40:40.237 of time trying to think about. Uh, I'm 00:40:40.320 --> 00:40:41.917 not sure if you mean it as like a 00:40:42.000 --> 00:40:46.397 research thing or a company thing. Uh, 00:40:46.480 --> 00:40:49.037 I'll answer both and I'll do it quickly 00:40:49.120 --> 00:40:50.397 because I know we're almost out of time. 00:40:50.480 --> 00:40:53.997 Um, on the research 00:40:54.080 --> 00:40:56.237 perspective, 00:40:56.320 --> 00:40:58.877 I bet there is another new architecture 00:40:58.960 --> 00:41:01.197 to find that is going to be like as big 00:41:01.280 --> 00:41:04.557 of a gain as transformers were over 00:41:04.640 --> 00:41:08.317 LSTMs. And I think you finally have models that 00:41:08.400 --> 00:41:11.597 are smart enough to help do that kind of research. 00:41:11.680 --> 00:41:14.637 So I would I would go look for like 00:41:14.720 --> 00:41:17.837 where can I find a mega 00:41:17.920 --> 00:41:23.117 breakthrough uh and I would use the models to help me on the product side. I 00:41:23.200 --> 00:41:26.557 guess we talked about this a little bit earlier, but I would I would just pick a 00:41:26.640 --> 00:41:29.117 big area and say what is possible now 00:41:29.200 --> 00:41:32.397 with AI that wasn't possible at all 00:41:32.480 --> 00:41:34.317 before. like where can I totally redo 00:41:34.400 --> 00:41:37.357 something that's like AI is the absolute 00:41:37.440 --> 00:41:42.637 core to the the interaction working and 00:41:42.720 --> 00:41:45.437 look I don't want to say this is like a once in a-lifetime opportunity because I 00:41:45.520 --> 00:41:48.477 hope the world keeps getting dramatically better every few years and 00:41:48.560 --> 00:41:51.677 that if we all came back here or actually when some of you come back here 00:41:51.760 --> 00:41:53.597 and sit up here and talk to the then 00:41:53.680 --> 00:41:58.157 current students um AGI will uh look 00:41:58.240 --> 00:42:01.277 like just a warm-up for whatever the next important thing was and that'll 00:42:01.360 --> 00:42:04.637 keep going for the rest of history. Um, 00:42:04.720 --> 00:42:07.677 but this is at least the best time ever 00:42:07.760 --> 00:42:11.960 so far. And what 00:42:13.200 --> 00:42:16.157 what you can do now is so crazily 00:42:16.240 --> 00:42:20.157 exciting that I think you should probably try to figure out how to take 00:42:20.240 --> 00:42:23.117 advantage of this moment. >> Yeah. 00:42:23.200 --> 00:42:26.317 >> And one last question. Um, a lot of labs 00:42:26.400 --> 00:42:30.397 like XAI and Google have their own data centers and even custom silicon for 00:42:30.480 --> 00:42:34.637 inference. Does OpenAI have any interest in developing hardware as well or stick 00:42:34.720 --> 00:42:36.877 to external partners? Why or why not? 00:42:36.960 --> 00:42:39.117 >> Uh we have a big custom silicon program. 00:42:39.200 --> 00:42:42.157 Um we 00:42:42.240 --> 00:42:44.717 we're very excited about our uh our 00:42:44.800 --> 00:42:47.677 inference chip and clearly the world 00:42:47.760 --> 00:42:52.077 wants a lot of cheap tokens and I think what we're working on there will be 00:42:52.160 --> 00:42:54.877 great. We have a very deep partnership with Nvidia. We do all of our training 00:42:54.960 --> 00:42:56.317 on Nvidia. We also use them for a lot of 00:42:56.400 --> 00:42:59.757 inference. Um but 00:42:59.840 --> 00:43:02.877 we are excited to be doing uh our our 00:43:02.960 --> 00:43:05.837 chip in our system. Um building data 00:43:05.920 --> 00:43:08.397 centers I would love to not have to do 00:43:08.480 --> 00:43:10.877 that. [laughter] Um if we have to at 00:43:10.960 --> 00:43:14.557 some point we will. Uh 00:43:14.640 --> 00:43:18.477 that's you know like you can't do everything well as a company and that's 00:43:18.560 --> 00:43:22.477 like a big intensive thing to do. Um if we can just design a great rack and have 00:43:22.560 --> 00:43:25.677 other people operate those and build the crazy buildings around them that'd be 00:43:25.760 --> 00:43:28.637 awesome. Thank you, Sam. Everyone, let's give it 00:43:28.720 --> 00:43:32.880 up for Sam. >> Thank you. [applause]