Sam Altman: OpenAI, GPT-5, Sora, Board Saga, Elon Musk, Ilya, Power & AGI | Lex Fridman Podcast #419

Sam Altman 0:00 I think compute is gonna be the currency of the future. I think it will be maybe the most precious commodity in the world. I expect that by the end of this decade, and possibly somewhat sooner than that, we will have quite capable systems that we look at and say, "Wow, that's really remarkable." The road to AGI should be a giant power struggle. I expect that to be the case.

Lex Fridman 0:26 Whoever builds AGI first gets a lot of power. Do you trust yourself with that much power? The following is a conversation with Sam Altman, his second time on the podcast. He is the CEO of OpenAI, the company behind GPT-4, ChatGPT, Sora, and perhaps one day the very company that will build AGI. This is the Lex Fridman Podcast. To support it, please check out our sponsors in the description. And now, dear friends, here's Sam Altman.

Lex Fridman 1:05 Take me through the OpenAI board saga that started on Thursday, November 16th, maybe Friday, November 17th for you.

Sam Altman 1:13 That was definitely the most painful professional experience of my life, and... chaotic, and shameful, and upsetting, and a bunch of other negative things. Uh, there were great things about it too, and I wish, I wish it had not been in such an adrenaline rush that I wasn't able to stop and appreciate them at the time, but, um... I came across this old tweet of mine, or this tweet of mine from that time period, which was like, it was like, you know, kind of going to your own eulogy, watching people say all these great things about you, and, uh, just, like, unbelievable support from people I- I love and care about. Uh, that was really nice. Um, that whole weekend I- I kind of like felt, with one big exception, I- I felt, like, a great deal of love. And very little hate. Um... Even though it felt like it just, I have no idea what's happening and what's gonna happen here, and this feels really bad, and... There were definitely times I thought it was gonna be like, one of the worst things to ever happen for AI safety. But I also think I'm happy that it happened relatively early. I thought at some point between when OpenAI started and when we created AGI, there was gonna be something crazy and explosive that happened. But there may be more crazy and explosive things still to happen. Um, it still, I think, helped us build up some resilience and be ready for... more challenges in the future.

Lex Fridman 3:02 But the thing y- you had a sense that you would experience is some kind of power struggle.

Sam Altman 3:08 The road to AGI should be a giant power struggle. Like, the world should... I- like, well, not should. I expect that to be the case.

Lex Fridman 3:17 And so you have to go through that as, like you said, iterate as often as possible, uh, in figuring out how to have a board structure, how to have organization, how to have, um, the kind of people that you're working with, how to communicate, all that, i- in order to, uh, deescalate the power struggle as much as possible.

Sam Altman 3:37 Yeah.

Lex Fridman 3:37 Pacify it.

Sam Altman 3:38 But at this point, it feels... You know, like something that was in the past that was really unpleasant and really difficult and painful. But we're back to work, and things are so busy and so intense that I don't spend a lot of time thinking about it. There was a time after, uh, there was like this fugue state, um, for kind of like the month after, maybe 45 days after, that was... I was just sort of like drifting through the days. I was so out of it. Um, I was feeling so down. Uh-

Lex Fridman 4:17 Just on a personal, psychological level.

Sam Altman 4:19 Yeah. Really painful. Um, and hard to like have to keep running OpenAI in the middle of that. I just wanted to like crawl into a cave and kinda recover for a while. But, you know, now it's like we're just back to working on a mission.

Lex Fridman 4:38 Well, it's still useful to go back there and reflect on board structures, on power dynamics, on how companies are run, the tension between research and product development and money and all this kind of stuff, so that you, who have a very high potential of building AGI, would do so in a slightly more organized, less dramatic way-

Sam Altman 5:06 Yeah.

Lex Fridman 5:06 ... in the future. So, there's value there to go both the personal psychological aspects of you as a leader and also just the- the board structure and all this kind of messy stuff.

Sam Altman 5:18 Definitely learned a lot about, um, structure and incentives and, um, what we need out of a- a board. Um, and I think that is... It is valuable that this happened now in some sense. Um, I think this is probably not, like, the last high stress moment of OpenAI, but it was quite a high stress moment. My company very nearly got destroyed. And we think a lot about many of the other things we've gotta get right for AGI, but thinking about, uh, how to build a resilient org and how to build a structure that will stand up to, like, a lot of pressure in the world, which I expect more and more as we get closer, I think that's super important.

Lex Fridman 6:01 Do you have a sense of how deep and rigorous the deliberation process by the board was? Like, can you shine some light...... on just human dynamics involved in situations like this? Was it just a few conversations and all of a sudden it escalates and, "Why don't we fire Sam?" kind of thing.

Sam Altman 6:19 I think... I think the board members were, are well-meaning people on the whole. Um, and I believe that in stressful situations, um, where people feel time pressure, whatever, uh, people understandably make suboptimal decisions, and I think one of the challenges for OpenAI will be, we're gonna have to have a board and a team, uh, that are good at operating under, under pressure.

Lex Fridman 7:00 Do you think the board had too much power?

Sam Altman 7:03 I think boards are supposed to have a lot of power. Um, but one of the things that we did see is, in, in most corporate structures, boards are usually answerable to shareholders, so, you know, there's, sometimes people have, like, super voting shares or whatever. Um, in this case, and I think one of the things with our structure that we maybe should have thought about more than we did, is that the board of a nonprofit has, unless you put other rules in place, like, quite a, quite a lot of power. They don't really answer to anyone but themselves and there's ways in which that's good, but what we'd really like is for the board of OpenAI to, like, answer to the world as a whole as much as that's a practical thing.

Lex Fridman 7:44 So, there's a new board announced.

Sam Altman 7:46 Yeah.

Lex Fridman 7:47 There's, I guess, uh, a new smaller board at first, and now there's a new final board.

Sam Altman 7:53 Not a final board yet. We've added some, we'll add more.

Lex Fridman 7:55 Added some, okay. What is fixed in the new one that was perhaps broken in the previous one?

Sam Altman 8:06 The old board sort of got smaller, uh, over the course of about a year. It was nine and then it went down to six. And then we couldn't agree on who to add. And the board also, uh, I think didn't have a lot of experienced board members, uh, and a lot of the new board members at OpenAI are, have just, have more experience as board members. Um, I think that'll help.

Lex Fridman 8:31 It's been criticized, some of the people that are added to the board. I heard a lot of people criticizing the addition of Larry Summers, for example. What, what's the process of selecting the board like? What's involved in that?

Sam Altman 8:43 So Brett and Larry were kind of, uh, decided in the heat of the moment over this, like, very tense weekend, and that was a, I mean, that weekend was, like, a real rollercoaster. It was like a lot of-

Lex Fridman 8:53 Mm-hmm.

Sam Altman 8:53 ... a lot of ups and downs. Um, and we were trying to agree on new board members that both sort of the executive team here and the old board members felt would be reasonable. Um, Larry was actually one of their suggestions, the old board members. Um, Brett, I think I had even previous to that weekend suggested, but he was, you know, busy and didn't wanna do it, and then we really needed help in Wood. Um, we talked about a lot of other people too, uh, but that was... I felt like if I was going to come back, uh, I needed new board members. Um, I didn't think I could work with the old board again in the same configuration, although we then decided, uh, and I'm grateful that Adam would stay, um, but we wanted to get to, uh, we considered various configurations, decided we wanted to get to a board of three, and, uh, h- had to find two new board members over the course of sort of a short period of time. So those were decided honestly without a, you know, that's like, you kinda do that on the battlefield. You don't have time to design a rigorous process then. Um, for new board members since, and new board members we'll add going forward, um, we have some criteria, uh, that we think are important for the board to have, different expertise that we want the board to have. Um, unlike hiring an executive where you need them to do one role well, the board needs to do a whole role of kind of governance and thoughtfulness, uh, well. And so one thing that Brett says, which I really like, is that, you know, we wanna hire board members in slates, not as individuals one at a time. And, uh, you know, thinking about a group of people that will bring nonprofit expertise, expertise in running companies, sort of good legal and governance expertise. Uh, that's kind of what we've tried to optimize for.

Lex Fridman 10:49 So is technical savvy important for the individual board members?

Sam Altman 10:52 Not for every board member, but for s- certainly some you need that. That's part of what the board needs to do.

Lex Fridman 10:56 So, I mean, the interesting thing that people probably don't understand about OpenAI, I certainly don't, is, like, all the details of running the business. When they think about the board, given the drama, they think about you, they think about, like, if you reach AGI or you reach some of these incredibly impactful products and you build them and deploy them, what's the conversation with the board like? And they kinda think, all right, what's the right squad to have in that kind of situation to deliberate ?

Sam Altman 11:25 Look, I think you definitely need some technical experts there, and then you need some people who are like, "What can... How can we deploy this in a way that will help people in the world the most?" And, and people who have a very different perspective. You know, I think a mistake that you or I might make is to think that only the technical understanding matters. And that's definitely part of the conversation you want that board to have. But there's a lot more about how that's gonna just, like, impact society and people's lives that you really want represented in there too.

Lex Fridman 11:55 And you're just kinda... Are you looking at the track record of people or you're just having conversations?

Sam Altman 12:00 Track record is a big deal. And you, you of course have a lot of conversations, but I, um... You know, there's some roles where I kind of...... totally ignore track record and just look at slope, kinda ignore the Y-intercept, but-

Lex Fridman 12:18 Thank you. Thank you for making it mathematical for the, for the audience.

Sam Altman 12:21 For a board member, like, I do care much more about the Y-intercept. Like, I think there is something deep to say about track record there, and experience is sometimes very hard to replace.

Lex Fridman 12:32 Do you try to fit a polynomial function or an exponential one to the, to the track record?

Sam Altman 12:36 That's not that... No.

Lex Fridman 12:37 Okay.

Sam Altman 12:37 A- an- analogy doesn't carry that far.

Lex Fridman 12:39 All right. You mentioned some of the low points, uh, that weekend. What were some of the low points, psychologically, for you? Uh, did you consider going, um, to the Amazon jungle and just taking ayahuasca and disappearing forever? Or...

Sam Altman 12:53 I mean, there's so many low... Like, it was kind of a very bad period of time. There were great high points too, like, uh, my phone was just, like, sort of non-stop blowing up with nice messages from people I work with every day, people I hadn't talked to in a decade.

Lex Fridman 13:09 Mm-hmm.

Sam Altman 13:09 I didn't get to, like, appreciate that as much as I should have, 'cause I was just, like, in the middle of this firefight, but that was really nice. But on the whole, it was, like, a very painful weekend, and also just, like, a very... It was like a battle fought in public, to a surprising degree, and that's, that was extremely exhausting to me, much more than I expected. Um, I mean, I think fights are generally exhausting, but this one really was. You know, the board did this, uh, Friday afternoon. I really couldn't get much in the way of answers, but I also was just like, "Well, the board gets to do this." And so I'm gonna think for a little bit about what I wanna do, but I'll try to li- find the, the blessing in disguise here. And I was like, well, I, you, you know my current job at OpenAI is, or it was, like, to, like, run a, you know, decently sized company at this point, and the thing I'd always liked the most was just getting to, like, work on, work with the researchers. And I was like, "Yo, I can just go do, like, a very focused AGI research effort." And I got excited about that. Didn't even occur to me at the time to, like, possibly, that this was all gonna get undone. This was like Friday afternoon.

Lex Fridman 14:18 Oh, so you accepted your, the death of this prev-

Sam Altman 14:22 Very quickly. Very quickly, like within, you know... I mean, I went through, like, a little period of confusion and rage, but very quickly. And by Friday night, I was like, talking to people about what was gonna be next, and I was excited about that. Um, I think it was Friday night, evening for the first time, that I heard from the exec team here, which was like, "Hey, we're gonna, like, fight this and, you know, we think w- whatever." And then I went to bed just still being like, "Okay, excited, like, onward."

Lex Fridman 14:52 Were you able to sleep?

Sam Altman 14:54 Not a lot. It was, one o- one of the weird things was there was this, like, period of four, four and a half days where sort of didn't sleep much, didn't eat much, and still kinda had, like, a surprising amount of energy. It was, you learn like a weird thing about adrenaline in wartime.

Lex Fridman 15:09 So you kind of accepted the death of a, you know, this baby, OpenAI, that-

Sam Altman 15:13 And I was excited for the new thing. I was just like, "Okay, this was crazy, but whatever."

Lex Fridman 15:17 It's a very good coping mechanism.

Sam Altman 15:18 And then Saturday morning, uh, two of the board members called and said, "Hey, we, you know, destabilized... We didn't mean to destabilize things. We don't want to destroy a lot of value here. You know, can we talk about you coming back?" And I immediately didn't want to do that, but I thought a little more and, and was like, "Well, I, you know, really care about the people here, the partners, shareholders, like, all of the... I love this company." And so I thought about it and I was like, "Well, okay, but like, here's, here's the stuff I would need." And, and then the most painful time of all was, over the course of that weekend, um, I kept thinking and being told and we all kept, not just me, like the whole team here kept thinking, while we were trying to, like, keep OpenAI stabilized while the whole world was trying to break it apart, people trying to recruit, whatever. Um, we kept being told like, "All right, we're almost done, we're almost done. We just need, like, a little bit more time." Um, and it was this, like, very confusing state. And then Sunday evening when, again, like every few hours, I expected that we were gonna be done and we're gonna, like, figure out a way for me to return and things to go back to how they were, um, the board then, uh, appointed a new interim CEO. And then I was like, "I mean that is, that is, that feels really bad." That was the low point of the whole thing.

Lex Fridman 16:35 (sighs)

Sam Altman 16:36 You know, I'll tell you something. I, it felt very painful, but I felt a lot of love that whole weekend.

Lex Fridman 16:43 Mm-hmm.

Sam Altman 16:44 It was not... Other than that one moment F- Sunday night, I would not characterize my emotions as anger or hate. Um, but I really just like... I felt a lot of love from people towards people. It was, like, painful, but it would like... The dominant emotion of the weekend was love, not hate.

Lex Fridman 17:04 You've spoken highly of, uh, Mira Murati, that she helped especially, as you put in a tweet, "In the quiet moments when it counts." Perhaps we could take a bit of a tangent. What do you admire about Mira?

Sam Altman 17:16 Well, she did a great job during that weekend, in a lot of chaos. But, but, people often see leaders in the moment, in like the crisis moments, good or bad. Um, but the thing I really value in leaders is how people act on a boring Tuesday at 9:46 in the morning.

Lex Fridman 17:34 Mm-hmm.

Sam Altman 17:35 And in, in just sort of the, the, the normal drudgery of the day-to-day. How someone shows up in a meeting, the quality of the decisions they make. That was what I meant about the quiet moments.

Lex Fridman 17:47 Meaning like, most of the work is done on a day-by-day-

Sam Altman 17:51 Yeah.

Lex Fridman 17:51 ... in the meeting-by-meeting, just, oh, just be present and, and make great decisions

Narrator 17:58 Yeah.

Lex Fridman 17:58 ... by doing so.

Sam Altman 17:58 I mean, look, what you wanted to s- have wanted to spend the last 20 minutes about, and I understand, is like this one very dramatic weekend.

Lex Fridman 18:05 Yeah.

Sam Altman 18:06 But that's not really what OpenAI is about. OpenAI is really about the other seven years.

Lex Fridman 18:10 Well, yeah. Human civilization is not about...... the invasion of the Soviet Union by Nazi Germany, but still that's something people-

Sam Altman 18:17 Totally.

Lex Fridman 18:17 ... focus on because-

Sam Altman 18:18 Very, very understandable.

Lex Fridman 18:19 It gives us an insight into human nature, the extremes of human nature, and perhaps some of the damage and some of the triumphs of human civilization can happen in those moments. So it's like illustrative.

Lex Fridman 18:31 Let me ask you about Ilya. Is he being held hostage in a secret nuclear facility?

Sam Altman 18:36 No.

Lex Fridman 18:37 What about a regular secret facility?

Sam Altman 18:39 No.

Lex Fridman 18:40 What about a nuclear non-secret facility?

Sam Altman 18:41 Neither of that.

Lex Fridman 18:42 Okay. (laughs)

Sam Altman 18:42 Not, not that either.

Lex Fridman 18:43 I mean, this is becoming a meme at some point. You've known Ilya for a, for a long time. He was, obviously he's in part, part of this drama with the board and all that kind of stuff. What's your relationship with him, uh, now?

Sam Altman 18:57 I love Ilya. I have tremendous respect for Ilya. I, uh, I don't have anything I can, like, say about his plans right now. That's, that's a question for him. Um, but I really hope we work together for, you know, certainly the rest of my career. He's a little bit younger than me, maybe he works a little bit longer. (laughs)

Lex Fridman 19:14 (laughs) You know, there's a, there's a meme that he saw something. Like, he maybe saw AGI and that gave him a lot of worry internally. Uh, what did Ilya see?

Sam Altman 19:28 Uh, well, he has not seen AGI. None of us have seen AGI.

Lex Fridman 19:31 Mm-hmm.

Sam Altman 19:31 We have not built AGI. Uh, I do think, uh, one of the many things that I really love about Ilya is he takes AGI and the safety concerns broadly speaking, you know, including things like the impact this is gonna have on society very seriously. And we, as we continue to make significant progress, um, Ilya is one of the people that I've spent the most time over the last couple of years talking about what this is going to mean, what we need to do to ensure we get it right, to ensure that we succeed at the mission. Um, so Ilya did not see AGI, um, but Ilya is a credit to humanity in terms of how much he thinks and worries about making sure we get this right.

Lex Fridman 20:30 I've had a bunch of conversation with him in the past. I think when he talks about technology, he's always, like, doing this long-term thinking type of thing. So he's not thinking about what this is gonna be in a year, he's thinking about it in 10 years.

Sam Altman 20:42 Yeah.

Lex Fridman 20:43 Just thinking from first principles, like, okay, if this scales, what are the fundamentals here? Where's this going? And so that, that's a foundation for then thinking about, like, all the other safety concerns and all that kind of stuff, um, which makes him a really fascinating human, uh, to talk with. Do you have, uh, any idea why he's been kind of quiet? Is it he's just doing some soul searching?

Sam Altman 21:08 Again, I don't want to, like, speak for Ilya.

Lex Fridman 21:11 (laughs) Mm-hmm.

Sam Altman 21:11 I think that y- you should ask him that. Um... He's definitely a thoughtful guy. Uh, I think I kind of think of Ilya as, like, always on a soul search in a really good way.

Lex Fridman 21:27 Yes. Yeah. Also, he appreciates the power of silence. Also, I'm told he can be a silly guy, which I've never-

Sam Altman 21:35 Totally.

Lex Fridman 21:35 I've never seen that side of him.

Sam Altman 21:36 It's very, it's very sweet when that happens. (laughs)

Lex Fridman 21:39 (laughs) I've never witnessed a silly Ilya, but, um, I look forward to, to that as well.

Sam Altman 21:43 I was at a dinner party with him recently and he was playing with a puppy, and I re- and he was, like, in a very silly mood, very endearing. And I was thinking like, "Oh man, this is, like, not the side of Ilya that the world sees the most."

Lex Fridman 21:55 So just to wrap up this whole saga, are you feeling good about the board structure-

Sam Altman 22:01 Yes.

Lex Fridman 22:01 ... about all of this and, like, where it's moving?

Sam Altman 22:04 I feel great about the new board. In terms of the structure of OpenAI, I, you know, one of the board's tasks is to look at that and see where we can make it more robust. Um, we wanted to get new board members in place first, uh, but, you know, we clearly learned a lesson about structure throughout this process. I don't have, I think, super deep things to say. It was a crazy, very painful experience. I think it was like a perfect storm of weirdness. It was like a preview for me of what's gonna happen as the stakes get higher and higher, and the need that we have, like, robust governance structures and processes and people. Um, I am kind of happy it happened when it did, but it was a shockingly painful thing to go through.

Lex Fridman 22:47 Did it make you be more hesitant in trusting people?

Sam Altman 22:50 Yes.

Lex Fridman 22:51 Just on a personal level?

Sam Altman 22:53 Yes. I think I'm, like, an extremely trusting person. I have, I've a- always had a life philosophy of, you know, like, don't worry about all of the paranoia, don't worry about the edge cases. You know, you get a little bit screwed in exchange for getting to live with your guard down.

Lex Fridman 23:06 Mm-hmm.

Sam Altman 23:07 And this was so shocking to me, I was so caught off guard, that it has definitely changed, and I really don't like this. It's definitely changed how I think about just, like, default trust of people and planning for the bad scenarios.

Lex Fridman 23:21 You got to be careful with that. Are you worried about becoming a little too cynical?

Sam Altman 23:26 Um, I'm not worried about becoming too cynical. I think I'm, like, the extreme opposite of a cynical person, but I'm, I'm, I'm worried about just becoming, like, less of a default trusting person.

Lex Fridman 23:36 I'm actually not sure which mode is best to operate in for a person who's developing AGI, trusting or untrusting. It's an interesting journey you're on. But in terms of structure, see, I'm more interested on the human level, like, how do you surround yourself with humans that are building cool shit, but also are making wise decisions?

Sam Altman 24:00 Yes.

Lex Fridman 24:00 'Cause the more money you start making, the more power the thing has, the weirder people get.

Sam Altman 24:05 You know, I think you could, like, could make all kinds of comments about the board members and the level of trust I should have had there, or how I should have done things differently. But in terms of the team here-I think you'd have to, like, give me a very good grade on that one. Um, and I have, uh, just like enormous gratitude and trust, and respect for the people that I work with every day, and I think being surrounded with people like that is, is really important.

Lex Fridman 24:39 Our

Lex Fridman 24:40 mutual friend Elon sued OpenAI. What do you think is the essence of what he's criticizing? To what degree does he have a point? To what degree is he wrong?

Sam Altman 24:52 I don't know what it's really about. We started off just thinking we were gonna be a research lab, and having no idea about how this technology was gonna go. It's hard to... because it was only, you know, seven or eight years ago, it's hard to go back and really remember what it was like then. But this was before language models were a big deal. This was before we had any idea about an API, or selling access to a chatbot. This was before we had any idea we were going to productize at all. So we're like, "Eh, we're just like gonna try to do research and, you know, we don't really know what we're going to do with that." I think with like many new, fundamentally new things, you start fumbling through the dark and you make some assumptions, most of which turn out to be wrong. And then it became clear that we were going to need to do different things, and also have huge amounts more capital. So we said, "Okay, well the structure doesn't quite work for that. How do we patch the structure?" Um, and then patch it again and patch it again, and you end up with something that does look kind of eyebrow raising to say the least. But we got here gradually with, I think, reasonable decisions at each point along the way, and doesn't mean I wouldn't do it totally differently if we could go back now with an oracle, but you don't get the oracle at the time. But anyway, in terms of what Elon's real motivations here are, I don't know.

Lex Fridman 26:12 To the degree you remember, what was the response that OpenAI gave in the blog post? Can you summarize it?

Sam Altman 26:21 Oh, we just said like, you know, "Elon said this set of things. Here's our characterization, or here's the sort of... not our characterization, here's like the characterization of how this went down." Uh, we tried to like not make it emotional, and just sort of say, like... "Here's the history."

Lex Fridman 26:44 I do think there's a degree of mischaracterization from Elon here about one of the points you just made, which is the degree of uncertainty you had at the time. You guys are a bunch of, like, a small group of researchers crazily talking about AGI when everybody's laughing at that thought.

Sam Altman 27:09 Wasn't that long ago Elon was crazily talking about launching rockets-

Lex Fridman 27:13 Yeah.

Sam Altman 27:13 ... when people were laughing at that thought. Uh, so I think he'd have more empathy for this.

Lex Fridman 27:20 I mean, I, I do think that there's personal stuff here. That there was a split. That OpenAI and a lot of amazing people here chose to part ways with Elon. So there's a personal thing.

Sam Altman 27:33 Elon chose to part ways.

Lex Fridman 27:37 Can you describe that exactly? The, the choosing to part ways.

Sam Altman 27:41 He thought OpenAI was gonna fail. Um, he wanted total control to sort of turn it around. We wanted to keep going in the direction that now has become OpenAI. He also wanted Tesla to be able to build an AGI effort. At various times he wanted to make OpenAI into a for-profit company that he could have control of, or have it merge with Tesla. Um, we didn't want to do that and he decided to leave, which that's fine.

Lex Fridman 28:06 So you're saying, and that's one of the things that the blog post says is that he wanted OpenAI to be basically acquired by Tesla?

Sam Altman 28:16 Yeah.

Lex Fridman 28:17 In those same way that... Or maybe something similar, or maybe something more dramatic than the partnership with Microsoft?

Sam Altman 28:23 My memory is the proposal was just like, yeah, like get acquired by Tesla and have Tesla have full control over it. I'm pretty sure that's what it was.

Lex Fridman 28:29 So what is the word "open" in OpenAI mean to Elon at the time? Ilya has talked about this in, in the email exchanges and all this kind of stuff. What does it mean to you at the time? What does it mean to you now?

Sam Altman 28:43 I would definitely pick a diff- Speaking of going back with an oracle, I'd pick a different name. Um, one of the things that I think OpenAI is doing that is the most important of everything that we're doing is putting powerful technology in the hands of people for free as a public good. Not, we're not... You know, we don't run ads on our free version. We don't monetize it in other ways. We just say, "As part of our mission, we wanna put increasingly powerful tools in the hands of people for free, and get them to use them." And I think that kind of open is really important to our mission. I think if you give people great tools and teach them to use them, or don't even teach them, they'll figure it out, and let them go build an incredible future for each other with that, uh, that's a big deal. So if we can keep putting like free or low cost, or free and low cost powerful AI tools out in the world, uh, I think that's a huge deal for how we fulfill the mission. Um, open source or not? Yeah, I think we should open source some stuff and not other stuff. Uh, the... It does become this like religious battle line where nuance is hard to have, but I think nuance is the right answer.

Lex Fridman 29:55 So he said, "Change your name to ClosedAI and I'll drop the lawsuit." I mean, is it going to become this battleground in, in the land of memes about the name?

Sam Altman 30:06 I, I think that speaks to the seriousness with which Elon means the lawsuit. And, uh, yeah, I mean, that's like an astonishing thing to say, I think. Like-

Lex Fridman 30:21 Well, I don't think the lawsuit ma- maybe correct me if I'm wrong, but I don't think the lawsuit is legally serious. It's more to make a point about the future of AGI and the company that's currently leading the way. So...

Sam Altman 30:37 Look, I mean Grok had not open sourced anything until people pointed out it was a little bit hypocritical, and then he announced that Grok will open source things this week. Uh, I don't think open source versus not is what this is really about for him.

Lex Fridman 30:48 Well, we'll talk about open source and not. I do think maybe criticizing the competition is great, just talking a little shit is great, but friendly competition versus like... I personally hate lawsuits.

Sam Altman 31:01 Look, I think this whole thing is like unbecoming of a builder, and I respect Elon as one of the great builders of our time, and, um, I know he knows what it's like to have like haters attack him and it makes me extra sad he's doing it to us.

Lex Fridman 31:18 Yeah, he's one of the greatest builders of all time. Potentially the greatest builder of all time.

Sam Altman 31:22 It makes me sad. And I think it makes a lot of people sad. Like there's a lot of people who've really looked up to him for a long time and said this- I said, you know, in some interview or something that I missed the old Elon, and the number of messages I got being like that exactly encapsulates how I feel.

Lex Fridman 31:36 I think he should just win. He should just, um, make X Grok beat GPT, and then GPT beats Grok, and it's just a competition, and that's just beautiful for everybody. But on the question of open source, do you think... There's a lot of companies playing with this idea, it's quite interesting. I would say Meta, surprisingly-

Sam Altman 31:59 Mm-hmm.

Lex Fridman 31:59 ... has led the way on this, or like, uh, at least took the first step in the game of chess of, like, really open sourcing the model. Of course it's not the, uh, state-of-the-art model, but open sourcing LLaMA, um, you know Google is flirting with the idea of open sourcing a smaller version. Have you... What are the pros and cons of open sourcing? Have you played around with this idea?

Sam Altman 32:22 Yeah, I think there- there is definitely a place for open source models, particularly smaller models that people can run locally, I think there's huge demand for. Um, I think there will be some open source models, there will be some closed source models. Uh, this, it won't be unlike other ecosystems in that way.

Lex Fridman 32:39 I listened to All-In Podcast talking about this, this lawsuit and all that kind of stuff, and they were more concerned about the precedent of going from non-profit to this cap-for-profit. What precedent this sets for other startups, is that something-

Sam Altman 32:55 I don't... (laughs) I would heavily discourage any startup that was thinking about starting as a non-profit and adding like a for-profit arm later. I'd heavily discourage them from doing that. I don't think we'll set a precedent here.

Lex Fridman 33:05 Okay. So most, most startups should go just-

Sam Altman 33:08 For sure.

Lex Fridman 33:09 ... traditional?

Sam Altman 33:09 I mean, again, if we knew what was going to happen, we would have done that too.

Lex Fridman 33:12 Well, like in theory, if you like dance beautifully here, you could, there's like some tax incentives or whatever, but-

Sam Altman 33:19 I don't think that's like how most people think about these things.

Lex Fridman 33:22 So it's not possible to save a lot of money for a startup if you do it this way?

Sam Altman 33:27 No, I think there's like laws that would make that pretty difficult.

Lex Fridman 33:30 Where do you hope this goes with Elon? Well, this- this tension, this dance, where do you hope this... Like if we go one, two, three years from now, your relationship with him on- on a personal level too, like friendship, friendly competition, just all this kind of stuff.

Sam Altman 33:51 Yeah, I- I really respect Elon, um... And I hope that years in the future we have an amicable relationship.

Lex Fridman 34:05 Yeah, I hope you guys have an amicable relationship like this month. (laughs) And just compete and win and, um, and explore these ideas together. Um, I do suppose there's competition for talent or whatever, but, uh, it should be friendly competition. Just build, build cool shit. And Elon is pretty good at building cool shit, but so are you.

Lex Fridman 34:32 So speaking of cool shit, uh, Sora. There's like a million questions that I could ask. First of all, it's amazing. It truly is amazing on a product level, but also just on a philosophical level. So let me just, uh, technical/philosophical ask, what do you think it understands about the world more or less than GPT-4, for example? The world model when you train on these patches versus language tokens.

Sam Altman 35:04 I think all of these models understand something more about the world model than most of us give them credit for. And because there are also very clear things they just don't understand or don't get right, it's easy to like look at the weaknesses, see through the veil and say, "Ah, this is just, this is all fake." But it's not all fake, it's just some of it works and some of it doesn't work. Like I remember when I started first watching Sora videos and I would see like a person walk in front of something for a few seconds and include it and then walk away and the same thing was still there. I was like, "Ah."

Lex Fridman 35:37 Mm-hmm.

Sam Altman 35:37 "That's pretty good."

Lex Fridman 35:38 Mm-hmm.

Sam Altman 35:39 Or there's examples where it like the underlying physics looks so well represented over, uh, you know, a lot of steps in a sequence. It's like, "Oh, this is, this is like quite impressive." But like fundamentally, these models are just getting better, and that will keep happening. If you look at the trajectory from DALLE-1 to 2 to 3 to Sora, you know there are a lot of people that were dunked on each version, saying, "It can't do this, it can't do that," and like look at it now.

Lex Fridman 36:05 Well, the thing you just mentioned is kind of with occlusions is basically modeling the physics, the three-dimensional physics of the world sufficiently well to capture those kinds of things.

Sam Altman 36:17 Well-

Lex Fridman 36:18 Or like under... Or yeah, maybe you can tell me. In order to deal with occlusions, what does the world model need to-

Sam Altman 36:24 Yeah, so what I would say is it's doing something to deal with occlusions really well. Would I represent that it has like a great underlying 3D model of the world?It's a little bit more of a stretch.

Lex Fridman 36:33 But can you get there through just these kinds of two-dimensional training data approaches?

Sam Altman 36:38 Uh, it looks like this approach is gonna go surprisingly far. I don't wanna speculate too much about what limits it will surmount and which it won't, but...

Lex Fridman 36:46 What are some interesting limitations of the system that you've seen? I mean, there's been some fun ones you've posted.

Sam Altman 36:52 There's all kinds of fun... I mean, like, you know, cats sprouting an extra limb at random points in a video. Uh, like, pick what you want, but there's still a lot of problem... uh, still a lot of weaknesses.

Lex Fridman 37:02 Do you think that's a fundamental flaw of the approach, or is it just, mm, you know, bigger model or better, like, technical details or better data, more data is going to solve those, uh, uh, the cats sprouting extremes?

Sam Altman 37:18 I would say yes to both. Like, I think there is something about the approach which just seems to feel different from how we think and learn and whatever, and then also I think it'll get better with skill.

Lex Fridman 37:30 Like I mentioned, LLMs have tokens, text tokens, and Sora has visual patches, so it converts all visual data, uh, diverse kinds of visual data, videos and images into patches. Is the training to the degree you can say fully self-supervised, or is there some manual labeling going on? Like, what's the involvement of humans in all this?

Sam Altman 37:49 I mean, without saying anything specific about the Sora approach, we, we use lots of human data in our work.

Lex Fridman 38:00 But not internet-scale data. So lots of humans. Lots is a complicated word, Sam. (laughs)

Sam Altman 38:07 Well, (laughs) I think lots is a fair word in this case.

Lex Fridman 38:11 But it doesn't... 'cause to me, lots... like, listen, I'm an introvert, and when I hang out with, like, three people, that's a lot of people.

Sam Altman 38:17 Yeah.

Lex Fridman 38:17 Four people, that's a lot. But I suppose you mean more than...

Sam Altman 38:21 More than three people work on labeling the data for these models, yeah.

Lex Fridman 38:24 Okay. All right. But fundamentally, there's a lot of self-supervised learning, 'cause, uh, you, th- what you mentioned in the technical report is internet-scale data. That's another beautiful... it's like poetry. Uh, so it's a lot of data that's not human label. It's like-

Sam Altman 38:42 Yeah.

Lex Fridman 38:42 It's self-supervised in that way.

Sam Altman 38:44 Yeah.

Lex Fridman 38:45 And then the question is how much int- how much data is there on the internet that could be used in this c- that, uh, is conducive to this kind of s- self-supervised way? If only we knew th- the details of the self-supervised. Do you, have you considered opening it up a little more, the details?

Sam Altman 39:02 We have. For... you mean for Sora specifically?

Lex Fridman 39:04 Sora specifically, the train-... 'cause it's so interesting that, like, can this LL... can the same magic of LLMs now start moving towards visual data, and h- what does that take to do that?

Sam Altman 39:18 I mean, it looks to me like yes, but we have more work to do.

Lex Fridman 39:22 Sure. What are the dangers? Why are you concerned about releasing the system? What, uh, what are some possible dangers of this?

Sam Altman 39:29 I mean, frankly speaking, one thing we have to do before releasing the system is, is just, like, get it to work at a, a level of efficiency that will deliver the scale people are gonna want from this, so that... I don't wanna, like, downplay that end. There's still a ton, ton of work to do there. But, you know, you can imagine, like, issues with deepfakes, misinformation, um, like... we try to be a thoughtful company about what we put out into the world, and it doesn't take much thought to think about the ways this can go badly.

Lex Fridman 40:05 There's a lot of tough questions here. Uh, you're dealing in a very tough space. Do you think training AI should be or is fair use under copyright law?

Sam Altman 40:14 I think the question behind that question is, do people who create valuable data deserve to have some way that they get compensated for use of it? And that, I think the answer is yes. I don't know yet what the answer is. People have proposed a lot of different things. We've some- tried some different models. But, you know, if I'm, like, an artist, for example, A, I would like to be able to opt out of people generating art in my style, and B, if they do generate art in my style, I'd like to have some economic model associated with that.

Lex Fridman 40:46 Yeah, it's that, uh, transition from CDs to Napster to Spotify. We have to figure out some kind of model.

Sam Altman 40:52 The model changes, but people have gotta get paid.

Lex Fridman 40:55 Well, there should be some kind of incentive, if we zoom out even more, for humans to keep doing cool shit.

Sam Altman 41:02 Out of everything I worry about, humans are gonna do cool shit, and society's gonna find some way to reward it. I, I... that seems pretty hardwired. We wanna create. We wanna be useful. We want to, like, achieve status in whatever way.

Lex Fridman 41:15 Mm-hmm.

Sam Altman 41:15 That's not going anywhere, I don't think.

Lex Fridman 41:17 But the reward might not be monetary, financial. It might be, like, fame and celebration of other cool p-

Sam Altman 41:25 Eh, maybe financial in some other way. Again, I don't think we've seen, like, the last evolution of how the economic system's gonna work.

Lex Fridman 41:31 Yeah, but artists and creators are worried. When they see Sora, they're like, "Holy shit."

Sam Altman 41:36 Sure, artists were also super worried when photography came out.

Lex Fridman 41:40 Yeah.

Sam Altman 41:40 A- and then photography became a new art form and people made a lot of money taking pictures, and I think things like that'll keep happening. People will use the new tools in new ways.

Lex Fridman 41:50 If you just look on YouTube or something like this, how much of that will be using Sora, like, AI-generated content do you think in the next five years?

Sam Altman 42:01 People talk about, like, how many jobs is AI gonna do in five years, and, and the framework that people have is, what percentage of current jobs are just gonna be totally replaced by some AI doing the job? The way I think about it is not what percent of jobs AI will do, but what percent of tasks will AI do and over what time horizon? So if you think of all of the, like, five-second tasks in the economy, the five-minute tasks, the five-hour tasks, maybe even the five-day tasks, how many of those can AI do? And I think that's a way more interesting, impactful, important question than...... how many jobs AI can do, because it is a tool that will work at increasing levels of sophistication and over longer and longer time horizons, for more and more tasks, and let people operate at a higher level of abstraction. So maybe people are way more efficient at the job they do, and at some point, that's not just a quantitative change, but it's a qualitative one too about the kinds of problems you can keep in your head. I think that for videos on YouTube, it'll be the same. Many videos, maybe most of them, will use AI tools in the production, but they'll still be fundamentally driven by a person thinking about it, putting it together, you know, doing parts of it, sort of-

Lex Fridman 43:16 Yeah.

Sam Altman 43:16 ... directing it and running it.

Lex Fridman 43:18 Yeah, that's so interesting. I mean, it's scary, but it's interesting to think about. I tend to believe that humans like to watch other humans, or other human-like-

Sam Altman 43:26 Humans really care about other humans, a lot.

Lex Fridman 43:29 Yeah. If there's a cooler thing that's more- that's better than a human, humans care about that for, like, two days, and then they go back to humans. (laughs)

Sam Altman 43:39 That seems very deeply wired.

Lex Fridman 43:41 It's the whole chess thing.

Sam Altman 43:42 Yeah.

Lex Fridman 43:43 Oh, this is yeah, but no. Let's everybody keep playing ch- And let's ignore the elephant in the room, that humans are really bad at chess, relative to AI systems.

Sam Altman 43:52 We still run races, and cars are much faster. I mean, this is- there's, like, a lot of examples.

Lex Fridman 43:56 Yeah. And maybe it'll just be tooling, like, in the Adobe suite type of way, where it can just make videos much easier and all that kinda stuff. Listen, I hate being in front of the camera. If I can figure out a way to not be in front of the camera, I would love it. Unfortunately, it will take a while. Like that, generating faces, though it's- it's getting there, but generating faces in video format is tricky when it's specific people versus generic people.

Lex Fridman 44:24 Let me ask you about GPT-4. There's so many questions. Uh, first of all, also amazing. It's- looking back, it'll probably be this kinda historic, pivotal moment with three, five, and four, with ChatGPT.

Sam Altman 44:40 Maybe five will be the pivotal moment. I don't know.

Lex Fridman 44:42 (laughs)

Sam Altman 44:43 Hard to say that looking forwards.

Lex Fridman 44:44 We never know. That's the annoying thing about the future, it's hard to predict. But for me, looking back, GPT-4, ChatGPT is pretty damn impressive, like historically impressive. So allow me, uh, to ask, what's been the most impressive capabilities of GPT-4 to you, and GPT-4 Turbo?

Sam Altman 45:06 I think it kinda sucks.

Lex Fridman 45:07 Hmm. Typical human also.

Sam Altman 45:09 It's-

Lex Fridman 45:09 Gotten used to an awesome thing.

Sam Altman 45:11 No, I think it is an amazing thing, um, but relative to where we need to get to and where I believe we will get to, uh, you know, at the time of, like, GPT-3, people were like, "Oh, this is amazing. This is this, like, marvel of technology," and it is, it was. Uh, but, you know, now we have GPT-4 and you look at GPT-3 and you're like, "That's unimaginably horrible." Um, I expect that the delta between five and four will be the same as between four and three, and I think it is our job to live a few years in the future and remember that the tools we have now are gonna kinda suck looking backwards at them, and that's how we make sure the future is better.

Lex Fridman 45:59 What are the most glorious ways in that GPT-4 sucks? Meaning, uh-

Sam Altman 46:05 What are the best things it can do?

Lex Fridman 46:06 What are the best things it can do, and the- the limits of those best things that allow you to say it sucks, therefore gives you an inspiration, a hope for the future?

Sam Altman 46:16 You know, one way I've been using it for more recently is sort of a- like a brainstorming partner.

Lex Fridman 46:23 Yep.

Sam Altman 46:24 And-

Lex Fridman 46:24 I'll use it for that.

Sam Altman 46:25 ... there's a glimmer of something amazing in there. I don't think it gets... You know, when people talk about it, it- what it does, they're like, "Oh, it helps me code more productively. It helps me write more faster and better. It helps me, you know, translate from this language to another," all these, like, amazing things. But there's something about the, like, kind of creative brainstorming partner, I need to come up with a name for this thing. I need to, like, think about this problem in a different way. I'm not sure what to do here. Uh, that I think, like, gives a glimpse of something I hope to see more of. Um, one of the other things that you can see, like, a very small glimpse of is when it can help on longer horizon tasks, you know, break down something in multiple steps, maybe, like, execute some of those steps, search the internet, write code, whatever, put that together. Uh, when that works, which is not very often, it's, like, very magical.

Lex Fridman 47:24 The iterative back and forth with a human. Well, it works a lot for me. What do you mean it won't work?

Sam Altman 47:29 Uh, w- iterative back and forth with a human, it can get more often. Well, then it can go do, like, a 10-step problem on its own.

Lex Fridman 47:33 Oh.

Sam Altman 47:34 Doesn't work for that too often. Sometimes.

Lex Fridman 47:37 Add multiple layers of abstraction, or do you mean just sequential?

Sam Altman 47:40 Uh, both. Like, you know, to break it down, and then do things at different layers of abstraction and put them together. Look, I don't wanna- I don't wanna, like, downplay the accomplishment of GPT-4.

Lex Fridman 47:51 Mm-hmm.

Sam Altman 47:51 Um, but I don't wanna overstate it either, and I think this point that we are on an exponential curve, we will look back relatively soon at GPT-4 like we look back at GPT-3 now.

Lex Fridman 48:03 That said, I mean, ChatGPT was a transition to where people, like, started to believe again. There was a kinda- there was an uptick of believing.

Sam Altman 48:14 Sure. Sure, sure, sure.

Lex Fridman 48:14 Not internally at OpenAI, perhaps. There's believers here, but, uh, when you think about

Sam Altman 48:19 ... And in that sense, I do think it'll be a moment where a lot of the world went from not believing to believing. Um, that was more about the ChatGPT interface than the... A- and- and by the interface-

Lex Fridman 48:30 Sure.

Sam Altman 48:30 ... and product, I also mean the post-training of the model and how we tune it to be helpful to you and how to use it than the underlying model itself.

Lex Fridman 48:38 How much have...... those two, uh, each of those things are important, the underlying model and the RLHF or something of that nature that tunes it to be more compelling to the human, more, uh, effective and productive for the human.

Sam Altman 48:55 I mean, they're, they're both super important, but the, the, the RLHF, the post-training step, the, you know, little wrapper of things that... from a compute perspective, little wrapper of things that we do on top of the base model even though it's a huge amount of work.

Lex Fridman 49:08 Mm-hmm.

Sam Altman 49:08 That's really important, to say nothing of the product that we build around it. Um... You know, in some sense, like, we did have to do two things. We had to invent the underlying technology, and then we had to figure out, uh, how to make it into a product people would love, which is not just about the actual product work itself, but this whole other step of how you align it and make it useful.

Lex Fridman 49:37 And how you make the scale work where a lot of people can use it at the same time, all that kinda stuff.

Sam Altman 49:43 And that. But, you know, that was, like, a known difficult thing. Like, we knew we were gonna have to scale it up. We had to go do two things that had, like, never been done before, uh, that were both, like, I would say quite significant achievements, and then a lot of things, like scaling it up, that other companies have had to do before.

Lex Fridman 50:01 How does the, the context window of going from 8K to 128K tokens compare from the... f- from GPT-4 to, to GPT-4 Turbo?

Sam Altman 50:12 People like long con- most people don't need all the way to 128 most of the time, although... You know, if we dream into the distant future, we'll have, like... like, way distant future, we'll have, like, context length of several billion. You will feed in all of your information, all of your history over time, and it'll just get to know you better and better, and that'll be great. For now, uh, the way people use these models, they're not doing that, and, you know, people sometimes post in a paper or, you know, a significant fraction of a code repository, whatever. Um... But most usage of the models is not using the long context most of the time.

Lex Fridman 50:50 I like that this is your I Have a Dream speech.

Sam Altman 50:53 (laughs)

Lex Fridman 50:54 One day, you'll be judged by the full context of your character, or, uh, of your whole lifetime. That's interesting. So, like, that's part of the expansion that you're hoping for, is greater and greater context.

Sam Altman 51:05 There's... I saw this internet clip once. I'm gonna get the numbers wrong, but it was, like, Bill Gates talking about the amount of memory on some early computer, maybe it was 64K, maybe 640K, something like that, and most of it was used for the screen buffer.

Lex Fridman 51:18 Hmm.

Sam Altman 51:19 And he just couldn't, seemed genuine, just couldn't imagine that the world would eventually need gigabytes of memory in a computer, or terabytes of memory in a computer. Um... And you always do, or you always do just need to, like, follow the exponential of technology and, and we're gonna, like... we will find out how to use better technology. So I can't really imagine what it's like right now for context lengths to go out to the billions someday. And they might not literally go there, but effectively, it'll feel like that. Um, but I know we'll use it and really not wanna go back once we have it.

Lex Fridman 51:56 Yeah, even saying billions 10 years from now might seem dumb because it'll be, like, trillions upon trillions.

Sam Altman 52:04 Sure.

Lex Fridman 52:04 There'll be some kinda breakthrough that will effectively feel like infinite context, but even 120... I, I have to be honest, I haven't pushed it to that degree (laughs) . Maybe putting in entire books or, like, parts of books and so on, papers. What are some interesting use cases of GPT-4 that you've seen?

Sam Altman 52:23 The thing that I find most interesting is not any particular use case, though we can talk about those, but it's people who kind of, like... This is mostly younger people, but people who use it as, like, their default start for any kind of knowledge work task.

Lex Fridman 52:38 Yeah.

Sam Altman 52:39 And it's the fact that it can do a lot of things reasonably well. You can use GPT-V. You can use it to help you write code. You can use it to help you do search. You can, uh, use it to, like, edit a paper. The most interesting thing to me is the people who just use it as the start of their workflow.

Lex Fridman 52:52 I do as well for, for many things. Like, uh, I use it as a, uh, a reading partner for reading books. It helps me think, help me think through ideas, especially when the books are classics so it's really well written about and... It actually is, is... I, I find it often to be significantly better than even, like, Wikipedia on well-covered topics. It's somehow more balanced and more nuanced. Or maybe it's me, but it inspires me to think deeper than a Wikipedia article does. I'm not exactly sure what that is. And you mentioned, like, this collaboration. I'm not sure where the magic is, if it's in here or if it's in there or if it's somewhere in between. I'm not sure. Uh, but one of the things that concerns me for knowledge tasks when I start with GPT is I'll usually have to do fact-checking after, like, check that it didn't come up with fake stuff. How, how do you figure that out, that, you know, GPT can come up with fake stuff that sounds really convincing? So g- how do you ground it in truth?

Sam Altman 53:55 That's obviously an area of intense interest for us. Uh, I think it's gonna get a lot better with upcoming versions, but we'll have to, you know, work on it and we're not gonna have it, like, all solved this year.

Lex Fridman 54:07 Well, the scary thing is, like, as it gets better, you'll start not doing the fact-checking more and more, right?

Sam Altman 54:13 I... I'm of two minds about that. I think people are, like, much more sophisticated users of technology than-

Lex Fridman 54:19 Sure.

Sam Altman 54:19 ... we often give them credit for, and people seem to really understand that GPT, any of these models hallucinate some of the time, and if it's mission-critical, you gotta check it.

Lex Fridman 54:27 Except journalists don't seem to understand that. I've seen journalists half-heartedly just using GPT-4. It's, it's-

Sam Altman 54:34 Of the long list of things I'd like to dunk on journalists for, this is not my top criticism of them.

Lex Fridman 54:40 Well, I think the bigger c- criticism is pro- perhaps the pressures and the incentives of being a journalist.... is that you have to work really quickly, and this is your shortcut. I- I would love our society to incentivize, like ...

Sam Altman 54:53 I would too.

Lex Fridman 54:55 ... long, like a journalist- journalistic efforts that take days and weeks, and- and rewards great in-depth journalism. Also, journalism that r- presents stuff in a balanced way, where it's like celebrates people while criticizing them, even though the criticism is the thing that gets clicks, and making shit up also gets clicks, and headlines that mischaracterize completely. I'm sure you have a lot of people dunking o- on ... Well, all that drama probably got a lot of clicks.

Sam Altman 55:21 Probably did. (laughs)

Lex Fridman 55:22 (laughs) Uh, and that- that's the, you know, that's a bigger problem about human civilization I would love to see solved is where we celebrate a bit more.

Lex Fridman 55:32 You've given ChatGPT the ability to have memories. You've been playing with that about previous conversations, and also the ability to turn off memory, which is, I wish I could do that sometimes, just turn on and off depending ... I guess sometimes alcohol can do that, but-

Sam Altman 55:47 (laughs)

Lex Fridman 55:47 ... not- not in, uh, not optimally, I suppose. Uh, what- what have you seen through that? Like, playing around with that idea of remembering conversations or not?

Sam Altman 55:56 We're very early in our exp- explorations here, but I think what people want, or at least what I want for myself, is a model that gets to know me and gets more useful to me over time. This is an early exploration. Um, I think there's, like, a lot of other things to do, but that's where we'd like to head. You know, you'd like to use a model and over the course of your life ... Or use a system. There'll be many models. And over the course of your life, it gets- it gets better and better.

Lex Fridman 56:26 Yeah. How hard is that problem? 'Cause right now, it's more like remembering little factoids and preferences and s- so on. What about remembering, like, don't you want GPT to remember all the shit you went through in November and all-

Sam Altman 56:39 Yeah.

Lex Fridman 56:39 ... all the drama, and then you can-

Sam Altman 56:40 Yeah, yeah, yeah.

Lex Fridman 56:41 'Cause right now, you're clearly blocking it out a little bit.

Sam Altman 56:43 It's not just that I want it to remember that. I want it to integrate the lessons of that-

Lex Fridman 56:48 Yes.

Sam Altman 56:49 ... and remind me in the future what to do differently or what to watch out for.

Lex Fridman 56:57 Mm-hmm.

Sam Altman 56:58 And, you know, we all gain from experience over the course of our lives, varying degrees, and I'd like my AI agent to gain with that experience, too. Um, so if we, if we go back and let ourselves imagine that, you know, trillions and trillions of context length, if I can put every conversation I've ever had with anybody in my life in there, if I can have all of my emails, input/output, like all of my input/output in the context window every time I ask a question, that'd be pretty cool, I think.

Lex Fridman 57:29 Yeah, I think that would be very cool. Um, people sometimes will hear that and be concerned about privacy. Is there ... What- what- what do you think about that aspect of it? The more effective the AI becomes at really integrating all the experiences and all the data that happened to you and give you advice ...

Sam Altman 57:48 I think the right answer there is just user choice. You know, anything I want stricken from the record for my AI agent, I wanna be able to, like, take out. If I don't want it to remember anything, I want that, too. You and I may have different opinions about where on that privacy utility trade-off for our own AI we wanna be, which is totally fine, but I think the answer is just, like, really easy user choice.

Lex Fridman 58:08 But there should be a- some high level of transparency from a company about the user choice, 'cause sometimes company in the past, companies in the past have been kind of-

Sam Altman 58:17 Absolutely.

Lex Fridman 58:17 ... shady about, like, eh, we're ... It's kind of presumed that we're collecting all your data, and we're using it for a good reason, for advertisement and so on. But there's not a transparency about the details of that.

Sam Altman 58:31 That's totally true. You- you know, you mentioned earlier that I'm, like, blocking out the November stuff. I-

Lex Fridman 58:35 Oh, just teasing you.

Sam Altman 58:36 Well, I mean, I think it was a very traumatic thing, and it did immobilize me for a long period of time. Like, definitely the hardest, like the hardest work thing I've had to do was just, like, keep working that period, 'cause I had to, like, you know, try to come back in here and put the pieces together while I was just, like, in sort of shock and pain, and you know, nobody really cares about that. I mean, I- the team gave me a pass, and I was not working at my normal level, but there was a period where I was just, like ... It was really hard to have to do both, but I kinda woke up one morning, and then I was like, "This was a horrible thing to happen to me. I think I could just feel like a victim forever, uh, or I can say this is, like, the most important work I'll ever touch in my life, and I need to get back to it." And it doesn't mean that I've repressed it, because sometimes I, like wake up in the middle of the night thinking about it, but I do feel, like, an obligation to keep moving forward.

Lex Fridman 59:32 Well, that- that's beautifully said, but there could be some lingering stuff in there. Like, what I would be concerned about is that trust thing that you mentioned, that being paranoid about people, uh, as opposed to just trusting everybody or most people, like using your gut. It's a tricky dance.

Sam Altman 59:50 For sure.

Lex Fridman 59:51 I mean, because I've seen in- in my part-time explorations, I've been diving deeply into the Zelensky administration and the Putin administration and the dynamics there in wartime in a very highly stressful environment, and what happens is distrust, and you isolate yourself both, and you start to not see the world clearly, and that's a concern. That's a human concern. You seem to have taken it in stride and kinda learned the good lessons and felt the love and let the love energize you, which is great, but still can linger in there. There's just some questions I would love to ask and your intuition about what's GPT able to do and not. So it's allocating approximately the same amount of compute for each token it generates. Is there room there in this kind of approach to slower thinking, sequential thinking?

Sam Altman 1:00:51 I think there will be a new paradigm for that kind of thinking.

Lex Fridman 1:00:55 Will it be similar, like architecturally, as what we're seeing now with LLMs? Is it a layer on top of the LLMs?

Sam Altman 1:01:03 Uh, I can imagine many ways to implement that. I think that's less important than the question you were getting at, which is, do we need a way to do a slower kind of thinking where the answer doesn't have to get, like... You know, it's li- like, I guess like spiritually you could say that you want an AI to be able to think harder about a harder problem-

Lex Fridman 1:01:26 Right.

Sam Altman 1:01:26 ... and answer more quickly about an easier problem. And I think that will be important.

Lex Fridman 1:01:30 Is that like a human thought that we're just having, you should be able to think hard? Is that a wrong intuition?

Sam Altman 1:01:34 I suspect that's a reasonable intuition.

Lex Fridman 1:01:37 Interesting. So it's not possible once the GPT gets like GPT-7, we'd just be, instantaneously be able to see, you know, here's, here's the proof of Fermat's theorem?

Sam Altman 1:01:49 It seems to me like you want to be able to allocate more compute to harder problems. Like, it seems to me that a system knowing... If, if you ask a system like that, Fermat's Last Theorem versus what's today's date, unless it already knew and had memorized the answer to the proof, assuming it's gotta go figure that out, seems like that will take more compute.

Lex Fridman 1:02:20 But can it look like a, basically LLM talking to itself, that kind of thing?

Sam Altman 1:02:25 Maybe. I mean, there's a lot of things that you could imagine working. What, like, what the right or the best way to do that will be, uh, we don't know.

Lex Fridman 1:02:37 This does make me think of the mysterious, the lore behind Q*.

Sam Altman 1:02:42 (laughs)

Lex Fridman 1:02:43 What's this mysterious Q* project? Is it also in the same nuclear facility?

Sam Altman 1:02:50 Uh, there is no nuclear facility.

Lex Fridman 1:02:52 Mm-hmm. That's what a person with a nuclear facility always says.

Sam Altman 1:02:54 I would love to have a secret nuclear facility.

Lex Fridman 1:02:56 (laughs)

Sam Altman 1:02:57 There isn't one.

Lex Fridman 1:02:59 All right. Uh-

Sam Altman 1:03:00 Maybe someday.

Lex Fridman 1:03:01 Someday? All right. (laughs) One can dream.

Sam Altman 1:03:05 OpenAI is not a good company at keeping secrets. It would be nice, you know, we're like been plagued by a lot of leaks, and it would be nice if we were able to have something like that.

Lex Fridman 1:03:14 Can you speak to what Q* is?

Sam Altman 1:03:16 We are not ready to talk about that.

Lex Fridman 1:03:17 See, but an answer like that means there's something to talk about. It's very mysterious, Sam.

Sam Altman 1:03:23 I mean, we work on all kinds of research.

Lex Fridman 1:03:25 Yeah.

Sam Altman 1:03:26 Uh, we have said for a while that we think better reasoning in these systems is an important direction that we'd like to pursue. We haven't cracked the code yet. Uh, we're in- we're very interested in it.

Lex Fridman 1:03:48 Is there gonna be moments, Q* or otherwise, where there's going to be leaps similar to ChatGPT, where you're like...

Sam Altman 1:03:56 That's a good question. Um, what do I think about that? It's interesting. To me, it all feels pretty continuous.

Lex Fridman 1:04:08 Right, this is kind of a theme that you're saying, is there's a gradual, you're basically gradually going up an exponential slope. But from an outsider perspective, from me just watching it, it does feel like there's leaps. But to you, there isn't.

Sam Altman 1:04:22 I do wonder if we should have... So, you know, part of the reason that we deploy the way we do is that we think, um, we call it iterative deployment. We, uh, rather than go build in secret until we got all the way to GPT-5, we decided to talk about GPT-1, two, three, and four. And part of the reason there is I think AI and surprise don't go together. And also, the world, people, institutions, whatever you wanna call it, need time to adapt and think about these things. And I think one of the best things that OpenAI has done is this strategy, and we, we get the world to pay attention to the progress, to take AGI seriously, to think about what systems and structures and governance we want in place before we're like under the gun and have to make a rush decision. I think that's really good. But the fact that people like you and others say, um, you still feel like there are these leaps makes me think that maybe we should be doing our releasing even more iteratively. I don't know what that would mean. I don't have an answer ready to go. But like our goal is not to have shock updates to the world. The opposite.

Lex Fridman 1:05:29 Yeah, for sure. More iter- iterative would be amazing. I think that's just beautiful for everybody.

Sam Altman 1:05:34 But that's what we're trying to do. That's like our state of the strategy, and I think we're somehow missing the mark. So maybe we should think about, you know, releasing GPT-5 in a different way or something like that.

Lex Fridman 1:05:44 Yeah, 4.71, 4.72, but people tend to like to celebrate, people celebrate birthdays. I don't know if you know humans, but they kinda have these, uh, milestones and-

Sam Altman 1:05:54 I do know some humans. Um, people do like milestones. I, uh, I totally get that. I think we like milestones too. It's like fun to, you know, say, declare victory on this one and go start the next thing. But, but yeah, I feel like we're somehow getting this a little

Sam Altman 1:06:12 bit wrong.

Lex Fridman 1:06:13 So, uh, when is GPT-5 coming out again?

Sam Altman 1:06:15 I don't know. That's the honest answer.

Lex Fridman 1:06:18 Oh, that's the honest answer. Is it blink twice if it's this year?

Sam Altman 1:06:25 (laughs) I also... We will release an amazing new model this year. I don't know what we'll call it.

Lex Fridman 1:06:36 So that goes to the question of like what, what's the way we release this thing?

Sam Altman 1:06:41 We'll release, over, in the coming months, many different things. Uh, I think they'll be very cool. Uh, I think before we talk about like a GPT-5 like model called that or called, or not called that, or a little bit worse or a little bit better than what, what you'd expect from a GPT-5, I think we have a lot of other important things to release.... first.

Lex Fridman 1:07:02 I don't know what to expect from GPT-5. (laughs) You're making me nervous and excited. Uh, what, what are some of the biggest challenges and bottlenecks to overcome for whatever it ends up being called? But let's call it GPT-5. Just interesting to ask, what are... Is it on the compute side? Is it on the technical side?

Sam Altman 1:07:21 It's always all of these... I was, I was, you know, what's the one big unlock? Is it, is it a bigger computer? Is it, like, a new secret? Is it something else? Um, it's all of these things together. Like, the thing that OpenAI, I think, does really well... This is actually an original Ilya quote that I'm gonna butcher, but it's something like, "We multiply 200 medium sized things together into one giant thing."

Lex Fridman 1:07:47 So there's this, uh, distributed constant innovation happening.

Sam Altman 1:07:50 Yeah.

Lex Fridman 1:07:51 So even on the tactical side, like, uh-

Sam Altman 1:07:53 Especially on the tactical side.

Lex Fridman 1:07:55 So even, like, detailed approaches, like, d- detailed aspects of every... How does that work with different disparate teams and so on? Like, how, how do they, how do (laughs) how do the medium sized things become one whole giant transformer? How does this...

Sam Altman 1:08:08 There's a few people who have to, like, think about putting the whole thing together, but a lot of people try to keep most of the picture in their head.

Lex Fridman 1:08:14 Oh, like the individual teams, individual contributors try to keep the big picture?

Sam Altman 1:08:16 At a high level, yeah. You don't know exactly how every piece works, of course. But one thing I generally believe is that it's sometimes useful to zoom out and look at the entire map, and... And I think this is true for, like, a technical problem, I think this is true for, like, innovating in business. Uh, but things come together in surprising ways, and having an understanding of that whole picture, even if most of the time you're operating in the weeds in one area, pays off with surprising insights. In fact, one of the things that I used to have and I thought was super valuable was, I used to have, like, a, a, a good map of that... All of the front- or most of the frontiers in the tech industry. And I could sometimes see these connections or new things that were possible that if I were only, you know, deep in one area, I wouldn't, I wouldn't, I wouldn't be able to, like, have the idea for it because I wouldn't have all the data. And I don't really have that much anymore. I'm, like, super deep now. Um, but I know that it's a valuable thing.

Lex Fridman 1:09:23 You're not the man you used to be, Sam.

Sam Altman 1:09:25 Very different job now than what I used to have.

Lex Fridman 1:09:28 Speaking of zooming out, let's zoom out to, uh, another cheeky thing, but profound thing perhaps that you said. You tweeted, uh, about needing seven trillion dollars.

Sam Altman 1:09:41 I did not tweet about that. I never said, like, "We're raising seven trillion dollars, blah, blah, blah."

Lex Fridman 1:09:45 Oh, that's somebody else?

Sam Altman 1:09:46 Yeah.

Lex Fridman 1:09:47 Oh, but you said, "Uh, fuck it, maybe eight," I think.

Sam Altman 1:09:50 Okay, I meme, like, once there's, like, misinformation out in the world.

Lex Fridman 1:09:53 Oh, you meme? But, sort of, misinformation may have a foundation of, like, insight there.

Sam Altman 1:10:01 Look, I think compute is gonna be the currency of the future. I think it will be maybe the most precious commodity in the world, and I think we-

Lex Fridman 1:10:09 Interesting.

Sam Altman 1:10:09 ... should be investing heavily to make a lot more compute. Uh, compute is... It's an unusual... I think it's gonna be an unusual market. Um, you know, people think about the market for, like, chips for mobile phones or something like that, and you can say that, okay, there's eight billion people in the world, maybe seven billion of them have phones, maybe there- or six billion, let's say. They upgrade every two years, so the market per year is three billion system on chip for smartphones. And if you make 30 billion, you will not sell 10 times as many phones because most people have one phone. Um, but compute is different. Like, intelligence is gonna be more like energy or something like that where the only thing that I think makes sense to talk about is at price X, the world will use this much compute, and at price Y, the world will use this much compute. Um, because if it's really cheap, I'll have it, like, reading my email all day, like, giving me suggestions about what I maybe should think about or work on, and trying to cure cancer, and if it's really expensive, maybe I'll only use it, or will only use it to try to cure cancer. So, I think the world is gonna want a tremendous amount of compute, and there's a lot of parts of that that are hard. Uh, energy is the hardest part. Building data centers is also hard, the supply chain is hard, and then of course fabricating enough chips is hard. Um, but this seems to me where things are going, like, we're gonna want an amount of compute that's just hard to reason about right now.

Lex Fridman 1:11:43 How do you solve the energy puzzle? Nuclear-

Sam Altman 1:11:46 That's what I believe.

Lex Fridman 1:11:47 Fusion?

Sam Altman 1:11:48 That's what I believe.

Lex Fridman 1:11:49 Nuclear fusion?

Sam Altman 1:11:50 Yeah.

Lex Fridman 1:11:51 Who's gonna solve that?

Sam Altman 1:11:53 I think Helion's doing the best work, but I'm happy there's, like, a race for fusion right now. Nuclear fission I think is also, like, quite amazing, and I hope as a world we can re-embrace that. It's really sad to me wh- how the history of that went, and hope we get back to it in a meaningful way.

Lex Fridman 1:12:08 So to you, part of the puzzle is nuclear fission, like, nuclear reactors as we currently have them. And a lot of people are terrified because of Chernobyl and so on.

Sam Altman 1:12:16 Well, I think we should make new reactors. I, I, I think it, it's just like, it's a shame that industry kind of ground to a halt.

Lex Fridman 1:12:22 And what, just mass hysteria is how you explain the halt?

Sam Altman 1:12:25 Yeah.

Lex Fridman 1:12:26 I don't know if you know humans, but that's one of the dangers, that's one of the security threats for, for, for, uh, nuclear fission is humans seem to be really afraid of it, and that's something we have to incorporate into the calculus of it. So we have to kinda win people over and to show how safe it is.

Sam Altman 1:12:44 I worry about that for AI.

Lex Fridman 1:12:46 Mm-hmm.

Sam Altman 1:12:47 I think some things are gonna go theatrically wrong with AI. I don't know what the percent chance is that I eventually get shot, but it's not zero.

Lex Fridman 1:12:57 Oh, like, we wanna stop this from-

Sam Altman 1:13:01 Maybe.

Lex Fridman 1:13:03 How do you decrease the theatrical nature of it? You know, I've already starting to- to hear rumblings, because I do talk to people on the, on both sides of the political spectrum, hear rumblings where it's going to be politicized AI, it's going to be politicized. Really, really worries me because then it's like maybe the right is against AI and the left is for AI 'cause it's going to help the people, or whatever, whatever the narrative and fo- formulation is, that really worries me. And then the theatrical nature of it can be leveraged fully. How do you fight that?

Sam Altman 1:13:38 I think it will get caught up in, like, left versus right wars. I don't know exactly what that's gonna look like, but I think that's just what happens with anything of consequence, unfortunately. What I meant more about theatrical risks is, like, AI is gonna have, I believe, tremendously more good consequences than bad ones, but it is gonna have bad ones, and there will be some bad ones that are bad but not theatrical. You know, like, a lot more people have died of air pollution than nuclear reactors, for example, but we worry, most people worry more about living next to a nuclear reactor than a coal plant. But something about the way we're wired is that although there's many different kinds of risks we have to confront, the ones that make a good climax scene of a movie carry much more weight with us than the ones that are very bad over a long period of time but on a slow burn.

Lex Fridman 1:14:36 Well, that's why truth matters, and hopefully AI can help us see the truth of things to have- have balance, to understand what are the actual risks, what are the actual dangers of things in the world. What are the pros and cons of the competition in this space, and competing with Google, Meta, xAI, and others?

Sam Altman 1:14:56 I think I have a pretty, like, straightforward answer to this that maybe I can think of more nuance later, but the pros seem obvious, which is that we get better products and more innovation faster and cheaper and all the reasons competition is good. And the con is that I think if we're not careful, it could lead to an increase in sort of an arms race that I'm nervous about.

Lex Fridman 1:15:21 Do you feel the- the pressure of an arms race, like in some negative con-

Sam Altman 1:15:25 Definitely in some ways, for sure. We spend a lot of time talking about the need to prioritize safety, and I- I've said for, like, a long time that I think if you think of a quadrant, uh, of slow timelines to the start of AGI, long timelines and then a short takeoff or a fast takeoff, I think short timelines, slow takeoff is the safest quadrant and the one I'd most like us to be in. But I do want to make sure we get that slow takeoff.

Lex Fridman 1:15:55 Part of the problem I have with this kind of slight beef with Elon is that their silos are created, and it, as opposed to collaboration on the safety aspect of all of this, it tends to go into silos and closed, open source perhaps in the model.

Sam Altman 1:16:10 Elon says at least that he cares a great deal about AI safety and is really worried about it, and I- I assume that he's not gonna race unsafely.

Lex Fridman 1:16:20 Yeah, but collaboration here I think is really, uh, beneficial for everybody on that front.

Sam Altman 1:16:26 Not really a thing he's most known for.

Lex Fridman 1:16:28 Well, he is known for caring about humanity, and humanity benefits from collaboration, and so there's always attention and incentives and motivations, and, uh, in the end, I do hope humanity prevails.

Sam Altman 1:16:42 I was thinking, someone just reminded me the other day about how the day that he got, uh, like surpassed Jeff Bezos for, like, s- richest person in the world, he tweeted a silver medal at Jeff Bezos. I hope we have less stuff like that as people start to work on-

Lex Fridman 1:16:58 I agree.

Sam Altman 1:16:58 ... towards AGI.

Lex Fridman 1:17:00 I think Elon is a friend and he's a beautiful human being and one of the most important humans ever, that- that stuff is not good.

Sam Altman 1:17:07 The amazing stuff about Elon is amazing, and I super respect him. I think we need him, all of us should be rooting for him and need him to step up as a leader through this next phase.

Lex Fridman 1:17:19 Yeah, I hope you can have one without the other, but sometimes humans are flawed and complicated and all that kind of stuff.

Sam Altman 1:17:24 There's a lot of really great leaders throughout history.

Lex Fridman 1:17:27 Yeah, and we can each be the best version of ourselves and strive to do so. Let me ask you,

Lex Fridman 1:17:35 um, Google, with the help of search, has been dominating the past 20 years. I think it's fair to say in terms of the access, the world's access to information, how we interact and so on, and one of the nerve-racking things for Google, but for the entirety of people in this space is thinking about how are people going to access information?

Sam Altman 1:17:59 Yeah.

Lex Fridman 1:17:59 Like, like you said, people show up to GPT as a-

Sam Altman 1:18:03 Yeah.

Lex Fridman 1:18:03 ... as a starting point. So is OpenAI going to really take on this thing that Google started 20 years ago, which is, how do we a- get-

Sam Altman 1:18:12 I find that boring.

Lex Fridman 1:18:13 (laughs)

Sam Altman 1:18:13 I- I mean, if the, if the question is, is like, is, if we can build a better search engine than Google or whatever, then sure we should, like, go, you know, like people should use a better product. But I think that would so understate what this can be. You know, Google shows you, like, 10 blue links, well, like, 13 ads and then 10 blue links, and that's, like, one way to find information. But the thing that's exciting to me is not that we can go build a better copy of Google Search, but that maybe there's just some much better way to help people find and act and on and synthesize information. Actually, I think ChatGPT is that for some use cases, and hopefully it will make it be like that for a lot more use cases.... but I don't think it's that interesting to say, like, how do we go do a better job of giving you, like, 10 ranked webpages to look at than what Google does?

Lex Fridman 1:19:12 Mm.

Sam Altman 1:19:12 Maybe it's really interesting to go say, "How do we help you get the answer or the information you need?"

Lex Fridman 1:19:17 Mm.

Sam Altman 1:19:17 How do we help create that, in some cases, synthesize that in others, or point you to it in, in yet others? Um, but a lot of people have tried to just make a better search engine than Google, and it's, it is a hard technical problem, it is a hard branding problem, it is a hard ecosystem problem. I don't think the world needs another copy of Google.

Lex Fridman 1:19:39 And integrating a chat client, like a ChatGPT, with a search engine-

Sam Altman 1:19:44 That's cooler.

Lex Fridman 1:19:46 It's cool, but it's tricky. It's awk- Uh, it's like if you just do it simply, it's awkward, because like if you just shove it in there-

Sam Altman 1:19:53 Yeah.

Lex Fridman 1:19:53 ... it's all, it can be awkward.

Sam Altman 1:19:54 As you might guess, we are interested in how to do that well.

Lex Fridman 1:19:57 Hmm.

Sam Altman 1:19:58 That would be an example of a cool thing, that's not just like-

Lex Fridman 1:20:01 How to do that well. Like a heterogeneous, like integrating-

Sam Altman 1:20:03 The intersection of LLMs plus search, I don't think anyone has cracked the code on yet. I would love to go do that. I think that would be cool.

Lex Fridman 1:20:13 Yeah. What about the ad side? Have you ever considered monetization of that?

Sam Altman 1:20:16 You know, I kind of hate ads, just as like an aesthetic choice. Uh, I think ads needed to happen on the internet for a bunch of reasons to get it going, but it's a more mature industry. The world is richer now. I like that people pay for ChatGPT and know that the answers they're getting are not influenced by advertisers. There is, I'm sure, there's an ad unit that makes sense for LLMs, and I'm sure there's a way to like participate in the transaction stream in an unbiased way that is okay to do. But it's also easy to think about like the dystopic visions of the future where you ask ChatGPT something and it says, "Oh, here's, you know, you should think about buying this product."

Lex Fridman 1:21:03 Yeah.

Sam Altman 1:21:03 "Or you should think about, you know, this, going here for va- your vacation or whatever." And I don't know, like, we have a very simple business model, and I like it, and I know that I'm not the product. Like, I know I'm paying, and that's how the business model works. And when I go use like Twitter or Facebook or Google or any other great product, but ad-supported great product, I don't love that, and I think it gets worse, not better, in a world with AI.

Lex Fridman 1:21:39 Yeah, I mean, I can imagine AI would be better at showing the best kind of version of ads, not in a dystopic future, but where the ads are for things you actually need. But then does that system always result in the ads driving the kind of stuff that's shown, all that c- It's... Um, yeah, I think it was a really bold move of Wikipedia not to do advertisements, but then it makes it very challenging in the, on, as a business model. So you're saying the current thing with OpenAI is sustainable from a business perspective?

Sam Altman 1:22:15 Well, we have to figure out how to grow, but looks like we're gonna figure that out. If the question is do I think we can have a great business that pays for our compute needs without ads, that, I think the answer is yes.

Lex Fridman 1:22:28 Hmm. Well, that's promising. I also just don't want to completely throw out ads as a-

Sam Altman 1:22:37 I'm not saying that. I, I, I'm, I guess I'm saying I have a bias against them.

Lex Fridman 1:22:42 Yeah, as, or m- I have a, also a bias and just a skepticism in general. And in terms of interface, 'cause I personally just have like a spiritual dislike of crappy interfaces, which is why AdSense when it first came out was a big leap forward versus like animated banners or whatever. But like it feels like there should be many more leaps forward in advertisement that doesn't interfere with the consumption of the content and doesn't interfere in a big fundamental way which is like what you were saying. Like it will, uh, manipulate the truth to suit the advertisers. Let me ask you about safety but also bias and like safety in the short term, safety in the long term. The Gemini 1.5 came out recently. There's a lot of drama around it, speaking of theatrical things, and it generated, uh, black Nazis and black founding fathers. I think fair to say was, uh,