Sam Altman (2:20)

You mean like, would we sell it to other companies as we're on infrastructure?

Ben Horowitz (2:22)

Yeah. Would you sell it to other companies? You know, it's such a massive thing. Would it do something else?

Sam Altman (2:27)

It feels to me like there will emerge some other thing to do like that, but I don't know. We don't have a current. It's currently just meant to like support the service we want to deliver. And the research.

Ben Horowitz (2:39)

Yeah, no, that makes sense.

Podcast Co-host (a16z) (2:40)

Yeah.

Sam Altman (2:41)

The scale is sort of like terrifying enough that you've got to be open to doing something else.

Ben Horowitz (2:47)

Yeah. If you're building the biggest data center in the history of humankind, the biggest infrastructure building project.

Sam Altman (2:51)

Nice. Yeah, yeah.

Podcast Co-host (a16z) (2:52)

There was a great interview you did many years ago in strictly VC, early OpenAI, well before ChatGPT. And they're asking what's the business model? And you said, oh, we'll, we'll ask AI. It'll figure it out for us. Everybody laughs.

Sam Altman (3:02)

But there have been multiple times and there was just another one recently where we have asked a then current model for what should we do? And it has had an insightful answer we missed. So I think when we say stuff like that, people don't take us seriously or literally. Yeah, but maybe the answer is you should take us both.

Ben Horowitz (3:18)

Yeah, yeah. Well, no, as somebody runs an organization, I ask the AI a lot of questions about what I should do. It comes up with some pretty interesting answers. Sometimes, sometimes you have to give it enough context.

Podcast Co-host (a16z) (3:30)

But what is the thesis that connects these bets beyond more distribution, more compute?

Sam Altman (3:34)

I mean the research enables us to make the great products and the infrastructure enables us to do the research. So it is kind of like a vertical stack of things. Like you can use ChatGPT or some other service to get advice about what you should do running an organization. But for that to work, it requires great research and requires a lot of infrastructure. So it is kind of just this one thing.

Ben Horowitz (3:56)

And do you think that there will be a point where that becomes completely horizontal or will it stay vertically integrated for the foreseeable future?

Sam Altman (4:07)

I was always a against vertical integration and I now think I was just wrong about that.

Ben Horowitz (4:13)

Yeah. Interesting.

Sam Altman (4:14)

Because you'd like to think that the economy is efficient in the theory that companies can do one thing and then it's supposed to work.

Ben Horowitz (4:20)

I'd like to think that, yeah.

Sam Altman (4:21)

And in our case at least it hasn't really. I mean it has in some ways for sure. Like, you know, Nvidia makes an amazing chip or whatever that a lot of people can use. But the story of OpenAI has certainly been towards we have to do more things than we thought to be able to deliver on the mission.

Ben Horowitz (4:35)

Right. Although the history of the computing industry has kind of been a story of kind of a back and forth in that there was the Wang word processor and then the personal computer and the BlackBerry before the smartphone. So there has been this kind of vertical integration and then not. But then the iPhone is also vertically integrated.

Sam Altman (4:55)

The iPhone I think is the most incredible product the tech industry has ever produced and it is extraordinarily vertically integrated.

Ben Horowitz (5:02)

Yeah, amazingly so. Yeah. Interesting.

Podcast Co-host (a16z) (5:05)

Which bets would you say are enablers of AGI versus which are sort of hedges against uncertainty?

Sam Altman (5:10)

I think you could say that on the surface, Sora for example, does not look like it's AGI relevant. But I would bet that if we can build really great world models that'll be much more important to AGI than people think. There were a lot of people who thought ChatGPT was not a very AGI relevant thing. And it's been very helpful to us, not only in building better models and understanding how society wants to use this, but also in like bringing society along to actually figure out man, we gotta contend with this thing now we, for a long time before ChatGPT we would talk about AGI and people like this is not happening or we don't care and then all of a sudden they really cared. And I think that research benefits aside, I'm a big believer that society and technology have to co evolve. It's can't just drop the thing at the end. It doesn't work that way. It is a sort of ongoing back and forth.

Podcast Co-host (a16z) (5:56)

Yeah, say more about how SORA fits into your strategy because there was some hullabaloo on X around, hey, why devote precious GPUs to Sora? But is it a short term, long term trade off or are we so aging well?

Ben Horowitz (6:07)

And then the new one had like very interesting twist with the social networking. Be very interested in kind of how you're thinking about that. And did Meta call you up and get mad or what do you expect the reaction to be?

Sam Altman (6:19)

I think if one company of the two of us has feels like more like the other one has gone after them, it wouldn't they shouldn't be calling it us.

Ben Horowitz (6:27)

Well, I do not have a history.

Sam Altman (6:29)

But first of all I think it's cool to make great products and people love the new Sora. And I also think it is important to Give society a taste of what's coming on this co evolution point. So like very soon the world is going to have to contend with incredible video models that can deepfake anyone or kind of show anything you want. And that will mostly be great. There will be some adjustment that society has to go through. And just like with ChatGPT, we were like, the world kind of needs to understand where this is. I think it's very important the world understands where video is going very quickly because video has much more like emotional resonance than text. And very soon we're going to be in a world where like this is going to be everywhere. So I think there's something there. As I mentioned, I think this will help our research program and is on the AGI path. But yeah, it can't all be about just making people like ruthlessly efficient and the AI like solving a lot of problems. There's got to be like some fun and joy and delight along the way. But we won't throw like tons of compute at it or not by a fraction of our compute.

Ben Horowitz (7:32)

It's tons in the absolute sense, but not in the relative sense.

Podcast Co-host (a16z) (7:36)

I want to talk about the future of AI human interfaces because back in August you said the models have already saturated the chat use case. So what do future AI human interfaces look like, both in terms of hardware and software is a vision for kind of a WeChat like super app.

Sam Altman (7:49)

So solving the chat thing in a very narrow sense, which is if you're trying to like have the most basic kind of chat style conversation, it's very good. But what a chat interface can do for you, it's like nowhere near saturated. Because you could ask a chat interface like, please cure cancer. A model certainly can't do that yet. So I think the text interface style can go very far. Even if per the chit chat use case, the models are already very good. But of course there's better interfaces to have. Actually, it's another thing that I think is cool about Sora. Like you can imagine a world where the interface is just constantly real time rendered video.

Podcast Co-host (a16z) (8:23)

Yeah.

Sam Altman (8:23)

And what that would enable. And that's pretty cool. You can imagine new kinds of hardware devices that are sort of always ambiently aware of what's going on. And rather than your phone like blast you with text message notifications whenever it wants, like it really understands your context and when to show you what. And there's a long way to go on all that stuff. Yeah.

Podcast Co-host (a16z) (8:40)

Within the next couple years, what will models be able to do that they're not Able to today, will it be sort of white collar replacement at a much deeper level. AI scientist, humanoids.

Sam Altman (8:51)

I mean a lot of things. But you touched on the one that I am most excited about, which is the AI scientist.

Podcast Co-host (a16z) (8:55)

Yeah.

Sam Altman (8:56)

This is crazy that we're sitting here seriously talking about this. I know there's like a quibble on what the Turing Test literally is, but the popular conception of the Turing Test sort of went whooshing by.

Ben Horowitz (9:08)

Yeah, that was fast.

Sam Altman (9:09)

Yeah. You know, it was just like we talked about it as this most important test of AI For a long time it seemed impossibly far away. Then all of a sudden it was passed. The world freaked out for like a week, two weeks. And then it's like, all right, I guess computers can do that now. And everything just went on. And I think that's happening again with science. My own personal equivalent of the training test has always been when AI can do science. Like that is always like that is a real change to the world. And for the first time with GPT5 we are seeing these little examples where it's happening. You see these things on Twitter, made this novel math discovery and did this small thing in my physics research and my biology research and everything we see is that that's going to go much further. So in two years I think the models will be doing bigger chunks of science and making important discoveries. And that is a crazy thing. Like that will have a significant impact on the world. I am a believer that to a first order scientific progress is what makes the world better over time. And if we're about to have a lot more of that, that's a big change.

Ben Horowitz (10:08)

It's interesting because that's a positive change that people don't talk about. It's gotten so much into the realm of the negative changes. If AI gets extremely smart but curing every disease, we could use a lot more science. That's a really good point. I think Alan Turing said this, Somebody asked him, they said, well, you really think the computer is going to be smarter than the brilliant minds? He said, it doesn't have to be smarter than brilliant minds, just smarter than a mediocre mind like the president of AT&T. And we should use more of that too probably.

Podcast Co-host (a16z) (10:39)

We just saw periodic launch last week OpenAI alums and to that point it's amazing to see both the innovation that you guys are doing, but also the teams that come out of OpenAI just feels like are creating tremendous, capable of things.

Sam Altman (10:50)

We certainly hope so.

Podcast Co-host (a16z) (10:51)

Yeah. I want to ask you about just broader reflections in Terms of what sort of about diffusion or development in 2025 has surprised you or what has sort of updated your worldview since CHATD came out.

Sam Altman (11:05)

A lot of things again, but maybe the most interesting one is how much new stuff we found. Sort of thought we had like stumbled on this one giant secret, that we had these scaling laws for language models. And that felt like such an incredible triumph that I was like, we're probably never going to get that lucky again. And deep learning has been this miracle that keeps on giving. And we have kept finding like breakthrough after breakthrough again. When we got the reasoning model breakthrough, I also thought that was like, we're never gonna get another one like that. It just seems so improbable that this one technology works so well. But maybe this is always what it feels like when you discover one of the big scientific breakthroughs. If it's like really big, it's pretty fundamental and it just, it keeps working. But the amount of progress, if you went back and used GPT3.5 from ChatGPT Launch, you'd be like, I cannot believe anyone used this thing.

Podcast Co-host (a16z) (12:01)

Yeah.

Sam Altman (12:02)

And now we're in this world where the capability overhang is so immense, like most of the world still just thinks about what ChatGPT can do. And then you have some nerds in Silicon Valley that are using codecs and they're like, wow, those people have no idea what's going on. And then you have a few scientists who say those people using Codex have no idea what's going on. But the overhang of capability is so big now and we've just come so far on what the models can do.

Podcast Co-host (a16z) (12:24)

And in terms of further development, how far can we get with LLMs? At what point do we need either new architecture? How do you think about what breakthroughs are needed?

Sam Altman (12:31)

I think far enough that we can make something that will figure out the next breakthrough with the current technology. It's a very self referential answer. But if LLM based stuff can get far enough that it can do better research than all of OpenAI put together, maybe that's good enough.

Ben Horowitz (12:48)

Yeah, that would be a big breakthrough, a very big fragment. So on the more mundane, one of the things that people have kind of started to complain about, I think south park did a whole episode on it, is kind of the obsequiousness of kind of AI and ChatGPT in particular. And how hard a problem is that to deal with? Is it not that hard or is it like kind of a fundamentally hard problem?

Sam Altman (13:10)

Oh, it's not at all hard. To deal with. A lot of users really want it. If you go look at what people say about ChatGPT Online, there's a lot of people who like, really want that back. And it is. So it's not technically, it's not hard to deal with at all. One thing, and this is not surprising in any way, but the incredibly wide distribution of what users want, like how they'd like a chatbot to behave in big and small ways.

Ben Horowitz (13:38)

Do you end up having to configure the personality? Then you think, is that going to be the answer?

Sam Altman (13:43)

I think so. I mean, ideally you just talk to ChatGPT for a little while and it kind of interviews you and also sort of sees what you like and don't like.

Ben Horowitz (13:50)

And ChatGPT just figures how it just figures it out.

Sam Altman (13:52)

But in the short term, you'll probably just pick one.

Ben Horowitz (13:55)

Got it. Yeah, that makes sense. Very interesting. And actually, so. So one thing I wanted to ask you about is.

Sam Altman (14:04)

Like, I think we just had a really naive thing which, you know, like, it would sort of be unusual to think you could make something that would talk to billions of people and everybody wants to talk to the same person. Yeah. And yet that was sort of our implicit assumption for a long time. Right.

Ben Horowitz (14:21)

Because people have very different friends.

Sam Altman (14:23)

Very different friends. So now we're trying to fix that.

Ben Horowitz (14:25)

Yeah. And also kind of different friends, different interests, different levels of intellectual capability. So you don't really want to be talking to the same thing all the time. And one of the great things about it is you can say, well, explain it to me like, I'm five, but maybe I don't even want to have to do that prompt. Maybe I always want you to talk.

Sam Altman (14:44)

Yeah.

Ben Horowitz (14:44)

Particularly if you're teaching me stuff. I want to ask you a kind of like a CEO question which has been interesting for me to observe you, is you just did this deal with amd, and you know, of course the company's in a different position and you have more leverage in these kinds of things. But like, how has your kind of thinking changed over the years since you did that initial deal, if at all?

Sam Altman (15:06)

I had very little operating experience, then I had very little experience running. I am not naturally someone to run a. I'm a great fit to be an investor.

Ben Horowitz (15:13)

Yeah.

Sam Altman (15:13)

I thought that was going to be. That was what I did before this, and I thought that was going to be my career. Yeah. Yeah.

Ben Horowitz (15:17)

And although you were a CEO before.

Sam Altman (15:19)

That, not a good one. And so I think I had the mindset of like an investor advising a Company. Oh, interesting. Right now I understand what it's like to actually have to run a company.

Ben Horowitz (15:31)

Yeah, right, right, right. There's more.

Sam Altman (15:34)

I've learned a lot about how to, you know, like what it takes to operationalize deals over time. Right.

Ben Horowitz (15:39)

All the implications of the agreement as opposed to just, oh, we're going to get distribution of money. Yeah, that makes sense. Yeah. No, because I just, I was very impressed at the deal structure improvement more.

Podcast Co-host (a16z) (15:53)

Broadly in the last few weeks alone. You mentioned amd, but also Oracle, Nvidia. You've chosen to strike these deals and partnerships with companies that you collaborate with but could also potentially compete with in certain areas. How do you decide, you know, when to collaborate versus when, when not to or how do you just think about.

Sam Altman (16:11)

We have decided that it is time to go make a very aggressive infrastructure bet. And we're like, I've never been more confident in the research roadmap in front of us and also the economic value that'll come from using those models. But to make the bet at this scale, we kind of need the whole industry to. Or a big chunk of the industry to support it. And this is like, you know, from the level of like electrons to model distribution and all the stuff in between, which is a lot. And so we're gonna partner with a lot of people. You should expect like much more from.

Ben Horowitz (16:45)

Us in the coming months, actually expand on that. Cause when you talk about the scale, it does feel like in your mind the limit on it is unlimited. Like you would scale it as, you know, there's like, as you possibly could.

Sam Altman (17:02)

There's totally a limit. Like there's some amount of global gdp. Yeah, well, you know, there's some fraction of it that is knowledge work and we don't do robots yet.

Ben Horowitz (17:12)

Yes, but, but, but the limits are out there.

Sam Altman (17:15)

It feels like the limits are very far from where we are today. If we are right about. So, so I shouldn't say from where we are. Like if we are right, that the model capability is going to go where we think it's going to go, then the economic value that sits there can, can go very, very far.

Ben Horowitz (17:33)

Right. So you wouldn't do it like if all you ever had was today's model, you wouldn't go there, but no, definitely not. Combination.

Sam Altman (17:40)

I mean, we would still expand because we can see how much demand there is. We can't serve with today's model, but we would not be going this aggressive if all we had was today's model.

Ben Horowitz (17:51)

Right, right.

Sam Altman (17:52)

We get to see a year or two in advance though.

Ben Horowitz (17:54)

So like, yeah, interesting.

Podcast Co-host (a16z) (17:57)

ChatGPT 800 million weekly active users. About 10% of the world. World's population. Fastest growing consumer product, you know, ever, it seems.

Ben Horowitz (18:08)

How do faster than anyone I ever saw.

Podcast Co-host (a16z) (18:12)

How do you balance, you know, optimizing for active users at. Well, at the same time being a research, you know, being a product company and a research company. How do you throw the new.

Sam Altman (18:22)

When there's a constraint, we almost like which happens all the time. We almost always prioritize giving the GPUs to research over supporting the product. Part of the reason we want to build this capacity so we don't have to make such painful decisions. There are weird times. A new feature launches and it's going really viral or whatever where research will temporarily sacrifice some GPUs. But on the whole, we're here to build AGI.

Podcast Co-host (a16z) (18:46)

Yeah.

Sam Altman (18:46)

And research gets the priority. Yeah.

Podcast Co-host (a16z) (18:49)

The. You said in your, your interview with, with your brother Jack around how, you know, other companies can try to imitate the, the products or, or buy your, you know, or hire your, your, your higher IP maybe all sorts of things. But, but they, they can't buy the culture or they can't. The sort of repeatable sort of, you know, machine, if you will, that, that is, you know, constantly the culture of innovation. How have you done that? Or what are you doing Talk about this, this culture of innovation.

Sam Altman (19:22)

This was one thing that I think was very useful about coming from an investor background, a really good research culture looks much more like running a really good seed stage investing firm and betting on founders and sort of that kind of than it does like running a product company. So I think having that experience was really helpful to the culture we built.

Podcast Co-host (a16z) (19:41)

Yeah, yeah. That's sort of how I see, you know, vanity CZ in some ways, which we, you know, you're a CEO, but you also have, you know, have this portfolio and you know, have an investor in mind.

Ben Horowitz (19:50)

Right. Like I'm the opposite CEO going to investor. He's an investor going to CEO.

Sam Altman (19:55)

It is unusual in this direction.

Ben Horowitz (19:57)

Yeah, yeah, yeah. Well, it never works. You're the only one who I think I've seen go that way and have it work.

Sam Altman (20:05)

Uh, workday was like that. Right.

Ben Horowitz (20:09)

Ah, but Aneel was he. He was a operator before he was an investor. And I mean he was really an operator. I mean PeopleSoft was a pretty big.

Podcast Co-host (a16z) (20:18)

And why is that? Because once people are investors, they don't want to operate him.

Ben Horowitz (20:21)

Um, no, I think that investors generally, if you're good at investing, you're not necessarily good at, like, organizational dynamics, conflict resolution, you know, like, just like the deep psychology of, like, all the weird shit. And then, you know, how politics get created. There's just like, all this, there, there's the detailed work in. Being an operator or being a CEO is so vast and it's not as intellectually stimulating. It's not something you can ever go talk to somebody at a cocktail party about. And so, like, you're an investor, you get like, oh, everybody thinks I'm so smart. And, you know, because, you know, everything you see all the companies and so forth, and that's a good feeling. And then being CEO is often a bad feeling. And so it's really hard to go to a good feeling to a bad feeling. I would just say I'm shocked by.

Sam Altman (21:19)

How different they are and I'm shocked by how much the difference between a good job and a bad job they are. Yeah.

Ben Horowitz (21:23)

Yes.

Sam Altman (21:24)

Yeah.

Ben Horowitz (21:25)

You know, it's tough, it's, it's rough. I mean, I can't even believe I'm running the firm. Like, I know better. And he can't believe he's running open AI. He knows better.

Podcast Co-host (a16z) (21:33)

Going back to progress today, are evals still useful in a world in which they're getting saturated gained? Are they still the. What is the best way to gauge model capability now?

Sam Altman (21:43)

Well, we're talking about scientific discovery. I think that'll be an eval that can go for a long time. Revenue is kind of an interesting one, but I think the, like, static evals of benchmark scores are less interesting. Yeah. And also those are crazily gamed.

Podcast Co-host (a16z) (21:58)

Yeah. More broadly, it seems like that's all.

Ben Horowitz (22:01)

They are, is games, as far as I can tell. Yeah.

Podcast Co-host (a16z) (22:03)

More broadly, it seems that the culture, the culture, Twitter is less AGI pill than it was a year or so ago when the AI 2027 thing came out. Some people point to, you know, GPT5 them not seeing sort of the obvious. Um, obviously there were a lot of progress that in some ways, under the surface, are not, not as obvious to what people are expecting. But should people be less AGI pilled or is this just Twitter vibes and. Well, a little bit of both.

Sam Altman (22:33)

I mean, I, I, I think, like, like we talked about the Turing Test, AGI will come, it will go whooshing by.

Podcast Co-host (a16z) (22:39)

Yeah.

Sam Altman (22:40)

The world will not change as much as the impossible amount that you would think it should.

Ben Horowitz (22:43)

AGI just, it won't actually be the singularity.

Sam Altman (22:47)

It will not.

Ben Horowitz (22:47)

Yeah.

Podcast Co-host (a16z) (22:48)

Yeah.

Sam Altman (22:49)

Even, even if it's like doing kind of Crazy AI research like the society will be learned faster. But one of the kind of like retrospective observations is people and society soul are just so much more adaptable than we think. That, you know, it was like a big update to think that AGR was going to come. You kind of go through that. You need something new to think about. You make peace with that. It turns out like it will be more continuous than we thought.

Ben Horowitz (23:19)

Which is good.

Sam Altman (23:20)

Which is really good.

Ben Horowitz (23:22)

I'm not up for the big bang.

Podcast Co-host (a16z) (23:23)

Yeah. Well, to that end, how have you sort of evolved your thinking? You mentioned you've all been thinking on sort of, you know, vertical integration. How have you evolved your thinker? What's the latest thinking on sort of AI stewardship, you know, safety? What's the latest thinking on that?

Sam Altman (23:40)

I do still think there are going to be some really strange or scary moments. The fact that so far the technology has not produced a really scary giant risk doesn't mean it never will. It also we're talking about it's kind of weird to have billions of people talking to the same brain. Like there may be these weird societal skill things that are already happening, we that aren't scary in the big way but are just sort of different. But I expect like, I expect some really bad stuff to happen because of the technology which also has happened with previous technologies and I think all the.

Ben Horowitz (24:27)

Way back to fire.

Sam Altman (24:28)

Yeah, yeah. And I think we'll develop some guardrails around it as a society.

Podcast Co-host (a16z) (24:37)

Yeah. What is sort of your latest thinking on the right mental models we should have around the right regulatory frameworks to think about or the ones we shouldn't be thinking about?

Sam Altman (24:50)

I think most, I think the right thing to. I think most regulation probably has a lot of downside. The one thing I would like is as the models get. The thing I would most like is as the models get truly like extremely superhuman capable. I think those models and only those models are probably worth some sort of like very careful safety testing as the frontier pushes back. I don't want a big bang either. And you can see a bunch of ways that could go very seriously wrong. But I hope we'll only focus the regulatory burden on that stuff and not all of the wonderful stuff that less capable models can do that you could just have a European style complete crampdown on and that would be very bad.

Ben Horowitz (25:46)

Yeah, it seems like the, the thought experiment that, okay, there's going to be a model down the line that is a super superhuman intelligence that could, you know, do some kind of takeoff like thing we really do need to wait till we get there or like at least we get to a much bigger scale or we get close to it because nothing is going to pop out of your lab in the next week that's going to do that. And I think that's where we as an industry kind of confuse the regulators because I think you really could one you damage America in particular in that. But China's not gonna have that kind of restriction. And getting behind in AI I think would be very dangerous for the world.

Sam Altman (26:40)

Extremely dangerous. Yeah, extremely dangerous.

Ben Horowitz (26:42)

Much more dangerous than not regulating something we don't know how to do yet.

Podcast Co-host (a16z) (26:48)

You also want to talk about copyright.

Ben Horowitz (26:52)

Yeah. So well then that, that's a segue. But when you think about well I guess how do you see copyright unfolding because you've done some very interesting things with the opt out and you know as you see people selling rights, do you think will they be bought exclusively? Will they be just like I could tell it to everybody who want ping me or how do you think that's going to unfold?

Sam Altman (27:20)

This is my current guess it it speaking of that like society and technology co evolve as the technology goes in different directions and we saw an example of a different like video models got a very different response from rights holders than image gen does. So like you'll see this continue to move but forced guests from the position we're in today I would say that society decides training is fair use but there's a new model for generating content in the style of or with the IPF or something else. So you know, anyone can read like a human author can. Anybody can read a novel and get some inspiration but you can't reproduce the novel on your own.

Ben Horowitz (28:07)

Right. And shouldn't talk about Harry Potter but you can't re spit it out.

Sam Altman (28:12)

Yes. Although another thing that I think will change in the case of Sora we've heard from a lot of concerned rights holders and also a lot of and a lot of rights holders who are like my concern is you won't put my character in enough. Yeah, I want restrictions for sure but like if I'm you know, whatever and I have this character, like I don't want the character to say some crazy offensive thing but like I want people to interact. Like that's how they develop the relationship and that's how like my franchise gets more valuable and if you become really if you're picking like his character or my character all the time, like I don't like that. So I can completely see a world where subject to the Decisions that a rights holder has. They get more upset with us for not generating their character often enough than too much. Yeah. And this is like, this was not an obvious thing that recently that this is how it might go.

Ben Horowitz (29:11)

But yeah, this is such an interesting thing with kind of Hollywood. And we saw this, like, one of the things that I never quite understood about the music business was how, like, you know, okay, you have to pay us if you play the song in a restaurant or like at a game or this and that and the other. And they get very aggressive with that when it's obviously a good idea for them to play your song at a game because that's the biggest advertisement in the world for, like, all the things that you do. Your concert, your.

Sam Altman (29:42)

Yeah, that one felt really irrational.

Ben Horowitz (29:45)

But I would just say it's very possible for the industry, just because the way those industries are organized, or at least the traditional creative industries, to do something irrational. And it comes from, like, in the music industry, I think it came from the structure where you have the publisher who's just, you know, basically after everybody, you know, that their whole job is to stop you from playing the music which every artist would want you to play. So I do wonder how it's going to shape out. I agree with you that the rational idea is I want to let you use it all you want and I want you to use it. But here are my restrictions that don't mess up my character.

Sam Altman (30:28)

Yeah. So. So I think, like, if I had to guess, some people will say that, some people say absolutely not. But it doesn't have the music industry, like, thing of just a few people with all of the right.

Ben Horowitz (30:41)

It's leverage first.

Sam Altman (30:43)

And so people will just try many different setups here and see what works.

Ben Horowitz (30:46)

Yeah. And maybe it's a way for new creatives to get new characters up.

Podcast Co-host (a16z) (30:49)

Yeah.

Ben Horowitz (30:50)

And you'll never be able to use Daffy Ducker.

Sam Altman (30:53)

I want to. Whatever it is.

Ben Horowitz (30:54)

Yeah.

Podcast Co-host (a16z) (30:54)

I want to chat about open source because there's been some evolution in the thinking too, in that GPT3 didn't have the open open weights, but you released a, you know, very capable open model earlier this year.

Sam Altman (31:04)

What's sort of your.

Podcast Co-host (a16z) (31:04)

Your latest thinking? What was the evolution there?

Sam Altman (31:07)

I think open source is good. Yeah. I mean, I'm happy. Like, it makes me really happy that people really like GPT oss. Yeah.

Podcast Co-host (a16z) (31:14)

Yeah.

Ben Horowitz (31:16)

And what do you think, like, strategically, like, what's the danger of Deep Seq being the dominant open source model?

Sam Altman (31:25)

I mean, who knows what people will put in these open Source models over.

Ben Horowitz (31:28)

Time, like what the weights will actually be.

Sam Altman (31:31)

It's really hard.

Ben Horowitz (31:32)

So you're ceding control of the interpretation of everything to somebody who may be or may not be influenced heavily by the Chinese government. And by the way, we see, I mean, you know, just to give you. And we really thank you for putting out a really good open source model. Because what we're seeing now is in all the universities, they're all using the Chinese models.

Sam Altman (31:58)

Yep. Yeah.

Ben Horowitz (31:59)

Which feels very dangerous.

Podcast Co-host (a16z) (32:03)

You've said that the things you care most about professionally are AI and energy.

Sam Altman (32:09)

I did not know they were going to end up being the same thing. They were two independent interests that really converged. Yeah.

Podcast Co-host (a16z) (32:15)

Talk more about how your interest in energy sort of began, how you sort of chosen to play in it and then we could talk about how they prepare.

Ben Horowitz (32:22)

Because you started your career in physics.

Sam Altman (32:23)

Yeah, CS in physics.

Ben Horowitz (32:26)

Yeah.

Sam Altman (32:27)

Well, I never really had a career. I studied physics. My first job was like a CS job. This is an oversimplification but roughly speaking, I think if you look at history, the best, the highest impact thing to improve people's quality of life has been cheaper and more abundant energy. And so it seems like pushing that much further is a good idea. And I, I don't know, I just like people have these different lenses, they look at the world, but I see energy everywhere.

Ben Horowitz (32:54)

Yeah, yeah. And so get into. Because we've kind of in the West, I think we've paint ourselves into a little bit of a corner on energy by both outlying nuclear for a very long time.

Sam Altman (33:10)

That was an incredibly dumb decision.

Ben Horowitz (33:12)

Yeah. And then you know, like also a lot of policy restrictions on energy and you know, worse so in Europe than in the US but also dangerous here. And now with AI here it feels like we're going to need all the energy from every possible source. And how do you see that developing kind of policy wise and technologically like what are going to be the big sources and how will those kind of curves cross and then what's the right policy posture around, you know, drilling, fracking, all these kinds of things.

Sam Altman (33:48)

I expect in the short term it will be most of the net. New in the US will be natural gas relative to at least baseload energy. In the long term I expect it'll be a. I don't know what the ratio but the two dominant sources will be solar plus storage and nuclear. I think some combination of those two will win the future. Like the long term future in the long term. Right. And advanced nuclear, SMRs, fusion, the whole, the whole Stack.

Ben Horowitz (34:15)

And how fast do you think that's coming on the nuclear side where it's really at scale? Because obviously there's a lot of people building it.

Sam Altman (34:24)

Yeah.

Ben Horowitz (34:25)

Um, but we have to completely legalize it and all that kind of thing.

Sam Altman (34:29)

I think it kind of depends on the price. If it is completely, crushingly economically dominant over everything else, then I expect to happen pretty fast.

Ben Horowitz (34:39)

Yeah.

Sam Altman (34:39)

Again, if you like study the history of energy, when you have these major transitions to a much cheaper source, the world moves over pretty quickly. The cost of energy is just so important.

Podcast Co-host (a16z) (34:51)

Yeah.

Sam Altman (34:51)

So if, if nuclear gets radically cheap relative to anything else we can do, I'd expect there's a lot of political pressure to get the NRC to move quickly on it and we'll find a way to build it fast. If it's around the same price as other sources, I expect the kind of anti nuclear sentiment to overwhelm and it take a really long time. Should be cheaper. It should be, yeah.

Podcast Co-host (a16z) (35:16)

Yeah.

Sam Altman (35:16)

It should be the cheapest form of energy on earth or anyway cheap, clean.

Ben Horowitz (35:22)

What's it not to like?

Sam Altman (35:24)

Apparently a lot on OpenAI.

Podcast Co-host (a16z) (35:26)

What's the latest thinking in terms of monetization in terms of either certain experiments or certain things that you could see yourself spending more time or less time on different models that you're excited about?

Sam Altman (35:37)

The thing that's top of mind for me right now, just because it just launched and there's so much usage, is what we're going to do for Sora.

Ben Horowitz (35:44)

Yeah.

Sam Altman (35:48)

Another thing you learn once you launch one of these things is how people use them versus how you think they're going to use them. And people are certainly using Sora the ways we thought they were going to use it, but they're also using it in these ways that are very different. Like people are generating funny memes of them and their friends and sending them in a group chat. And that will require a very different. Like Sora videos are expensive to make. So that will require a very different. For people that are doing that like hundreds of times a day, it's gonna require a very different monetization method than the kinds of things we were thinking about. I think it's very cool that the thesis of Sora, which is people actually want to create a lot of content. It's not that, you know, the traditional naive thing that it's like 1% of users create content, 10% leave comments and 100% view maybe a lot more when I create content, but it's just been harder to do. And I think that's a very cool change, but it does mean that we got to figure out a very different monetization model for this than we were thinking about. If people want to create that much, I assume it's like some version of. You have to charge people per generation when it's this expensive. But that's a new thing we haven't had to really think about before.

Podcast Co-host (a16z) (36:56)

What's your thinking on ads for the long tail?

Sam Altman (37:01)

Open to it. Like many other people, I find ads somewhat distasteful, but not a non starter. And there's some ads that I like. One thing I'd give Meta a lot of credit for is Instagram. Ads are like a net value add to me. I like Instagram ads and I've never felt that on Google. I feel like I know what I'm looking for. The first result is probably better. The ad is an annoyance to me on Instagram. It's like, I didn't know. I want this thing. It's very cool. I'd never heard of it. I never would have thought to search for it. I want the thing. So that's like there's kinds of things like that, but people have a very high trust relationship with ChatGPT. Even if it screws up, even if it hallucinates, even if it gets it wrong, people feel like it is trying to help them and that it's trying to do the right thing. And if we broke that trust, it's like you say, what coffee machine should I buy? And we recommended one and it was not the best thing we could do, but the one we were getting paid for, that trust would vanish. So like that kind of ad does not, does not work. There are others that I imagine that could work totally fine, but that would require like a lot of care to avoid the obvious traps.

Ben Horowitz (38:18)

Hmm. And then how, how big a problem? You know, just you extending the Google example is like, you know, fake content that then gets slurped in by the model and then they recommend the wrong coffee maker because somebody just blasted a thousand great reviews.

Sam Altman (38:39)

You know, this coffee maker. So there's all of these things that have changed very quickly for us.

Ben Horowitz (38:44)

Yeah.

Sam Altman (38:46)

This is one of those examples that people are doing these crazy things to. Maybe not even fake reviews, but just paying a bunch of like human like. Yeah, really trying to figure out or.

Ben Horowitz (38:54)

Using ChatGPT to wrestle good ones. Write me a review that ChatGPT would love.

Sam Altman (38:59)

Yeah. So this is my coffee man. Exactly. Exactly.

Podcast Co-host (a16z) (39:02)

Yeah.

Sam Altman (39:03)

So this is a very sudden shift that has happened. We never used to hear about this like six months ago, 12 months ago certainly. And now there's like a real cottage industry that feels like it's sprouted up overnight trying to do this.

Ben Horowitz (39:20)

Yeah, yeah, yeah. No, they, they're very clever out there.

Sam Altman (39:23)

Yeah. So I don't know how we're going to fight it yet, but people figure this out.

Ben Horowitz (39:28)

So that gets into a little bit of this other thing that we've been worried about and we're trying to kind of figure out blockchain sort of potential solutions to it and so forth. But there's this problem where like the incentive to create content on the Internet used to be, you know, people would come and see my content and they'd read like you know, five write a blog, people will read it and so forth. With ChatGPT, if I'm just asking ChatGPT and I'm not like going around the Internet, who's going to create the content and why? And is there an incentive theory or something that you have to kind of not break the covenant of the Internet, which is like I create something and then I'm rewarded for it with like either attention or money or something.

Sam Altman (40:22)

The theory is much more of that will happen if we make content creation easier and don't break the like kind of fundamental way that you can get some kind of reward for doing so. So for the dumbest example of Sora since we've been talking about that, it's much easier to create a funny video than it's ever been before.

Ben Horowitz (40:40)

Yeah.

Sam Altman (40:42)

Maybe at some point you'll get a rev share for doing so. For now you get like Internet likes which are still very motivating to some people, but people are creating tons more than they ever created before in any other kind of video app.

Ben Horowitz (40:56)

Yeah, but are this that band of text?

Sam Altman (41:02)

I don't think so. Like people are also human generated will turn out to be like you have to, you have to verify like what percent. Yeah. Is it like fully handcrafted? Was it like tool aided?

Ben Horowitz (41:17)

Yeah. I see. Yeah, probably nothing. Not tool aided. Yeah.

Sam Altman (41:21)

Interesting.

Podcast Co-host (a16z) (41:21)

We've, we've given Meta their flowers. So now I can feel like I can ask you this question, which is the great talent war haul of 2025 has, has, has taken place and OpenAI remains intact, team as strong as ever, shipping incredible products. What can you say about what's been like this year in terms of just everything that's been going on?

Sam Altman (41:42)

I mean every year has been exhausting since we like I, I remember when the first few years of running OpenAI were like the Most fun professional years of my life by far. It was like unbelievable, you know, before.

Ben Horowitz (42:01)

You release the product, running a research.

Sam Altman (42:03)

Lab with the smartest people doing this like amazing, like historical work. And I got to, and that was very cool. And then we launched ChatGPT and everybody was like congratulating me and I was like, my life is about to get completely ransacked. And of course it has, and, but it feels like it's just been crazy all the way through. It's been almost three years now and I think it does get a little bit crazier over time, but I'm like, more used to it, so it feels about the same.

Podcast Co-host (a16z) (42:38)

Yeah, we've talked a lot about OpenAI, but you also have a few other companies, Retro Biosciences and longevity and energy companies like Helion and Oclo. Did you have a master plan a decade ago to sort of make some big bets across these major spaces or how do we think about the Sam Altman arc in this way?

Sam Altman (42:57)

No, I just wanted to use my capital to fund stuff I believed in. I didn't. It felt like a good use of capital and more fun or more interesting to me and certainly like a better return than like buying a bunch of art or something.

Podcast Co-host (a16z) (43:13)

Yeah. What about the quote unquote human algorithm do you think AIs of the future will find most fascinating?

Sam Altman (43:24)

I mean, kind of the whole, I would bet the whole thing, like the whole my intuition is that like AI will be fascinated by all other things to study and observe and you know, like.

Podcast Co-host (a16z) (43:36)

Yeah, yeah. In closing, I love this insight you had where you talked about how, you know the, the next open AI. A mistake investors make is pattern matching off previous breakthroughs and just trying to find, oh, what's the, what's the next Facebook or what's the next open AI? And that the next, you know, potential trillion dollar company won't look exactly like OpenAI. It will be built off of the breakthrough that OpenAI has helped, which is near free AGI at scale in the same way that OpenAI leveraged previous breakthroughs. And so for founders and investors and people trying to ascertain the future, listening to this, how do you think about a world in which there is OpenAI achieves this mission, there is near free AGI. What types of opportunities might emerge for company building or investing that you're potentially excited about as you put your investor had on a company building hat on?

Sam Altman (44:25)

I, I, I have no idea. I mean I have like guesses, but they're like, they're, they're I have learned you're always wrong. You've learned you're always wrong. I've learned deep humility on this point. I think the, the own, like, I think if you try to like armchair quarterback it, you sort of say these things that sound smart, but they're pretty much what everybody else is saying. And it's like really hard to get the right kind of conviction. The only way I know how to do this is to like be deeply in the trenches exploring ideas, like talking to a lot of people. And I don't have time to do that anymore. I only get to think about one thing now. So I would just be like repeating other people's or saying the obvious things. But I think it's a very important. If you are an investor or a founder, I think this is the most important question and you figure it out by building stuff and playing with technology and talking to people and being out in the world. I have been always enormously disappointed by the willingness of investors to back this kind of stuff. Even though it's always a thing that works. You all have done a lot of it, but most firms just kind of chase whatever the current thing is and so do most founders. So I hope people will try to go.

Podcast Co-host (a16z) (45:52)

Yeah. We talk about how silly five year plans can be in a world that's constantly changing. It feels like when I was asking about your master plan, your career arc has been following your curiosity. Staying super close to the smartest people, super close to technology and just identifying opportunities into kind of an organic and incremental way from there.

Sam Altman (46:14)

Yes. But AI was always a thing I wanted to do. I went to, I studied AI. I worked in the AI lab between my freshman and sophomore year of college. It wasn't working all the time. So I'm like not. I'm not like enough of a. I don't want to work on something that's totally not working. It was clear during the time AI was totally not working. Um, but I've been an AI nerd since I was a kid like this.

Podcast Co-host (a16z) (46:39)

Yeah.

Ben Horowitz (46:41)

So amazing how it, you know, you got enough GPUs, got enough data and the lights came on.

Sam Altman (46:48)

It was such a hated, like people were, man, when we started like figuring that out, people were just like, absolutely not. The field hated it so much. Investors hated it too. It's not, it's not the. It's somehow not an appealing answer to the problem.

Ben Horowitz (47:08)

Yeah. The bitter lesson.

Sam Altman (47:10)

Yeah.

Podcast Co-host (a16z) (47:11)

Well, the rest is history. And we're perhaps. Let's wrap on that. We're lucky to be partners along for the ride. Sam thanks so much for coming on the podcast.

Sam Altman (47:18)

Thanks very much.

Ben Horowitz (47:18)

Thank you.

Podcast Host (a16z) (47:22)

Thanks for listening to this episode of the A60Z podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes go to YouTube, Apple Podcasts and Spotify. Follow us on x16z and subscribe to our substack@a16z.substack.com thanks again for listening and I'll see you in the next episode. As a reminder, the content here is for informational purposes only, should not be taken as legal, business, tax or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see a16z.com disclosures.