00:08:19 · Aditya Agarwal, Elad Gil
[00:08:19] S1: Of the frameworks we talk a lot about in SPC is, like, are you in modality one or two? Modality one is that it doesn't actually matter if the good or bad. The only thing that matters is how petite it's drawing. Right? And often in those kind of, like, domains, there's often not just one player. There's often two or three. It's often pretty neck and neck in the early days, but really the only thing that Paris is actually winning. And then modality two is you're actually betting something actually heretical slash non consensus. But by definition, that should mean that you should find it hard to get funded. You should probably not mean... Most people should actually laugh you out of a karoo. Right? Or they should say that, like, this acu doesn't make any sense. And I think a lot of people want to do modality too, but they're still seeking kind of, like, the validation offer, you know, whether it be customers or employees or investors. And I think mortality too is actually very lonely. And I think it's... There's not that many companies that I think are able to pull that off. I'm curious. Have you seen any good mortality to companies? [00:09:15] S0: There's a few, and there's also a lot of stuff that took off in ways that people didn't anticipate. Right?, but also ChatGPT. It was launched Thanksgiving week. This is... It's a buried launch. November 2020. I... It was like, oh, it's nobody's gonna pay attention, but then send me how someone's launch it during Thanksgiving. So, like, what does that be in terms of our ability to predict what's gonna be compelling?
00:09:15 · Elad Gil, Aditya Agarwal
[00:09:15] S0: There's a few, and there's also a lot of stuff that took off in ways that people didn't anticipate. Right?, but also ChatGPT. It was launched Thanksgiving week. This is... It's a buried launch. November 2020. I... It was like, oh, it's nobody's gonna pay attention, but then send me how someone's launch it during Thanksgiving. So, like, what does that be in terms of our ability to predict what's gonna be compelling? [00:09:37] S1: So today, we have three to four players, and it's called it three players who are kind of dominating the frontier. I will say four. Because, obviously, you know, OpenAI is Anthropic. There's Google. And then we'll put all the Chinese open source models into their own kind of bucket. Right? So they say there are four kind of big categories. Do you think that this is a stable, or do you anticipate this shifting, call it, in a five year time frame? [00:10:02] S0: Yeah. And then I'd I'd probably add XAI as an ongoing wealth correction. [00:10:05] S1: Sorry. You're right. I mean, if you want the if you want the beans and what's happened right now, you should go raise. Yeah. As in med, Grok is the best of that. Yeah.
00:10:12 · Elad Gil
[00:10:12] S0: And You know, so I wrote a post about this maybe two or four years ago where I tried to predict the foundation model market. And at the time, what I thought would happen was that you'd end up with three players, each of what each would be aligned with a hyperscaler. And it'd be kind of a captive hyperscaler model relationship where the hyperscaler would fund it and then it'd be on the... On that platform. And so I thought it'd be Google for itself with GCP and then OpenAI and Microsoft because there'd be relationship at the time. Then I thought Anthropic maybe partners with Amazon or something. And then I thought NVIDIA would be the primary funder of open source. And if you look at every technology wave, there's usually a big company that funds and monetizes the open source. So during the nineties for Linux, I was IBM, where they spend billions of dollars effectively on Linux development and really monetize it by selling it through services. And I I got it wrong. I got it partially right and partially wrong. I got it right in terms of thinking it'd be in a holopoly market. And the reason if I would be in a holopoly because of the scale of capital needed to do it. So, eventually, you just don't have new entrants really able to compete. But I got it wrong in a few ways. One is Meta and I've been The US based funder, for the time being, China... The Chinese government became the other means... Major source of economic funding for open source models. And then I got it wrong in terms of the models are partnering more aggressively across. Right? And traffic is part of the GCP and Amazon. Microsoft is working with multiple models. It's, you know, Google is working with Anthropic. So I... It's much more of a overlapping world than what I anticipated, and everybody kinda cross and busted. It's actually honestly closer to what happened in China across a few different waves of, like, the big Chinese companies effectively funding the versions of Uber and, you know, other sort of next gen applications. So I I do think the natural structure, assuming one of the companies doesn't truly lift off in terms of model capabilities ahead of everybody else's oligopoly, That seems to be a natural state for now. I do think one interesting thing that's emerged is the importance of the harness, relative to some of these applications like Claude Code.
00:12:09 · Elad Gil
I think a big shift there that I observed was when, Fi two came out for OpenAI. Was less switching than I anticipated because some people argued it was a bit of a better model. But people had already been using cloud in a harness that was really optimized for using cloud, and so fewer people switched than expected would. It could be the model's only incrementally better. It could be a variety of thinking. It's an open question to my mind is how much does the harness matter for stickiness now versus the core model. And if that transition happens, then that has really key implications in terms of how you think about things. And then the other piece of it that's the interesting question is when do the... If certain types of models asymptote and functionality... And if you hit the asymptote and other aspects become more important in terms of switching or not, if you don't hit the asymptote and it continues to be, what's the best model again with this overlay? Is it significantly differently... Different enough that you'll abandon whatever harness you're using? And then the question is, like, what's the enterprise version of the harness?
00:13:06 · Aditya Agarwal
[00:13:06] S1: I don't think anybody in this room could probably confidently predict whether we are kidding that assymptote because it seems as though we've kind of been in, like, a three to four month kind of cycle of, like, someone having a leap for the last almost three and a half years. So I I treat a lot about Claude Code, which means that I have people who are my friends at OpenAI Codex being like, Yo, can you switch and use it? And I'm like, No, I have a bunch of contacts and I know how to do these things. It's hard for me to switch. So I think the hardness thing is real. And it has also surprised me that there hasn't been as much chatter about trying out 5.2 or some of the more recent models. And maybe you're right, maybe it's incrementally better, maybe it would not of feel like I think Opus 4.6 came out pretty close to 5.2, so maybe all of that is contributing to it. But I guess the question in here is, do you do you think that we are running out of model iterations that are significant? I don't personally think so. What did you say today?
00:14:03 · Elad Gil, Aditya Agarwal
[00:14:03] S0: Yeah. No. I think there's tons of room. I think the the question is more what is the closeness between the models, and what is the utility you get through things at ancillary? And the ancillary things include the harness. Includes brand, actually. Yeah. Right? What you could tell your friends you're using. Yeah. Yeah. No. Seriously, I don't know if it matters. So I think I think it's a couple different things. You just get used to having things configured as your way, as your types of prompts, or, you know, everything is kinda set up for you. And I think it's a recent phenomenon. I think it's very new, and that's why I think it's not discussed very much as, like, a thing. [00:14:32] S1: As you kind of, from your vantage point, you know, obviously we've had, we're still continuing to, I would say, innovate along, okay, let's do, you know, longer chains of thought, let's do better RL, let's do longer context, let's do multimodal, let's do omni model, Let's do, like, world's models and so on. Right? So how are you... Like, when you kinda think about the vectors along which these model setting crew over Callaway into forty four month horizon, how do you think about At this stage, you might as well just go work for a foundation model company. [00:15:04] S0: Yeah. We all will be [00:15:05] S1: in the long run. Yeah. We are.