The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
01:02:40 · Thomas Sohmers
[01:02:40] S0: It is interesting that with the GPT six launch, Greg Brockman had said that he doesn't think that they're going to be pricing things in tokens much longer and that they they want to be moving into, you know, cost per useful result, like, to that. And I don't think that's where it'll end up because that's really difficult to price and, you know, qualia, etcetera. But I think that the price per token is really great because you can easily calculate the cost to generate a token. So determining a margin on that and pricing it in in bulk volume to generic customers is really easy. And I think that's going to stick around in large form because that is so easy. We'll see for the largest providers of tokens how they potentially evolve their business models in terms of if you have a GPT seven or eight that is superhuman and and can fully function as an employee in an amazing capacity. Capacity, and OpenAI calculates through whatever method that's running at full tilt, etcetera, it's only going to cost them, you know, however many hundreds of thousands dollars to produce tokens continuously with that, they may decide that it's actually easier and they'll be able to get more adoption if they just charged a million dollars a year just, you know, using a random number to have full unlimited usage of that virtual agent worker. So that may be how things evolve.
01:03:58 · Harry Stebbings, Thomas Sohmers
[01:03:58] S1: Can I ask you? I... I'm always very careful of being, like, the young naive one. I'm not that young anymore, but, like, being the naive one who's not seen cycles. But Gavin Baker says it well when he says, I can't speak to a company that don't have numbers that are parabolically up into the right and just everything is better than it's ever been. What would be the first signs of a crack in the chasm by a shift from frontier models to open weight models? Anthropic and OpenAI are not continuing in the same level, not quite growth rate because it's impossible to say, but level of growth missing numbers next year and then the bubble getting burst a little bit whether the two core leaders are having some form of strife. [01:04:40] S0: I I agree that that's a possibility. The reason I don't think it's likely is I think that development of open source models and and things happening locally, etcetera, will actually drive greater token volumes for for the big guys. [01:04:53] S1: I'm sorry. How does that work? I thought they were competitive.
01:04:53 · Harry Stebbings, Thomas Sohmers
[01:04:53] S1: I'm sorry. How does that work? I thought they were competitive. [01:04:56] S0: Yeah. No. I I think that the smarter and more capable that Siri is on my phone is going to result on in it doing a whole bunch of background tasks and things that remove me from having to be the one that instigates having requests and and data be processed by even smarter models. I I really do think that in a lot of AI applications right now, the bottleneck is actually a human making some sort of decision and different tasks have different levels of autonomy that that will result in things getting sent to be processed by by a model by OpenAI or Anthropic. But I think the the next really big order of magnitude... Couple orders of magnitude increase in token volumes is going to come when us humans trust a local LLM that has access to all of our data all the time to have it decide to do things on its own that it is not smart enough to do. Right now, I trust Astra a lot more than myself on a whole lot of different things, but I still prompt it to do things, and maybe it'll go run autonomously for twelve hours or three days. I think the next big leap is when I trust a model running on my laptop or on my phone to prompt the smarter models to do even more wider set of tasks.
01:06:11 · Harry Stebbings, Thomas Sohmers
[01:06:11] S1: When we look at, like, the data economy that powers the larger models which you believe in, we see Merkur, we see Surge hitting 3,000,000,000 in revenue. How big do these companies become? Because Anthropic and OpenAI are 4 to $5,000,000,000,000 businesses. They... Feasible. It's wholly feasible, isn't it, that McCor and Serge are $200,000,000,000 businesses, which serve both Frontier Labs and some of the world's biggest enterprises be... Building their own models. [01:06:38] S0: I think my only skepticism there is on there being vertical integration by the Frontier Labs. I think the reason that hasn't happened is because Anthropic and OpenAI have better uses of their capital and mental power, etcetera, than doing all of the, you know, Scale AI, Mercor, etcetera work. But I I think that won't always exist. And let... Let's say that GPT seven or eight could be an effective replacement for Sam Altman in terms of being able to manage, you know, a a large business, why they wouldn't just have agents be taking over those tasks. [01:07:12] S1: Before we leave, I like to finish on a tone of optimism. What are you most excited about today that you think the world does not spend enough time on that we should spend time on?
01:07:21 · Thomas Sohmers
[01:07:21] S0: I'm very sympathetic to the problems that I think the the smarter set of the AI alignment, AI safety community are when it when it comes to thinking about how do you align incentives. Like, lot a of people just talk about AI alignment being a problem. I think there's... A a key part of that is human alignment. It's like how do we, society, you know, human race, align ourselves to have a good outcome that I think will be empowered by artificial intelligence. And so we discussed all... A bunch of the different problems that we're facing geopolitically and socially and how these different things are handled. And I think a lot of smart people are doing good work on the AI alignment problem and and thinking through how we solve that, but they may be gated in what can be done there if we don't get better human alignment on, be it regulatory frameworks and energy production, where we're going to put the data centers, etcetera, etcetera. And I I think framing it as this being a similar sort of technical problem that smart people can work and reason through will hopefully get more people thinking about it that way. And I think a core element that gets discounted by, I think, a lot of people in that sphere, there there are a lot of economic factors. And I I think it's the economic factors that actually will drive real decision making and and actions. And if we don't look at it from, you know, a rational, you know, self interested actors and and all these different things, you're just not gonna make progress.
01:08:50 · Harry Stebbings, Thomas Sohmers
[01:08:50] S1: Thomas, this has been the most varied discussion ever from education on, you know, unbelievable infrastructure evolution to Dario and Sam. You are a star. Thank you so much for joining me today. [01:09:01] S0: Thank you so much, Harry.