Robert Ta argues the real money in AI isn't frontier models themselves, but in distilling their capabilities into cheaper versions and selling them to enterprises for high-ROI tasks. Premium frontier SKUs exist, but the trickle-down to lower-cost products is where companies like OpenAI and Anthropic actually profit.
Do we think there is a business to be made out of serving frontier intelligence? I think in Jensen's paper here, he basically says yes, there's going to be needs for frontier-level intelligence. He sort of talks about it like tasks. The way I think about it is that way too. There are lower value tasks, higher value tasks in terms of just capitalism. He's saying, hey, we want startups that have established businesses, universities, public institutions to be able to build on advanced models without training one from scratch or paying frontier model prices for every task. Open weights let every organization match the right model to the right job at the right cost, reserving frontier-scale capability for genuine frontier problems and running efficient specialized models everywhere else. I suppose there's a question there, which is how valuable are these frontier-level intelligence tasks? To what businesses? To what research institutions? What is the ROI thesis of that? Let's just talk about distillation and for a second, this is a pattern that just happens in, say, cars. The whole car industry is like this where they have a leading edge. Grand Touring has all the trim as whatever model. And then the next few generations after they innovate on that one, the innovators buy it. And the next few generations, they roll out the features of that into the lower-end models. That's kind of what's happening. Like without looking at all the, how do you train? How do you label data? How are you doing evals? Anthropic, OpenAI have been competing at like this thing could solve more complicated coding tasks or this thing could solve longer horizon, longer running tasks with fewer errors. With that move, they're just competing with these higher-value tasks. There's a hypothesis there that we're seeing play out in real time, which is the enterprise companies FDEs have the most money and the highest value tasks. Okay, let's roll a bunch of money into FDEs and then try to get there to learn what are those and then invest. And so I could see a model where it's like OpenAI, Anthropic, the Frontier Labs, they sell a SKU, which is, this is the leading edge shit. And then they charge some crazy rate for it. And then that just helps them learn what to bleed down to their lower end models, which might end up making a bigger business. I think it's playing out where it would make sense that sell the Frontier Intelligence, invest into that if it makes a lot of money and solves these really high value tasks for these high value customers. Take that, make the features that come out of that learning loop and those product lines, embed those features over time, over generations or whatever that meets market expectations for the lower market offerings. I could see that happening.
