| It's such a small playing field with too few players. I have a slide in a presentation on the topic that's an inverted pyramid, as pretty much the entire LLM field rests on only a few companies, who aren't necessarily even doing everything correctly. The fact that they even have a seat at such a small table with so much in the pot already and much more forecasted means they command a large buy in regardless of their tech. They don't ever need to be in the lead, they just need to maintain their seat at the table and they'll still have money being thrown their way. The threat of missing the next wave or letting a competitor gain exclusive access is too high at this point. Of course, FOMO driving investments is also the very well known pattern of a bubble, and we may have a bit of a generative AI bubble among the top firms where large sums of money are going to go down the drain on investing into overvalued promises because the cost of missing a promise that will actually come to fruition is considered too high. Ironically the real payoff is probably in focusing on integration layers at this point, particularly given the gains in performance over the past year in research by developing improved interfacing with SotA models. LLMs at a foundational pretrained layer are in a race towards parity. Having access to model A isn't going to be much more interesting than having access to model B. But if you have a plug and play intermediate product that can hook into either model A or B and deliver improved results to direct access to either - that's where the money is going to be for cloud providers in the next 18 months. |