Q Got it. Um, and then, and then does that lead to, um, More model fragmentation models that are good at programming versus writing versus poetry versus image generation, or, or, or does this all feedback into one model? Does the idea of the consumer needing to pick a model disappear? Are we in a temporary period for that paradigm?
A I think the main reason that we've seen that so far is, uh, because people are trying to make the best of the capital. Like we are all still GPU poor in many ways. And people are focusing those GPUs on the sort of like spectrum of wars that I think is most important. Um, and I'm, I'm a bit of a big model guy. Um, I, I really do think that similar to how we saw with large pre-trained models before with small fine-tuned models made it Like, had gains over the sort of GPT-II era, but then were obsoleted by GPT-IV being generally good at everything. I think, to be honest, you're going to see this generalization and learning across all kinds of things that means you benefit from having large single models rather than specialization or area fine-tuned models.
AI assessment note: “you benefit from having large single models rather than specialization or area fine-tuned models”