Well, let's not forget that text models are not the only models! Video models are much slower and need comparatively more resources, and all they can do even at that size is generate videos a few seconds long. Clearly a ton more work is going to go into those, and demand for them will probably increase as more creative tools get authored using them as a central part of the workflow. Low-res local rendering for preview might be a thing, but the lion's share of the work for high-res, near-realtime rendering is going to be done on huge clusters for a long time yet.
This is definitely a good point. I imagine the max capacity for video models is significantly lower than for text models (there just aren't as many professionals in video as there are people who write text or code) but I could be wrong.
I think there’s still an open question around are the ultra-large next-gen models worth it? For those of us without early access to Mythos, it’s hard to verify whether it’s been held back from the public due to actually being “too dangerously powerful to release yet” as implied or because the gains aren’t outpacing the costs.
I think GPT 4.5 showed that there is indeed a practical limit we're close too. That was supposedly a high-trillions of parameter model that was deprecated almost immediately because it was slow, insanely expensive, and had questionable benefits over the smaller models. Though apparently the new Mythos and whatever GPT Spud is (if it wasn't 5.5) are back up in the high trillions.
Actually having used it a bit, I'm quite excited to see a modern model of similar size.
I think what people didn't realize was, just because the GPT-4.5 model didn't get better on the benchmarks, didn't mean the model wasn't different than the earlier models. It was being compared to thinking models that were being developed at the same time.
The GPT 4.5 model still has some of the most "human" like abilities in communication even though it isn't particularly good a problem solving. It hadn't under gone the same type of reinforcement training.
I still use GPT 4.5 sometimes, in creative exercises it can be surprisingly effective. The model is still available.
yes and no. We've reached the point where larger models are higher quality, but they're also too expensive and slow to be used broadly. The giant models, however are still useful for training smaller models that are actually deployable.