The hardware to run it locally would be fairly expensive and would require using a very simple model compared to alternatives. Also much more wasteful if you were only using that hardware for AI use, as you’d be distributing the hardware out rather than centralizing so it’d be often idle and when replaced create more waste than a centralized server rack.
Also, additional per user post-training seems to me both wasteful and not necessary. In context learning is often much more powerful but frequently overlooked.
Probably less so.
The hardware to run it locally would be fairly expensive and would require using a very simple model compared to alternatives. Also much more wasteful if you were only using that hardware for AI use, as you’d be distributing the hardware out rather than centralizing so it’d be often idle and when replaced create more waste than a centralized server rack.
Also, additional per user post-training seems to me both wasteful and not necessary. In context learning is often much more powerful but frequently overlooked.