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I'm sure that's very important in principle, much less sure that it matters in practice. Put differently, I struggle to complete the following sentence: "This l

by Arnt 2y ago

I'm sure that's very important in principle, much less sure that it matters in practice. Put differently, I struggle to complete the following sentence: "This limitation limits utility sharply, and it cannot be worked around because …" Maybe others can complete it, maybe it'll be easy to complete it in twenty years, with a little more hindsight. Maybe.

ben_w 2y ago
> Put differently, I struggle to complete the following sentence: "This limitation limits utility sharply, and it cannot be worked around because …" Ok, but that's more on you than on current AI; the models which get distributed (both LLMs and Stable Diffusion based image generators) are already found in re-trained and specialised derivatives created by people who know how to and have a sufficiently powerful graphics card.
- Arnt 2y ago
  Which is a kind of workaround for the inability to learn after the end of training… It's not clear to me how much this workaround mitigates the inability to learn after training. Is it clear to you? If so, please feel free to post a wall of text ;)
  - ben_w 2y ago
    To me, that seems like describing ovens and stoves as work-arounds for supermarkets providing frozen food? The weights are frozen on purpose. You can "thaw" them.