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July
@july
a crazy idea: the fact that most (if not close to all) models, papers, are all going to be obsolete in a few years even though they feel so new today
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Kyle Mathews
@kam
well or they won't. Progress isn't guaranteed without new conceptual breakthroughs. I don't really see any improvements coming until models get embodied (i.e. exist as robots so can learn from reality)
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Ben 🟪
@benersing
So you think we’re near the end of this cycle?
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Kyle Mathews
@kam
quite possibly. All the new models released in the last year have been somewhere between gpt 3 & 4. Lots to do w/ evals, fine-tuning, training on propritary data, efficient inference, etc. but "intelligence" of models seems like it's topped out — see https://warpcast.com/kam/0x1dd60ed3 & linked @vgr post
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July
@july
Agree with you on this, we’ll probably need a step change akin to CNNs did for deep learning that transformers have done for LLMs
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Ben 🟪
@benersing
What role, if any, do you see quantum playing in this?
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