Evidence actually supports that capabilities are leveling off, and cheaper/faster is not really coming. Just log-linearly more capability at smaller parameter counts as they saturate.

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sipjca 2 minutes ago | parent | next [-]

what do you mean cheaper/faster is not really coming? the cost of the same level of intelligence steadily decreases year over year. computer hardware also advances at the same time enabling cheaper and faster serving (or move to local)

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bad_haircut72 an hour ago | parent | prev | next [-]

not an AI researcher - this is probably true for these "everything" LLMs but I think specialized models are gonna be the next big thing

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ACCount37 an hour ago | parent [-]

"Specialized models" are a bit of a doozy.

The biggest generalist models beat the most fine-tuned specialists, as a rule. You can bias an LLM away from literature knowledge and towards coding capabilities, but that buys you very little performance, and for too much effort.

Generality and intelligence seem to be entangled very heavily in LLMs.

	▲	CamperBob2 20 minutes ago \| parent [-]
		And yet, there's VibeThinker 3B to bring this long-held premise into question (if not to blast it to pieces.) It is practically illiterate by the standards of larger models, yet performs like models 100x its size on mathematical and logical reasoning tasks.

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ACCount37 an hour ago | parent | prev [-]

What "evidence"? Because we keep running out of benchmarks to distinguish frontier model performance. If capabilities are "leveling off", we're not seeing it yet.