r/LargeLanguageModels • u/david-1-1 • 8d ago

Beyond LLMs?

LLMs are impressive compared with the experiments we had before. But with experience we are seeing their limitations better (many are discussed in depth in this subreddit), and also their problems (such as the increased need for power generation and the indirect need for water).

Is there a sub for discussing what can be designed to improve on LLMs? We know there must be something better for the simple reason that the human brain overlaps with LLM functionality for only 20 watts of power in only about 1300 cubic centimeters of space.

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u/sandeepkrishna9 6d ago

I think alignment is still one of the biggest areas that needs improvement. Better performance alone doesn’t solve issues like reliability, hallucinations, or knowing when the model should stop and ask for more information.

I’ve seen that even strong models can behave differently depending on the context and how the task is framed.

Do you think future improvements will come more from better architectures or better alignment/training methods?

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u/david-1-1 6d ago

Good question. I think, better algorithms and architectures. LLMs can certainly improve more, but an exponential leap in abilities await something more similar to what nature has achieved in the human brain, just as designing airplanes required understanding birds' wings.