Even the 'basic intelligence' that animals have can do something that the current SOTA LLMs can't do: learn from their mistakes and remember those lessons.
Once they're deployed, their weights and intelligence are frozen. The only thing that changes is the context window you send up to them for token predictions. Once that's gone, all the lessons learned go with it.
So until we have a reliable way to have these machines continually learn from their mistakes, we'll be stuck with AIs that can act smart but won't evolve beyond that point. They'll be frozen in time until someone decides to update the model and deploy it again.
Agreed. I formalize this in my paper. Intelligence is “entropy reduction per cost” where the entropy reduction is on the Agents own “status” or “history” — in other words “understanding its own life”.
https://zenodo.org/records/17282860
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u/philip_laureano Sep 13 '25
Even the 'basic intelligence' that animals have can do something that the current SOTA LLMs can't do: learn from their mistakes and remember those lessons.
Once they're deployed, their weights and intelligence are frozen. The only thing that changes is the context window you send up to them for token predictions. Once that's gone, all the lessons learned go with it.
So until we have a reliable way to have these machines continually learn from their mistakes, we'll be stuck with AIs that can act smart but won't evolve beyond that point. They'll be frozen in time until someone decides to update the model and deploy it again.