zlacker

My alternative definition would be something like this. Intelligence is the capacity to solve problems, where a problem is defined contextually. This means that what is and is not intelligence is negotiable in situations where the problem itself is negotiable. If you have water solve a maze, then yes the water could be said to have intelligence, though that would be a silly way to put it. It’s more that intelligence is a material phenomenon, and things which seem like they should be incredibly stupid can demonstrate surprisingly intelligent behavior.

LLMs are leagues ahead of viruses or proteins or water. If you put an LLM into a code editor with access to error messages, it can solve a problem you create for it, much like water flowing through a maze. Does it learn or change? No, everything is already there in the structure of the LLM. Does it have agency? No, it’s a transparently deterministic mapping from input to output. Can it demonstrate intelligent behavior? Yes.

>>Briggy+(OP)
That's an interesting way of looking at it, though I do disagree. Mainly because, as you mention, it would be silly to claim that water is intelligent if it can be used to solve a problem. That would imply that any human-made tool is intelligent, which is borderline absurd.

This is why I think it's important that if we're going to call these tools intelligent, then they must follow the processes that humans do to showcase that intelligence. Scoring high on a benchmark is not a good indicator of this, in the same way that a human scoring high on a test isn't. It's just one convenient way we have of judging this, and a very flawed one at that.

Anyway, cheers for the discussion!