[inimino]

Evolution operates on genes, which do not encode synaptic connections for one thing. The analogy you're making here is so stretched it's hard to begin to say what's wrong with it. Backpropagation and natural selection are about as different as two things can be. About the only thing you can say they have in common is that both can be modeled as optimization processes.

What's the difference between a star and a bonfire? Both use fuel and produce heat and light.

[mewpmewp2]

I mean the point was about LLMs not truly being problem solvers because they were trained to do so as opposed to having been evolved through evolution. I'm looking for what the difference is specifically within that dimension. Biological pigeons had their own process of evolution how they reached to have the type of neural networks and systems in themselves that gave them the ability to count - but not in all contexts for sure.

So yes, my point is that both have an optimisation process that through time lend them those emerging capabilities.

[inimino]

No, the point was that LLMs are not good at problem solving because they are not good at problem solving, not because they were not evolved. We don't understand how we or animals solve problems, which is why we haven't yet succeeded in replicating that in AI. You're the one bringing in these incredibly strained analogies, because you want GPT 4 to be more than it is or something, I'm not sure.