💾 Archived View for osanwe.benson.earth › s › Cognition › 10 captured on 2024-12-17 at 09:55:10. Gemini links have been rewritten to link to archived content
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The question is simple: Neural networks are thought to be a roughly decent model of how the brain works, although there's a lot we don't know.
Humans can do some pretty impressive things that non-human animals absolutely cannot do when it comes to analogy and representing abstract relationships.
The main way neural networks get better is scaling (i.e. bigger brains). If neural nets are a good model of brains, then why is the human/animal distinction so abrupt?
Note that LLMs can definitely do analogy really well (which makes sense because it's baked into language).
Oct 24 · 8 weeks ago
Maybe the only reason the human/animal distinction seems abrupt is because all the other hominids are extinct.
🦉 satya [OP/mod] · Oct 26 at 09:11:
This might be part of the picture, but even if there is a large evolutionary gap, the qualitative difference lends support to the idea that there’s something important new feature, some computational capability that’s not just quantitatively different from our predecessors but qualitatively different.
And this seems to really butt up against the idea that our brains are basically neural networks with Hebbian training.