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Comment by throwup238

9 hours ago

I also strongly hold this belief largely due to Moravec’s paradox, which is kind of approaching this issue from the side.

Sort of like large language models work on top of what our language has encoded in our massive training datasets, I think biological intelligence is built on top of the parts of the brain that encode the real physical world. These parts grow/train from embodied experimentation and instinct early on in an organism’s life and only then is higher intellect built on top of it (that’s my hypothesis). Their specialization and interconnections give rise to the hardest parts of intelligence long before we’re “thinking”.

Stuff like LLMs and chess engines work because we’ve done all the job of encoding the world into tokens/positions/etc they understand, but that’s wholly inadequate for the kind of AGI we’re striving for. Next up is giving it the tools to interact with the physical world and to really experiment with some self directed “play”. Time will tell just how high the resolution of sensor and mechanical control they’ll need (hopefully not the entire human visual cortex and entire sensory input worth). I think most of the RSI will have to occur in those lower level encoders, not LLMs.

I don't think Moravec's paradox is the same, and you could argue that one no longer holds -- though I'm not sure. You could also argue that Moravec's paradox still holds but that we now have such powerful computers and huge models that we have been able to brute force our way to the capabilities it talks about. It takes many many orders of magnitude more compute power to do things like spatial location, language processing, etc. than it does to do more closed-form things like chess... we just actually have that compute power now.