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“Embodied” being one of the key things that you’re ignoring The brain =\= a human agent You need sensors and effectors and a highly variable motor system You
by AndrewKemendo 3y ago
“Embodied” being one of the key things that you’re ignoring
The brain =\= a human agent
You need sensors and effectors and a highly variable motor system
You can’t be “generally intelligent” if you do not have boundaries on your computing system which are mobile and have independent actions.
In order to perform as well if not better than a human then you need to perform as well, if not better than a human in all possible environments, and those include the top of the world, the bottom of the ocean, every factory line, flying airplanes, etc…
- sdenton4 3y agoHow could you do anything intelligent without a strong beak? https://falseknees.tumblr.com/post/654380023602708480 https://falseknees.tumblr.com/post/654380023602708480 The interactivity I mentioned is the bit that I think is actually important from embodiment - the ability to take an action in the world, see the result, and adjust expectations. What you've called 'independent actions.' But there's certainly no proof that a general intelligence needs to be bounded and mobile - a pedantic thought-experiment-counterexample would be an 'uploaded' human mind: the people of San Junipero don't stop being generally intelligent once they are in a distributed simulation... More generally, we don't actually know the boundaries on how general intelligence could arise and what shape it could take, because we don't really understand intelligence at all.
- AndrewKemendo 3y agoThe only thing we do know about “intelligence” is that more compute = better performance on tasks we use to evaluate increasing generalization on tasks. So map out the computing power and hardware requirements of an average adult human with IQ 100 and no disabilities and that should tell you what you need. It’s probably 3x harder than just a brain.
- nightski 3y agoI don't think that's even true. Where are you getting this? I can create an extremely compute heavy model that performs very poorly. Just adding more compute does not mean better performance on its own. Given the same model too much compute can even mean over-fitting and worse generalization. It doesn't all come down to compute.