I have no good argument that a human-sized EfficientZero would somehow need to be much slower than humans.
Arguing otherwise sounds suspiciously like moving the goalposts after an AI effect: “look how stupid DL agents are, they need tons of data to few-shot stuff like challenging text tasks or image classifications, and they OOMs more data on even something as simple as ALE games! So inefficient! So un-human-like! This should deeply concern any naive DL enthusiast, that the archs are so bad & inefficient.” [later] “Oh no. Well… ‘the curves cross’, you know, this merely shows that DL agents can get good performance on uninteresting tasks, but human brains will surely continue showing their tremendous sample-efficiency in any real problem domain, no matter how you scale your little toys.”
As I’ve said before, I continue to ask myself what it is that the human brain does with all the resources it uses, particularly with the estimates that put it at like 7 OOMs more than models like GPT-3 or other wackily high FLOPS-equivalence. It does not seem like those models do ‘0.0000001% of human performance’, in some sense.
I have no good argument that a human-sized EfficientZero would somehow need to be much slower than humans.
Arguing otherwise sounds suspiciously like moving the goalposts after an AI effect: “look how stupid DL agents are, they need tons of data to few-shot stuff like challenging text tasks or image classifications, and they OOMs more data on even something as simple as ALE games! So inefficient! So un-human-like! This should deeply concern any naive DL enthusiast, that the archs are so bad & inefficient.” [later] “Oh no. Well… ‘the curves cross’, you know, this merely shows that DL agents can get good performance on uninteresting tasks, but human brains will surely continue showing their tremendous sample-efficiency in any real problem domain, no matter how you scale your little toys.”
As I’ve said before, I continue to ask myself what it is that the human brain does with all the resources it uses, particularly with the estimates that put it at like 7 OOMs more than models like GPT-3 or other wackily high FLOPS-equivalence. It does not seem like those models do ‘0.0000001% of human performance’, in some sense.