Eric Drexler has argued that the computational capacity of the human brain is equivalent to about 1 PFlop/s, that is, we are already past the human-brain-human-lifetime milestone. (Here is a gdoc.) The idea is that we can identify parts of the human brain that seem to perform similar tasks to certain already-existing AI systems. It turns out that e.g. 1-thousandth of the human brain is used to do the same sort of image processing tasks that seem to be handled by modern image processing AI… so then that means an AI 1000x bigger than said AI should be able to do the same things as the whole human brain, at least in principle.
Has this analysis been run with nonhuman animals? For example, a chicken brain is a lot smaller than a human brain, but can still do image recognition, so perhaps the part of the chicken that does image recognition is smaller than the part of the human that does image recognition.
Eric Drexler has argued that the computational capacity of the human brain is equivalent to about 1 PFlop/s, that is, we are already past the human-brain-human-lifetime milestone. (Here is a gdoc.) The idea is that we can identify parts of the human brain that seem to perform similar tasks to certain already-existing AI systems. It turns out that e.g. 1-thousandth of the human brain is used to do the same sort of image processing tasks that seem to be handled by modern image processing AI… so then that means an AI 1000x bigger than said AI should be able to do the same things as the whole human brain, at least in principle.
Has this analysis been run with nonhuman animals? For example, a chicken brain is a lot smaller than a human brain, but can still do image recognition, so perhaps the part of the chicken that does image recognition is smaller than the part of the human that does image recognition.
It is known that birds brains are much more mass-effective than mammalian.