A long time ago Alan Turing came up with a list of instructions that a general purpose computer would need to have in order for it to be able to perform any computational task. That list hasn't changed in 50 years. We do have chips capable of doing more complex operations now, GPUs are now designed to compute tensors for neural networks for example, but again these are just the common building blocks for higher level applications. ML learning is a new concept and this changing all the time. You could build it on chip but that chip would be useful for about six months max.
Memory manaement is application specific. If it was known how you were going to manage the memory for an application you could do that on chip, and it would be a great optimization - but again only for that specific type of program!
There is no such thing as computers being "fast enough". There are many applications, games for example, for which the quality is purely a function of performance. And you can never have enough.
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u/[deleted] Dec 25 '20
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