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As far as I know, there hasn't really been a quantum leap in AI in decades. Most of the fundamentals of the things you see in AI and machine learning are old, like 70s and 80s. The big change is that we have way more and cheaper processing power, so you can see AI happening in fields and areas that were just impossible in the past.

A true Turing Test passing machine, is still something that we seem to be more than a quantum leap behind of.

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Who says we need a quantum leap? Most technologies progress by slow iterative improvement. The idea of sudden significant breakthroughs is mostly a myth. Even in biology, the human brain only has some slight differences from other primates. Which in turn aren't terribly different from other animals.

In any case, I think there has been tons of progress since the 80s. Taking the best algorithms from the 80s and running them on modern hardware would fail. The core idea of backpropagation and gradient descent was there, but not much else.

I suspect the "quantum leap" itself will be yielded by a new method of parameter updates, perhaps one that expands the scope of neural networks as they are presently defined.

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