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Comment by ttlei

8 years ago

Current ML algorithms have been worked on for decades earlier. They are gaining momentum again due to big data and computing power.

To me "current ML" in the parent comment meant deep learning. Open a computer vision paper from this month and the prior art section almost only contains references from between 2014 to 2018.

Yes the NN layer architecture might be based on ideas from the previous era, but the way the algo actually solve the problem is completely different.

And that's just because it's the only way we can do it right now. When we can apply deep learning to itself it, to select better architectures and hyperparameters, will find strategies we didn't think about or didn't consider worth trying.