Does Computational Complexity Restrict Artificial Intelligence (AI) and Machine Learning?

3 thoughts on “Does Computational Complexity Restrict Artificial Intelligence (AI) and Machine Learning?”

1. "About 10^40 atoms in the human head" is clearly an overestimate. As it happens, there's a web page where this question is addressed (http://education.jlab.org/qa/mathatom_03.html ) and this gives the answer as 4.56*1026.

2. I think the current computation model like CPU/GPU +Memory which mimic basic Neumann computer is the bottleneck in complex computation. Our all algorithms and assumptions are based on this basic computation model, we are bounded by CPU/ memory. If we have solved questions like NP-hard we need different computation model which I don't know now … and we want to mimic brain whose computation model is completely different than ours one, we are trying to fit the square peg in round hole. That is why we will be always restricted. Once the new computation model comes beyond Neumann's limitations we could solve the problem.. Even though we are trying to mimic neurons with deep learning models, unfortunately, we can not mimic , as underlying base computation unit is not same!

3. He shrugs off noncomputable programs as very rare. They are rare in applied comp sci today, but definable, formally, they are so common compared to comparable problems (lower infinity cardinality). This guy is so loose he makes errors!

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