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AI algorithmic progress is outpacing Moore’s Law at it best.

Compared to 2012, it now takes 44 times less compute to train a neural network to the level of AlexNet.

How that affect self-driven car is still to be determine, but progress is very real

This is only in terms of effeciency, not in terms of accuracy of overall performance.

Of course, but it's a great example - there is certainly a lot of progress in the other dimensions as well.

However this gain also directly translates to a real-world result improvement: You can now train a lot more at the same cost.