Are there any insights that you can give based off the info you've learned about quantum computation that you might not have been able to reach if you hadn't learned about it?
From my __very__ shallow understanding, because all of the efficiency increases are in very specific areas, it might not be useful for the average computer science interested individual?
Nearly all of quantum computation is theoretical algorithms and the hard engineering problems haven't been solved. Most of the math though has a large amount of overlap of AI / ML and all of deep learning to the point that Quantum computers could be used as "ML accelerators" by using algorithms (this is called Quantum Machine learning) [1]. Quantum computing could be learned with a limited understanding of Quantum theory unless you are trying to engineer the hardware.
Possibly of interest, but I wrote a (hopefully approachable) report on quantum perceptrons a few years back [1]. Perhaps it's found elsewhere, but I was surprised by how, at least in this quantum algo's case, the basis of training was game theoretic not gradient descent!
