Ah. The experiment has to return its result as a quantum state.
Yeah this isn’t the sort of progress that leads to faster AI algorithms. The thing to watch out for is people trying to combine the speed advantages of quantum annealing with the memory advantages of batched stochastic gradient descent.
My personal expectation is that it won’t pan out in time, and we’ll mostly just see quantum computers used to simulate quantum systems and break old encryption protocols.
Yeah, the link is about faster modeling of physical quantum systems, nothing to do with AI/ML as we know it:
The exponential advantage holds in predicting properties of physical systems, performing quantum principal component analysis on noisy states, and learning approximate models of physical dynamics.
Preprint: https://arxiv.org/abs/2112.00778
Ah. The experiment has to return its result as a quantum state.
Yeah this isn’t the sort of progress that leads to faster AI algorithms. The thing to watch out for is people trying to combine the speed advantages of quantum annealing with the memory advantages of batched stochastic gradient descent.
My personal expectation is that it won’t pan out in time, and we’ll mostly just see quantum computers used to simulate quantum systems and break old encryption protocols.
Yeah, the link is about faster modeling of physical quantum systems, nothing to do with AI/ML as we know it: