So far, the only known algorithm relevant to AI that would run faster on a theoretical quantum computer is linear search, where quantum computers offer a modest speedup (linear search is O(n) on a classical computer, while Grover's algorithm is O(sqrt(n)) for quantum computers - this means that for a list of a million elements, you can scan it in 1 000 steps on a quantum computer instead of 1 000 000 steps on a classical one).

However, even this is extremely theoretical at this time - no quantum computer built so far can execute Grover's algorithm, they are not reliable enough to get any result with probability higher than noise, and anyway can't apply the amount of steps required for even a single pass without losing entanglement. So we are still very very very far away from a quantum computer that could reach anything like the computing performance of a single consumer-grade GPU. We're actually very far away from a quantum computer that even reaches the performance of a hand calculator at this time.

Pure Quantum Gradient Descent Algorithm and Full Quantum Variational Eigensolver https://arxiv.org/abs/2305.04198

There is not an "OS" or anything even remotely like it. For now these things behave more like physics experiments than computers.

You can play around with "quantum programming" through (e.g.) some of IBM's offerings and there has been work on quantum programming languages like q# from Microsoft but its unclear (to me) how useful these are.

that's not the way to think about quantum computing AFAIK.

Think of these as accelerators you use to run some specific algorithm the result of which your "normal" application uses.

More akin to GPUs: your "normal" applications running on "normal" CPUs offload some specific computation to the GPU and then use the result.

> "an OS for those"

Or at least an OS driver for the devices supporting quantum computing if/when they become more standard.