Earlier quoted context omitted.
There's a lot of research at the "P = BQP?", "NP I can tell you that Shor's algorithm for factoring takes O((log n)^2 (log log n)(log log log n)) (we can round that up to O((log n)^4) if you want) to a the best known classical algorithm of O(exp(1.9 * (log n)^(1/3) (log log n)^(2/3))) But unless I tell you how fast each gate is, that tells you nothing about the constant time factors. Also, all these quantum algorithm…
But could quantum computing accelerate AI workloads such as graph traversal/rewriting? Iff quantum computing is only useful at breaking encryption, I don't see the point in funding quantum computing research.
Quantum computing is not expected to have large impacts on machine learning at this time after Ewin Tang's paper. There's an especially large amount of fluff in this area, though.