Could AI providers follow the same strategy? Just throw any spare inference capacity at something to make sure the GPUs are running 24/7, whether that's model training, crypto mining, protein folding, a "spot market" for non-time-sensitive/async inference workloads, or something else entirely.
I have to imagine some of them try this. I know you can schedule non-urgent work loads with some providers that run when compute space is available. With enough work loads like that, assuming they have well-defined or relatively predictable load/length, it would be a hard but approximately solvable optimization problem.
I've seen things like that, but I haven't heard of any provider with a bidding mechanic for allocation of spare compute (like the EC2 spot market).
I could imagine scenarios where someone wants a relatively prompt response but is okay with waiting in exchange for a small discount and bids close to the standard rate, where someone wants an overnight response and bids even less, and where someone is okay with waiting much longer (e.g. a month) and bids whatever the minimum is (which could be $0, or some very small rate that matches the expected value from mining).
Since they were run 24/7, there was rarely the kind of heat stress that kills cards (heating and cooling cycles).