I have a passing familiarity with the areas they talk about in the paper, and it feels... dubious. Mainly because of the dedicated accelerator problem. Even dedicated neural net accelerators are having difficulty gaining traction against general purpose compute units in a market that is ludicrously hot for neural net processing, and this is talking about accelerating Monte-Carlo processes which are pretty damn niche in application nowadays (especially in situations where you're compute-limited). So even if they succeed in speeding up that application, it's hard to see how worthwhile it would be. And it's not obvious from the publicly available information whether they're close to even beating the FPGA emulation of the concept which was used in the paper.