If this perspective is accurate then it has deep implications for the economics of AI: the marginal cost of solving an idiosyncratic problem is small (you just need to map it to one of the canonical problems, and apply that solution), but there’s very high value in making progress on the canonical problems. So we would expect AI labs to be spending huge amounts of compute on advancing the SoTA on the few deep problems of the world, and providing a service that solves idiosyncratic problems very cheaply.