3 ms·
Indexing is a special case of AI. At the limit, optimal cutting and learning are equivalent problems. Non-trivial spatial representations push these two things
by jandrewrogers 1y ago
Indexing is a special case of AI. At the limit, optimal cutting and learning are equivalent problems. Non-trivial spatial representations push these two things much closer together than is normally desirable for e.g. indexing algorithms. Tractability becomes a real issue.
Practically, scalable indexing of complex spatial relationships requires what is essentially a type of learned indexing, albeit not neural network based.
- RaftPeople 1y ago> is essentially a type of learned indexing, albeit not neural network based. NN is just function approximation, why do you think that could not be a valuable part of the solution? It seems like a dynamically adjusted/learned function approximator is a good general tool to most of these hard problems.