Probabilistic Reasoning

Latency is where elegant AI architectures go to become invoices. A neuro-symbolic system looks clean on a slide: a neural model sees patterns, a symbolic module checks rules, a probabilistic module handles uncertainty, and the final system behaves more reliably than a pure neural model improvising under fluorescent lighting. Lovely. Very architectural. Very responsible. ...

Proofs are supposed to be the respectable part of AI: tidy, inspectable, and resistant to the usual neural-network fog machine. Then reality turns up, as it so often does, carrying a bill. In neurosymbolic AI, the bill is search. A system may know the rules. It may even combine them with neural perception. But if answering a query requires enumerating a vast space of possible proofs, the promise of “interpretable reasoning” quickly becomes a very elegant way to run out of time. ...