NP-completeness hit AI researchers with a theoretical ceiling: many problems in search, reasoning, and computer vision are NP-complete or worse, meaning there is no known efficient algorithm to solve them—one must exhaustively search all candidate solutions, which is computationally infeasible for problems with many variables.
factualpending
Speaker
Michael WaldridgeEvidence Quote
“the problem is that the number of candidate Solutions in that case just grows astronomically um so for example if there are something like 70 cities there would be more possible candidate Solutions than there are atoms in the universe”
Source
Don’t Believe AI Hype, This is Where it’s Actually Headed | Oxford’s Michael Wooldridge | AI History— Johnathan BiCreated: 8/11/2026, 7:08:35 AM
My Notes
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