Understanding NP-Hard Problems in AI and Encryption | Scott Aaronson

Can one math problem unlock AI, break encryption, and solve it all?

Watch the full interview with Scott Aaronson here: https://www.youtube.com/watch?v=EYyOSD4qdJQ&list=PL87anKnyrxSINa7feABRBcXA_fIQzqPH0&index=4

In this clip, theoretical computer scientist Scott Aaronson explains the stakes of the legendary P vs NP problem, why so many optimization challenges—from the traveling salesman problem to training large neural networks—are “NP-complete,” and how solving just one of them efficiently would let us solve all of them.

Scott breaks down NP-hardness, NP-completeness, and the surprising link between classic math puzzles and modern AI training. He also discusses approximation theory, why some problems resist even near-perfect solutions, and what it would mean for cryptography if a fast algorithm were found. Whether you’re curious about quantum computing, AI optimization, or the future of encryption, this is a masterclass in computational complexity.

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