N N Taleb's Probability Questions (UNOFFICIAL) STEPHEN WOLFRAM VISITS RWRI 19, SUMMER SCHOOL 2024
Nov 11, 2025
Stephen Wolfram, a pioneering computer scientist and the mind behind Mathematica and Wolfram|Alpha, dives deep into computational irreducibility and its significance. He explores how cellular automata can model biological evolution and how randomness aids adaptive searches. The discussion extends to the interplay between neural networks and irreducibility, touching upon challenges in extrapolation. Wolfram links these concepts to climate modeling and policy, advocating for conservative approaches amid uncertainty. His insights weave together AI, ethics, and the nature of scientific discovery.
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Simple Rules, Irreducible Complexity
- Very simple programs can produce irreducible complex behavior that resists short explanations.
- Computational irreducibility explains why some systems require step-by-step simulation to know outcomes.
Minimal Cellular Evolution Example
- Wolfram built a minimal cellular-automaton model to mimic evolution and observed stepwise adaptive gains from random mutations.
- Different mutation paths produce varied 'fitness' improvements resembling evolutionary branches.
Irreducibility Enables Discovery
- High-dimensional rule spaces plus effective randomness let adaptive processes avoid getting permanently stuck.
- Computational irreducibility creates enough local variety that evolution and search can still find progress paths.