Conformal Bootstrap in the Age of AI

The conformal bootstrap studies strongly coupled quantum field theories through symmetry, unitarity and crossing symmetry without relying on perturbation theory. This talk reviews recent analytic functional approaches to the numerical bootstrap and introduces new results. It then considers how machine learning could navigate consistent conformal field theories. Neural networks can construct crossing-symmetric correlators from limited physical input; their tendency toward simple, smooth solutions may reveal additional organizing principles behind bootstrap constraints.