Quantum100 ⊗ AI Workshop

In this talk I discuss how understanding the observable consequences of quantum gravity, in particular string theory models, is accelerated using AI methods. This overview will highlight several examples of using physics inspired neural networks to solve Einsteins equations in higher dimensions, differentiable programming to find solutions to string theory equations of motion, and how conditional generative models enable an efficient study of the inverse problem connecting UV string theory constructions with observable quantities. Time permitting I comment on how automated workflows using LLMs can accelerate our research on these long-standing questions even further.