I love AI x physics intersection! It's an endless rabbithole. You can: - make better AI/ML systems for modeling physical systems (ferminet <https://deepmind.google/discover/blog/ferminet-quantum-physics-and-chemistry-from-first-principles/>, <https://www.microsoft.com/en-us/research/blog/breaking-bonds-breaking-ground-advancing-the-accuracy-of-computational-chemistry-with-deep-learning/> , cosmology <https://www.pnas.org/doi/full/10.1073/pnas.2022038118>, <https://x.com/wgilpin0/status/1925164094010609809>, lagrangian neural networks <https://arxiv.org/abs/2003.04630>, <https://en.wikipedia.org/wiki/Physics-informed_neural_networks> ,...), - do automated discovery of physical laws ( latent space squeezing https://www.youtube.com/watch?v=XRL56YCfKtA , Physics-tailored machine learning reveals unexpected physics in dusty plasmas <https://www.pnas.org/doi/10.1073/pnas.2505725122>,...) - study existing AI/ML systems using methods from physics (the principles of deep learning theory book <https://arxiv.org/abs/2106.10165> statistical physics <https://arxiv.org/abs/2505.10559>, <https://arxiv.org/abs/2501.19281> , <https://arxiv.org/abs/2506.04374>, <https://www.lesswrong.com/s/mqwA5FcL6SrHEQzox>,...) - design and advance better AI/ML architectures that use insights/methods from physics (diffusion models, <https://en.wikipedia.org/wiki/Diffusion_model#Non-equilibrium_thermodynamics>, flow matching <https://arxiv.org/abs/2210.02747> , <https://en.wikipedia.org/wiki/Quantum_machine_learning>, liquid neural networks <https://arxiv.org/abs/2006.04439>,...), - make neurosymbolic systems to do physics algebraically (formal theorem proving <https://deepmind.google/discover/blog/ai-solves-imo-problems-at-silver-medal-level/>, neural search in Lean <https://physlean.com/> <https://arxiv.org/abs/2405.14333>, or outside of Lean <https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/> <https://deepmind.google/discover/blog/funsearch-making-new-discoveries-in-mathematical-sciences-using-large-language-models/>, DreamCoder <https://arxiv.org/abs/2006.08381>,...), - do machine designed physics experiments <https://www.youtube.com/watch?v=T_2ZoMNzqHQ> - do machine learning for particle physics <https://atlas.cern/Updates/Feature/Machine-Learning> - discovery of bigger novel theories (což je totálně v plenkách) <https://x.com/MLStreetTalk/status/1957535063660474492> More here: <https://en.wikipedia.org/wiki/Machine_learning_in_physics> At CERN they use ML for various things [Learning by machines, for machines: Artificial Intelligence in the world's largest particle detector](https://atlas.cern/Updates/Feature/Machine-Learning) etc.