Actually AI has a lot to do with material design. I can't do a proper explanation, so please bear with this information dump: - We don't have a strong physical

Actually AI has a lot to do with material design. I can't do a proper explanation, so please bear with this information dump: - We don't have a strong physical theory for solid state physics. Quantum stuff doesn't scale well from 1 atom to a mole of atoms, because 10^23 goes into the exponent of number of energy levels in the system, and then we also have to model interaction of those levels. - Physical properties of materials depend on their crystal structure, unevenness of that structure, spectrum of size of crystals, temperature, pressure, fields they're exposed to and current position of stars in the sky. Even the "wrong" solid state physics equations we have are highly non-linear. - State-of-the-art effects are usually achieved with combinations of such materials. - Exact parameters of the process used to put those materials together radically change the behavior of the system. Put that nanolayer with a different sort of vapor deposition or at different pressure, and the thing will stop working. Ever wondered why we don't produce all the neodymium magnets at N55 grade? Because even precise description of the process is not enough. - AI doesn't care about the exact physics, but is sometimes very good at navigating in the large parameter space. - Google have recently made AI that predicted thousands of novel material structures. They found more materials than were found by all human research over the whole humankind history. I wouldn't expect AI to explain what's going on in solid-state physics anytime soon, but exploring crystal structures, doping, and process parameters automatically might actually get us new materials a couple hundred years faster.