Symbolic regression looks for concise, human readable mathematical expressions to describe functional dependences in data. Ultimately a very effective symbolic regression technique can be conceived of as a system for automatic discovery of physical laws, given suitable data. The current state of the art for symbolic regression is based on genetic algorithms, see e.g. PySR https://github.com/MilesCranmer/PySR

Will we see a major breakthrough in symbolic regression in terms of speed, ease of use, robustness to noise or other dimensions by Dec 31, 2025?

Resolution is subjective so I won't bet on this market.