This is a great comment. I first learned ML at Google in Boulder in 2017 using TensorFlow. We were introduced by the google images team to re-create Uber's fare estimation algorithm using 25+ years of New York City taxi data. GPS locations, fares, times of day, routes, etc. As expected, given gradient descent and how people chose to use the parameters, everyone had very different algorithms by the end. This is what has been known with ML for years (even with GPT, just massive models), but something that can process and learn on the fly is something else entirely and is pretty exciting for the future. Philosophical questions abound.