If you are referring to building ML services, why would a CS degree be necessary? The technology behind generative deep learning falls more in the domain of sta

If you are referring to building ML services, why would a CS degree be necessary? The technology behind generative deep learning falls more in the domain of statistics and information theory than pure computer science (in the discrete mathematics and algorithms/data structures sense of the word). A foundation in scientific programming and a good intuition for multivariable calculus and Bayesian statistics goes much further. I would wager that the perfect candidates for ML research are found in physicists, electronic engineers and other quantitative disciplines (perhaps computational chemists too). Most programmers' CS training are nowhere near enough to understand for example autoencoders at the information theoretic level. How many enterprise java programmers do you think can explain what latent space is? Calling API endpoints and building products around prompts is not the same as actually understanding ML to be a practitioner.