There is a non-trivial amount of work being done at university research labs that has yet to feel the effects of the machine learning revolution because PIs aren’t investing (or cannot afford) programmers, and scientific equipment is manufactured by a small handful of companies who have little incentive to innovate. Please note that n=2, but both myself and a friend of met have met people working in life science labs…
True, there is a nontrivial amount of very useful software which could be written for universities across the science and engineering fields, but very little money to pay for it. Generally, grant money cannot be spent on software so investment in tools is negligible.
Really? That seems a few decades behind the times.