As somebody who's recently starting to learn more about ML, a lot of the work of an ML engineer does seem to be automate-able (not doing research or pushing boundaries but just applying ML to some product need). For example, choosing hyperparameters, evaluating which features to collect, etc seem to be things that can be automated with very little human input.
His slide on "learning to learn" has a goal of removing the ML expert in the equation. Can somebody who's more of an expert in the field comment on how plausible it is? Specifically, in the near future, will we only need ML people who do research, due to the application being so trivial to do once automated?
His slide on "learning to learn" has a goal of removing the ML expert in the equation. Can somebody who's more of an expert in the field comment on how plausible it is? Specifically, in the near future, will we only need ML people who do research, due to the application being so trivial to do once automated?