Yep. We have to keep in mind the distinction between "applied ML" and "ML research" (while realizing that this is a continuum, not a binary distinction). Not everybody is doing cutting edge original research... some people really can just get by with downloading DL4J, reading a few tutorials, and then applying a basic network to their problem, and create some value in the process.
I think cars are a good analogy. In the early days of automobiles, you needed to be something just short of a mechanical engineer to keep one going for any length of time, and it was routine to need to carry around tools and spare parts to perform significant repairs. You really needed to know a pretty good bit about how the car worked to use it effectively. But over time cars developed better abstractions and became more dependable and it became possible to operate a car without caring one lick about how it works, beyond know that it needs gas (or electricity!) and taking it in for the occasional tuneup /tire change / alignment / etc.
I wouldn't say we're at the point yet where ML afford one the opportunity to be completely divorced from caring about the underlying details, but I think we are at a point where you can legitimately get useful stuff done without needing to be able to, say, derive the equations for backprop by hand.
I think cars are a good analogy. In the early days of automobiles, you needed to be something just short of a mechanical engineer to keep one going for any length of time, and it was routine to need to carry around tools and spare parts to perform significant repairs. You really needed to know a pretty good bit about how the car worked to use it effectively. But over time cars developed better abstractions and became more dependable and it became possible to operate a car without caring one lick about how it works, beyond know that it needs gas (or electricity!) and taking it in for the occasional tuneup /tire change / alignment / etc.
I wouldn't say we're at the point yet where ML afford one the opportunity to be completely divorced from caring about the underlying details, but I think we are at a point where you can legitimately get useful stuff done without needing to be able to, say, derive the equations for backprop by hand.