It's easy for people (especially people who like tech) to forget this. "Innovation" in the sense of better algorithms or improved computations are great, but th

It's easy for people (especially people who like tech) to forget this. "Innovation" in the sense of better algorithms or improved computations are great, but they don't solve problems - applications do. That's why many 'hot' areas (like machine learning, for example) have a large gap between industry and academia. Researchers focus on "innovation" in terms of new approaches, aiming for marginally higher performance, and requiring increasingly complex models/infrastructure to unlock the remaining performance. On the other hand, combining an existing technology with industry knowledge of how to apply it can have a huge impact.