“Everything being subsumed by TensorFlow” doesn’t seem to me like a particularly worrisome outcome. The status quo is “everything being a Python library,” and people generally seem to view that as positive. The PyData movement brought another level of interoperability to the ecosystem, so you can combine elements from Pandas, SciPy, sklearn, etc with good runtime performance and low cognitive load. Bringing everything into TensorFlow abstractions makes more optimizations possible (especially on heterogeneous architectures), and perhaps even more importantly, makes it easy to run end-to-end gradient descent on compositions of parts from across the ecosystem.
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