Accelerating scikit-learn is a smart move. At the algorithmic level for every ML use case there is probably x 10 non-ML data science projects. Also, it is good to have a true community framework that does not depend on the success of the metaverse for funding ;-)
The lock-in is an important consideration, but if the scikit-learn API is fully respected it would seem less relevant. It also suggests a pattern for how other hardware vendors could accelerate scikit-learn as a genuine contribution?
The lock-in is an important consideration, but if the scikit-learn API is fully respected it would seem less relevant. It also suggests a pattern for how other hardware vendors could accelerate scikit-learn as a genuine contribution?