Microsoft is busy prepping developers for the next big Windows 10 update, version 1803, and it is putting the focus on machine learning. Due in March or April this year, the new version will include a new machine-learning framework for using machine-learning models in Windows applications.
Until now, much of the machine-learning focus we’ve seen across the entire computer industry has been on cloud systems. Data sets are processed to build models, and these models can be used to recognize patterns. For example, an industrial system visually inspecting manufactured items for defects would train its model by processing images of known working and known defective items. The machine-learning system would learn what the good objects and bad objects look like and build a model. This model could then be used to examine images of newly made items, and it could then classify them as either likely working or likely defective.
The cloud focus has existed because building the models generally requires large data sets and substantial computing power. However, running the model to use it to classify data is much less demanding. That’s not to say that it’s necessarily trivial—running models against live video, for example, can still require multiple GPUs to perform acceptably—but it tends to be “PC scale” rather than “cloud scale.”
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