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The algorithms being used in machine learning are not actually new; they're decades old, and many of them were first used in problems in systems engineering. As early as the 1990s, researchers realized that the field of AI was studying the same concepts with different terminology, but for a variety of factors it was the AI space that found the most success. Nevertheless, we're coming back full circle as we see the integration of data, software, and physical equipment starting to blend together. What comes next in the world of data? And how can we learn from the technology of the past?