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Dimension reduction and clustering have long been the focus of AI/ML. Reference, Bishops book an early 2000's classic, Pattern Recognition and Machine Learning, chapter 9.1 is k-means clustering.

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People started using machine learning as a term to differentiate the goal from actual intelligence. They're not the same. Early work in AI was generally about achieving goals (aka A*, blocks world, etc), which is not the same thing as dimensionality reduction or clustering.

Russell and Norvig (1995) include machine learning as one of the four elements needed to pass the Turing Test. They cite Gold's Identification of Language in the Limit from 1967 as a laying the groundwork for machine learning applied to natural language processing.

http://stpk.cs.rtu.lv/sites/all/files/stpk/materiali/mi/arti...

http://web.mit.edu/~6.863/www/spring2009/readings/gold67limi...

Metallurgy is an important aspect of high end bicycle design. But you would never argue that metallurgy is bicycle design.

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