Technology Requirements for Deep and Machine Learning

July 14, 2017 Rob Farber Having been at the forefront of machine learning since the 1980s when I was a staff scientist in the Theoretical Division at Los Alamos performing basic research on machine learning (and later applying it in many areas including co-founding a machine-learning  based drug discovery company), I was lucky enough to participate in the creation and subsequently to observe first-hand the process by which the field of machine-learning grew to become a ‘bandwagon’ that eventually imploded due to misconceptions about the technology and what it could accomplish. Fueled by across-the-board technology advances including algorithmic developments, machine learning has again become a bandwagon that is becoming rife with misconceptions coupled with misleading marketing. That said, the extraordinary capabilities of machine learning technology can be realized by understanding what is marketing fluff and what is real. It is truly remarkable that machines, for the first time in human history, can deliver better than human accuracy on complex ‘human’ activities such as facial recognition, and further that better-than-human capability was realized solely by providing the machine with example data. Significant market applicability means that machine learning, and particularly the subset of the field called deep-learning, is now established and…

Link to Full Article: Technology Requirements for Deep and Machine Learning

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