Machine Learning Vs. Artificial Intelligence: Unpacking Their Histories

“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media. Today’s column is written by Ken Rona, chief data scientist at IgnitionOne. There is a lot of excitement and some confusion across the ad industry around machine learning, and for good reason. The availability of cheap storage and processing has made sophisticated machine learning available to a much wider range of industries than what was available even five years ago. The media business has seen machine-learning solutions find homes in a wide variety of applications, from predicting how likely a user will click on an ad to classifying users in lookalike models and optimizing campaign delivery. This wider use has brought increased attention to various components of machine learning, and that’s where the confusion arises. Perhaps no piece of the machine-learning toolkit has grown in popularity quite like artificial intelligence (AI), which has become so widely discussed that many use the terms interchangeably, as evidenced by recent vendor surveys and press coverage. The use of the term AI to encapsulate a broad variety of algorithms, statistical and otherwise, creates even more confusion. Vendor marketing teams have flipped the nomenclature and…


Link to Full Article: Machine Learning Vs. Artificial Intelligence: Unpacking Their Histories

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