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Machine Learning: Solving Complex Problems Without Clear Rules or Algorithms

By Dick Weisinger

Machine learning (ML) is a kind of artificial intelligence (AI) that enables computers to be able to observe and recognize patterns in processes and events and to then to be able to apply that information in a way that enables them to emulate the responses to events which were observed.  Machine learning software differs from standard programming because computers are not programmed to perform explicit tasks or actions.

Jeff Bezos, CEO of Amazon, said that “over the past decades computers have broadly automated tasks that programmers could describe with clear rules and algorithms. Modern machine learning techniques now allow us to do the same for tasks where describing the precise rules is much harder…”

Machine learning has been applied to very complex problems, like autonomous vehicles, natural language processing, and image and speech recognition.  Some of the machine learning techniques used are called “deep learning” and neural networks.

Bezos said that “much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising replacements, fraud detection, translations and much more. Though less visible, much of the impact of machine learning will be of this type — quietly but meaningfully improving core operations…  Watch this space. Much more to come.”

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