In this blog, we discuss cognitive computing and other technologies with a focus on supply chain management and innovation. Other topics of discussion include digital enterprise transformation, marketing, the Internet of Things, and smart cities. Our goal is to advance the public discussion about how cognitive computing and other advanced technologies affect the world in which we live.
Bradd C. Hayes is the active editor of this blog.
As digital streams drained into oceans of data, a new age was born — the Digital Age. It is no coincidence that machine learning matured rapidly in this new age. Ishan Gupta
Much of the current discussion about artificial intelligence (AI) actually involves a sub-set of AI called machine learning. Erika Morphy explains, “Machine learning is the use of computing resources that have the
Machine learning (ML) is a subset of artificial intelligence (AI). In recent years, however, ML has taken center stage in the business world. Bernard Marr (@BernardMarr), a strategic performance consultant, writes, “At
“The first thing you need to know about AI (and machine learning),” writes Eric Knorr (@EricKnorr), “is that it’s full of confusing, overlapping terminology, not to mention algorithms with functions that are
Machine learning is one of the current buzzwords frequently found in articles about the future of business. Other terms with which machine learning is often associated include artificial intelligence (AI) and cognitive
According to research conducted by Vanson Bourne for SoftServe, “62% of medium to large organizations expect to implement machine learning for Business Analytics purposes within the next two years.”[1] A press release
In Part 3 of this series of articles about machine learning, I emphasized the growing belief that insights obtained using big data analytics (in the words of Narendra Mulani [@npmulani]), are the
This article is a continuation of a discussion on machine learning that I began in two other articles with the same title (Part 1 and Part 2). “As data is transformed into
In Part 1 of this article, I noted that there are five principal ways that machines learn. They are: Supervised learning — where you teach it Unsupervised learning — where you let
“In the age of data science,” Shelly Palmer (@shellypalmer), Managing Director of the Digital Media Group at Landmark Ventures, writes, “machine learning and pattern matching are the building blocks of competitive advantage.”[1]
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