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Getting Real About Autonomous Cars
Among my least lucrative, but most interesting jobs is being a “digital fellow” at the MIT Initiative on the Digital Economy. There are often interesting developments happening there on the topics of artificial intelligence (AI), digitization, and digital platforms. That was certainly the case on March 8, when I attended
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Improve New Product Development with Predictive Analytics
Recently on this site, one of us wrote about the new product development analytics used by Netflix. In a nutshell, the company classified the key attributes of past and current products or services and then they modeled the relationship between those attributes and the commercial success of the offerings. This
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The Benefits of Ignoring When Executives Misunderstand Artificial Intelligence
With the hype surrounding Artificial Intelligence (AI) today, almost everyone in the analytics and data science space has been asked about AI by their business partners. Unfortunately, during these conversations it often becomes apparent that the business person really doesn’t have a clue what AI really is or what AI
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The Myth of the Data Scientist Shortage
Technologists and business folks alike overstate the shortage of data scientists. They just need to know where to look.Data scientists—people who can manage and analyze big, unstructured data—were once as scarce as vegetarian dogs. If your business wasn’t based in Silicon Valley or Boston, if you couldn’t offer massive stock
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Beyond the Black Box in Analytics and Cognitive
There is a growing crisis in the world of analytics and cognitive technologies, and as of yet there is no obvious solution. The crisis was created by a spate of good news in the field of cognitive technology algorithms: they’re working! Specifically, a relatively new and complex type of algorithms—deep
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IT Organizations: The Shoemaker's Analytical Children
For the great majority of years in the past decade, Chief Information Officers named “business intelligence and analytics” as their top focus in Gartner Inc. annual surveys of technology priorities. That set of technologies moved to number one in the survey in 2006 and stayed there until 2009. It fell
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Move Your Analytics Operation from Artisanal to Autonomous
Many organizations today are wondering how to get into machine learning, and what it means for their existing analytics operation.There are many different types of machine learning, and a variety of definitions of the term. I view machine learning as any data-driven approach to explanations, classifications, and predictions that uses
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Six Very Clear Signs That Your Job is Due to be Automated
Anesthesiologists’ jobs look safer than radiologists’ jobs. Here’s why.In H. G. Wells’s classic The War of the Worlds, the narrator pauses a moment to rue the fact that he didn’t react sooner to the arrival of an “intelligence greater than man’s”—in his case, Martians landing on earth. Comparing himself to
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Just How Smart are Smart Machines?
The number of sophisticated cognitive technologies that might be capable of cutting into the need for human labor is expanding rapidly. But linking these offerings to an organization’s business needs requires a deep understanding of their capabilities.If popular culture is an accurate gauge of what’s on the public’s mind, it
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Effective Operational Analytics is About More than Analytics
Many times when I speak with analytics managers or business people interested in analytics, they tell me that performing some analytics on data is not the primary problem they have. “We have to get the analytics integrated with the process and the systems that support it,” they say. This issue,