Welcome to the Momenta Learning News on Machine Learning. This is issue 62, please feel free to share this post.
Machine learning algorithms and artificial intelligence tools are receiving a lot of attention in the analytics world these days, and industry experts and experienced users say the plaudits are well deserved.
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Understanding and managing unwarranted clinical variation is a significant and costly challenge in today’s value-based health economy. Every patient is unique, so variation is a natural element in most healthcare delivery. But improving patient outcomes, minimizing medical errors and reducing costs is difficult when hospitals are unable to draw hidden insights from their own data.
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By Dick Weisinger Machine Learning algorithms are becoming widely used. Microsoft, Google, IBM and Amazon, for example, have all added machine learning options to their cloud offerings. Facebook has open-sourced its hardware design. Yahoo has also released an open-source AI tool called CaffeOnSpark. Chinese giant Baidu has also released open-source AI software.
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It makes no sense to look at the Industrial Revolution as a race between humans and steam power to see who is stronger, or between humans and cars to see who is faster, CIO Journal Columnist Irving Wladawsky-Berger argues. Similarly, we must now learn to adapt to and work with our increasingly smart machines.
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Quantum computers could be closer than we thought, thanks to new steps toward an easier way to build them. A computer that uses the quirks of quantum physics to work on data should be capable of things far beyond any machine in use today.
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ALPHABET ALPHA MALE CEO Eric Schmidt has poured high horsery on panic-mongering artificial intelligence (AI) talk from Stephen Hawking and Elon Musk, and kind of accused them of not knowing what they’re talking about. Musk and Hawking have expressed concerns about the rise of the robots, and the former even has something of an escape plan.
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Data analysis experts from universities around the country gathered June 9 for a roundtable discussion on “Educating in a Data-Driven World,” hosted by Tableau Software at the St. Regis hotel in Washington, D.C.
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“One person, in a literal garage, building a self-driving car.” That happened in 2015. Now to put that fact in context, compare this to 2004, when DARPA sponsored the very first driverless car Grand Challenge. Of the 20 entries they received then, the winning entry went 7.2 miles; in 2007, in the Urban Challenge, the winning entries went 60 miles under city-like constraints.
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As massive cloud vendors like Google, Amazon and Microsoft spend billions per quarter building and operating the world’s largest computing platforms, is the era of the corporate data center drawing to a close?
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In his new book, The Perfect Bet: How Science and Math Are Taking the Luck Out of Gambling , Adam Kucharski details how trying to understand dice games led one mathematician to develop probability theory, how one of the first wearable computers was designed to covertly predict the fall of a roulette ball, and how poker-playing bots are advancing more quickly than we think.
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