Archive for 2016

IBM Watson ups the healthcare market ante with $2.6 billion acquisition of Truven

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Healthcare is one of the most logical domains for cognitive computing. The stakes are high: outcomes are often a matter of life or death. It has well organized, extensively tagged information sources. And healthcare/pharmaceutical companies are sophisticated users of advanced software technologies for research, particularly for drug discovery and patient management.

It’s no surprise, then, that IBM has been creating a partner ecosystem and developing technologies aimed at this domain. It has also been gobbling up existing vendors like Phytel, Explorys, ...

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Big Data and Cognitive Computing – Part 4

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In Part 3 of this series, we took up the important issues that come up on the level of functional description as terms are fired off to delineate (or not) big data and cognitive computing. We found that confusion tends to arise immediately from the many statements we can read which appear to wrap big data and cognitive computing into the same phenomenon.

We also found that conversations around big data analytics often seem to ignore the reality that an application ...

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Finding a Model for Information Negotiations—Human or Machine?

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This week, a research group asked me, “For cognitive computing to take off, what advances do you think we need to make the in next five years?” I answered the question, listing the components of a cognitive system, and then discussing which ones were still fairly primitive. But the question continues to haunt me. The fact is that we’ve had most of the components for cognitive computing for a very long time. Language understanding, machine learning, categorization, voting algorithms, search, ...

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Microsoft Makes Deep Learning Toolkit Available on GitHub

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Microsoft announced that it has open sourced its Computational Networks Toolkit and that the software is now available to the public at hosting service GitHub. Microsoft used the toolkit to help train the Cortana personal assistant product in language recognition – at a rate an order of magnitude faster than with prior approaches.

Read more at The Next Web

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Big Data and Cognitive Computing – Part 3

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In Parts 1 and 2 of our series on Big Data and Cognitive Computing, we proposed that these two trends are often brought up in conversation, but that those conversations rarely help clarify the important differences between these two trends. Are we truly confident that we know which is which and why that is so?

We felt that finding a way to describe these two trends in simple terms—and differentiate among them and define their relationship to each other—could help lower ...

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