Microsoft In Recovery Room After Tay

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Microsoft appears to have been emboldened by the success of its Xiaoice chat bot in China to try a US-based chat bot with the personality of a 19-year-old girl in order to attract the 18-24 year-old demographic. What it found was that the US market responded to the introduction by attacking the bot’s learning algorithms with hate speech and “training” Tay to be an eager participant within its first few hours online.

Microsoft acted at once to shut down the experiment ...

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CSC’s Leading Edge Forum Declares “Matrix” Era

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London-based Leading Edge Forum, a research arm of CSC (Computer Sciences Corporation) issued a new study, titled Embracing ‘the Matrix’ and the Machine Intelligence Era. The study declares that the current intersection of Cloud computing and “machine intelligence” will bring about an “ever more capable digital ecosystem” that they dub “The Matrix.”

Read more at Leading Edge Forum

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Supreme Court Ideal Point Miner (SCIPM)

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Researchers at the Discovery Analytics Center at Virginia Tech have developed a model that learns Supreme Court justices’ judicial preferences and voting behavior. Using the model, they report that they have been successful in assessing justices’ views on issues, anticipating their alignments in different cases, and predicting which justice may become a swing vote on an issue that divides the court.

Read more at The Conversation.com

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Looking at Unpredictability in truly Cognitive Systems

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The recent Google AlphaGo victory over a human Go grandmaster is notable not only for the prodigious capabilities of deep learning on display from the machine but also for the surprise one of AlphaGo’s moves brought to Lee Se-Dol, the human competitor. As Lee stated, this was “not a human move.” He is reported to have felt the need to leave the room for 15 minutes to regain his composure.

Researcher Jonathan Tapson, Director of the MARCS Institute for Brain, Behaviour ...

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Stirrings in the Cognitive Services Nest

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The widely splashed news of the founding of Noodle.ai and its first CEO, Stephen Pratt, lately of IBM Global Business Services, represents another indicator of increasing interest in the services opportunity connected with cognitive computing.

Founding investment firm TPG Growth, having passed on Palantir and other opportunities with stratospheric valuations, decided to roll its own offering to compete with IBM in the enterprise cognitive services space.

Read more at The New York Times

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HPE Haven OnDemand Machine Learning & Search

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HP Enterprise has joined the list of enterprise cloud service providers offering component APIs to enable customers to develop what HP calls “augmented human intelligence” applications. The Haven OnDemand service runs on the Microsoft Azure cloud for now and offers “over 60” APIs including text analysis, image recognition, speech recognition, predictive analytics, and search.

Read more at eWeek

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February Scorecard on Cognitive and Watson

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In an insightful perspective piece, The New York Times tech columnist Steve Lohr recaps IBM’s experience with Watson since Jeopardy, including early failures in health care and maturing expectations of what it takes to build a business model around enterprise cognitive systems. Lohr sets the larger context for the story by including points of view from industry players including executives from both today’s startups and from the first AI boom in the 1980s.

Read more at The New ...

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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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