Artificial Intelligence Articles

Artificial IntelligenceData ScienceMachine Learning

From Jeopardy winners and Go masters to infamous advertising-related racial profiling, it would seem we have entered an era in which artificial intelligence developments are rapidly accelerating. But a fully sentient being whose electronic “brain” can fully engage in complex cognitive tasks using fair moral judgement remains, for now, beyond

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Artificial IntelligenceData ScienceEventsMachine LearningUnderstanding Big Data

Ajit Jaokar is a leading expert working at the intersection of Data Science, IoT, AI, Machine Learning, Big Data, Mobile, and Smart Cities. He teaches IoT and Data Science at Oxford and also is a director of Smart Cities Lab in Madrid. Ajit’s work involves applying machine learning techniques to

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Artificial IntelligenceData ScienceMachine Learning

From Decentralized Model Exchanges to Model Audit Trails [This is based on a talk I first gave on Nov 7, 2016. Here are the slides.] In recent years, AI (artificial intelligence) researchers have finally cracked problems that they’ve worked on for decades, from Go to human-level speech recognition. A key

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Artificial IntelligenceContributorsData Science

You may not see it, but it’s there. Artificial intelligence, that is. It’s beating us at our most complicated games, helping curate the news we read every day, ever improving our search results, driving our cars, and on and on and on. We’ve entered into what some experts are calling

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Artificial IntelligenceConversationsInterviewsTechnology & IT

  Nicolas Boudot is the EMEA Director at Softbank Robotics, where he has been responsible for partnerships and for promoting the use of humanoid robots in the B2B, educational and consumer markets, since 2001, when Aldebaran Robotics, the makers of Nao humanoid robots, was acquired by Softbank Mobile. He has

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Artificial IntelligenceContributorsMachine Learning

There is general agreement that language is the key to AI, but who holds the key to language – algorithms or people? According to the hype, the key to automated natural language understanding lies in vast data collections containing millions of words coupled with machine learning algorithms. If you believe

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