Google didn't completely scrap its robotic dreams after it sold off Boston Dynamics and shuttered the other robotic start-ups it acquired over the pas
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AI security expert Dawn Song warns that “adversarial machine learning” could be used to reverse-engineer systems—including those used in defense.
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Big data analytics, as it is now practiced, was forged by workers at technology hotbeds like Facebook. Some of those adept engineers have set out on their own, with the goal to simplify data movement and querying, as recent product introductions from Interana and Rockset show.
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Machine learning is offering new possibilities and opportunities, allowing companies to create new industry opportunities and blur existing ones.
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Businesses can’t ignore machine learning if they want to compete in the future.
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When it comes to Big Data, these computer science terms are often used interchangeably, but they are not the same thing. While it may sound confusing, it is actually simple to differentiate the terms when you understand how they work together. Here is the difference between AI and Machine Learning
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Data science and ML are different in key ways. In some ways, one can be seen as a subset of the other. Both are important in current IT progress.
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A Grant Thornton survey of CFOs found finance leaders will invest in emerging technologies with real returns on investment.
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The massive commitment advances the company’s foundation in advanced analytics, machine learning, deep learning, natural language processing, and computer vision. Find out what this AI investment means for SAS and its customers.
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