Researchers launched an in-house Data Science and Artificial Intelligence (DSAI) challenge to beat MIT’s machine-learning models for predicting clinical trial outcomes. The results are now available.
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Integrating robots into a manufacturing system is often prohibitively expensive. A new approach could change that.
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Machine learning is a powerful form of artificial intelligence that is affecting every industry. Here’s what you need to know about its potential and limitations and how it’s being used.
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AI is a tool to get things done. To use it properly and generate value, organizations need the right capabilities — including a good understanding of data.
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In a new book, MIT roboticist Daniela Rus looks at the powers and limitations of robots and how humans can work with them to unlock new capabilities.
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Companies make common data science mistakes. Here’s an expert’s guide to what they are and how to avoid them.
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MIT Sloan and CSAIL researchers apply artificial intelligence techniques to one of the largest datasets of clinical trial outcomes to handicap the drug and device approval process
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In a new book about the history of Kendall Square from the MIT Press, author Robert Buderi chronicles the area's biggest successes in innovation.
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Matt Beane, SM ’14, PhD ’17, argues those using artificial intelligence will become incrementally de-skilled unless they are consciously upskilling at the same time.
MassRobotics, a nonprofit founded by several MIT alumni, is advancing an industry that will play an increasingly important role in our lives.
