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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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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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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.
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MIT researchers have developed a methodology for systematically tracking the outcomes of academic licensing transactions as a means of increasing funding to bridging the “valley of death.”
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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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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The studies describe new methods for accelerating drug approvals during pandemics and for providing more accurate measures of the probabilities of success for clinical trials of vaccines.
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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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A new study led by MIT Sloan Prof. Andrew W. Lo finds that borrowing ideas and tools from the gaming community can improve online teaching techniques and improve learning outcomes for students.
