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Crowdsourcing to better forecast drug approvals
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.
Practical ways to tackle manufacturing’s labor crunch
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A panel of practitioners explores how to solve worker shortages and offers three best practices for success.
How smaller firms can integrate collaborative robots
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Integrating robots into a manufacturing system is often prohibitively expensive. A new approach could change that.
10 big data blunders to avoid
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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.
Using data science to forecast clinical trial outcomes
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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
Robots could give humans ‘superpowers’
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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.
Why We're Different
Here, leadership is not a title or a person. It’s a process. We begin with self-awareness, then combine science-based frameworks, personalized coaching, and practical applications to develop leaders.
Our Impact
Leadership at MIT is not a title or a person. It’s a process. We begin with self-awareness and combine science-based frameworks, personalized coaching, and practical applications to develop leaders.
Machine learning, explained
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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.