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.
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.
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.
Integrating robots into a manufacturing system is often prohibitively expensive. A new approach could change that.
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.
Companies make common data science mistakes. Here’s an expert’s guide to what they are and how to avoid them.
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
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.
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.
Artificial intelligence was top of mind at the 2025 MIT Sloan Reunion. In two talks, MIT alumni went to the furthest reaches of possibility with AI, both in terms of its capacity to do harm and its potential to solve existence's toughest problems.
