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.
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.
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.
From alternative fuels and next-gen batteries to compact fusion and carbon capture, here is a sampling of clean tech companies with ties to MIT.
Integrating robots into a manufacturing system is often prohibitively expensive. A new approach could change that.
Car owners, on average, would want $3,300 to give up ownership and use of their vehicle for a month during the pandemic.
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
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.
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.
