New method enables AI for safety-critical situations
The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.
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Laboratory for Information and Decision Systems (LIDS)
The benefits of medical AI assistance vary based on user expertise
Study finds non-experts deferred to LLM-based diagnostic assistance, even when it was wrong, while clinicians caught AI errors.
Read MoreAlexander Rakhlin named director of the MIT Statistics and Data Science Center
An expert in machine learning, statistics, and computation, Rakhlin succeeds Professor Ankur Moitra.
Read MoreProfessor Emeritus Dimitri Bertsekas, influential computer scientist and prolific author, dies at 83
Known for his clear and elegant writing style, Bertsekas shaped fields from control and optimization to large-scale computation and artificial intelligence.
Read MoreFollowing the questions where they lead
Assistant Professor Bailey Flanigan has arrived at complex computational methods for helping democracy thrive.
Read MoreHelping AI models to meet the real world
Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources.
Read MoreNew method aims to keep kids safe from illegal AI-generated content
Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.
Read MoreNew chip could help tiny robots traverse complex environments
Researchers combined an efficient algorithm with dedicated hardware to rapidly generate 3D maps for navigation using minimal memory and power.
Read MoreGames people — and machines — play: Untangling strategic reasoning to advance AI
Assistant Professor Gabriele Farina mines the foundations of decision-making in complex multi-agent scenarios.
Read MoreA new debiasing technique called WRING avoids creating or amplifying biases that can occur with existing debiasing approaches.
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