Two from MIT named 2026 Knight-Hennessy Scholars
The prestigious fellowship funds graduate studies at Stanford University.
Q&A: Expanding MIT’s global reach through Universal Learning
Dimitris Bertsimas and Megan Mitchell discuss the motivation behind Universal Learning, and what sets the new MIT Open Learning educational initiative apart.
Universal AI is “a pathway to AI fluency that’s accessible and approachable to anyone, anywhere”
New AI education program from MIT Open Learning debuts with AI-powered personalization and a free introductory course for learners everywhere.
Study: Firms often use automation to control certain workers’ wages
MIT economists found US companies tend to target employees earning a “wage premium,” which increases inequality but not necessarily productivity.
Games 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.
Beacon Biosignals is mapping the brain during sleep
Founded by Jake Donoghue PhD ’19 and former MIT researcher Jarrett Revels, the company is creating an AI-driven platform to help diagnose and treat disease.
Improving understanding with language
MIT senior Olivia Honeycutt investigates how the ways we communicate can shape our views of the world.
Making the case for curiosity-driven science
President Sally Kornbluth spoke in front of a packed crowd about growing challenges to the U.S. research ecosystem as funding for America’s top research universities becomes increasingly strained.
Solving the “Whac-a-mole dilemma”: A smarter way to debias AI vision models
A new debiasing technique called WRING avoids creating or amplifying biases that can occur with existing debiasing approaches.
The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing
Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.
Enabling privacy-preserving AI training on everyday devices
A new method could bring more accurate and efficient AI models to high-stakes applications like health care and finance, even in under-resourced settings.
A faster way to estimate AI power consumption
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.
MIT scientists build the world’s largest collection of Olympiad-level math problems, and open it to everyone
New dataset of 30,000-plus competition math problems from 47 countries gives AI researchers a harder test — and students worldwide a better training ground.
Teaching AI models to say “I’m not sure”
A new training method improves the reliability of AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.
Jacob Andreas and Brett McGuire named Edgerton Award winners
The associate professors of EECS and chemistry, respectively, are honored for exceptional contributions to teaching, research, and service at MIT.