New AI education program from MIT Open Learning debuts with AI-powered personalization and a free introductory course for learners everywhere.

Assistant Professor Gabriele Farina mines the foundations of decision-making in complex multi-agent scenarios.

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.

A new debiasing technique called WRING avoids creating or amplifying biases that can occur with existing debiasing approaches.

Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.

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.

The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.

A new training method improves the reliability of AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.

The associate professors of EECS and chemistry, respectively, are honored for exceptional contributions to teaching, research, and service at MIT.

Founded by Tristan Bepler PhD ’20 and former MIT professor Tim Lu PhD ’07, OpenProtein.AI offers researchers open-source models and other tools for protein engineering.

Researchers use control theory to shed unnecessary complexity from AI models during training, cutting compute costs without sacrificing performance.

MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.

A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.