MIT News Artificial Intelligence

With $25 million investment from the Commonwealth of Massachusetts, MIT to build a new shared-use facility to serve as a statewide quantum toolbox.

A new study of the postwar U.S. shows which kinds of workers historically filled new tech-enabled jobs.

Connor Coley works at the interface of chemistry and machine learning, to discover and design new drug compounds.

MIT faculty member in electrical engineering and computer science to focus on innovation in engineering education and new pedagogical approaches.

The prestigious fellowship funds graduate studies at Stanford University.

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

Dimitris Bertsimas and Megan Mitchell discuss the motivation behind Universal Learning, and what sets the new MIT Open Learning educational initiative apart.

MIT economists found US companies tend to target employees earning a “wage premium,” which increases inequality but not necessarily productivity.

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

MIT senior Olivia Honeycutt investigates how the ways we communicate can shape our views of the world.

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.

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.

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.

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.

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.