MIT News about AI

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• Media Advisory: MIT to establish regional quantum hub

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

• Technology usually creates jobs for young, skilled workers. Will AI do the same?

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

• Building AI models that understand chemical principles

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

• Justin Solomon appointed associate dean of engineering education

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

• 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.

• Bringing AI-driven protein-design tools to biologists everywhere

  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.

• Human-machine teaming dives underwater

  Researchers are developing hardware and algorithms to improve collaboration between divers and autonomous underwater vehicles engaged in maritime missions.

• Q&A: MIT SHASS and the future of education in the age of AI

  As the School of Humanities, Arts, and Social Sciences marks 75 years, Dean Agustín Rayo reflects on how AI is reshaping higher education and why SHASS disciplines continue to be central to MIT’s mission.

• A philosophy of work

  As the NC Ethics of Technology Postdoctoral Fellow, Michal Masny is advancing dialogue, teaching, and research into the social and ethical dimensions of new computing technologies.

• New technique makes AI models leaner and faster while they’re still learning

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

• Sixteen new START.nano companies are developing hard-tech solutions with the support of MIT.nano

  Startup accelerator program grows to over 30 companies, almost half of them with MIT pedigrees.

• Helping data centers deliver higher performance with less hardware

  Researchers developed a system that intelligently balances workloads to improve the efficiency of flash storage hardware in a data center.

• Working to advance the nuclear renaissance

  Dean Price, assistant professor in the Department of Nuclear Science and Engineering, sees a bright future for nuclear power, and believes AI can help us realize that vision.

• Evaluating the ethics of autonomous systems

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

• Preview tool helps makers visualize 3D-printed objects

  By quickly generating aesthetically accurate previews of fabricated objects, the VisiPrint system could make prototyping faster and less wasteful.

• MIT researchers use AI to uncover atomic defects in materials

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