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Daniela Rus receives Bavarian Minister-President’s High-Tech Prize

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Autonomous vehicles, Awards, honors and fellowships, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Faculty, Human-computer interaction, MIT Schwarzman College of Computing, Robotics, School of Engineering

Daniela Rus, director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Panasonic Professor of Computer Science, has received the 2026 High-Tech Prize of the Bavarian Minister-President for her contributions to robotics, artificial intelligence, and autonomous systems. Awarded jointly by the Bavarian State Government and the Bavarian Academy of Sciences and Humanities, it is […]

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Following the questions where they lead

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer science and technology, Democracy, Electrical engineering and computer science (EECS), Faculty, government, Labor and jobs, Laboratory for Information and Decision Systems (LIDS), MIT Schwarzman College of Computing, Political science, Politics, Profile, Public health, School of Engineering, School of Humanities Arts and Social Sciences, Technology and society

Ever since she was a child playing on her family’s farmland in Wisconsin, Bailey Flanigan was guided by her own selective, yet wide-ranging, curiosity. Describing her young self as spirited and a bit unruly, she directed her energies to everything from building booby traps to doing experimental construction projects to exploring an intense interest in

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A better way to turn 2D designs into 3D models for rapid prototyping

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer modeling, Computer science and technology, Design, Machine Learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT-IBM Computing Research Lab, Research, School of Engineering, Systems design

Engineers often use vision-language models to produce new designs, such as for airplane or automobile components. To simulate how those components will perform in realistic situations, they’ll use tried-and-true computer-aided design (CAD) software to generate 3D models of those designs, which they can put through virtual crash or durability tests. Researchers from MIT and elsewhere have

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3 Questions: Neural transparency and the future of AI design

ai, AI (Artificial Intelligence), Algorithms, Apps, Artificial Intelligence, Computer science and technology, data, ethics, Faculty, Human-computer interaction, Interview, Machine Learning, Media Lab, Mental health, Research, Safety, School of Architecture and Planning, Technology and society

Millions of people are now designing their own personalized artificial intelligence companions, yet most have little idea how those creations will actually behave. In a new paper, MIT Media Lab Assistant Professor Pat Pataranutaporn and his graduate student researchers Anthony Baez and Sheer Karny introduce “neural transparency,” a tool that lets everyday users glimpse inside

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Helping AI models to meet the real world

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Business and management, Computer science and technology, data, Electrical engineering and computer science (EECS), Faculty, IDSS, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), MIT intellectual property, MIT Schwarzman College of Computing, Profile, Research, School of Engineering, Startups

Systems using artificial intelligence to enhance forecasting, planning, and decision-making in businesses have been proliferating in recent years, but in many cases, they lack the detailed, specific information about the organization itself, limiting the usefulness of those tools. Devavrat Shah, a principal investigator at MIT’s Laboratory for Information and Decision Systems (LIDS), faculty member with the

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New method aims to keep kids safe from illegal AI-generated content

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer science and technology, ethics, Human-computer interaction, Institute for Medical Engineering and Science (IMES), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Privacy, Public health, Research, School of Engineering

With the exploding popularity of generative artificial intelligence, many open-source models are now available online for anyone to adapt for their task, such as generating product renderings in a certain artistic style. But these models also find their way into the hands of nefarious actors who may optimize them to produce illegal content, like hate speech

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Q&A: What is agentic AI today, and what do we want it to be?

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Electrical engineering and computer science (EECS), Human-computer interaction, Interview, Machine Learning, MIT Schwarzman College of Computing, School of Engineering

The deployment of automated software systems called AI agents has recently exploded. A November 2025 report by MIT Sloan School of Management and Boston Consulting Group found that 35 percent of surveyed businesses had already deployed AI agents, while another 44 percent planned to implement agentic AI soon. To understand the fundamentals and potential impacts of these

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3 Questions: Beyond data-driven aesthetics

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“Beyond Data-Driven Aesthetics,” by MIT Architecture alumnus and researcher Alexandros Haridis, on view at the MIT Keller Gallery through June 30, examines 20th- and 21st-century efforts to transform computing into a medium for creative production and aesthetic judgment in architecture and the applied arts. Drawing on philosophy, mathematics, computer science, and design computation, the exhibition

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LLMs help robots understand vague instructions and focus on key details

Aeronautical and astronautical engineering, ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, automation, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Machine Learning, MIT Schwarzman College of Computing, Natural Language Processing, Research, Robotics, School of Engineering

Imagine working at a warehouse or office sometime in the near future, and you’re asked to help a new trainee learn the basics of their job. The catch: It’s a robot. To teach them, you might want to play a game of “show and tell” — that is, physically showing how to do something a

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Improving the speed and energy-efficiency of AI agents

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Defense Advanced Research Projects Agency (DARPA), Electrical engineering and computer science (EECS), Electronics, Machine Learning, MIT Schwarzman College of Computing, Research, School of Engineering, Software, Sustainability

Agentic workflows are artificial intelligence-powered software systems that chain together multiple models and external tools to tackle complicated tasks, like analyzing a video and answering questions about it.But the way these highly fragmented systems are designed and deployed often causes inefficiencies that can lead to wasted computation, energy, and cost. To improve efficiency, researchers from MIT

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