Computer Science and Artificial Intelligence Laboratory (CSAIL)

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AI agents create virtual playgrounds to help robots get crucial training data

3-D, ai, AI (Artificial Intelligence), Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Robotics, School of Engineering, Simulation

Robots walking down the street, surrounded by astounded onlookers, is an increasingly common sight. But these machines aren’t yet the do-it-all assistants you’d want working in a kitchen or factory, and a major bottleneck is data. Much like humans, robots learn best by experience. The challenge is that it’s labor-intensive and time-consuming to physically teach […]

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Tiny robot boats build floating structures

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Most people think of the waterfront as the edge of the city. A team of MIT researchers sees it as a dynamic, Lego-like construction site.Their new system, called “FloatForm,” is a swarm of small square robotic boats that assemble themselves into larger structures on the water, break apart, and reassemble into something new, all with

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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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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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MIT in the media: Exploring how curiosity-driven science is an essential ingredient in America’s success

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Over the past 80 years, America’s bold, sustained investment in scientific research, and the discoveries, ideas and innovations that flowed from it made America a world leader. The nation’s scientific leadership has been essential to our shared prosperity and national security, and delivered real benefits for all Americans.On June 16, Scientific American released a special section,

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Improving the speed and energy-efficiency of AI agents

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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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Exploring the societal impacts of AI

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At the recent AI and Society Forum at MIT, experts from across the Institute discussed the potential benefits and dangers of technological innovation on labor, the nature of work, civil discourse, election administration, and other topics.The event featured individual research presentations and panel discussions, as well as a musical performance exploring the use of generative artificial intelligence

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When it comes to predicting people’s preferences, it pays to consider “the power of three”

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In his 1927 paper, “A law of comparative judgment,” the American psychologist L. L. Thurstone proposed that when people select one option among multiple alternatives, they are picking the one that has the highest value to them, even though they cannot assign a particular number to that choice. Thurstone was a pioneer of “psychometrics” — a

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MIT affiliates win 2026 Hertz Foundation Fellowships

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The Hertz Foundation announced that it awarded 2026 fellowships to three current MIT students as well as an incoming graduate student. They are: Annika Marschner, Alvin Q. Meng, Zachary S. Siegel, and Matthew Wanta.The prestigious science and technology award provides each recipient with five years of financial support — a stipend and full tuition equivalent — which gives them

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Teaching AI agents to ask better questions by playing “Battleship”

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In 2026, the hype for artificial intelligence agents is louder than ever before. These semi-autonomous programs can “think” and execute well-defined tasks in areas like customer service and software development, typically using language models (LMs). But fields like medical diagnosis and scientific discovery require them to inquire about a vast range of solutions in uncertain

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