Computer Science and Artificial Intelligence Laboratory (CSAIL)
Computer Science and Artificial Intelligence Laboratory (CSAIL)

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

“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.

Tiny robot boats build floating structures

MIT researchers developed FloatForm, a swarm of small aquatic robots that snap together like ants forming a raft, assembling into reconfigurable structures on the water.

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

Computer scientist Phillip Isola cuts through the hype to explain how AI agents work and what the future might hold for this rapidly advancing technology.

LLMs help robots understand vague instructions and focus on key details

To help robots do chores in places like homes and factories, a new approach from MIT uses one language model to clarify users’ instructions, then another to ignore irrelevant info.

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

“Scientific American” showcases the history and future of America’s scientific engine, highlighting promising young scientists and icons at MIT and beyond.

Improving the speed and energy-efficiency of AI agents

A new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications.

Exploring the societal impacts of AI

During the AI and Society Forum, leading MIT researchers examined critical questions about AI’s influence on employment and democracy.

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

MIT researchers provide a major upgrade to the nearly century-old idea of random utility models.

MIT affiliates win 2026 Hertz Foundation Fellowships

The fellowships in applied sciences, engineering, and mathematics recognize doctoral students who are pursuing solutions to the most pressing challenges in science and technology.

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

MIT researchers use the classic game as a test bed for AI agents, finding a small AI model can outperform the biggest ones at 1 percent of the cost.