MIT Schwarzman College of Computing
MIT Schwarzman College of Computing

Helping AI models to meet the real world

Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources.

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.

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

Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.

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.

Toward a future that preserves benefits of neurotechnology for all

PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.

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.

Inaugural Music Technology Research Showcase celebrates work of new graduate program’s initial students

Associate Professor Anna Huang delivers the keynote address, “In Search of Human-AI Resonance,” to a capacity crowd.

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.