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.
Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources.
Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.
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.
In a new Keller Gallery exhibition, Alexandros Haridis SM ’17, PhD ’22 traces centuries of ideas about aesthetic judgment and explores how design can make complex computational systems visible.
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.
A new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications.
During the AI and Society Forum, leading MIT researchers examined critical questions about AI’s influence on employment and democracy.
Researchers combined an efficient algorithm with dedicated hardware to rapidly generate 3D maps for navigation using minimal memory and power.
Researchers show that for certain kinds of games, an overlooked class of algorithms performs much better than expected.
A new spatial memory system for robots efficiently captures details about the objects they see while exploring their environment.