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.

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

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.

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

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.