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.
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.
MIT researchers’ approach captures subtle atomic patterns, improving predictions of material properties.
Leaders, faculty across MIT discuss fostering innovation and talent in Greater Boston in special series of articles published alongside the outlet's annual list of 'Tech Power Players'
A new spatial memory system for robots efficiently captures details about the objects they see while exploring their environment.
Researchers establish key insights for reading and writing information for quantum sensing, communication, computing, and control.
MIT researchers provide a major upgrade to the nearly century-old idea of random utility models.
The fellowships in applied sciences, engineering, and mathematics recognize doctoral students who are pursuing solutions to the most pressing challenges in science and technology.
A new kernel called Fractal gives researchers a cleaner view of what’s happening inside a processor, and has already surfaced previously unknown behavior in Apple’s M1.
Founded by two researchers from MIT, Ferveret reduces the amount of energy and water required to cool the chips that power AI.
IAIFI enters its second phase with increased funding, broader ambitions, and a growing community at the frontier of AI and fundamental physics.