Using ideas from game theory to improve the reliability of language models
A new “consensus game,” developed by MIT CSAIL researchers, elevates AI’s text comprehension and generation skills.
Machine learning
A better way to control shape-shifting soft robots
A new algorithm learns to squish, bend, or stretch a robot’s entire body to accomplish diverse tasks like avoiding obstacles or retrieving items.
President Sally Kornbluth and OpenAI CEO Sam Altman discuss the future of AI
The conversation in Kresge Auditorium touched on the promise and perils of the rapidly evolving technology.
HPI-MIT design research collaboration creates powerful teams
Together, the Hasso Plattner Institute and MIT are working toward novel solutions to the world’s problems as part of the Designing for Sustainability research program.
Creating bespoke programming languages for efficient visual AI systems
Associate Professor Jonathan Ragan-Kelley optimizes how computer graphics and images are processed for the hardware of today and tomorrow.
An AI dataset carves new paths to tornado detection
TorNet, a public artificial intelligence dataset, could help models reveal when and why tornadoes form, improving forecasters' ability to issue warnings.
MIT faculty, instructors, students experiment with generative AI in teaching and learning
At MIT’s Festival of Learning 2024, panelists stressed the importance of developing critical thinking skills while leveraging technologies like generative AI.
Mapping the brain pathways of visual memorability
For the first time, researchers use a combination of MEG and fMRI to map the spatio-temporal human brain dynamics of a visual image being recognized.
This tiny chip can safeguard user data while enabling efficient computing on a smartphone
Researchers have developed a security solution for power-hungry AI models that offers protection against two common attacks.
To build a better AI helper, start by modeling the irrational behavior of humans
A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals.