Computer science and technology
Computer science and technology

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.

A crossroads for computing at MIT

The MIT Schwarzman College of Computing building will form a new cluster of connectivity across a spectrum of disciplines in computing and artificial intelligence.

New AI method captures uncertainty in medical images

By providing plausible label maps for one medical image, the Tyche machine-learning model could help clinicians and researchers capture crucial information.

A faster, better way to prevent an AI chatbot from giving toxic responses

Researchers create a curious machine-learning model that finds a wider variety of prompts for training a chatbot to avoid hateful or harmful output.

A new computational technique could make it easier to engineer useful proteins

MIT researchers plan to search for proteins that could be used to measure electrical activity in the brain.

Second round of seed grants awarded to MIT scholars studying the impact and applications of generative AI

The 16 finalists — representing every school at MIT — will explore generative AI’s impact on privacy, art, drug discovery, aging, and more.

Large language models use a surprisingly simple mechanism to retrieve some stored knowledge

Researchers demonstrate a technique that can be used to probe a model to see what it knows about new subjects.

Engineering household robots to have a little common sense

With help from a large language model, MIT engineers enabled robots to self-correct after missteps and carry on with their chores.