MIT researchers propose “PEDS” method for developing models of complex physical systems in mechanics, optics, thermal transport, fluid dynamics, physical chemistry, climate, and more.
A new study finds that language regions in the left hemisphere light up when reading uncommon sentences, while straightforward sentences elicit little response.
MIT community members made headlines with key research advances and their efforts to tackle pressing challenges.
Using generative AI, MIT chemists created a model that can predict the structures formed when a chemical reaction reaches its point of no return.
Study shows computational models trained to perform auditory tasks display an internal organization similar to that of the human auditory cortex.
During the last week of November, MIT hosted symposia and events aimed at examining the implications and possibilities of generative AI.
By analyzing bacterial data, researchers have discovered thousands of rare new CRISPR systems that have a range of functions and could enable gene editing, diagnostics, and more.
Two studies find “self-supervised” models, which learn about their environment from unlabeled data, can show activity patterns similar to those of the mammalian brain.
Researchers coaxed a family of generative AI models to work together to solve multistep robot manipulation problems.
Inspired by physics, a new generative model PFGM++ outperforms diffusion models in image generation.
