Complex, unfamiliar sentences make the brain’s language network work harder
A new study finds that language regions in the left hemisphere light up when reading uncommon sentences, while straightforward sentences elicit little response.
Machine learning
Leveraging language to understand machines
Master's students Irene Terpstra ’23 and Rujul Gandhi ’22 use language to design new integrated circuits and make it understandable to robots.
Using AI, MIT researchers identify a new class of antibiotic candidates
These compounds can kill methicillin-resistant Staphylococcus aureus (MRSA), a bacterium that causes deadly infections.
Image recognition accuracy: An unseen challenge confounding today’s AI
“Minimum viewing time” benchmark gauges image recognition complexity for AI systems by measuring the time needed for accurate human identification.
Computational model captures the elusive transition states of chemical reactions
Using generative AI, MIT chemists created a model that can predict the structures formed when a chemical reaction reaches its point of no return.
Three MIT students selected as inaugural MIT-Pillar AI Collective Fellows
The graduate students will aim to commercialize innovations in AI, machine learning, and data science.
Deep neural networks show promise as models of human hearing
Study shows computational models trained to perform auditory tasks display an internal organization similar to that of the human auditory cortex.
Closing the design-to-manufacturing gap for optical devices
A new method enables optical devices that more closely match their design specifications, boosting accuracy and efficiency.
A computer scientist pushes the boundaries of geometry
Justin Solomon applies modern geometric techniques to solve problems in computer vision, machine learning, statistics, and beyond.
MIT Generative AI Week fosters dialogue across disciplines
During the last week of November, MIT hosted symposia and events aimed at examining the implications and possibilities of generative AI.