AI agents help explain other AI systems
MIT researchers introduce a method that uses artificial intelligence to automate the explanation of complex neural networks.
School of Engineering
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.
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.
MIT in the media: 2023 in review
MIT community members made headlines with key research advances and their efforts to tackle pressing challenges.
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.
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.