AI agents help explain other AI systems
MIT researchers introduce a method that uses artificial intelligence to automate the explanation of complex neural networks.
MIT researchers introduce a method that uses artificial intelligence to automate the explanation of complex neural networks.
A new study finds that language regions in the left hemisphere light up when reading uncommon sentences, while straightforward sentences elicit little response.
Kwesi Afrifa, a senior majoring in urban planning and computer science, wants to create cultural hubs that are inviting to everyone.
Swallowing the device before a meal could create a sense of fullness, tricking the brain into thinking it’s time to stop eating.
Master’s students Irene Terpstra ’23 and Rujul Gandhi ’22 use language to design new integrated circuits and make it understandable to robots.
A cheaper water desalination device, a wearable ultrasound scanner, and a new kind of supercapacitor were some of MIT News’ most popular articles.
Top Institute stories dealt with a presidential inauguration, international accolades for faculty and students, “Dialogues Across Difference,” new and refreshed community spaces, and more.
MIT community members made headlines with key research advances and their efforts to tackle pressing challenges.
The highly influential professor served for 25 years as executive officer of the Department of Electrical Engineering and Computer Science.
These compounds can kill methicillin-resistant Staphylococcus aureus (MRSA), a bacterium that causes deadly infections.
Through the GradEL program, Lieutenant Asia Allison is developing a deeper understanding of her own background and profile as a leader.
MIT researchers find that in mice and human cell cultures, lipid nanoparticles can deliver a potential therapy for inflammation in the brain, a prominent symptom in Alzheimer’s.
“Minimum viewing time” benchmark gauges image recognition complexity for AI systems by measuring the time needed for accurate human identification.
Using generative AI, MIT chemical engineers and chemists created a model that can predict the structures formed when a chemical reaction reaches its point of no return.
Six teams of mechanical engineering students pitched “wild” products during the annual capstone course prototype launch event.