AI model speeds up high-resolution computer vision
The system could improve image quality in video streaming or help autonomous vehicles identify road hazards in real-time.
The system could improve image quality in video streaming or help autonomous vehicles identify road hazards in real-time.
“Lightning” system connects photons to the electronic components of computers using a novel abstraction, creating the first photonic computing prototype to serve real-time machine-learning inference requests.
A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds.
With a new technique, a robot can reason efficiently about moving objects using more than just its fingertips.
MIT system demonstrates greater than 100-fold improvement in energy efficiency and a 25-fold improvement in compute density compared with current systems.
MIT researchers investigate the causes of health-care disparities among underrepresented groups.
The challenge involves than just a blurry JPEG. Fixing motion artifacts in medical imaging requires a more sophisticated approach.
A new study bridging neuroscience and machine learning offers insights into the potential role of astrocytes in the human brain.
“PhotoGuard,” developed by MIT CSAIL researchers, prevents unauthorized image manipulation, safeguarding authenticity in the era of advanced generative models.
Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.