Most antibiotics target metabolically active bacteria, but with artificial intelligence, researchers can efficiently screen compounds that are lethal to dormant microbes.
MIT researchers plan to search for proteins that could be used to measure electrical activity in the brain.
The 16 finalists — representing every school at MIT — will explore generative AI’s impact on privacy, art, drug discovery, aging, and more.
Researchers demonstrate a technique that can be used to probe a model to see what it knows about new subjects.
Novel method makes tools like Stable Diffusion and DALL-E-3 faster by simplifying the image-generating process to a single step while maintaining or enhancing image quality.
FeatUp, developed by MIT CSAIL researchers, boosts the resolution of any deep network or visual foundation for computer vision systems.
MIT CSAIL postdoc Nauman Dawalatabad explores ethical considerations, challenges in spear-phishing defense, and the optimistic future of AI-created voices across various sectors.
By enabling models to see the world more like humans do, the work could help improve driver safety and shed light on human behavior.
MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.
Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
