New algorithm unlocks high-resolution insights for computer vision
FeatUp, developed by MIT CSAIL researchers, boosts the resolution of any deep network or visual foundation for computer vision systems.
FeatUp, developed by MIT CSAIL researchers, boosts the resolution of any deep network or visual foundation for computer vision systems.
Joining three teams backed by a total of $75 million, MIT researchers will tackle some of cancer’s toughest challenges.
MIT CSAIL postdoc Nauman Dawalatabad explores ethical considerations, challenges in spear-phishing defense, and the optimistic future of AI-created voices across various sectors.
Software allows scientists to model shapeshifting proteins in native cellular environments.
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.
Lightmatter, founded by three MIT alumni, is using photonic technologies to reinvent how chips communicate and calculate.
Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse.
After acquiring data science and AI skills from MIT, Jospin Hassan shared them with his community in the Dzaleka Refugee Camp in Malawi and built pathways for talented learners.
MIT LIDS awarded funding from the Appalachian Regional Commission as part of a multi-state collaborative project to model and test new smart grid technologies for use in rural areas.
Alumni-founded Pienso has developed a user-friendly AI builder so domain experts can build solutions without writing any code.
Adaptive smart glove from MIT CSAIL researchers can send tactile feedback to teach users new skills, guide robots with more precise manipulation, and help train surgeons and pilots.
Using a machine-learning algorithm, researchers can predict interactions that could interfere with a drug’s effectiveness.
MIT engineers developed a tag that can reveal with near-perfect accuracy whether an item is real or fake. The key is in the glue on the back of the tag.