Engineering household robots to have a little common sense
With help from a large language model, MIT engineers enabled robots to self-correct after missteps and carry on with their chores.
With help from a large language model, MIT engineers enabled robots to self-correct after missteps and carry on with their chores.
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.
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 computing 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.