Large language models use a surprisingly simple mechanism to retrieve some stored knowledge
Researchers demonstrate a technique that can be used to probe a model to see what it knows about new subjects.
Researchers demonstrate a technique that can be used to probe a model to see what it knows about new subjects.
With help from a large language model, MIT engineers enabled robots to self-correct after missteps and carry on with their chores.
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.
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.
By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse.
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.