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.

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.

The team used machine learning to analyze satellite and roadside images of areas where small farms predominate and agricultural data are sparse.

Researchers developed a simple yet effective solution for a puzzling problem that can worsen the performance of large language models such as ChatGPT.

Exploiting the symmetry within datasets, MIT researchers show, can decrease the amount of data needed for training neural networks.

MIT CSAIL researchers develop advanced machine-learning models that outperform current methods in detecting pancreatic ductal adenocarcinoma.

PhD students interning with the MIT-IBM Watson AI Lab look to improve natural language usage.