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.
Researchers developed a simple yet effective solution for a puzzling problem that can worsen the performance of large language models such as ChatGPT.
MIT CSAIL researchers develop advanced machine-learning models that outperform current methods in detecting pancreatic ductal adenocarcinoma.
A multimodal system uses models trained on language, vision, and action data to help robots develop and execute plans for household, construction, and manufacturing tasks.
This new method draws on 200-year-old geometric foundations to give artists control over the appearance of animated characters.
Using generative AI, MIT chemists created a model that can predict the structures formed when a chemical reaction reaches its point of no return.
Using machine learning, the computational method can provide details of how materials work as catalysts, semiconductors, or battery components.
A new, data-driven approach could lead to better solutions for tricky optimization problems like global package routing or power grid operation.
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
Computer vision enables contact-free 3D printing, letting engineers print with high-performance materials they couldn’t use before.