New AI model could streamline operations in a robotic warehouse
By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse.
By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse.
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.
This new method draws on 200-year-old geometric foundations to give artists control over the appearance of animated characters.
A new method enables optical devices that more closely match their design specifications, boosting accuracy and efficiency.
Justin Solomon applies modern geometric techniques to solve problems in computer vision, machine learning, statistics, and beyond.
MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.
A new, data-driven approach could lead to better solutions for tricky optimization problems like global package routing or power grid operation.
Rodney Brooks, co-founder of iRobot, kicks off an MIT symposium on the promise and potential pitfalls of increasingly powerful AI tools like ChatGPT.
Human Guided Exploration (HuGE) enables AI agents to learn quickly with some help from humans, even if the humans make mistakes.