By enabling users to chat with an older version of themselves, Future You is aimed at reducing anxiety and guiding young people to make better choices.

New dataset of “illusory” faces reveals differences between human and algorithmic face detection, links to animal face recognition, and a formula predicting where people most often perceive faces.

A new method called Clio enables robots to quickly map a scene and identify the items they need to complete a given set of tasks.

The technique leverages quantum properties of light to guarantee security while preserving the accuracy of a deep-learning model.

MIT researchers speed up a novel AI-based estimator for medication manufacturing by 60 times.

By analyzing X-ray crystallography data, the model could help researchers develop new materials for many applications, including batteries and magnets.

Researchers find large language models make inconsistent decisions about whether to call the police when analyzing surveillance videos.

“Co-LLM” algorithm helps a general-purpose AI model collaborate with an expert large language model by combining the best parts of both answers, leading to more factual responses.

“ScribblePrompt” is an interactive AI framework that can efficiently highlight anatomical structures across different medical scans, assisting medical workers to delineate regions of interest and abnormalities.

Researchers developed an easy-to-use tool that enables an AI practitioner to find data that suits the purpose of their model, which could improve accuracy and reduce bias.