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.

Researchers have developed a wearable ‘smart choker’ that uses a combination of flexible electronics and artificial intelligence techniques to allow people

“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.

Listening in on neural activity is a promising way of restoring the ability to communicate for people whose bodies no longer can. Artificial neural networks are the key middleman in the process.

The software tool NeuroTrALE is designed to quickly and efficiently process large amounts of brain imaging data semi-automatically.