MIT scientists unveil the first open-source simulation engine capable of constructing realistic environments for deployable training and testing of autonomous vehicles.

Pinpointing risks can also help businesses save money as they become more resilient.

Jonathan Weissman and collaborators used their single-cell sequencing tool Perturb-seq on every expressed gene in the human genome, linking each to its job in the cell.

A machine-learning method imagines what a sentence visually looks like, to situate and ground its semantics in the real world, improving translation, like humans can.

Researchers have created prototypes that enable screen-reader users to quickly and easily navigate through multiple levels of information in an online chart.

A distributed sensor network may help researchers identify the physical processes contributing to diminishing sea ice in the planet’s fastest-warming region.

Explanation methods that help users determine whether to trust machine-learning model predictions can be less accurate for disadvantaged subgroups, a new study finds.

Study shows AI can identify self-reported race from medical images that contain no indications of race detectable by human experts.

Searchable tool reveals more than 90,000 known materials with electronic properties that remain unperturbed in the face of disruption.

Graduate student Sarah Cen explores the interplay between humans and artificial intelligence systems, to help build accountability and trust.