Researchers are developing hardware and algorithms to improve collaboration between divers and autonomous underwater vehicles engaged in maritime missions.

Researchers use control theory to shed unnecessary complexity from AI models during training, cutting compute costs without sacrificing performance.

Startup accelerator program grows to over 30 companies, almost half of them with MIT pedigrees.

Researchers developed a system that intelligently balances workloads to improve the efficiency of flash storage hardware in a data center.

By quickly generating aesthetically accurate previews of fabricated objects, the VisiPrint system could make prototyping faster and less wasteful.

This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.

This new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.

With this new technique, a robot could more accurately detect hidden objects or understand an indoor scene using reflected Wi-Fi signals.

An AI control system co-developed by SMART researchers enables soft robotic arms to learn a broad set of motions once and adapt instantly to changing conditions without retraining.