Robotic lab sets up and runs optics experiments on demand
The autonomous system could speed up testing of high-tech materials for applications such as solar cells, sensors, video displays, and quantum technologies.
The autonomous system could speed up testing of high-tech materials for applications such as solar cells, sensors, video displays, and quantum technologies.
The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.
Atlas Building Composites is commercializing MIT research to turn plastic waste into parts for buildings and other infrastructure.
The work is part of a multiyear effort to develop a distributed sensor network for relaying data collected from this critical region.
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.
The new, more intuitive system could speed up the training process for excavator operators.
MIT engineers introduce an adaptive physical therapy system that uses generative AI to learn from physical therapists and interactively support stroke patients.
Director of CSAIL and MIT professor honored for her contributions to robotics, artificial intelligence, and autonomous systems.
MIT students designed, built, and tested a jet engine with AI copilots, assessing AI’s usefulness in developing high-performance aerospace systems.
“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.
MIT engineers’ design could lead to a new class of aerial-aquatic vehicles for ocean exploration.
MIT researchers developed FloatForm, a swarm of small aquatic robots that snap together like ants forming a raft, assembling into reconfigurable structures on the water.
Three MIT teams took five top awards in the 2026 NASA RASC-AL Competition for designing critical elements for the moon base and future missions to Mars.
To help robots do chores in places like homes and factories, a new approach from MIT uses one language model to clarify users’ instructions, then another to ignore irrelevant info.
During the AI and Society Forum, leading MIT researchers examined critical questions about AI’s influence on employment and democracy.