A simpler method for learning to control a robot
Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.
Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.
A new technique helps a nontechnical user understand why a robot failed, and then fine-tune it with minimal effort to perform a task effectively.
EECS professor appointed to new professorship in the MIT Schwarzman College of Computing.
PIGINet leverages machine learning to streamline and enhance household robots' task and motion planning, by assessing and filtering feasible solutions in complex environments.
Researchers create a privacy technique that protects sensitive data while maintaining a machine-learning model’s performance.
“FrameDiff” is a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy.
Study shows moving can help foster a more robust social network, by strengthening “long ties” with others.
Prestigious awards recognize community support of MIT’s goals, values, and mission.
Luca Carlone and Jonathan How of MIT LIDS discuss how future robots might perceive and interact with their environment.
PhD student Will Sussman studies wireless networks while fostering community networks.
This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development.
BioAutoMATED, an open-source, automated machine-learning platform, aims to help democratize artificial intelligence for research labs.
A new technique produces perovskite nanocrystals right where they’re needed, so the exceedingly delicate materials can be integrated into nanoscale devices.
A new computational method facilitates the dense placement of objects inside a rigid container.
Training artificial neural networks with data from real brains can make computer vision more robust.