Computer Science and Artificial Intelligence Laboratory (CSAIL)
Computer Science and Artificial Intelligence Laboratory (CSAIL)

A faster way to teach a robot

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.

Armando Solar-Lezama named inaugural Distinguished College of Computing Professor

EECS professor appointed to new professorship in the MIT Schwarzman College of Computing.

AI helps household robots cut planning time in half

PIGINet leverages machine learning to streamline and enhance household robots’ task and motion planning, by assessing and filtering feasible solutions in complex environments.

AI helps household robots cut planning time in half

PIGINet leverages machine learning to streamline and enhance household robots’ task and motion planning, by assessing and filtering feasible solutions in complex environments.

A new way to look at data privacy

Researchers create a privacy technique that protects sensitive data while maintaining a machine-learning model’s performance.

Generative AI imagines new protein structures

MIT researchers develop “FrameDiff,” a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy.

Learning the language of molecules to predict their properties

This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development.

Educating national security leaders on artificial intelligence

Experts from MIT’s School of Engineering, Schwarzman College of Computing, and Sloan Executive Education educate national security leaders in AI fundamentals.

Researchers teach an AI to write better chart captions

A new dataset can help scientists develop automatic systems that generate richer, more descriptive captions for online charts.

Computer vision system marries image recognition and generation

MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single system.