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.
MIT Schwarzman College of Computing
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.
3 Questions: Honing robot perception and mapping
Luca Carlone and Jonathan How of MIT LIDS discuss how future robots might perceive and interact with their environment.
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.
MIT scientists build a system that can generate AI models for biology research
BioAutoMATED, an open-source, automated machine-learning platform, aims to help democratize artificial intelligence for research labs.
When computer vision works more like a brain, it sees more like people do
Training artificial neural networks with data from real brains can make computer vision more robust.
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.
MIT-Pillar AI Collective announces first seed grant recipients
Six teams conducting research in AI, data science, and machine learning receive funding for projects that have potential commercial applications.