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.
Algorithms
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.
Day of AI curriculum meets the moment
Global participation in MIT RAISE’s free K-12 program more than doubles in its second year.
If art is how we express our humanity, where does AI fit in?
MIT postdoc Ziv Epstein SM ’19, PhD ’23 discusses issues arising from the use of generative AI to make art and other media.
Bringing the social and ethical responsibilities of computing to the forefront
The inaugural SERC Symposium convened experts from multiple disciplines to explore the challenges and opportunities that arise with the broad applicability of computing in many aspects of society.
MIT researchers make language models scalable self-learners
The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.
Scaling audio-visual learning without labels
A new multimodal technique blends major self-supervised learning methods to learn more similarly to humans.
Driven to driverless
Cindy Alejandra Heredia’s journey from Laredo, Texas, took her to leading the MIT autonomous vehicle team and to an MBA from MIT Sloan.
A more effective way to train machines for uncertain, real-world situations
Researchers develop an algorithm that decides when a “student” machine should follow its teacher, and when it should learn on its own.
Probabilistic AI that knows how well it’s working
It’s more important than ever for artificial intelligence to estimate how accurately it is explaining data.