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

The system analyzes the likelihood that an attacker could thwart a certain security scheme to steal secret information.

Six teams conducting research in AI, data science, and machine learning receive funding for projects that have potential commercial applications.

MIT researchers characterize gene expression patterns for 22,500 brain vascular cells across 428 donors, revealing insights for Alzheimer’s onset and potential treatments.

By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.

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.

The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.

A new multimodal technique blends major self-supervised learning methods to learn more similarly to humans.

Using insights into how people intuit others’ emotions, researchers have designed a model that approximates this aspect of human social intelligence.

Researchers develop an algorithm that decides when a “student” machine should follow its teacher, and when it should learn on its own.