Making sense of all things data
Data, and more specifically using data, is not a new concept, but it remains an elusive one. It comes with terms like “the internet of things” (IoT) and “the cloud,”…
Data
3 Questions: Honing robot perception and mapping
Walking to a friend’s house or browsing the aisles of a grocery store might feel like simple tasks, but they in fact require sophisticated capabilities. That's because humans are able…
Learning the language of molecules to predict their properties
Discovering new materials and drugs typically involves a manual, trial-and-error process that can take decades and cost millions of dollars. To streamline this process, scientists often use machine learning to…
Educating national security leaders on artificial intelligence
Understanding artificial intelligence and how it relates to matters of national security has become a top priority for military and government leaders in recent years. A new three-day custom program…
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.
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.
Novo Nordisk to support MIT postdocs working at the intersection of AI and life sciences
MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellows Program will support up to 10 postdocs annually over five years.
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.