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.
Six teams conducting research in AI, data science, and machine learning receive funding for projects that have potential commercial applications.
MIT students share ideas, aspirations, and vision for how advances in computing stand to transform society in a competition hosted by the Social and Ethical Responsibilities of Computing.
MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellows Program will support up to 10 postdocs annually over five years.
MIT postdoc Ziv Epstein SM ’19, PhD ’23 discusses issues arising from the use of generative AI to make art and other media.
NOMIS Foundation honors the Ford Professor of Economics for his contributions to understanding the effects of technological change and globalization on jobs and earnings prospects for workers.
New online journal seeks to bring together the MIT community to discuss the social responsibilities of individuals who design, implement, and evaluate technologies.
A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.
Recipients Luis Antonio Benítez, Carolina Cuesta-Lazaro, and Fernando Romero López receive support for their scientific research.
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.
By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.
The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.
The Brazilian social justice reporter is a fellow at the MIT Center for International Studies.
A new multimodal technique blends major self-supervised learning methods to learn more similarly to humans.
Cindy Alejandra Heredia’s journey from Laredo, Texas, took her to leading the MIT autonomous vehicle team and to an MBA from MIT Sloan.
Selecting the right method gives users a more accurate picture of how their model is behaving, so they are better equipped to correctly interpret its predictions.