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.
Computer science and technology
Envisioning the future of computing
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.
Defining the public interest in new technologies
New online journal seeks to seeks to bring together the MIT community to discuss the social responsibilities of individuals who design, implement, and evaluate technologies.
A step toward safe and reliable autopilots for flying
A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.
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.
New model offers a way to speed up drug discovery
By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.
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.
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.
New tool helps people choose the right method for evaluating AI models
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.