2023-24 Takeda Fellows: Advancing research at the intersection of AI and health
Thirteen new graduate student fellows will pursue exciting new paths of knowledge and discovery.
Thirteen new graduate student fellows will pursue exciting new paths of knowledge and discovery.
Rama Ramakrishnan helps companies explore the promises and perils of large language models and other transformative AI technologies.
Complimentary approaches — “HighLight” and “Tailors and Swiftiles” — could boost the performance of demanding machine-learning tasks.
The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.
Two studies find “self-supervised” models, which learn about their environment from unlabeled data, can show activity patterns similar to those of the mammalian brain.
The 15th Kendall Square Association annual meeting explored new and old aspects of the neighborhood.
AI models that prioritize similarity falter when asked to design something completely new.
The award honors research on public policy with a focus on economic and governmental reforms.
Researchers coaxed a family of generative AI models to work together to solve multistep robot manipulation problems.
Some researchers see formal specifications as a way for autonomous systems to "explain themselves" to humans. But a new study finds that we aren't understanding.
Amid the race to make AI bigger and better, Lincoln Laboratory is developing ways to reduce power, train efficiently, and make energy use transparent.
Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.
By focusing on causal relationships in genome regulation, a new AI method could help scientists identify new immunotherapy techniques or regenerative therapies.
Study shows users can be primed to believe certain things about an AI chatbot’s motives, which influences their interactions with the chatbot.
In campus talk, Daron Acemoglu offers vision of “machine usefulness,” rather than autonomous “intelligence,” to help workers and spread prosperity.