Technique enables AI on edge devices to keep learning over time
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
Computer vision enables contact-free 3D printing, letting engineers print with high-performance materials they couldn’t use before.
How do powerful generative AI systems like ChatGPT work, and what makes them different from other types of artificial intelligence?
MIT CSAIL researchers combine AI and electron microscopy to expedite detailed brain network mapping, aiming to enhance connectomics research and clinical pathology.
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.