MIT Generative AI Week fosters dialogue across disciplines
During the last week of November, MIT hosted symposia and events aimed at examining the implications and possibilities of generative AI.
During the last week of November, MIT hosted symposia and events aimed at examining the implications and possibilities of generative AI.
MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.
A new, data-driven approach could lead to better solutions for tricky optimization problems like global package routing or power grid operation.
Rodney Brooks, co-founder of iRobot, kicks off an MIT symposium on the promise and potential pitfalls of increasingly powerful AI tools like ChatGPT.
Human Guided Exploration (HuGE) enables AI agents to learn quickly with some help from humans, even if the humans make mistakes.
By analyzing bacterial data, researchers have discovered thousands of rare new CRISPR systems that have a range of functions and could enable gene editing, diagnostics, and more.
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
MIT CSAIL researchers combine AI and electron microscopy to expedite detailed brain network mapping, aiming to enhance connectomics research and clinical pathology.
Rama Ramakrishnan helps companies explore the promises and perils of large language models and other transformative AI technologies.
Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.