AI accelerates problem-solving in complex scenarios
A new, data-driven approach could lead to better solutions for tricky optimization problems like global package routing or power grid operation.
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.
Twelve teams of students and postdocs across the MIT community presented innovative startup ideas with potential for real-world impact.
MIT CSAIL researchers innovate with synthetic imagery to train AI, paving the way for more efficient and bias-reduced machine learning.
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
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.
The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.