Dealing with the limitations of our noisy world
Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse.
Exploiting the symmetry within datasets, MIT researchers show, can decrease the amount of data needed for training neural networks.
Hundreds of participants from around the world joined the sixth annual MIT Policy Hackathon to develop data-informed policy solutions to challenges in health, housing, and more.
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.
How do powerful generative AI systems like ChatGPT work, and what makes them different from other types of artificial intelligence?
By focusing on causal relationships in genome regulation, a new AI method could help scientists identify new immunotherapy techniques or regenerative therapies.
The MIT and Accenture Convergence Initiative for Industry and Technology selects three new research projects to support.
Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.