In the new economics course 14.163 (Algorithms and Behavioral Science), students investigate the deployment of machine-learning tools and their potential to understand people, reduce bias, and improve society.
Fifteen new faculty members join six of the school’s academic departments.
MIT professors Roger Levy, Tracy Slatyer, and Martin Wainwright appointed to the 2024 class of “trail-blazing fellows.”
The MIT Schwarzman College of Computing building will form a new cluster of connectivity across a spectrum of disciplines in computing and artificial intelligence.
MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.
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.
MIT LIDS awarded funding from the Appalachian Regional Commission as part of a multi-state collaborative project to model and test new smart grid technologies for use in rural areas.
An easy-to-use technique could assist everyone from economists to sports analysts.
During the last week of November, MIT hosted symposia and events aimed at examining the implications and possibilities of generative AI.
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.
A cross-departmental team is leading efforts to utilize machine learning for increased efficiency in heating and cooling MIT’s buildings.