Using generative AI to improve software testing
MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.
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.
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.
The MIT Schwarzman College of Computing awards seed grants to seven interdisciplinary projects exploring AI-augmented management.