3 Questions: On biology and medicine’s “data revolution”
Professor Caroline Uhler discusses her work at the Schmidt Center, thorny problems in math, and the ongoing quest to understand some of the most complex interactions in biology.
IDSS
Simpler models can outperform deep learning at climate prediction
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
A new way to test how well AI systems classify text
As large language models increasingly dominate our everyday lives, new systems for checking their reliability are more important than ever.
Eco-driving measures could significantly reduce vehicle emissions
New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.
New algorithms enable efficient machine learning with symmetric data
This new approach could lead to enhanced AI models for drug and materials discovery.
How to more efficiently study complex treatment interactions
A new approach for testing multiple treatment combinations at once could help scientists develop drugs for cancer or genetic disorders.
Unpacking the bias of large language models
In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.
Melding data, systems, and society
A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.
AI-enabled control system helps autonomous drones stay on target in uncertain environments
The system automatically learns to adapt to unknown disturbances such as gusting winds.
Envisioning a future where health care tech leaves some behind
The winning essay of the Envisioning the Future of Computing Prize puts health care disparities at the forefront.