Protecting the rights of internet users, in Mexico and worldwide
PhD student Mariel García-Montes researches the internet’s far-reaching impact on society, especially regarding privacy and young people.
A fast and flexible approach to help doctors annotate medical scans
“ScribblePrompt” is an interactive AI framework that can efficiently highlight anatomical structures across different medical scans, assisting medical workers to delineate regions of interest and abnormalities.
Study: Transparency is often lacking in datasets used to train large language models
Researchers developed an easy-to-use tool that enables an AI practitioner to find data that suits the purpose of their model, which could improve accuracy and reduce bias.
Making a measurable economic impact
Saeed Miganeh’s work at MIT is helping him answer important questions about designing effective programs for poverty mitigation and economic growth in African countries.
New open-source tool helps to detangle the brain
The software tool NeuroTrALE is designed to quickly and efficiently process large amounts of brain imaging data semi-automatically.
MIT researchers use large language models to flag problems in complex systems
The approach can detect anomalies in data recorded over time, without the need for any training.
New framework empowers pavement life-cycle decision-making while reducing data collection burden
MIT Concrete Sustainability Hub research presents a streamlined pavement life-cycle assessment framework to enable a large set of stakeholders to conduct environmental analysis of pavements.
Study: Flying keeps getting safer
Reflecting a “Moore’s Law of aviation,” commercial flight has become roughly twice as safe each decade since the 1960s; Covid-19 added a wrinkle, however.
Method prevents an AI model from being overconfident about wrong answers
More efficient than other approaches, the “Thermometer” technique could help someone know when they should trust a large language model.
Groundbreaking poverty alleviation project expands with new Arnold Ventures, J-PAL North America collaboration
Shared commitment to data-driven approach will help identify new policy solutions to reduce poverty and increase economic mobility in the US.
Roadmap details how to improve exoplanet exploration using the JWST
Scientists created the step-by-step guide to unlock the potential of NASA’s James Webb Space Telescope for identifying habitable worlds in the universe.
Study: When allocating scarce resources with AI, randomization can improve fairness
Introducing structured randomization into decisions based on machine-learning model predictions can address inherent uncertainties while maintaining efficiency.
How to assess a general-purpose AI model’s reliability before it’s deployed
A new technique enables users to compare several large models and choose the one that works best for their task.
Machine learning and the microscope
PhD student Xinyi Zhang is developing computational tools for analyzing cells in the age of multimodal data.
When to trust an AI model
More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world.