data

Q&A: Hey AI, who should I vote for this year?

MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.

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When AI art has no author: Study finds generated images often can’t be traced to training data

A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.

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How a medical database developed at MIT evolved into a global standard of data-sharing

The visionary PhysioNet platform launched 25 years ago, based on a system developed at MIT in the 1970s. It has become one of the most comprehensive biomedical and clinical data repositories in existence.

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3 Questions: Neural transparency and the future of AI design

Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI’s neural network before their chatbot ever says a word.

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