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“Personhood credentials allow you to prove you are human without revealing anything else about your identity,” says Tobin South (Credits: MIT News; iStock).
CSAIL article

As artificial intelligence agents become more advanced, it could become increasingly difficult to distinguish between AI-powered users and real humans on the internet. In a new white paper, researchers from MIT, OpenAI, Microsoft, and other tech companies and academic institutions propose the use of personhood credentials, a verification technique that enables someone to prove they are a real human online, while preserving their privacy.

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MosaicML (L-R): Naveen Rao, Michael Carbin, Julie Shin Choi, Jonathan Frankle, and Hanlin Tang (Credit: Courtesy of MosaicML).
CSAIL article

The impact of artificial intelligence will never be equitable if there’s only one company that builds and controls the models (not to mention the data that go into them). Unfortunately, today’s AI models are made up of billions of parameters that must be trained and tuned to maximize performance for each use case, putting the most powerful AI models out of reach for most people and companies.

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alt="The dataset contains movements and physiological responses of badminton players and can be used to build AI-driven coaching assistants. This development could improve the quality of forehand clear and backhand drive strokes across all skill levels, from beginners to experts (Credit: SeungJun Kim at GIST)."
CSAIL article

In sports training, practice is the key, but being able to emulate the techniques of professional athletes can take a player’s performance to the next level. AI-based personalized sports coaching assistants assist with this by utilizing published datasets. With cameras and sensors strategically placed on the athlete's body, these systems can track everything, including joint movement patterns, muscle activation levels, and gaze movements.

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Ryan Williams headshot
CSAIL article

The European Association for Theoretical Computer Science (EATCS) recently awarded Ryan Williams, MIT EECS professor and CSAIL member, with the 2024 Gödel Prize for his 2011 paper, “Non-Uniform ACC Circuit Lower Bounds.” Williams receives this honor for presenting a novel paradigm for a “rich two-way connection" between algorithmic techniques and lower-bound methods.