The Brown Institute, Lenfest Local Lab and Philadelphia Inquirer are partnering to build content audit tools

Our collaborative project won the Google GNI Innovation Challenge, securing $300,000 to build and test machine learning-based tools that help newsrooms analyze equity and representation in their work at scale. Editor’s note: This post was co-written and edited by Michael Krisch, Deputy Director of the Brown Institute; Sarah Schmalbach, Product Director of the Lenfest Local

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‘Sylvia’ Premiering at IDFA DocLab

Have you ever known an aging robot? Meet Sylvia, the first aging virtual influencer. Premiering on November 20, 2020 at the International Documentary FilmFestival Amsterdam (IDFA), attendee’s can look back on Sylvia’s life, and witness its end. Virtual Influencers are computer-generated characters that exist on social media and appear as real humans. These characters are complex

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‘Changing Course’: Lectures on Data Representations and Equitable Approaches to Computing

Each year, the Brown Institute sponsors talks that explore the intersection between media and technology. This year we have three virtual presentations lined up, each challenging us to think about data and computation in new ways. Johanna Drucker starts the series by looking at alternatives to representing time — looking beyond graphic standards such as

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Magic Grant projects ‘Public Analysis of TV News’ and ‘Sports Illustrated’ featured on Bloomberg QuickTake

On October 21, 2020, Ashlee Vance, Senior Writer at Bloomberg Businessweek interviewed Stanford Professor Kayvon Fatahalian and highlighted advancements in artificial intelligence through Magic Grant projects Public Analysis of TV News and Sports Illustrated. In the piece, Vance and Fatahalian highlight the tremendous opportunities that AI has provided for media makers. Both also offer thoughtfulness

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Institute Director Agrawala talks Deep Fakes with the Stanford Institute for Human-Centered AI

To spot a deep fake, researchers looked for inconsistencies between “visemes,” or mouth formations, and “phonemes,” the phonetic sounds. Using AI to Detect Seemingly Perfect Deep-Fake Videos was published on the Stanford Institute for Human-Centered Artificial Intelligence Blog on 10/13/2020, which featured Brown Institute Director Maneesh Agrawala. In the article, Agrawala spoke to the struggles

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Magic Grant project ‘Synthesizing Novel Video from GANs’ featured in Engadget

On August 14, 2020, the tech outlet Engadget featured recent research produced by the Magic Grant ‘Synthesizing Novel Video from GANs’ developed by grantee Haotian Zhang, alongside Cristobal Sciutto under faculty direction from Maneesh Agrawala and Kayvon Fatahalian.’ The article titled “These AI-generated tennis matches are both eerie and impressive,” describes the system developed under

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Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods

Authors Daniel Y. Fu, Mayee F. Chen, Frederic Sala, Sarah M. Hooper, Kayvon Fatahalian, Christopher Ré Abstract Weak supervision is a popular method for building machine learning models without relying on ground truth annotations. Instead, it generates probabilistic training labels by estimating the accuracies of multiple noisy labeling sources (e.g., heuristics, crowd workers). Existing approaches

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