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
‘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
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
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
Announcing the Launch of the Stanford Cable TV News Analyzer
The Brown Institute for Media Innovation is pleased to announce the launch of the Stanford Cable TV News Analyzer, an interactive tool that gives the public the ability to not just search transcripts, but also compute the screen time of public figures in nearly 24-7 broadcasts from CNN, Fox News and MSNBC. Each day, cable
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
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
Columbia Local News Initiative Is Hiring For Three New Roles!
By Al Johri. Journalists around the country are doing ever more important work under ever tighter budgets and more uncertain conditions. As we collectively navigate COVID-19, the work that local news organizations do could not be more vital to the communities they serve. Local newsrooms need every advantage they can get to focus on the