Deepfake Detector Wins PennApps XX

Deepfake Detector Wins PennApps XX

Team DeFake: Aarati Srikumar, Daniel Li, George Diwan and Sofiya Lysenko

An app designed to detect deepfakes took home the grand prize at PennApps XX, beating nearly 250 tech projects developed over the course of a weekend. The top three team members took home a bevy of tech items, software subscriptions and gift cards; nearly $100,000 worth of prizes were award across a variety of technical categories.

PennApps, the nation’s first student-run college hackathon, was founded in 2009 and has been running biannual invitational events since. Contestants from around the world arrive on a Friday afternoon, form teams and come up with ideas for digital apps or hardware projects, which they must complete before a demo session on Sunday morning. There, the projects are evaluated by a panel of tech industry judges, who rate them on originality, technical difficulty, polish, and usefulness

Team DeFake: Aarati Srikumar, Daniel Li, George Diwan and Sofiya Lysenko

This year’s winning project was DeFake, a browser extension that uses machine learning to assess the likelihood that a given video has been subtly manipulated. Deepfakes are a new method of using artificial intelligence to impersonate famous figures, using pre-existing video and audio clips to generate photo-realistic fabrications. Worried about deepfakes being “particularly influential in the outcome of this and future elections,” the team “wanted to develop a level of protection and reality for users.”

In second place was Jaught, a virtual whiteboard system that allows users to share notes and teach lessons using a web-camera. Jaught digitally converts handwriting and can be controlled with hand gestures.

ImpromPPTX took third place. The app automatically generates a slideshow presentation in real time, based on what the speaker is saying. Uses your computer microphone to listen while you talk. It can retrieve images and graphs, as well as make relevant titles and summarize the speaker’s words into bullet points.

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