Photo courtesy of Uncommon Hacks 2019
What kind of world would you want to create? Close your eyes. Whatever the idea, Uncommon Hacks gave the opportunity to create one. Uncommon Hacks is University of Chicago (UChicago)’s annual hackathon which was held this year between February 16 and 17. It is a weekend-long celebration; It is a portal where implications of new technology get its birth at UChicago; It is the hackathon where everyone comes to Chicago to have fun, brainstorm, and innovate tech-related projects with friends.
Illinois Tech’s ACM (Association of Computer Machinery) supported Illinois Tech students who were chosen to participate in the 2019 Uncommon Hacks. Illinois Tech students won two places in the hackathon, while one of the teams from Illinois Tech won the judge’s place. Erik Quintanilla, another Illinois Tech student, won the best use of Google Cloud Platform sponsor prize.
The team Jabber (which included Vinesh Kannan, Mohsin Haider and Hasan Rizvi) created a web-based platform to end the suffering of poor quality video calls. Jabber replaces video with quirky, customizable face animations to accompany voice calls with your friends. They simplified and tracked facial movement and expressions using clmtracker, an open source library developed by Audun Mathias Øygard, based on research by Jason Saragih. They created Jabber using browser-based features to connect to device cameras and microphones, Firebase, Socket.io, and Express to manage other real-time features and store users' recorded stories. Jabber does not store any identifying information about users. Video data is not streamed to other users or stored in the database. Audio data is streamed to other users in the chatroom, but not stored in the database. You also can try Jabber without creating an account: “jabberchat.glitch.me”.
Erik Quintanilla created Oracle which runs on the world’s most beautiful web page, takes from you a couple of sentences, and uses these sentences as context. These will generate the rest for you. According to Erik, the idea came from the recent backlash to Open AI’s release of the GPT-2 model that was not going to be released to the public because it was “too good”. Given a couple of sentences for context, the Oracle AI will write the following paragraphs given those sentences as context, which is still very impressive for a neural network.