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Ars Electronica 2019 - AI Lab

Ars Electronica 2019 - AI Lab

Rainer Stropek

September 09, 2019
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  1. They can only work with zeroes and ones. The world

    does not consist of just zeroes and ones.
  2. Two young people, no computer science professionals Mentors from CoderDojo

    Linz Discover AI for face detection Combine face detection with game development Can they teach the computer to detect faces and emotions? Can they build games controlled by head movement and facial expressions?
  3. For training a good face detection AI, you need thousands

    of training images Diversity is super important to avoid a biased AI Data is the new gold Many universities make their image databases available for research purposes (e.g. XM2VTS) Commercial companies try to gather data through e.g. free services For startup, it is hard to compete with internet giants Snowball effect A lot of power controlled by only a few organizations
  4. Mechanical Turk Fake chess-playing machine constructed in the late 18th

    century Amazon Mechanical Turk Crowdsourcing website People perform discrete on-demand tasks that computers are currently unable to do „Turkers“ People labelling AI for large enterprises Blue-collar job of the AI era
  5. Video capturing in Browser Face detection: face-api.js Completely done in

    Browser → privacy Uses Tensorflow.js, pretrained models Detection sent back to server Websockets Separate detection and processing Scalability
  6. Scratch Extension Based on React Receives detection from server via

    Websockets Control game with your face Face movement Expression (happiness)
  7. Try our face detection Car Race Don‘t Laugh Challenge Emotional

    Pong Discuss AI with us How did we build the project? What did we learn? What can you build? Develop your own face-controlled Scratch game