AI platform for data science and machine learning CrowdFlower announced on Thursday the first round winners of the “AI For Everyone” Challenge. The winning proposal, which receives $1 million, are computer vision projects that will label millions of images to build the largest collection of training data libraries for facial recognition and living cells. The first round winner was Kiva engineer Melissa Fabros. CrowdFlower stated:
“Kiva engineer Melissa Fabros’ winning submission centers around the creation of the world’s largest, most diverse set of training data for facial recognition. One of the biggest problems with facial recognition today is the limited amount of training data available to teach an algorithm how to process the image. As a result, algorithms struggle to accurately process the faces of people across a wide range of skin colors or if the image isn’t perfectly clear or well lit. Kiva, which has been focused on crowdfunding micro-loans in across 80 countries has amassed a database of more than 900,000 human faces from varying global ethnicities.”
Finalists were selected by a group of distinguished judges including members of CrowdFlower’s Scientific Advisory Board: Barney Pell, founder at Moon Express; Pete Warden, Staff Research Engineer at Google; Monica Rogati, independent data science advisor; Adrian Weller, Senior Research Fellow at the University of Cambridge; Jack Clark, Director of Strategy and Communications at OpenAI and Lukas Biewald, founder at CrowdFlower. Selection is based on the innovation of the project, its importance to the advancement of AI and the overall potential impact of the proposed initiative.
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“Kiva engineer Melissa Fabros’ winning submission centers around the creation of the world’s largest, most diverse set of training data for facial recognition. One of the biggest problems with facial recognition today is the limited amount of training data available to teach an algorithm how to process the image. As a result, algorithms struggle to accurately process the faces of people across a wide range of skin colors or if the image isn’t perfectly clear or well lit. Kiva, which has been focused on crowdfunding micro-loans in across 80 countries has amassed a database of more than 900,000 human faces from varying global ethnicities.”
