Video is a complex data structure: it's composed of large amounts of images, sound and text. Not only it's complex but, to understand that data, you need complex Machine Learning models. In this talk, we are going to talk a bit about the work we have done at Uru to understand videos in the media and advertising vertical, talking specifically about how we managed to leverage Deep Learning models to extract meaningful data in those videos and how we leveraged a serverless architecture to achieve real time processing speeds
Brunno Attorre is the Co-founder and CTO of Uru, a NYC based company that is using computer vision and artificial intelligence to help video understanding and monetization for brands and publishers. Previous to Uru, Brunno helped build machine learning solutions for Brazilian E-Commerce company Buscapé and worked as a Software Engineer at J.P. Morgan & Chase.
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