Andrej Karpathy

I'll present our work on training reinforcement learning agents to interact with and complete tasks in web browsers. In the short term our agents are learning to interact with common UI web elements like buttons, sliders and text fields. In the longer term we hope to address more complex tasks, such as achieving competence in interactive online exercises intended for schoolchildren to learn mathematics. I'll use these examples to also give a short but complete Reinforcement Learning tutorial.

Andrej is a 5th year PhD student at Stanford University, studying Deep Learning and its applications to Computer Vision and Natural Language Processing. He is also Head of Artificial Intelligence and Autopilot Vision at Tesla. In particular, his recent work has focused on Image Captioning, Recurrent Neural Network Language Models and Reinforcement Learning. On a side, he enjoys implementing state of the art Deep Learning models in Javascript, competing against Convolutional Networks on the ImageNet challenge, and blogging. Before joining Stanford he completed an undergraduate degree in Computer Science and Physics at the University of Toronto and a Computer Science Master's degree at the University of British Columbia.

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