Andrej Karpathy
About
Andrej Karpathy is from San Francisco, California, United States. In Andrej's previous role as a Sr Director of AI at Tesla, Andrej worked in Palo Alto until Jul 2022. Prior to joining Tesla, Andrej was a Research Scientist at OpenAI and held the position of Research Scientist at San Francisco Bay Area. Prior to that, Andrej was a PhD student at Stanford University from Sep 2011 to Sep 2016. Andrej started working as Research Intern at Google DeepMind in London, UK in Jun 2015. From Jun 2013 to Sep 2013, Andrej was Google Research Summer Intern at Google, based in Mountain View, CA. Prior to that, Andrej was a Google Research Summer Intern at Google, based in Mountain View, CA from May 2011 to Sep 2011.
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Andrej Karpathy's past jobs
I lead the computer vision team of Tesla Autopilot. The team is focused on all aspects of 1) data gathering (in-house data labeling, custom labeling interfaces), 2) neural network training, 3) the science of making it work (e.g. segmentation, detection, 3D/depth estimation), and 4) deployment in production running on our custom chip. Today, the Autopilot increases the safety and convenience of driving, but the team's goal is to develop and deploy Full Self-Driving to our rapidly growing fleet of millions of cars. Our Aug 2021 Tesla AI Day (https://www.youtube.com/watch?v=j0z4FweCy4M) provides the most detailed and up-to-date overview of this effort.
As one of the founding members, I helped with much of the early recruiting/structuring. As a research scientist, I worked on deep learning for generative models (e.g. image generation with PixelCNN++) and deep reinforcement learning (e.g. computer controlling keyboard and mouse to accomplish various tasks on web interfaces such as filling out forms).
My PhD thesis was focused on the design of novel convolutional/recurrent neural networks and their applications in computer vision, natural language processing and their intersection. As an example, this includes the tasks of translating from images to language ("image captioning"), and conversely, image retrieval based on natural language queries. I designed and was the primary instructor for the first deep learning class Stanford - CS 231n: Convolutional Neural Networks for Visual Recognition. The class became one of the largest at Stanford and has grown from 150 enrolled in 2015 to 330 students in 2016, and 750 students in 2017. http://cs231n.stanford.edu/
Model-based Deep Reinforcement Learning research
Supervised Deep Learning / Computer Vision for YouTube videos
Unsupervised Deep Learning / Computer Vision for YouTube videos