A lot of our code is in the process of being transitioned from Software 1.0 (code written by humans) to Software 2.0 (code written by an optimization, commonly in the form of neural network training). In the new paradigm, much of the attention of a developer shifts from designing an explicit algorithm to curating large, varied, and clean datasets, which indirectly influence the code. I will provide a number of examples of this ongoing transition, cover the advantages and challenges of the new stack, and outline multiple opportunities for new tooling.
Andrej is a Director of AI at Tesla, where he focuses on computer vision for the Autopilot. Previously he was a research scientist at OpenAI working on Reinforcement Learning and a PhD student at Stanford working on Convolutional/Recurrent neural network architectures for images and text.