Deep Learning State of the Art (2019) - MIT

New lecture on recent developments in deep learning that are defining the state of the art in our field (algorithms, applications, and tools). This is not a complete list, but hopefully includes a good sampling of new exciting ideas. For more lecture videos visit our website or follow code tutorials on our GitHub repo. INFO: Website: https://deeplearning.mit.edu GitHub: https://github.com/lexfridman/mit-dee... Slides: http://bit.ly/2HiZyvP Playlist: http://bit.ly/deep-learning-playlist OUTLINE: 0:00 - Introduction 2:00 - BERT and Natural Language Processing 14:00 - Tesla Autopilot Hardware v2+: Neural Networks at Scale 16:25 - AdaNet: AutoML with Ensembles 18:32 - AutoAugment: Deep RL Data Augmentation 22:53 - Training Deep Networks with Synthetic Data 24:37 - Segmentation Annotation with Polygon-RNN++ 26:39 - DAWNBench: Training Fast and Cheap 29:06 - BigGAN: State of the Art in Image Synthesis 30:14 - Video-to-Video Synthesis 32:12 - Semantic Segmentation 36:03 - AlphaZero & OpenAI Five 43:34 - Deep Learning Frameworks 44:40 - 2019 and beyond CONNECT: If you enjoyed this video, please subscribe to this channel. Twitter: / lexfridman LinkedIn: / lexfridman Facebook: / lexfridman Instagram: / lexfridman