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Explore Deep Learning State of the Art (2019) with 166,758 views, 2,880 likes, and 76 comments. Experience the impact of this video content that has captured audience attention.

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-deep-learning 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: https://twitter.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/lexfridman - Instagram: https://www.instagram.com/lexfridman

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