Star Trek Deep Space Nine Opening Intro Season 6

>> YOUR LINK HERE: ___ http://youtube.com/watch?v=zR11FLZ-O9M

First lecture of MIT course 6.S091: Deep Reinforcement Learning, introducing the fascinating field of Deep RL. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI AGI), and podcast conversations, visit our website or follow TensorFlow code tutorials on our GitHub repo. • INFO: • Website: https://deeplearning.mit.edu • GitHub: https://github.com/lexfridman/mit-dee... • Slides: http://bit.ly/2HtcoHV • Playlist: http://bit.ly/deep-learning-playlist • OUTLINE: • 0:00 - Introduction • 2:14 - Types of learning • 6:35 - Reinforcement learning in humans • 8:22 - What can be learned from data? • 12:15 - Reinforcement learning framework • 14:06 - Challenge for RL in real-world applications • 15:40 - Component of an RL agent • 17:42 - Example: robot in a room • 23:05 - AI safety and unintended consequences • 26:21 - Examples of RL systems • 29:52 - Takeaways for real-world impact • 31:25 - 3 types of RL: model-based, value-based, policy-based • 35:28 - Q-learning • 38:40 - Deep Q-Networks (DQN) • 48:00 - Policy Gradient (PG) • 50:36 - Advantage Actor-Critic (A2C A3C) • 52:52 - Deep Deterministic Policy Gradient (DDPG) • 54:12 - Policy Optimization (TRPO and PPO) • 56:03 - AlphaZero • 1:00:50 - Deep RL in real-world applications • 1:03:09 - Closing the RL simulation gap • 1:04:44 - Next step in Deep RL • CONNECT: • If you enjoyed this video, please subscribe to this channel. • Twitter: / lexfridman • LinkedIn: / lexfridman • Facebook: / lexfridman • Instagram: / lexfridman

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