Chapter
Making Reinforcement Learning Work
1:31:44 - 1:35:46 (04:02)
The human element of catching the system when it fails is key to making reinforcement learning work effectively.
Clips
The guest expresses his exhaustion with safety engineers who prioritize safety over innovation in autonomous driving, claiming that in the long term, this approach kills safety.
1:31:44 - 1:33:07 (01:22)
Summary
The guest expresses his exhaustion with safety engineers who prioritize safety over innovation in autonomous driving, claiming that in the long term, this approach kills safety. This sentiment is echoed in the discussion of reinforcement learning and the role of temperature parameters in deviating from the argmax.
ChapterMaking Reinforcement Learning Work
EpisodeGeorge Hotz: Comma.ai, OpenPilot, and Autonomous Vehicles
PodcastLex Fridman Podcast
Comma.ai Founder George Hotz talks about the learning process of self-driving cars and how mistakes are necessary for exploration.
1:33:07 - 1:34:03 (00:56)
Summary
Comma.ai Founder George Hotz talks about the learning process of self-driving cars and how mistakes are necessary for exploration. He also discusses the importance of driver monitoring and the current development of Comma.ai.
ChapterMaking Reinforcement Learning Work
EpisodeGeorge Hotz: Comma.ai, OpenPilot, and Autonomous Vehicles
PodcastLex Fridman Podcast
The success of reinforcement learning depends heavily on human intervention and oversight when the system encounters trouble.
1:34:04 - 1:35:46 (01:42)
Summary
The success of reinforcement learning depends heavily on human intervention and oversight when the system encounters trouble. While there is potential for reinforcement learning to greatly improve certain areas of AI, it is important to recognize the limitations and the potential risks involved.