Chapter
The Importance of Data Selection and Neural Network Architectures for Self-Driving Cars
1:11:07 - 1:16:25 (05:18)
In order to solve the self-driving car problem, the perception problem must be solved by detecting and replicating what humans do when they drive, using optical sensors and neural networks. The data selection process and neural network architecture are crucial components of this process.
Clips
Andre Carpathi and his team are leading the way in selecting data sets, developing neural network architectures, and testing and validating networks for real-world artificial intelligence.
1:11:07 - 1:13:16 (02:09)
Summary
Andre Carpathi and his team are leading the way in selecting data sets, developing neural network architectures, and testing and validating networks for real-world artificial intelligence. Despite having a lot of talented people driving the process, there is still work to be done to create a pleasant experience over long distances.
ChapterThe Importance of Data Selection and Neural Network Architectures for Self-Driving Cars
Episode#252 – Elon Musk: SpaceX, Mars, Tesla Autopilot, Self-Driving, Robotics, and AI
PodcastLex Fridman Podcast
The key to solving the challenge of self-driving cars is to recreate the way humans perceive and drive using optical sensors and neural networks.
1:13:16 - 1:16:25 (03:09)
Summary
The key to solving the challenge of self-driving cars is to recreate the way humans perceive and drive using optical sensors and neural networks. It is a difficult problem that is yet to be fully understood.