Date of video 31 Jul 2021.
comma three devkit https://comma.ai/shop/products/three
Video title: Building a Super Human Driving Agent

Harald Schäfer social media:
-   / harald-schafer-567830132  
- https://github.com/HaraldSchafer
View original video on Youtube:
-    • Building a Super Human Driving Agent ...  
comma.ai youtube playlist:
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Chapters:
00:00:00 Intro Harald Schäfer
00:00:39 What is a real self driving car
00:02:21 The classical approach to self driving
00:03:54 Classical perception
00:04:41 Classical planning
00:08:02 The flaws of classical approach to self driving
00:09:17 Remembering how to drive
00:10:02 Why is end to end better
00:11:23 The new approach to self driving
00:11:55 Is all starts with data
00:12:45 So much diversity
00:14:12 What is the output?
00:14:44 Localization
00:15:18 GNSS
00:17:08 Sensor fusion
00:19:58 Time to train
00:20:48 Validation
00:21:48 Quote about software engineering
00:22:09 Simulator
00:24:16 Problem: cloning
00:27:10 Solution: train in simulator
00:28:25 Testing Testing Testing
00:29:33 Does model know it's speeds?
00:29:47 Is model accurate?
00:30:05 Does it drive well?
00:31:09 Does model predict swerve
00:32:05 Problem 2: Desire where do you want to go?
00:33:19 End-to-end that works
00:33:57 Technical difficulties
00:34:28 End-to-end lane changes
00:34:40 Technical difficulties
00:36:22 Some questions
00:36:27 Training the model components
00:37:06 End-to-end lane changes
00:37:53 End-to-end lane less
00:38:49 Longitudinal end-to-end
00:39:24 End-to-end forward collision warning
00:40:10 End-to-end stop lines
00:40:48 What is next for comma research?
00:41:32 Q&A
00:42:11 Driving without GPS data
00:43:22 Good data for training
00:44:35 Bad stop sign human driving data
00:45:10 Training out unwanted behavior
00:46:19 End-to-end lateral control
00:47:03 Explaining the model behavior
00:48:37 Larger training models and edge cases
00:49:44 Driver alertness
00:50:49 Community contributions
00:52:15 Evolution of end-to-end approach
00:53:31 Bounding boxes
00:54:40 Adding more complexity
00:55:20 VR sensor fusion
00:56:00 How big does the models have to get
00:57:00 End-to-end not fully end-to-end
00:58:20 Hardware limitations for Level 5
00:59:13 Data visualization of the model
01:00:02 Driving data utilization and benefits for the user
01:00:42 Path prediction on curvature
01:01:43 Pedestrian crossings
01:02:15 Lane changes and blind spot monitoring
01:02:47 Simulator scaling to more complex scenarios
01:03:37 Self-supervised learning
01:04:07 Hand labeling and comma-pencil usecase
01:05:19 Model mistakes and failure prediction
01:06:09 Artificial general intelligence
01:06:49 Failures of localizer
01:08:08 Model reliability and scaling to city driving
01:08:56 Differences between drivers in different cities
01:09:18 Humans teaching the car how to drive
01:10:00 End-to-end lateral planning model cheating
01:10:46 Training process and incremental learning
01:11:58 George Hotz More GPUs
01:12:02 Biggest limiting factor of improvement
01:13:11 Visual geometry lane lines bug how it was fixed
01:13:49 Harald's birthday

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