Weekend Reads - Tesla AI Andrej Karpathy on Scalability in Autonomous Driving

Key Notes

• 1 million internet connected devices
• Navigate on Autopilot / Right Lane changes
• Summon to parking lot
• Divide into smaller problems, Solve and incrementally provide features
• 360 degree safety features / Safety assist
• Detection to avoid / alert accidents
• Ambition - Full Self Driving
• High Definition Maps Approach
• Similar to human decision making
• No Lidar maps approach

Neural Networks in Production

• Static objects / parking lines, Cross walks
• Hard to achieve predictions
• Stop sign on walls / flash lights / held by person / occlusion
• Situations where it applies right / left
• When to ignore , Largest dataset of stop sign
• Techniques to boost occluded data
• Chinese / Korean / Japanese Signs
• Hydranet, 48 Networks, 1000 predictions
• Shared CNN backbone
• 50 Plus seems people
• Curate dataset, new landmark
• Segmentation / Detection etc..

• Curate dataset, new landmark
• Segmentation / Detection etc..

Summary - Most of them direct detections, shared backbone, transfer learning, a lot of datasets

Tesla Logs Analysis

NTSB Tesla Analysis

Happy Learning!!!