This is exactly as I predicted. To the point that it needs its own thread. Its funny how I have been right about everything I have said concerning the tesla's autopilot yet I have received unprecedented backlash. EAP HW2 - my experience thus far... [DJ Harry] (only one camera active) Enhanced Autopilot 2 may never happen before Full Self Driving is ready! (my accurate predicted timeline) Whether its the delay for parity or number of cameras currently being used, or how neural networks/deep learning works and the way Tesla leverages it. All the way down to the requirement of High Definition maps that are accurate to 5-10 CM unlike Tesla's current high precision map that uses GPS logging and is only accurate to a-couple meters. All the way down to the fact that Tesla hadn't started their HD map development and didn't have / couldn't process the raw video data from Mobileye's AP1. I also said when they start their HD map development we will all know about it through announcement from Elon Musk himself or through data uploads from Wi-Fi. Infact in my very first post in this forum I listed exactly how this video collection will happen and what it will be used for. I have also said in the past that they will only need short video clip or even just a picture in some cases and processed meta data in most cases. The short video clips are then annotated by a human and collated to be used in training the specific models. Tesla are doing two things. They are creating a 5-10 cm HD map for the car to localize in (requires only metadata processed by the on-board dnn model). The HD Map also includes exact location of traffic lights. How traffic light works in SDCs is that they look for the exact position of a traffic light. They don't look at the entire picture. since they know the exact position of what traffic light they want to examine from the HD map, they focus on it (requires only metadata). HD Maps also includes what traffic light exactly corresponds to a lane or road. At an intersection there could be 10 traffic lights facing you and you need to know exactly which one you should be paying attention to in relation to where you want to go (*requires maybe video) Detection NN Models are not perfect and you can get accuracy of 80% easily but to improve on that, you need millions of more pictures to train the network with. Improving a traffic light or stop sign detection model will (require video clip/image). It can also be improved to only take a picture of intersections that are not mapped yet / intersections that it fail to properly recognize. When Raw Video clip ( which are just small number of picture frames) are uploaded, they are annotated by a human and collated. Why would you need video clips and not just metadata For example if your car were to come to a stop at an intersection with no car directly in-front of it and that intersection haven't been mapped and it doesn't detect a traffic/stop sign. The car will take a picture with the assumption that its traffic sign/light detection model failed and there must be a stop light, or stop sign somewhere. The picture gets sent back to HQ, which is then annotated by a human and collated.