Active Learning, Data Selection, Data Auto-Labeling, and Simulation in Autonomous Driving — Part 4
It’s time for Tesla! Would be an interesting one!
Tesla
In this talk on Tesla AI Day in 2019, Andrej Karpathy explains the active learning procedure at Tesla, which they call the Data Engine. For example, in an object detection task and for a bike attached to the back of a car, the neural network should detect just one object (car) for downstream tasks such as decision-making and planning. Check the following image:
They find a few images that show this pattern and use a machine learning mechanism to search for similar examples in their fleet to fix this problem. The returned images from the fleet can be as follows:
Then human annotators will annotate these examples as single cars, and the neural network will be trained on these new examples. So, in the future, the object detector will understand that it is just an attached bike to a car and consider that as just a single car. They do this all the time for all the rare cases. So their model will become more and more accurate over time.
