Part 6/12:
Understanding how neural networks operate offers insight into Tesla's technological edge. These AI systems classify objects—like distinguishing a square from a circle—by analyzing pixels through multiple layers of computation. When errors occur, such as misclassifying a shape, Tesla owners can report these mistakes, which are then used in a process called backpropagation. This process adjusts neural network parameters based on new data, making subsequent decisions more accurate.
For example, footage of Tesla navigating complex environments—like construction zones or crowded city streets—demonstrates the neural network's evolving ability to interpret ambiguous or challenging scenes. The model continuously improves by learning from mistakes, akin to human learning, reducing errors over time.