Part 3/13:
The Underlying Technology Powering Tesla's Self-Driving Systems
Tesla's approach to self-driving has evolved significantly, heavily emphasizing neural networks. The company now employs a single, large end-to-end neural network that processes raw sensor inputs—including pixel data from cameras and other sensory information—and directly produces driving actions such as steering and acceleration. This shift away from traditional modular perception-planning models offers several advantages:
- Implicit perception: Rather than explicitly detecting vehicles, road boundaries, or obstacles, the neural network learns to interpret scenes holistically, allowing for more nuanced decision-making.