Neural Networks

Tesla's autonomous driving system relies heavily on deep neural networks for perception, planning, and control. The system uses multiple specialized networks:

1. **Perception Networks**: Process camera inputs to detect objects, lanes, traffic signs, and other road elements 2. **Occupancy Networks**: Predict 3D occupancy of space around the vehicle 3. **Planning Networks**: Generate safe driving paths 4. **Control Networks**: Execute steering, acceleration, and braking commands

These networks are trained on massive datasets collected from Tesla's fleet of vehicles, using techniques like: - Supervised learning on labeled data - Self-supervised learning - Reinforcement learning - End-to-end training