Part 6/15:
Tesla's new approach integrates reinforcement learning, a technique where the AI learns through trial, error, and reward schemes in simulated environments. Think of RL as giving the car a virtual driving “game” where it tries various maneuvers, receives feedback, and improves over time.
Why RL?
Handling rare or unseen scenarios: RL allows the vehicle to explore thousands to millions of potential scenarios virtually, something impossible with real-world data collection.
Optimizing specific behaviors: By designing reward functions, Tesla can bias the system toward safe, smooth, and socially acceptable maneuvers like polite lane changes or proper intersection behavior.