The hidden system behind Tesla autonomy

Why feature stores matter more than the models Everyone thinks Tesla wins because they have better AI. That's only part of the story. The real edge isn't the model sitting at the center of Autopilot. It's the infrastructure that feeds it, the system that takes raw, messy sensor data from the physical world and turns it into something a neural network can actually reason about. The car doesn't see the road. It sees features. Every fraction of a second, Tesla’s system ingests camera feeds, vehicle speed, steering angle, nearby objects, and driver behavior. These are raw signals, useless by themselves. Feature store: transforming raw signals into structured input That data gets transformed into something the model can use, such as distance to obstacle, lane position, object classification, motion prediction. These are features. And every single braking decision, every lane change, every speed adjustment is made on top of them. Here's the shift most people miss Most ML teams are stuck aski