The Tesla FSD Computer Executes Autonomous Driving
At the core of Tesla's self-driving vehicles beats a key component: the Full Self-Driving (FSD) computer. This system, known internally as Hardware 4.0, acts as the car's artificial intelligence brain, tirelessly processing the data captured by its sensors to navigate autonomously. Its mission is to interpret the world in real time and decide how to move through it 🤖.
Architecture Centered on Neural Processing
The power of the FSD computer does not reside in a conventional processor, but in multiple neural processing units (NPUs) designed by Tesla. These NPUs work redundantly to ensure the system never fails. They are optimized for a single purpose: executing the complex deep neural networks that form the autonomous driving software. This dedicated architecture enables handling an astronomical number of operations per second, which is essential for analyzing high-definition video, recognizing objects, anticipating their movements, and plotting the vehicle's route without interruptions.
Key hardware features:- Redundant processing: Multiple NPUs operate in parallel to guarantee absolute safety and reliability.
- Specific optimization: The silicon is custom-made to efficiently run driving neural networks.
- High performance: Capacity to process the equivalent of eight high-resolution video streams simultaneously.
The real challenge is not just seeing the world, but understanding and predicting it in a fraction of a second. That's what the FSD computer does.
Real-Time Environment Perception
The system does not just see; it builds a model of the world. It integrates and synchronizes data from the eight cameras surrounding the car, and in some models, also radar and ultrasonic sensor information. With this data, it generates a dynamic 3D representation of the environment, often called "vector space". This digital map includes the position, speed, and probable trajectory of other cars, pedestrians, signs, lanes, and any obstacles.
Functions of specialized neural networks:- Detection: Identify the presence of all objects in the scene.
- Classification: Label each object (car, person, bicycle, cone).
- Prediction: Calculate where the detected objects will move.
- Planning: Decide the safe trajectory and speed for the vehicle.
Local Computing and the Future of the System
All this computing power happens locally, within the vehicle itself. This approach is called edge computing and is crucial because it eliminates dependence on a stable internet connection and reduces latency. While Tesla is already developing a successor to this hardware, the current FSD computer demonstrates how dedicated artificial intelligence can perceive and react to a constantly changing environment. It puts computing power into perspective: while a car computer processes multiple video streams to dodge obstacles, sometimes we have trouble getting the router to work 🚗💨.