Digging Deeper into Differences Between Tesla Full Self-Driving & Waymo Driver - CleanTechnica

The article from CleanTechnica explores the fundamental differences between Tesla’s Full Self-Driving (FSD) system and Waymo’s autonomous driving approach, emphasizing that the contrast goes far beyond the commonly cited “cameras vs. lidar” debate. A key insight is that Waymo’s rapid scaling to new cities is primarily driven by its advanced training infrastructure, leveraging Google’s TPU (Tensor Processing Unit) pods and the JAX machine learning framework, which it shares with Google DeepMind’s Gemini model. Waymo employs a single large “Foundation Model” trained on diverse data from multiple cities, enabling generalization and faster deployment. This is complemented by a sophisticated simulation engine, Waymax, which allows extensive virtual testing to validate safety before physical fleet deployment, significantly reducing the timeline for expansion. The article highlights a philosophical divergence in how each company conceptualizes the driving task. Tesla’s “Reflex” approach treats driving as a biological process of vision and reaction, using an end-to-end neural network that processes