Navigating Scaling and Long Tail: VLAs, Data Generation, and Mapping Approaches in Autonomy

About this session

Deploying autonomous vehicles on public roads at scale demands high robustness of perception and mapping stacks. This includes handling rare, unpredictable "long-tail" scenarios - the ultimate stretch of perception systems. Overcoming these edge cases requires moving beyond traditional methods of perception toward a new generation of learned, scalable approaches. In this presentation, Doron Portnoy, senior staff ML engineer, Perception at Zoox, will take a technical deep-dive into how Vision-Language-Action (VLA) models are being architected and fine-tuned to interpret complex, unprecedented environments. Because training these intelligent models demands elusive, hard-to-capture data, he will also dive into how the industry is bridging the gap through innovative synthetic data generation and scene editing techniques. Last, Doron will anchor how spatial mapping approaches for L4 have evolved to unlock autonomous driving at scale.