Tesla is on the road towards full autonomy, building next-generation self-driving capabilities on a unified neural network trained on massive amounts of visual data collected from its fleet. But what does this mean and why is it important?
At its core, Tesla’s approach boils down to this: trains gigantic deep learning models directly on raw sensory data from cameras and sensors on Tesla vehicles out in the real world. This stands in contrast to many self-driving initiatives that rely on detailed 3D maps as a key input to guide autonomous vehicles. Tesla’s map-less approach has advantages – it allows the system to navigate roads and situations it hasn’t seen before. However, it requires immense amounts of data and compute power to train robust models.
To enable this video-based autonomy, Tesla AI teams are pushing the boundaries of neural network scale and efficiency. Engineers train models with millions of video clips across thousands of GPU servers in Tesla’s in-house supercomputer, one of the world’s largest AI training clusters. These models ingest frames from fleet videos to directly output driving commands – no intermediary steps. Such “end-to-end” networks learn holistic real-world driving capabilities beyond what humans could code manually.
However, effectively leveraging such enormous data and models comes with immense infrastructure and optimization challenges. Tesla AI researchers invent new techniques to parallelize network training over many devices and optimize how models store and access data. What hardware and code efficiencies allow such giant networks to drive autonomy in real-time within the computing constraints of a production car? These questions are at the cutting edge of Tesla’s self-driving initiative.
The progress Tesla makes towards full autonomy not only has immense business impact but also stands to enable groundbreaking applications of AI. As scientists push autonomous driving along, they drive breakthroughs in core disciplines like computer vision and reinforcement learning. Tesla’s self-driving pursuit, while ambitious, accumulates research that spins up future AI.
So will Tesla lead the charge in true autonomy? Tesla AI team share more job on X/Twitter about AI Research Scientist, Foundation Models, Autopilot AI, Location in California.
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