[Research] A visual deep dive into Tesla’s data engine as pioneered by Andrej Karpathy.

TL;DR: Tesla uses lightweight "trigger classifiers" to detect rare scenarios when their ML model underperforms. Relevant data is uploaded to a server to improve the model, which is then trained again to cover different failure modes.


How Tesla Continuously and Automatically Improves Autopilot and Full Self-Driving Capability On 5M+ Cars. A visual guide: [How Tesla sets up their iterative ML pipeline](https://open.substack.com/pub/codecompass00/p/tesla-data-engine-trigger-classifiers?r=rcorn&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true)


P.S.: I spent several hours researching and preparing a visual deep dive of Tesla’s data engine as pioneered by …

andrej karpathy classifiers data data engine deep dive failure machinelearning research server tesla visual