April 21, 2024, 11:19 a.m. | /u/ml_a_day

Deep Learning www.reddit.com

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 5-minute 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 …

andrej karpathy classifiers data data engine deep dive deeplearning failure server tesla visual

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