David Lee summarized and analyzed Andrej Karpathy recent technical presentation on Tesla FSD.
Andrej indicated that Tesla already has over 1.8 Exaflop of processing power with 10 Petabytes of storage for its AI training computer. This is the training supercomputer that Tesla is using before the full Dojo system is set up.
Andrej also indicated that Tesla uses 221 event triggers for FSD.
Gave a talk at CVPR over the weekend on our recent work at Tesla Autopilot to estimate very accurate depth, velocity, acceleration with neural nets from vision. Necessary ingredients include: 1M car fleet data engine, strong AI team and a Supercomputer https://t.co/osmEEgkgtL pic.twitter.com/A3F4i948pD
— Andrej Karpathy (@karpathy) June 21, 2021
Tesla has spent 4 months solving depth analysis using only vision. They did this using a massive data set.
Tesla has a large, diverse and clean data set for FSD. You want a large amount of edge cases for training and this is where the 221 triggers were used to capture edge cases.
Tesla has captured and is using over one million edge case video clips.
They run the system through shadow mode many times. They can then test new software against the million edge cases to see if handling is being improved.
Vision the only scalable low-cost solution for self-driving.
SOURCES- Tesla, David Lee Investing, Tesla Daily
Written By Brian Wang, Nextbigfuture.com (Brian owns shares of Tesla)
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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