Tesla FSD Beta v9.0 Explained - 4D Surround Cameras with Neural Networks
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In this video 📝 we are going to talk about how Tesla's FSD Beta 9 works and what approaches they take to solve full self driving. We will see some examples of what the car sees when it's driving around and how they use its cameras, sensors, and neural networks to make predictions for the next action to take. We will talk about their total rewrite of their code to make the frames sequential where all 8 cameras are now connected together instead of doing predictions on each individual frame. This makes it possible to detect if obstacles are static or dynamic. We will see what the neural networks do and how they are used for different kinds of detection at Tesla. One of the most important things for Tesla's Neural Networks and their way to fully autonomous driving is their training process with their new 4D sequential frames from all 8 cameras at the same time.
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Tags:
#Tesla #TeslaFSD #TeslaFSDBeta #TeslaNeuralNetworks #FSD #AutonomousCars #NeuralNetworks #ComputerVision #DeepLearning
Watch video Tesla FSD Beta v9.0 Explained - 4D Surround Cameras with Neural Networks online without registration, duration hours minute second in high quality. This video was added by user Nicolai Nielsen 26 December 2020, don't forget to share it with your friends and acquaintances, it has been viewed on our site 5,692 once and liked it 194 people.