They are already deploying the kinds of models talked about here in their FSD beta software (along with regular FSD/AP software) and they run just fine on curre

They are already deploying the kinds of models talked about here in their FSD beta software (along with regular FSD/AP software) and they run just fine on current FSD hardware in the cars with acceptable latency. Just because you need a monstrous supercomputer to train these models doesn't mean you cannot run inference on them on much more light-weight devices. Some reasons being: 1. Training requires them to make use of ridiculous amount of data which requires large GPU compute + RAM and super high bandwidth to keep the GPUs fed at all times. Backpropagation requires a LOT of bookkeeping that adds on a lot of RAM requirement at train-time. 2. Inference is a lot easier. You just need to worry about keeping up with your 8 cameras and running them through your network. You also aren't calculating any gradients and dealing with needing to do any of the bookkeeping for backpropagation so you need a LOT less RAM 3. There are a ton of tricks you can do to make a trained network a lot more efficient for inference such as lower precision models (int8 or in their case, CFP8), network pruning, compiler tricks, etc. It is quite impressive that they've managed to fit all this into their current V3 hardware. That being said, they are definitely starting to really hit the limits of V3 and in the long-run will likely need to upgrade the FSD hardware on newer cars. They are probably trying to avoid having to provide a retrofit for all cars in the fleet as that would be prohibitively expensive.