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Comment by sashank_1509 | Hacker News Reader

Is it plausible they can use the large GPT model, to distill a smaller car driving model only from it and then run that onboard. Seems like that will solve all your issues.

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I'd be very surprised if at the very least Tesla/xAI aren't actively investigating that already. The general purpose intelligence to deal with complex new situations will never fit into a pure driving model, because it will need to understand human behaviour on a level that goes way beyond what people do on a road. I'm pretty sure that an eventual level 5 system will look closer to GPT than any traditional driving model. The biggest issue is indeed latency and we probably won't see it in real cars until a multi-trillion parameter model like GPT-6 fits on a simple ASIC that can run in an affordable car. Right now a stack of B200s that can run a frontier intelligence model costs more than a car itself. But a GPT-8 running something like 20k tokens/s on a Taalas HC5 will almost certainly be able to drive a car under real conditions.

I imagine a mix of models would make sense - GPT controller to make overall decisions and override things (let’s avoid the dark alley it looks dangerous), driving model to handle what humans do when they are just driving and not thinking about it, maybe some other models too

This is what Tesla does. Elon Musk has been selling FSD for more than 10 years and a huge chunk of Teslas have computers too old to run the current best model, which IIRC is already transformer-based.

Because having to offer upgrades to so many cars is expensive, Tesla puts a distilled model on older cars that performs worse and has no redundancy.

Time will tell if he can get away with this (hopefully not) but you are describing a system that's near-L4 and already exists today.

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