Elon Musk Says Tesla Car Fleet Potentially Biggest Inference Computer By Far; What That Could Mean



With the just arrived age of GPT, the need for massive computer power has also arrived. Many opportunities have been unleashed, but the amount of compute necessary to solve really big problems is a limiting factor. Well, one solution would be to use your idle computer in your car, tied together with 5.5 million other idle computers in Tesla Cars. Brian Wang explains.

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14 thoughts on “Elon Musk Says Tesla Car Fleet Potentially Biggest Inference Computer By Far; What That Could Mean”

  1. I think many in the Tesla community underestimate the bond that many Americans have to gasoline powered cars (& especially trucks!). Car culture is in our blood, it defines us. The roar of a V8 puts a smile on any red-blooded America's face and the smell of gas & even exhaust is familiar, perhaps even pleasant in a way. It seems like Americans are digging in, especially conservatives. Hybrids are gimmicky but will be a gap fill for many. If Elon wants to win over conservatives he needs to make cars that aren't total spaceships or computers on wheels. Make a normal looking BEV sports sedan, truck & minivan with some analog-style controls. Make a "Hal switch" that can physically disconnect FSD, internet etc so we dont fear that Obama will shut down our car if we post a MAGA meme. Make solar & powerwalls affordable & widely available so more people will attain true energy independence. Continue to champion free speech and liberty. Maybe do a hat tip to American car culture: show up at classic car shows, go to a NASCAR race, monster truck rally etc.

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  2. It's not just the cost of the electricity
    It's the cost of the heat. Which can be very taxing on you hardware. Probably not worth solving all the math problems, if you are replacing your hardware every few years or passing on hardware damage in the used car market.

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  3. Hybrids will succeed for a time, but once people realize how much more they are still paying for fuel and added complexity vs an EV they will then move over. It’s a good transition step for many.

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  4. I wonder if there are problems in "wealthy sectors", like energy generation and use, military, pharmaceuticals, etc., where there is currently a solution, but not very accurate. Having a whole load of compute could make the solution more accurate, and potentially save millions. An example could be calculating the optimised use of grid infrastructure, so that the existing is used to its full potential, before upgrading, which would cost $billions….

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  5. There's no reason to suppose the Tesla will pay its customers for the use of the processors in their cars. ALL Tesla vehicles already function as parts of a distributed computing system. Tesla has been using them without compensation from the beginning to develop FSD features that aren't standard. FSD has to be bought as an extra cost option. So the conditions of sale for driver assistance very likely has language that allows them Tesla to make program changes, download data, and do anything with data- in the vehicle or elsewhere – that isn't linked to the user personally, that might directly or otherwise enhance the driving experience. That could include anything that helps Tesla to continue to be able to provide (unspecified) services.

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