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Why should it take a long time to retrain AI? If a route suddenly changes - say, a detour is put up around a construction area - an AI car should notice that, after say 10 out of 10 sister cars in its AI network have changed their route, it should do the same. That ought to take maybe a whole half hour (if ten sisters passed by in that time frame).


Unfortunately this is not at all how AI works.
But before I explain, consider this. Has there EVER been a documented case where something like this has been demonstrated or even mentioned that it does work like this?
Second, in my Tesla I get a software update about once a month, maybe twice. It takes ~25 minutes. I don't get an update 30 minutes after someone puts up a construction sign.

Sure, if the cloud map data has has a road closure noted due to construction, then if I request a route to someplace it should warn me and/or route me on a different road. But this has nothing to do with "training the AI" in the car. Waze (Google) maps has been doing this for more than a decade and it really works better being not specific to a car vendor, IMO.

Convolutional neural nets work by training a model with a large dataset so that it can "generalize" how it operates -- i.e. not having to have exactly seen the same situation before but still be able to make the correct choices. Training the AI model controlling an individual car is a different thing than some cloud code or possibly some cloud AI looking at what current traffic is doing and recommending different routes.

Mike
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