"they can’t effectively use past experience either"
While I'm unsure whether the on board computer of your autonomous car will be able to leverage past experience, I thought it was a forgone conclusion that the telemetry from all the cars on the road will be used to iteratively improve the core model. Which would then be dispersed as an os upgrade, effectively teaching your individual unit from the past experience from all the units on the road so far.
But it’s not memory. Currently you just show your neural net a million examples of a thing and it derives a function which, given an example input, minimizes the output error. That’s it. It’s not like “last time I caught a ball in a similar situation I moved like this, so let me start with that and correct based on visuals, audio, proprioception, and cognition”, all within 20 milliseconds, before you even fully understand you’re about to catch a ball. That’s not to mention that you also maintain the illusion of a continuous and static visual field, without even noticing, in stereo.
> last time I caught a ball in a similar situation I moved like this, so let me start with that and correct based on visuals, audio, proprioception, and cognition
There are types of neural networks (and other algorithms) that work literally like that. Just because a simple deep perceptron does not work like that does not mean no network does.
While I'm unsure whether the on board computer of your autonomous car will be able to leverage past experience, I thought it was a forgone conclusion that the telemetry from all the cars on the road will be used to iteratively improve the core model. Which would then be dispersed as an os upgrade, effectively teaching your individual unit from the past experience from all the units on the road so far.