Earlier quoted context omitted.
This isn't reversing the question - it's asking an entirely different question. My question was about the value of the data to a consumer. Presumably, this data is a mixture of location history, sensor/actuator logs (maybe human readable?), and maybe various state data for ML algorithms. Depending on the human "readability" of this data - how could someone without proprietary knowledge find any value in it? That's my…
But Tesla's defense is not that the data is in a proprietary format that can't be decoded. And even if it were, are you suggesting Tesla logs and stores data solely in a non-industry format for which there is not an ETL function that turns it into something less opaque? And what do you base this speculation that Tesla does something so strange? Because Tesla has a machine-learning heavy reputation? Google does far mo…
I never said it was. I'm not sure why you continue to try to come up with unrelated arguments to push your agenda in a discussion completely unrelated to what you're talking about.
"And what do you base this speculation that Tesla does something so strange?"
Because educated speculation can lead to positive and constructive discourse? I have a fair amount of experience in the ML and CS field and I could imagine a situation where the data is in fact difficult to analyze.
Also, logging geolocation data is a fair amount different than logging neural weights or other types of ML data. Without knowledge of the types and composition of ML algorithms those numbers simply won't help you. Which was my point to begin with.