[icanhackit]

> My comment is saying it doesn't matter if they wanted to use it for something as trivial as ECU updates

What I'm saying is that you've completely missed the OP's point: The advantage Tesla has in the autopilot space is that they are able to have hundreds of thousands of real-world test units for their autopilot systems by running the neural net in parallel with the driver inputs (i.e. shadow mode) versus companies that at best have a few hundred test units thus limited material to improve/iterate on their deep learning models.

A metaphor for the situation is Apple playing catchup in the AI and voice recognition space to Google because Google had years of material and huge sums of it to build their deep learning models while Apple had comparatively little. The underlying technologies used by either company might be very similar, but you can't throw hardware at the problem to play catch up -- you need that real-world input/learning material for the deep-learning model to be robust.

[BoorishBears]

I haven't completely missed any point, you just seem to be insistent on missing mine.

My point is the way that Tesla has gained this, using consumer vehicles as testbeds, not just for collection, but for actual running code in charge of managing peoples lives is utter nonsense and traditional automakers are choosing to stay away from it.

I mean, this isn't even a hypothetical, we've literally seen it happen, AP regressions where a lane transition your car was taking fine one day suddenly sends your car aimed at a concrete barrier!

You can call them slow, or whatever you want, but thank god the real auto manufacturers are not so flippant about the value of human life.