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Enhanced Summon = FSD Baby Steps?

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Active Member
Apr 25, 2019
Something I was ruminating on the other day...

I've heard a few people saying they think enhanced summon is a waste of time and a gimmick. However, I think Tesla are using it as a test-bed for FSD. Yes, enhanced summon is slow and clunky in some ways, but the set of problems it has to solve are *very* much related to the needs of FSD (traffic awareness, safely negotiating a complex mess of cars, signs, curbs etc. So Tesla can deploy early versions of FSD algorithms (not all of them, of course) but have them used in controlled conditions (slow speed, driver watching, only when holding down the common button etc). That way, they get the mass-testing from the Tesla owner base w/o the dangers/liability of testing on public roads at full speed.

Just a thought, wonder what others think?
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Absolutely agree. Anybody who thinks it's a waste of time apparently has a very short memory and can't recall any other "growing pains" with other technology, such as the early days of cell phones or computers or the first DVRs that could only hold 4 hours of video. I myself had a hard time imagining the utter paradigm shift the DVR has brought to television.

Granted, yes, enhanced summon is probably not what people were expecting, and it likely has no more practical use other than as a novelty to show your friends and family, although even this amount of usage will grant useful information for Tesla to improve their offering. On the other hand, using it in the rain is a potential practical application. I've also used it to come and pick me up when I have a lot of heavy items to carry. So it's not entirely useless.

I don't know how much of enhanced summon is directly applicable to FSD. Navigating a parking lot is quite different from navigating a road, although eventually FSD will have to navigate the last several hundred feet through a parking lot to pick up and drop off passengers, so in that sense it is important.
It seems that Tesla has already been chewing on the lowest of the low-hanging fruit (i. e. largely uneventful and predictable highway driving), and people using it against the explicit direction from Tesla are helping them train the neural nets on the ultimate goal (surface streets), so they've jumped to starting to collect data for the hardest and most chaotic environment (parking lots).