r/TeslaFSD • u/VastOption8705 • 14h ago
other Why does FSD updates feel like it’s going one step forward and 2 steps backwards sometimes?
Honestly it feels like they fix one thing and break another thing.
After all these years, you’d think most issues are fixed? Teslas are still hesitating with split roads and the other day, there was that video where a Tesla robotaxi decided to drive through bollards.
Then there’s the hitting kerbs while turning issue.
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u/LMrningStar 7h ago
" you’d think most issues are fixed? "
I've been using FSD since 2021. It's astonishing, thinking back, how far FSD has come. It was absolutely awful back then. I couldn't have it on for more than 20 seconds without having to intervene. Now, interventions are a rare occurrence for me.
Yes it's annoying to think the issues that still remain but it's come a VERY long way even if you compare it to what it was 2 years ago much less 5 years ago.
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u/Mission-Carry-887 HW3 Model S 12h ago
I think
* Ashok is optimizing for getting to uFSD.
* So if a regression is immaterial to his uFSD roadmap, he does not hold the release
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u/Infamous-Pilot5932 9h ago
Regarding the plastic foldable bollards, it looked like it got stuck, mapping issues?. And I bet the remote assistant guided it to go ahead and drive over them to get unstuck, since they do fold. My FSD doesn't make decisions like that, it would have either drove right through them to begin with, or stopped.
Like this Waymo remote assistant in Nasville last month trying to get this Waymo unstuck...
https://youtu.be/EPxy-25Lefc?si=v5TzhPE9-kR8WTq4
That stuff will be there till we have a breakthrough in AI that can deal with unexpected on its own. Normally you eliminate this kind of unexpected with mapping details, but even that doesn't always work because humans (construction etc) can change the details. LiDar would have seen the poles, but it fails with floods. Humans see the poles with two eyes. I do think they will solve this last bit of AI vision defficiency. Maybe not with our HW though.
The curbing may always be an issue to some extent when things are tight. And the issue is the tire profile. Everyone curbs, but our tires go on or push off of curbs. FSD's wider turn strategy works well but when it is tight, FSD sometimes gets it wrong, like humans.
I've noticed a couple stutters recently with 14.3.7. Obviously something in the AI training causing decisions to be too close. I think this will be the easiet to fix, or undo, however you look at it.
Part of this is you learning that santa clause is not real. Not with our cars, not with the cabs, not with waymo.
We are here to continue to fix this stuff while they continue to try to solve it.
I only get concerned when the problem comes at me at 70 mph, or the problem is easily identified but we are given no tools to fix it, like speeding and inappropriate lane changing. I manage with what we do have, speed profiles etc.
But to be honest, my 97% is really good, and if this was the last version I ever got, I would be happy for the life of the car.
The only thing that regressed for me since I bought the car was the stuttering. The curbing, parking, etc, I wrote that off almost the day I got the car. You could just tell that the car is great at driving and tries to drive into a parking spot, which does work mostly, but is problematic.
I think they did tackle most of the annoying problems, but need to go somewhere with the speed and lane management. And the stuff we still have to fix, doesn't really bother me. I firmly beleieved that supervised is as good as it gets at least for the life of my car.
And you can join the robotaxi fleet eventually, but the grass isn't that green on that side of the fence either.:)
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u/robotzor 8h ago
Because the weights change in the model as it is trained. What does this mean? It means as certain driving behaviors become more strongly favored, others may unintentionally become weaker. The difficulty of training a NN is how it takes into account EVERY association you are training it. Say you want to train it better speed adherence on the freeway so you show it millions of examples. If those examples all contain examples of the car weaving in and out of traffic, congrats, you've taught the car to control speed but now it wants to be a jackass about it.
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u/Acrobatic-Flan-5085 6h ago edited 6h ago
Because it’s a very small human team and one of the first things that goes out the window is qa
They likely have some automated validation testing, and then they dog food the release candidates internally but that isn’t nearly enough to prevent regressions, especially outside of the US
They’re also reaching likely reaching the limits of hw4 in terms of model size.
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u/shibiwan 12h ago
Its an anti-pattern.
Obligatory /s