Mercedes launched level 3 autonomous vehicles in Germany a year or two ago I thought?
https://www.caranddriver.com/reviews/a39966189/2022-mercedes...
https://www.caranddriver.com/reviews/a39966189/2022-mercedes...
All I have seen Mercedes do could have been accomplished by manual programming. But manual programming does not scale. Look at the progress Tesla made from FSD 11 to FSD 12. Nothing indicates that Mercedes is capable of this type of progress.
LOOK AT THE PROGRESS!!!1
And with FSD 34 it will be able to take the easiest highway exit ramp there is on this planet, Mountain View on HWY101, without killing you.
And what does "manual programming" even mean? Do you REALLY believe the xbox360-grade hardware in the tesla is doing AI inferencing? It's not. It's a heuristic.
The biggest problem is really how do you get to 10^n miles per disengagement, for n>=5. Waymo is kinda getting there, Tesla isn't anywhere near that today.
Getting there is really hard, because that's when you get all of the long tail events like bears, moose, wild turkeys, horse mounted police officers, costume conventions, pickup trucks carrying traffic cones and road signs, flooded streets, construction pilot cars, vehicles driving the wrong way on the highway, downed electric poles, NYC steam plumes, and tons of other scenarios. Highway driving in nice and sunny conditions is easy compared to that.
Do you know of any reverse engineering that proves that there really is running anything in regards of inferencing on the NPUs?
Also, just as you said - there are tons of corner cases in the real world, especially once you aren't on a 10-lane US highway which has been designed for monster trucks driven by 16 year olds (no offence) but one of the roundabouts of hell in Paris.
Where would the training data been coming from?
So, I have my doubts.
During summer, there is a red flower growing near the entrance of my parking garage. It constantly is seen as a red light, and the entrance of my garage is often mistaken for a huge truck suddenly magically appearing. Again: Nobody would use a Captcha these days: "Is this a red flower or a traffic light?".
Again, smells like heuristic. "Amount of red pixels in a certain form and spot".
Typically, inference in a machine learning context means feeding a model some input and looking at its output. I'm pretty sure that they are running some model on the vehicle that takes pixels as input and says this part of the image is a car/truck/traffic sign/lane line/etc. It might be misclassifying things (eg. the flower as a red light), but would still be running some kind of model.
As you point out though, the model only seems to do some simple object detection, but doesn't have much of an understanding of what it sees (eg. does it make sense that there would be a traffic light at this location). There are plenty of videos of it getting confused by all kinds of situations (eg this one from a few years ago https://www.businessinsider.com/tesla-fsd-full-self-driving-... ).
That and the fact that Elon has spent the last decade saying they're 6-12 months from actual full self driving.
Tesla - 0 disengagements.
MB - 50 disengagements.
This is not even fair comparison. MB can take all the responsibility they want when no one is going to use their system.