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We see FSD v12 in 38.10
What is the guess for the purpose of 44.X?
Once it is ready, won’t us on 38 get 38.10?
Who and why does anyone want 44.X?
2023.44 contains non-FSD software changes.

2023.38.10 is a test version that went to employee cars only. There is almost no chance of this, or any 2023.38.X version containing V12 will go out to cars on the production branch. There is a remote possibility that cars on the development branch could see V12 on 2023.38.X, but that is very remote, IMO, and likely to be limited to the OG testers.

The current rumor is that Tesla is targeting V12 for the Holiday Update. If this happens (also a remote possibility) then it will go out on a later version, like 2023.48.X.

Last year, the Holiday Update was on 2022.44.X. But, since 2023.44.1 is already going out, the Holiday Update is more likely to be on 2023.48.X. In any event, at best, V12 will be packaged with whatever release contains the annual sack of toys (lumps of coal?) from Elon.

More likely, V12 will miss this year altogether and be on a 2024.X version. One month is very little time to gather feedback from employee cars, retrain a new version to fix issues and retest. And, it's likely that there will be multiple iterations before release.

But I would be happy to be proven wrong.
 
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In practical terms it means that Tesla is no longer hand-crafting the heuristics to control the car. Instead, they're using a neural network, which can be trained to figure out control heuristics by, well, instinct. Instead of a bunch of software engineers working long and hard for years on ways to create clever heuristics that cover every conceivable scenario, the system can be told "Do it like this" and then be shown zillions of scenarios of "proper driving". The system just figures out how to respond to scenarios.

The outcome that we're all hoping for is that FSD will break free of its log jam of poor decision-making. The hand-built heuristics had reached a peak and were no longer providing much in the way of improvements. We want neural networks to inject some machine learning magic that turns FSD from a frightened teen driver into a competent chauffeur.

The end-to-end term is used to say that all of the steps in the decision making process are now neural networks. The current solution is many steps of neural networks, but the last step is not. The last step is C++ code hand-written by engineers. Once Tesla has replaced that last step with a neural network, it'll be entirely neural networks; all neural networks from start-to-finish - end-to-end.

There is also a use of that term which means that the entire decision making process is covered by one big neural network. Folks argue about which one is really end-to-end and which one Tesla is pursuing. I think the consensus is that, for now, Tesla is still going with a bunch of steps, but all of them are neural networks.

There are two ways to make a decision:

  • A clear algorithmic way of deciding and doing things.
- If it is this situation then do this thing. If it is that situation do that thing.​

  • Another way is, by learning from actions of many others.
- When a light turned green, what did others do. 99.9% of car started moving through intersection. Okay then I will do the same thing.​

- On the freeway, when an another car is merging and is slightly ahead of me with same or higher speed, what did others do? well over 95% of cars on the right most lane slowed down for the other car to merge. Well that is what I will do here.​
How does this type of stuff affect the OEDR? For example in the v12 clip that Elon posted to Twitter, his vehicle at one point exhibited the same red light issues that have existed for many versions (since inception likely) where the vehicle can sometimes see an adjacent green light controlling another lane, mistakenly assign the green light to its lane, and tries to proceed on what is actually a red light.

I have an idea of what the theory is, I don't know what any of this means in terms of real-world performance or how anything will be different. Or why Tesla is out there validating with Chuck's ULT if they aren't manually tweaking however they manually tweak stuff to make it work, rather than all of this being crafted by end-to-end AI. And if the system needs correction for something like Chuck's ULT because the behavior isn't what's expected or wanted, how is the behavior corrected and how does that differ from the corrections that would have been made before v12?

If the process towards identifying and making corrections is different, is the correction itself any different? Or is it just the same thing in the end?

I dunno, it'll be interesting to see because right now it feels like taking a different path to arrive at the same destination. Really hoping it's not just more of the same.
 
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I have an idea of what the theory is, I don't know what any of this means in terms of real-world performance or how anything will be different. Or why Tesla is out there validating with Chuck's ULT if they aren't manually tweaking however they manually tweak stuff to make it work, rather than all of this being crafted by end-to-end AI. And if the system needs correction for something like Chuck's ULT because the behavior isn't what's expected or wanted, how is the behavior corrected and how does that differ from the corrections that would have been made before v12?
Classic NN training would mean adding training data to correct any problems. You can also “over sample” edge cases to emphasize them.

I don’t know what they actually do. Elon has the habit of exaggeration - he also doesn’t distinguish between end goal and the current practical situation. He might say “end-to-end” - but the team might introduce some manually coded tweaks.
 
I have an idea of what the theory is, I don't know what any of this means in terms of real-world performance or how anything will be different.
We don't know, which is why we're holding our breath while Tesla goes through the process. We don't know what the vehicle hardware is inherently capable of, and we don't know how much of that capability Tesla's engineers are capable of exploiting. If you're trying to get amped up in anticipation of it, forget it. There's no point in doing that now, just as there has never been a point in doing it in the past. Just wait and see what they pull off.

I think the worst case is that HW3 is worse at driving than the engineered heuristics, that HW4 is slightly better, and that they have a plan for HW5 that should do the trick.

I think that the best case is finding that HW3 can pull off highway level 3 autonomy, with good level 2 on city streets. That HW4 is knocking on the door of level 3 autonomy for city streets, given good enough driving conditions (e.g. not during snow or heavy rain). Then Tesla will announce their plans for HW5, which they assure us will provide level 4 everywhere, but which will end up just making a solid level 3 system.

But HW6...
 
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Last year, the Holiday Update was on 2022.44.X. But, since 2023.44.1 is already going out, the Holiday Update is more likely to be on 2023.48.X. In any event, at best, V12 will be packaged with whatever release contains the annual sack of toys (lumps of coal?) from Elon.
Holiday version will be 2023.x.25. That’s what they have done in the past. Could be 44 or 48.
 
If the process towards identifying and making corrections is different, is the correction itself any different? Or is it just the same thing in the end?
The potential for end-to-end is more "automated" fixing of issues as any intervention can go through the streamlined / no-engineers-required process of auto-labeling and training. There can still be special focused effort to take on specific issues like running red lights or unprotected lefts, and this could be in the form of curating data collection for these scenarios, and even this can be relatively low engineering effort than before as 12.x's design hopefully is general enough to avoid code or neural network architectural changes.

Both these processes for end-to-end rely primarily on human examples of expected driving, so another benefit of 12.x should also be that it should drive more comfortably / human-like than 11.x.
 
Could mean V12 is closer than 2nd half of next year I was thinking.
Or is not what you thought!

V12 Beta very much seems like it is going to be a small incremental change.

I’m just surprised with the small change they’ve apparently made in V12 Beta that they have been able to so quickly reduce (apparently - since they are doing limited release) regressions - seems like the planner would be particularly tricky to swap out. I guess it may be a very limited replacement for now - perhaps only certain planning tasks are being transitioned first? Seems tricky to do it piecemeal - but perhaps easier than the alternative, where they would actually have to remove most of the traditional code (seems very doubtful at this point - likely just an aspirational thing that Elon and Ashok have talked about - maybe that will happen in v12)!!!

I wonder when they will do end to end? Perhaps that will be v13? Or maybe v12 (not v12 Beta)? Now THAT seems like it could take a while.


That is, it isn't involved in the autonomy system

I sure hope it is! Seems like Cybertruck could be extremely hazardous otherwise (very large blind spot, especially at high ride heights). Since they have to stitch images anyway, it doesn’t seem like adding another image before feeding it into the NNs would require anything special, at least not special beyond what they already do. I don’t know how different the software is between S3XY or how they manage it, but clearly it has to be able to adapt to different sensor positions.

Doesn’t seem like HW4 is defined by how many cameras it has.
 
It's possible the training for V12 creates a "base model," which can then undergo "finetuning." The base model can take months to train, whereas the finetuning can be done multiple times a week.
Yeah, this would likely be the case for the foundational / world model generally understanding how things behave based on the cameras and other inputs. So adding say an extra camera with "HW4.1" would probably go through a much longer process of collecting video then training for the model to internally understand how to stitch in a front bumper camera. Similarly, differences in camera resolution and positioning will likely need some extra effort if there's a unified base model shared across all vehicles.

The finetuning step can be in the form of various outputs such as the CVPR examples of generating action conditioned RGB or panoptic segmentation, so presumably predicting driving control outputs is another finetuning task that is faster to iterate on than retraining a base model.
 
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V12 Beta very much seems like it is going to be a small incremental change
Just making sure, you're suggesting that the end-to-end livestream from August is a separate development path from what we'll get with 12.x because 3 months from demo to employee testing is not enough time to make things safe? Tesla had been working on it with enough confidence in the approach to present at CVPR in June, and from Isaacson's biography, Elon Musk tried it out in April and was impressed enough to focus resources on this approach for over half a year now.

Perhaps the red light confusion from the demo was a recent regression from additional training of other situations such as maintaining flow with adjacent vehicles, but even then, Tesla now knowing this is a potential issue with end-to-end probably spent extra effort to make sure it doesn't regress again. Are there so many other issues that would prevent end-to-end 12.x deployment to customers?
 
Are there so many other issues that would prevent end-to-end 12.x deployment to customers?
Who knows !?

In particular, how good is Tesla’s test suit and simulation ? With any major change this is always the issue. You have to start from scratch and test everything and anything could be bad …

When we get V12 I’m going to take things slowly and test my regular routes in low traffic before starting to use regularly and be extra-extra vigilant.