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TeslaTSLA & the Investment World: 2025

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Probably the wrong forum for this...but does anybody understand why a different form factor vehicle (like Cybertruck) is such a difficult addition?

In my admittedly non-AI-familiar brain: I can understand why camera locations need to be at least similar from one model to the next...but beyond thatit seems like the model used to drive the car could/should include parameters related to vehicle geometry (lengthwidthheight)where that geometry is relative to the camerasand probably also some vehicle dynamics information (how it acceleratesdeceleratesand turns given some software input). It seems likebeyond thatnot much training should be needed...much like a human -- a new car is a bit unfamiliarbut you get used to it within a few mileswhether it's a Mini Cooper or an F-250.

I could see the Cybertruck adding some addtional complexity due to the rear-wheel steeringsince that's a dynamic variable that wasn't present before. I could also imagine that perhaps having a completely different power steering setup like Cybertruck could add some extra need for different code...but even those seem rather minornot the sort of thing that needs an extra year of training across thousands of vehicles.

To meit seems likeat least in an ideal worldall of the vehicles with the same AI hardware and camera setup should be able to run the same codewith just slight modifiers based on the geometry and dynamics notes above.

Sorry for off-topic...just looking for a quick few sentences explanation/theorizingsince this came to mind after AndrewZ's post.
I'm no expertbut I am an ex AI coder from ages back and think about this a lot :D
The thing iswhen you go end-to-endyou are basically ignoring a lot of data that you might *think* would be helpful. End-to-end NNs means that the car is literally driving like a human. I drive a model Ybut have no idea how wide it isor how long it isor what its exact turning radius is. The way I drive it is the way any human drives a new car when they buy it: They drive VERY carefullyand gradually push the limits until they get a near miss with a bumper or a wing mirrorand at that point you have 'learned' how wide and long your car is. You probably also make use of gauging shadows and reflections etc.

I doubt that there is anywhere in the FSD code where it is helpful to just plug in the dimensions of the vehicle. Ditto the stopping distances at speedsor even the turning circle.

In theory you could stitch together a whole bunch of neural networks and have some glue-code that links them and gets involved in the decision makingand MAYBE you could include a system for specifying vehicle data there. To some extent Tesla MUST be doing this to ensure the vehicles obey laws to the letter where humans do not. I suspect that the actual arrangement of code is a bit hacky and a bit of a messas all large codebases become...

So TL;DR: The cybertruck was probably running standard FSD in shadow mode for a whileand doing so cautiouslytesting the limits. I suspect Tesla want to first check no weird anomalies are presentand also only enable FSD for a vehicle when they have 10,000+ miles of shadow FSD metrics to sanity-check against.
 
"next year for surewe’ll have over a million robotaxis on the road." is non-committal?

I don't think that hyphenated word means what you think it means.




If you mean driverless then not only do we not know thatwe know for a fact they're NOT doing that as they don't the proper permits to do so in California.

(unless by private you mean entirely on private property- which is pretty pointless for telling us anything about public road capability or safety).
Elon said "Robo-Taxi hardware capable vehicles" or something to that effect. That also ended up not being true but still different than what you imply
 
In the long-term yesbut realistically the order that keeps the company alive to get to this FSD dream is: carsmegapackspowerwallsand then FSD software sales.

I'll go on record with others that againFSD won't be ready in 2025. If it isI'll be selling my shares and gone from the site! :)

Happy New Year!

FSD won't be ready in 2025? What do you mean by "ready"?
 
It’s never been difficult for Tesla to pivot on anything. Ever. Dropping Mobileye was a pivot. Dropping radar was a pivot. Going vision-onlydespite many cries from so-called “experts”was a pivot. Dropping heuristics and going end-to-end was a pivot.

Each of these was a massive change in approach. Tesla does not fall victim to the sunk cost fallacy.

Not only is Tesla the one creating and setting trendsthey’re also among the fastest pivoting companies in the world.
I didn't disagree with your postas I think the intent of what you said is valid: Tesla has demonstrated many times they are willing to make the decision to change course despite needing to start from at/near square oneabandon plans/effort/sunk costtake on a new roleetc...

But I think to suggest it hasn't been difficult doesn't acknowledge that doing so (often successfully) is what sets Tesla apart. Making the decision no doubt has been difficult... and then executing on that decision is a tremendous effort... the fact that from the outside it often doesn't seem so is a testament to how hard they work.

Seats not up to par? We'll make out own.

One of the leading autonomous system OEM's equipment/offerings not up to snuff? We'll not only build our own systembut we'll spin our own custom neural net CPU ASIC's to do it.

Availability of compute for model training not available/cost-effective? We'll build our own supercomputer

Electric power steeringsteel panel forming equipmentcell manufacturesingle piece casting processesetc... the examples go on.


Soin essence I agree with youjust wanted to point out that indeed it is precisely the difficulty in pivoting that makes it so amazing.
 
Training a perception and autonomous driving neural network requires tons and tons of video data of driving. Much different storymuch larger moat. Many petabytes of data must be uploaded from the field to gather the data to do something like what Tesla’s doing. Who else can do that? Not many.
... but.... can't the stealing Chinese steal the curated and trained data directly from Tesla? They have done it with impunity in the past. Cisco and Tesla comes to my mind.

Why steal the raw material when you can steal the finished product.
 
... but.... can't the stealing Chinese steal the curated and trained data directly from Tesla? They have done it with impunity in the past. Cisco and Tesla comes to my mind.

Why steal the raw material when you can steal the finished product.
In theory yes. But I don't think stealing petabytes of data is an easy task. Tesla is not foolish enough to make it available to a public networkand you can't walk into the server room with a 50 PB jumpdrive ;),
 
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I didn't disagree with your postas I think the intent of what you said is valid: Tesla has demonstrated many times they are willing to make the decision to change course despite needing to start from at/near square oneabandon plans/effort/sunk costtake on a new roleetc...

But I think to suggest it hasn't been difficult doesn't acknowledge that doing so (often successfully) is what sets Tesla apart. Making the decision no doubt has been difficult... and then executing on that decision is a tremendous effort... the fact that from the outside it often doesn't seem so is a testament to how hard they work.
Not saying that pivoting is easy. Just that Tesla has no problem committing to a decision to pivotvery much because Elon is acutely aware of sunk cost fallacyand his DNA is built on the concept of "fail fastfail oftenand iterate."
 
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Excellent work by Jordan as usual. If you want to know why the Cybercab only has wireless chargingthis has many answers. It shows how thoroughly Tesla has thought about the overall cost structure of the robotaxi business.


Nah. The real experts we have floating around on the forum will tell you Tesla has no real cost or scaling advantages over the likes of Waymo. :rolleyes:
 
I don't see this thread on the TSLA Investor Discussions page. I could only get to it clicking the link @ggr posted
Que?
Screenshot 2025-01-01 at 12.43.58.png
 
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