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As I recall the timeline he didn’t become an advocate until Tesla ran a profit in the Q3 earnings call. I may be mistaken.
Cramer switched sides just before his birthday last year, which was February. It was discussed here in Main. He cited his daughter's Tesla trip from WA state to CA and how much she loved the ride even though she's not a "car" person.
 
In fact there were a lot of Tiger Woods posts yesterday. They didn't make the cut because they were too far OT.

If Woods's first name had been Cathie they would have stood a better chance.
Because I doubt that Tiger is the first name on his birth certificate, perhaps it is Cathie.
 
.......

I'd be curious about the "many other things" but just the transition to 360 degree 4D makes me excited about the next iteration. I won't be surprised if the timeline is a tad too optimistic but I don't care. More than ever, this is now a matter of "when", no longer "if".
The decision to allow some of the FSD Beta testers to post videos has really helped provide visibility on the actual status of FSD and the progress that is being made. Without this these twitter threads on next steps would not be happening and there would be no idea if things were moving forward or not.
 
So you think praising Tesla while shorting them is worse than spreading lies and deceit while shorting them?:confused:

Personally, I think he's done shorting TSLA and he learned an expensive (but eminently affordable) lesson. Up until recently he was spreading a lot of doubt about the viability of many of Tesla's initiatives. But I don't think he was being deceitful since he probably believed his doubts. :rolleyes:

Yes. I had to chuckle during his 60 Minutes piece where he details how he reads thousands of pages of climate change related materials and has experts in to further tutor him. Yet he can't read graphs of battery performance trends and understand it's only when they will be used for long haul trucking not if. Even smart people get their chance to be stupid occasionally.
 
I interpret it as simply first determining the pixels that matter (ie. Cars) vs those that don't (ie. Phallic shaped clouds), before focusing computational resources on those that matter. This conserves processing requirements, especially when they are going 4D (time).
He didn't say how the focal areas are determined but ideally they will be dynamic, based on detection of a perceived threat, or unsatisfactory confidence or other criteria. This would on the one hand mimic human behaviour but with potential for super-human performance. The car can "zoom in" on a part of the image when it's not sure if something has been correctly identified.

I'd be curious about the "many other things" but just the transition to 360 degree 4D makes me excited about the next iteration. I won't be surprised if the timeline is a tad too optimistic but I don't care. More than ever, this is now a matter of "when", no longer "if".
I am not sure how dynamic based on perceived threat would work with neural networks. The weights are the same, ie static and the architecture is also static. How would you do this dynamically?

Zooming in is an interesting idea. They could have one first low cost neural network that decides which regions that need zoom. Then run different neural networks with different resolutation on the images with the same output format. Then stitch these together. But imo this seems like really bad feature engineering which we have been moving away from and to run this on a fixed runtime in an embedded control system seems like a terrible idea. And the number of neural networks that would be needed to train, store and load would be huge...

If you have any idea how this would work, explain it!

I think they will crop out the ego vehicle before they are input to the neural network, not any cropping while running the neural network.
 
Alan Mulally, former CEO of both Boeing and Ford ( and "Savior of Ford") is working with Churchill.

Mulally visited Lucid factory and determined they are not ready for a Spring release. Told Rawlinson there is no need to meet an artificial deadline.

Rawlinson agreed and moved release date from "Spring 21 to 2nd half of 2021."

This is almost a nothing burger.

Edit Plan still calls for 6k units delivered for 2021 and 20k units delivered in 2022.

https://www.bizjournals.com/sanjose...-says-first-deliveries-have-been-delayed.html

How was spring 21 an ‘artificial’ deadline?

Answer: It wasn’t. It was a ‘real’ deadline and they're going to miss it.

Almost a nothing burger? Is that like being almost pregnant? :confused:

Here’s my almost artificial prediction; they’re not making 6,000 vehicles before year end if the release date is 2nd half of this year. I base that on some almost artificial historic data from Tesla’s 2012 almost nothing burger of handing out the first Model S’s in June 2012 (or was it July?) and delivering 2,500ish? by year end only by very real herculean efforts. Rawlinson and company are made of softer stuffs than Elon and company.
 
Alan Mulally, former CEO of both Boeing and Ford ( and "Savior of Ford") is working with Churchill.

Mulally visited Lucid factory and determined they are not ready for a Spring release. Told Rawlinson there is no need to meet an artificial deadline.

Rawlinson agreed and moved release date from "Spring 21 to 2nd half of 2021."

This is almost a nothing burger.

Edit Plan still calls for 6k units delivered for 2021 and 20k units delivered in 2022.

https://www.bizjournals.com/sanjose...-says-first-deliveries-have-been-delayed.html

So they thought they were a month away from production, but Alan Mulally took one look and informed them they're actually 6-10 months away?? Right, nothing Nikola going on here..
 
How was spring 21 an ‘artificial’ deadline?

It is artificial because it was pulled out of thin air. There is no government mandate or industry standard for that deadline.


Almost a nothing burger? Is that like being almost pregnant? :confused:

No, it is like a milligram burger. That is almost a nothing burger.

Here’s my almost artificial prediction; they’re not making 6,000 vehicles before year end if the release date is 2nd half of this year. I base that on some almost artificial historic data from Tesla’s 2012 almost nothing burger of handing out the first Model S’s in June 2012 (or was it July?) and delivering 2,500ish? by year end only by very real herculean efforts. Rawlinson and company are made of softer stuffs than Elon and company.

Tesla began production in mid June 2012 and delivered ~2452

Tesla delivered ~22,300 Model S in 2013.

Here is my prediction: Lucid will beat both first year and second year Tesla deliveries.

Not because Lucid employees have bigger Johnsons but because Tesla had $400M for Model S program while Lucid will have ~$5B for Air program. And EV supply chains are deeper and wider today.
 
Small request....please all stop posting for a while....I am WAY behind.

Went for a nice long camping trip and only now can resume my staring at this forum.

B8AA288D-A4F0-4868-A21D-185E30E07BF1.gif
 
It is artificial because it was pulled out of thin air. There is no government mandate or industry standard for that deadline.




No, it is like a milligram burger. That is almost a nothing burger.



Tesla began production in mid June 2012 and delivered ~2452

Tesla delivered ~22,300 Model S in 2013.

Here is my prediction: Lucid will beat both first year and second year Tesla deliveries.

Not because Lucid employees have bigger Johnsons but because Tesla had $400M for Model S program while Lucid will have ~$5B for Air program. And EV supply chains are deeper and wider today.

looks like deadlines were for the SPAC/IPO ... money grab
 
It is artificial because it was pulled out of thin air. There is no government mandate or industry standard for that deadline.

No, it is like a milligram burger. That is almost a nothing burger.

Tesla began production in mid June 2012 and delivered ~2452

Tesla delivered ~22,300 Model S in 2013.

Here is my prediction: Lucid will beat both first year and second year Tesla deliveries.

Not because Tesla employees have bigger Johnsons but because Tesla had $400M for Model S program while Lucid will have ~$5B for Air program. And EV supply chains are deeper and wider today.

You’ve been very positive on this company despite the fact they’ve literally done almost nothing more than Faraday to this point even with all the advantages.

Full disclosure (if I haven’t been clear in the past): I believe Lucid is going to amount to a real nothing burger when the history books are updated.
 
Does Spring last one day?

What does Elon mean when he says X will be delivered by end of year?

No you don’t. You don’t get to make a new set of rules or hand wave things away when Lucid misses deadlines AFTER listing all the advantages to which they have because Tesla came before.

Lucid has ZERO excuses for missing deadlines, for being over budget, for getting anything wrong. They’ve consciously presented themselves as better than including that lovely little luxury chart you posted for us, have all sorts of Tesla employees who’ve done this before, bags full of money, EV supply chains, PR, etc...

No sir, they don’t get an almost nothing burger pass.
 
I am not sure how dynamic based on perceived threat would work with neural networks. The weights are the same, ie static and the architecture is also static. How would you do this dynamically?

Zooming in is an interesting idea. They could have one first low cost neural network that decides which regions that need zoom. Then run different neural networks with different resolutation on the images with the same output format. Then stitch these together. But imo this seems like really bad feature engineering which we have been moving away from and to run this on a fixed runtime in an embedded control system seems like a terrible idea. And the number of neural networks that would be needed to train, store and load would be huge...

If you have any idea how this would work, explain it!

I think they will crop out the ego vehicle before they are input to the neural network, not any cropping while running the neural network.

Don't take the "zoom" part too literally. The main advancement (at least I wasn't aware of it before) is the concept of a focal area. "Perceived threat" means, for instance, the car is about to perform a left turn with oncoming traffic, so left of center forward is an area to prioritise; the rearward facing part of the surround view is less relevant. Focal areas might get higher resolution input and/or more / different (neural) network resources. As you already stated, the important aspect is the optimised usage of available resources through prioritizing.
 
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So, were you able to locate any TMC user's mountain retreat while on this (wink, wink, nudge, nudge) "camping" trip? :)
Quickly before Market opens....it was more about testing Mountain ...err...equipment.
Boring stuff like high flying completely silent stealthy helicopters.
Deep ground penetrating radar...silly stuff like that.