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While we speculate about Optimus we should specifically examine the potential for generalized humanoid robots, especially when specific applications might typically be more efficiently and cheaply executed by purpose-specific robotic solutions, already ubiquitous.

Until there is competitive advantage to humanoid solutions what use is Optimus?
That is a serious question, not rhetorical. when we can answer that question we can seriously estimate total potential markets.
2 advantages I can think of already:

- Optimus would have the flexibility to be deployed on 10 different tasks as needed, vs just one for a specialized robot.

-Humanoid robot likely doesn’t need any special hardware or setup, since the world is primarily designed for humans.

Both of these probably justify an Optimus at 10x the cost of a specialized robot.
 
I agree. The balanced non-clickbaity part was excellent!

But there are other with regular news episodes - would it be OK to share your best ones when markets are closed?

Brighter with Herbert - interesting guests - and regular roundtable with other Hyper Bulls:


Electrified - news summary:


Randy Kirk - interesting guests and regular news summary:


Regular co-hosts with much knowledge such as Bradford Ferguson and Larry Goldberg are appreciated by me.
Rob has/had the best analytical work; others provide this too but not to the level of quality that Rob would provide, imo.
Rob did mention that he will still cover Tesla (e.g. the upcoming earnings call) but he won't put out content daily.
Let's hope he gives a crumb or two every once in a while.
 
The Bot Will Drive Future Valuation of Tesla

I've been pondering over this for a few months. We all likely came to Tesla years ago to route for the acceleration of a path to a sustainble energy future via electrified vehicles and energy products. That path is well on it's way now. We then looked excitedly at adjacent ventures, mostly robotaxis, as an exciting path to grow the company's value while aligned with greenfiying the economy.

But the path toward a software stack that is at a high enough level of fidelity to "turn on" for robotaxis nationwide may still years away. While FSD progress has been good and should improve with iterations of V12, we can't ignore the rigorous statistical nature that is required to be true robotaxi. While the FSD Beta Tracker estimates of about 100 miles / critical disengagement may be biased, we know it's not near the 10,000 miles / critical disengagement we need to get to to allow the car to work as a robotaxi. My best estimate is that the software needs to reduce interventions / disengagements by a factor of 10x at minimum, if not 100x to reach that utility.

I do believe that is achievable, but on what timeframe is less clear. I do know that I will rely more on quantitative metrics too the progress than simply listening to Youtubers alone. No bias in entries can mask a 10x improvement in rates. I am excited to see this happen over the next year or two. This can add a trillion dollars in valuation.

But what I've realized is that Tesla can deliver a subset of the eventual utility of the Bot in a much shorter time frame than we may be expecting. As I did my graduate work in modeling humanoid robotics, I am explicity attentive to how well it will learn a robust dynamic balancing policy to handle diverse environments. This is essential for allow the Bot to be used at a wide volume and scale of tasks.

But, does that even need to be achieved for a company to use the bot in a profitable manner?

Let me attempt to "skate where the puck is going".

Tesla has already illustrated a highly competent hardware package, even in the video shared yesterday.


We know even outside of Tesla, that there is an acceleration of progress on deep neural nets for learning and executing a range of manipulation tasks. These bots will be able to watch a human perform a task a series of times, then be able to generally replicate it.

When I look at the hardware and software stack, and integrate it with what Tesla's AI team will be able to execute in a year or two from now, I see the Bot being able to perform a decent variety of tasks, even if limited in locomotive capabilities.

Imagine, for instance, if the Bot was only trained to perform a set of tasks in a fast food restaurant. Identifying the types of pieces of chicken, combining the various sides as per what was ordered, and putting it into the bag and giving to the customer. The perception and dexterity capabilities are already there. The bot may not be able to perform all tasks in the restaurant, but I bet it could handle 1 out of 4 employees.

Employees are expensive. In California, minimum wage is $15 / hour, so for 12 hours a day, you will spend almost $70k per year for that work.

A company would easily pay $35k / year for a Bot to replace that human work.

There are 200,000 fast food restaurants in the U.S. alone. If they are purchased for $50k with 50% gross margins, that's 5 billion dollars in gross profit. We haven't even talked about any other works in the restaurant, let alone other jobs.

The potential profit of the Bot is simply orders of magnitude higher than robotaxis, and the threshold performance is lower for many jobs. You can have a Bot that ruins 5% of the food and still be massively profitable. A 5% hiccup in a car is unacceptable.

Given all this, it seems to be the Bot might be able to start generating revenues and profits before any robotaxi services. In fact I predict it. I believe Tesla Bot will generate a billion dollars in profits before robotaxis, and never look back.

And when this happens - maybe 2-3 years from now - the market will being valuing the future growth of that market and the numbers could be staggering - adding multiple trillions to the market cap.

Well said, I keep coming to this realization as well. Every time I think about the progress and potential of Optimus (from an investing point of view) it makes me giggle with glee. 😎
 
A few pages back we were discussing training Optimus using people who had expertise in the task being trained (an “expert shirt folder” was the example there).

It just occurred to me that I don’t think this is necessary.

Just as AlphaZero (AlphaGo? Can’t remember which) was set up to digitally play against itself for neural net training, which made it vastly better, you could also do this with tasks.

As long as you have a way of scoring each attempt with some sort of penalty function (using metrics such as time taken to fold the shirt, minimizing limb movement, number of creases, etc) you could set the bot up to train itself by doing tasks over and over again, and scoring the result of each.

So you start by getting the NN good enough to perform the task, then let it do the task autonomously over and over and over again. Because each attempt will be slightly different, it could evaluate the metrics of each attempt when finished (maybe a human is needed to score how good the resulting folded shirt looks), and save the “playthrough” for attempts that happened to “fold the shirt” better than its current capabilities.

Then, after 100 or 1000 saved runs, take the data and retrain the net. And boom: now the bot is better at the task.

Such a thing could be done nearly fully autonomously. Not an AI expert but based on my knowledge of it, I think this would work.

It’s analogous to how we get better: we do something a lot of times, and our brains pick up on small details that make the attempt better. We then use those little tricks the next time and get better at a task over time.

Yes it helps to be taught initially by an expert in some field, but the other way to get better is to practice something over and over again, evaluate each attempt, and use the tiny pieces of each attempt that were better than your best.

You just described a category of AI techniques called ‘Reinforcement learning’.
See Reinforcement learning - Wikipedia

More than a year ago I decided to enroll in a local AI course for experienced software developers, with as main motivation the desire to be able to make more sense of all the AI hype of the moment, and in particular to be able to better assess the capabilities of Tesla in the AI field.
As it happens, this weekend I have an exam for my just completed semester on ‘Reinforcement Learning’.
So far my main conclusion about AI is: ‘It’s all easier said than done’.
 
So getting away from the latest Elon crisis, what do folks think about the upcoming Financials? They set new production and delivery records, but how much will it affect the margins? What about EPS?

Or will other things revealed in the call and/or financial documents drive an upward change in the SP?

We're getting close, so if you're working on a prediction, please share!

(Paging @The Accountant ... I know it's tax time, but your input is always valued)

I no longer forecast earnings but I can offer some thoughts on Q4 vs Q3:

Potential Downsides:
- Auto pricing (price cuts continued on certain vehicles in certain markets).
- Regulatory credits for Q4 may not be able to match the robust number in Q3 ($554m)

Potential Upsides:
- Product mix (more S&X as % of sales and more MY vs M3 bring better margins)
- Lower COGS as the record production number spreads fixed costs over more cars
- Lower COGS as certain metal costs are declining.
- Lower leasing (2% Q4 vs 4% Q3). Cash/loan sales bringer higher margin dollars
- Lower Stock Based Compensation as Tesla reduced stock/option grants in Q4
- Energy Segment - Higher sales and margins vs Q3

Neutral Items:
- FX should have small impact (Q4 vs Q3)
- Cybertruck should not have much impact as pre-production costs in R&D now move to COGS

Wild card item:
- Tesla may have sold its remaining Bitcoin in Q4 for a $300m gain. This is a hunch based on an accounting nuance with a new accounting rule coming into effect.
 
2 advantages I can think of already:

- Optimus would have the flexibility to be deployed on 10 different tasks as needed, vs just one for a specialized robot.

-Humanoid robot likely doesn’t need any special hardware or setup, since the world is primarily designed for humans.

Both of these probably justify an Optimus at 10x the cost of a specialized robot.
In theory, yes. We are very far away from generalized flexibility for even ten different tasks. As a fan of nearly everything Asimov I seriously hope for a Susan Calvin learning from a Robbie.
Realistically there are major advances still to be made when independent short folding is not yet perfected.

Advances will be rapid and impressive, no doubt. Still, ten times the value of specialized robots is a huge stretch. Specialized ones for specific surgeries, for example, command huge margins. Industrial robots of many types also command huge margins. All of those require highly skilled human training to operate effectively.

Now we are postulating that suddenly and soon Optimus will dwarf everything.
If any advance is too good to be true, even for an optimist, it will not happen quickly.
 
I no longer forecast earnings but I can offer some thoughts on Q4 vs Q3:

Potential Downsides:
- Auto pricing (price cuts continued on certain vehicles in certain markets).
- Regulatory credits for Q4 may not be able to match the robust number in Q3 ($554m)

Potential Upsides:
- Product mix (more S&X as % of sales and more MY vs M3 bring better margins)
- Lower COGS as the record production number spreads fixed costs over more cars
- Lower COGS as certain metal costs are declining.
- Lower leasing (2% Q4 vs 4% Q3). Cash/loan sales bringer higher margin dollars
- Lower Stock Based Compensation as Tesla reduced stock/option grants in Q4
- Energy Segment - Higher sales and margins vs Q3

Neutral Items:
- FX should have small impact (Q4 vs Q3)
- Cybertruck should not have much impact as pre-production costs in R&D now move to COGS

Wild card item:
- Tesla may have sold its remaining Bitcoin in Q4 for a $300m gain. This is a hunch based on an accounting nuance with a new accounting rule coming into effect.
Don’t forget the Suez Canal on the downside.
On the upside the revenue from Charging equipment sales, and Europe and other Supercharger revenues plus VPP operation all should have been, in aggregate, material margin contributors for Q1.
 
I no longer forecast earnings but I can offer some thoughts on Q4 vs Q3:

Potential Downsides:
- Auto pricing (price cuts continued on certain vehicles in certain markets).
- Regulatory credits for Q4 may not be able to match the robust number in Q3 ($554m)

Potential Upsides:
- Product mix (more S&X as % of sales and more MY vs M3 bring better margins)
- Lower COGS as the record production number spreads fixed costs over more cars
- Lower COGS as certain metal costs are declining.
- Lower leasing (2% Q4 vs 4% Q3). Cash/loan sales bringer higher margin dollars
- Lower Stock Based Compensation as Tesla reduced stock/option grants in Q4
- Energy Segment - Higher sales and margins vs Q3

Neutral Items:
- FX should have small impact (Q4 vs Q3)
- Cybertruck should not have much impact as pre-production costs in R&D now move to COGS

Wild card item:
- Tesla may have sold its remaining Bitcoin in Q4 for a $300m gain. This is a hunch based on an accounting nuance with a new accounting rule coming into effect.
Interesting. Is it worth your time and our while were you to flesh out just a bit why you suggest

1. Q4 credits might not match or exceed Q3’s?

and

2. Why stock comp. might be lessened in Q4?
 
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Alas, investors were willing to scoop of those shares when they approached 212 and once the strong recovery began it was off to the races. Note that TSLA wasn't pulled up by the macros, it was more the other way around
Indeed, TSLA bounced off the Aug 18th low of $212.36

sc.TSLA.200-DayChart.2024-01-16.png



He just is setting expectations on what his priorities are in a future compensation deal. Please don't lose any sleep over this.
Its an important revelation that Tesla's next CEO comp. deal has been held up with the BoD waiting for a verdict from the Chancery Court of Deleware over Elon's 2018 plan. It's hard to believe that trial concluded in 2022 and the Court has still not issued a ruling. Who do they think they are, the $EC?! :p

"Justice delayed is Justice denied". -- William E. Gladstone​
"18 months" -- Chancery Court​
 
So why is this making national news when in Norway it's no problem? I just had a family friend mention this to me yesterday and now I see it on NPR...Are all these new owners who are not used to the cold weather yet?


It is yet to be determined what the actual problem or combination of problems was. Tesla might want to get on top of this. This is getting airtime in every news group and small local news feed in Canada. Proof that EV’s are no good in the cold.

It wasn’t a power outage because you could see the lights on the stalls. What takes a whole supercharger down? We just came thru a minus 27 cold snap and we could pin a supercharger at 250 kw with a pre-conditioned car.

Weird.
 
2. Why stock comp. might be lessened in Q4
Tesla is reducing stock compensation plans.
I work for big tech. This likely isn't a cancellation, but a 1 year pause. Most big tech companies either didn't do bonuses or salary increases this past year. The reality is that for most Tesla employees this would be a ~5-20k hit a year since the stock vests over 4 years.
https://www.nasdaq.com/articles/tes...erit-based-stock-compensations-bloomberg-news
 
It is yet to be determined what the actual problem or combination of problems was. Tesla might want to get on top of this. This is getting airtime in every news group and small local news feed in Canada. Proof that EV’s are no good in the cold.

It wasn’t a power outage because you could see the lights on the stalls. What takes a whole supercharger down? We just came thru a minus 27 cold snap and we could pin a supercharger at 250 kw with a pre-conditioned car.

Weird.
Key phrase "pre-conditioned car". Chicago is around 1/4 houses and over 50% apartments. People who use Superchargers (esp at the locations far from freeways) likely don't have home charging. If they try to charge a frozen pack at the start of their trip all they will pull is heating power which will take maybe 15 minutes or more to get the pack to a temperature where it will charge.
If new to EVs, they might see this as "the charger is broken". There were 3 of 10 posts down though at one site.
This is a case where a lot of level 2 spots would be handy for conditioning.
 
It is yet to be determined what the actual problem or combination of problems was. Tesla might want to get on top of this. This is getting airtime in every news group and small local news feed in Canada. Proof that EV’s are no good in the cold.

It wasn’t a power outage because you could see the lights on the stalls. What takes a whole supercharger down? We just came thru a minus 27 cold snap and we could pin a supercharger at 250 kw with a pre-conditioned car.

Weird.
From the photo, one of two things happened. A run on the chargers while there was no power outage. People didn't navigate to the Supercharger so there was no preconditioning which caused the Superchargers to go into cold battery mode (the distance to the Supercharger might have been so short that it wouldn't make a lot of difference. I've noticed on trips that the first Supercharge in the morning the preconditioning a -3 C doesn't complete by the time I've driven four miles to the Supercharger. Assuming they are locals and don't have home charging, they should pre-warm the car before driving to the Supercharger.). Or a combination. This appears to be a driver education issue because Tesla can't change the physics of battery charging.
 
So why is this making national news when in Norway it's no problem? I just had a family friend mention this to me yesterday and now I see it on NPR...Are all these new owners who are not used to the cold weather yet?

This is what I think is going on .
I stopped at a local supercharger yesterday . MX had 130 miles on the battery , can max charge to 220 miles. Outside temp was 1F with wind chill of -4F. The battery wasn’t preconditioned, it took almost 45 min for the battery to warm up before it could start taking any charge . As I knew this , I went grocery shopping . I think most nee owners don’t think much about preconditioning the battery and to see the car not accept charge for close to an hr while the battery is warming up , makes them think the car cannot be charged in cold weather . Newbies🤦🏼‍♂️
 
If they try to charge a frozen pack at the start of their trip all they will pull is heating power which will take maybe 15 minutes or more to get the pack to a temperature where it will charge.
Depends on the vehicle. The non-heat pump Model 3s can take up to an hour to heat the pack before it starts charging. (From Out Of Spec video last year where they tested this.) Which obviously adding an hour to the charge time of even half of the vehicles is going to likely make for long queues at the Supercharge, resulting in cooling batteries even for people that pre-conditioned on the way.