Moderators' Choice: Posts of Particular Merit

[StarFoxisDown!]

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I also watched the Doug Demuro Review of Plaid and it was fine and accurate. If you have watched any of Doug’s video’s you know his style and he praised Plaid more than almost any car he has reviewed. Did he say some silly stuff about how people who aren’t experienced should not be driving this car, for sure, but overall, you could not ask for a better review. And, his Doug Score was TOPS of all other cars he has reviewed except for the McLaren F1. Not sure how anyone else could watch his review and feel different.

On another note, I was talking with a friend yesterday who is a CFP and knows stocks and I was telling him that I thought TSLA, based on @accountant and others on this forum as well as Cathie Wood,who have done the forward numbers, could be a $2000-$3000 stock in 4-6 years based on these projections.

He stated that those projections are crazy and that TSLA would have a market cap in the $3Trillion dollar range and there would be no other car manufacturers in the market. Not happening. When I explained that Energy and Solar and FSD would be part of those projections, he stated that we have seen TSLA’s high of $900 and don’t expect more because the “competition” is coming not only in automotive but every other segment they are in. After some more debate and him
Adamant that I am too much of a fanboy and don’t know the financials, I changed the subject.

your thoughts?? And, do you think that we are really not looking at the whole picture and maybe not realizing that TSLA’s market cap and stock price has already seen its best days?

Why don't you use cold hard facts/data with him?

Since you referenced the Accountant.....why not take a screenshot of Accountant's modeling out for the next 5 years.....then go over the Q2 earnings with your friend...the gross margins, the operational margin, and the EPS. It doesn't take a math whiz to simply take the Q2 numbers and project out Tesla's future earnings at different production levels....even without any further increase in margins or factoring in any FSD/Robotaxi.

Some key questions to pose to your friend who would then have to confront their bias -

- How come Tesla's operational margin is 2-3X Ford/GM's at only a 200k/quarter rate?

- Tesla did over a 1.5 billion in profit in Q2 on 200k sales......Ford couldn't even reach operational profit (feel free to point out to your friend that Ford's entire 1 billion profit was "Other Revenue" )

- Go through earnings over the past year and ask him to explain if he knows why Tesla's profits/earnings are growing exponentially faster than their revenue. Does he understand why?

- Feel free to point out that right now half of Tesla's production is coming from probably the most expensive location to manufacture in the world (Fremont CA).

- When Tesla gets to 2-2.5 million annual production rate, their hardware margins and operational margin will be comparable to Apple's (before Apply heavily moved into software but even still, Apple was value at 1.5 trillion before software became a big addition to their profits)

- At that 2-2.5 million annual production rate using just the current gross and operational margins (which is dumb for the sake of this I'll just use Q2's), Tesla's operational margins will go from 2-3X Ford/GM's to in the range of 5-6X.......again without factoring in Tesla recognizing the other half of the deferred FSD revenue and no Robotaxi

- Ask him if he understands why legacy auto's P/E multiples and Price to Sales ratio are so low.........if you have the time go through legacy auto's previous year of earnings......if you really want to rub it in, go through legacy auto's previous 5 years of sales, earnings, growth......

Point is......people love to use the auto maker comparison. Use facts against them, not just general or broad facts......use specific cold hard facts and data. I'm gonna guess he wants to change the subject very quickly

(If you can't tell, I've dealt with plenty of friends/acquaintances that think they're stock/financial pro's....some of them even are and I LOVE rubbing the facts/data in their faces)

 

[RobsJester]

“Why Bots and what will they be used for?”

I have a theory - always Frame Elon’s endeavors as pieces to make human-life multi planetary

Try it, it’s a fun game: think of a feature of any Musk company and consider how it’s directly applicable to enabling life on Mars

Teslabot - In short, life on Mars will be exceedingly dangerous, and frankly, Mars will require expendable labor. Also, humans and life-support require a lot of room on a rocket - SpaceX can pack 50 times more 125lbs 5’ Teslabots per rocket

Boring/tunnels - the atmosphere on Mars is thin and surface is baked with solar radiation, Marian colonies will be subterranean. Thus the Boring Co

SolarCity - most viable way to Power Mars is solar. Winter will be very long and brutal on Mars, so Megapack & Stationary Storage

Starlink - clearly Cable and phone lines are nonexistent on Mars and the atmosphere may not be conducive for radio waves, requiring a planet-wide satellite Internet for colonies to communicate

Cybertruck Stainless Steel Exoskeleton - Starship uses the same grade of Stainless. Service Centers in various climates all over the world will note possible issues with stainless prior to launching the first reusable rockets to Mars.

Neural link - Mars will require our best and brightest, removing the finger/voice data bottleneck will increase productivity for the few colonists

Autopilot/FSD - labor on Mars will be scarce - vehicles will need to be autonomous

Ok, the theory does fall apart when considering sophomoric ideas like Fartmode and Snake-Jazz, but hey, everyone needs a little fun

To bookend for shareholders - the Q posed at the event is quite valid: is there a market for very expensive robots to replace low-waged labor? Perhaps not. But, I suspect Teslabot will be in development for years with limited impact on R&D. Initial delivery in late 2020’s to coincide with SpaceX first rockets to Mars - Teslabot production scaled lockstep with Starship production, and by mid-2030’s, SpaceX and Pentagon will buy the entire production run in perpetuity

 

[new_sneakers]

Elon has just replied to Lex Fridman tweeting about his thoughts on AI Day saying "Summarized well". Here is the text of Lex's AI Day reaction video:

Lex Fridman

Tesla AI Day presented the most amazing real-world AI and engineering effort I have ever seen in my life. I wrote this, and I meant it.

Why was it amazing to me? No, not primarily because of the Tesla Bot.

It was amazing because:

• I believe the autonomous driving task, and the general, real-world, robotics perception and planning task, is a lot harder than people generally think, and I also believed that
• The scale of effort in algorithm, data, annotation, simulation, inference compute and training compute required to solve these problems was something no one would be able to do in the near-term.
• Yesterday was the first time I saw in one place just the kind and the scale of effort that is a chance to solve this, the autonomous driving problem, and the general, real-world, robotics perception and planning problem.
• This includes:
• The neural network architecture and pipeline,
• The autopilot compute hardware in the car,
• Dojo compute hardware for training,
• The data, and the annotation,
• The simulation for rare edge-cases, and, yes,
• The generalised application of all of the above, beyond the car robot, to the humanoid form.

Let’s go through the big innovations:

The neural network:

• Each of these is a difficult, and I would say brilliant design idea, that is either a step- or a leap-forward from the state of the art in machine learning.
• First is to predict in vector-space, not in image-space. This alone is a big leap beyond what is usually done in computer vision, that usually operates in the image-space, in the 2-dimensional image.
• The thing about reality is that it happens out there in the 3-dimensional world, and it doesn’t make sense to be doing all the machine learning on the 2-d projections of it on to images. Like many good ideas, this is an obvious one, but a very difficult one.
• Second is a fusion of camera sensor data before the detections (the detections perfomed by the different heads of the multi-task neural network). For now the fusion is at the multi-scale feature level.
• Again, in retrospect, an obvious but a very difficult engineering step, of doing the detection and the machine learning on all of the sensors combined, as opposed to doing them individually and combining all the decisions.
• Third is using video context to model not just vector-space, but time. At each frame, concatenating positional encodings, multi-cam features, and ego kinematics, using a pretty cool spatial recurring neural network architecture, that forms a 2-d grid around the car where each cell of the grid is a RNN (recurring neural network).
• The other cool aspect of this is that you can then build a map in the space of RNN features, and then do planning in that space, which is a fascinating concept.
• Andrej Karpathy, I think, also mentioned some future improvements, performing the fusion earlier in the neural network. Currently the fusion of space and time are late in the network. Moving the fusion earlier on takes us further toward full, end-to-end driving with multiple modalities, seamlessly fusing – integrating – the multiple sources of sensory data.
• Finally, the place where there is currently – from my understanding – the least amount of utilisation of neural networks is planning. So, obviously optimal planning in exospace (?) is intractable, so that you have to come up with a bunch of heuristics. You can do those manually, or you can do those through learning. So the idea that was presented was to use neural networks as heuristics, in a similar way that neural networks were used as heuristics in the Monte Carlo tree search for Mu-Zero and AlphaZero to different games, to play Go, to play chess. This allows you to significantly improve on the search through action space, for a plan that doesn’t get stuck in the local optima and gets pretty close to the global optimum.
• I really appreciated that the presentation didn’t dumb anything down, but maybe in all the technical details it was easy to miss just how much brilliant innovation there was here.
• The move to predicting in vector-space is truly brilliant. Of course you can only do that if you have the data, and you have the annotation for it, but just to take that step is already taking a step outside the box of the way things are currently done in computer vision. Then fusing seamlessly across many camera sensors. Incorporating time into the whole thing in a way that’s differentiable with these spatial RNNs. And then of course using that beautiful mess of features, both on the individual image side, and the RNN side, to make plans, using neural network architecture as a heuristic, I mean all of that is just brilliant.
• The other critical part of making all of this work is the data and the data annotation.
• First, is the manual labelling. So to make the neural networks that predict in vector space work, you have to label in vector-space. So you have to create in-house tools, and as it turned out, Tesla hired an in-house team of annotators to use those tools, to then perform the labelling in vector-space, and then project it out into the image-space. First of all, that saves a lot of work, then second of all, that means you’re directly performing the annotation in the space in which you are doing the prediction.
• Obviously, as was always the case, as is the case with self-supervised learning, auto-labelling is the key to this whole thing. One of the interesting things that was presented was the use of clips of data: that includes video, IMU, GPS, odometry and so on, for multiple vehicles in the same location and time, to generate labels of both the static world and the moving objects and their kinematics. That’s really cool, you have these little clips, these buckets of data from different vehicles, and they’re kind of annotating each other. You’re registering them together to then combine a solid annotation of that particular part of road at a particular time. That’s amazing because the more the fleet grows, the stronger that kind of auto-labelling becomes, and the more edge-cases you are able to catch that way

Speaking of edge-cases, that’s what Tesla is using simulation for, is to simulate rare edge-cases that are not going to appear often in the data, even when that data set grows incredibly large.

And also, they are using it for annotation of ultra-complex scenes where accurate labelling of real-world data is basically impossible, like a scene with a hundred pedestrians, which is I think the example they used. So I honestly think the innovations on the neural network architecture and the data annotation is really just a big leap.

Then there’s the continued innovation on the autopilot computer side.

• The neural network compiler that optimises latency, and so on.
• There’s, uh, I think I remember really nice testing and debugging tools, for variance of candidate-trained neural networks to be deployed in the future, or you can compare different neural networks together. That’s almost like developer tools for to-be-deployed neural networks.
• And it was mentioned that almost ten thousand GPUs are currently being used to continually retrain the network. I forget what the number was but I think every week or every two weeks the network is fully retrained, end-to-end.

The other really big innovation, but unlike the neural network and the data annotation this is in the future, so to-be-deployed still, it’s still under development – is the Dojo computer, which is used for training.

• So the Autopilot computer is the computer on the car that is doing the inference, and the Dojo computer is the thing that you would have in the data centre, that performs the training of the neural network.
• There’s a – what they’re calling a single training tile – that is nine petaflops (laughing). It’s made up of D1 chips that are built in-house by Tesla. Each chip with super-fast I/O, each tile also with super-fast I/O, so you can basically connect an arbitrary number of these together, each with a power supply and cooling.
• And then I think they connected a million nodes, to have a compute centre. I forget what the name is, but it’s 1.1 exoflops. So combined with the fact that this can arbitrarily scale, this is basically contending to be the world’s most powerful neural network computer.
• Again, the entire picture that was presented on AI Day was amazing, because the – what would you call it? – the Tesla AI Machine can improve arbitrarily through the iterative data engine process of auto-labelling plus manual labelling of edge-cases – so the labelling stage, plus data collection, re-training, deploying. And again you go back to the data collection, the labelling, re-training, deploying. And you can go through this loop as many times as you want to arbitrarily improve the performance of the network.

I still think nobody knows how difficult the autonomous driving problem is, but I also think this loop does not have a ceiling. I still think there’s a big place for driver sensing, I still think you have to solve the human-robot interaction problem to make the experience more pleasant, but dammit (laughing) this loop of manual and auto-labelling that leads to re-training, that leads to deployment, that goes back to the data collection and the auto-labelling and the manual labelling is incredible.

• Second reason this whole effort is amazing is that Dojo can essentially become an AI training as a service, directly taking on Amazon Web Services and Google Cloud. There’s no reason it needs to be utilised specifically for the Autopilot computer. The simplicity (laughing) of the way they described the deployment of PyTorch across these nodes – you could basically use it for any kind of machine learning problem. Especially one that requires scale.
• Finally the third reason all of this was amazing is that the neural network architecture and data engine pipeline is applicable to much more than just roads and driving. It can be used in the home, in the factory, and by robots of basically any form, as long as it has cameras and actuators, including, yes, the humanoid form.

As someone who loves robotics, the presentation of a humanoid Tesla Bot was truly exciting. Of course, for me personally, the lifelong dream has been to build the mind, the robot, that becomes a friend and companion to humans, not just a servant that performs boring and dangerous tasks. But to me these two problems should, and I think, will be solved in parallel.

The Tesla Bot, if successful, just might solve the latter problem, of perception and movement and object manipulation. And I hope to play a small part in solving the former problem, of human-robot interaction, and yes, friendship. I’m not going to mention love when talking about robots. Either way, all this to me paints an exciting future. Thanks for watching. Hope to see you next time.

 

[ZachF]

They must have done an estimate for the number of people who will switch to ride hail from other modes, such as car ownership.*

It’s like the market for iPads/tablets. 20 years ago everybody would have agreed there was no such market.

edit *also people with own car who will use cheap ride hail when it suits, such as drinking occasions and trips to places where it’s difficult to park.

Precisely.

I don't think many people have done the math on how cheap per-mile robotaxi services could be.

A $20,000 robotaxi amortized over 1,000,000 miles is 2 cents per mile.

The biggest savings is the driver. If you assume ~$30/hour labor cost at an average speed of ~30mph that's $1 per mile. Robotaxi will do it for a fraction of a penny worth of electricity.

Electricity is already cheaper than gas, and a fleet operator could purchase electricity at cheaper industrial rates (8c vs. 13c). 4mi per KWh at 8c per KWh is 2c per mile.

If you assume maintenance is the same as the capital cost (it's probably less) that's another 2 cents per mile.

Add these up, and you're at 6 cents per mile to build, pay off, maintain, and fuel up a car that can drive itself. 6 cents per mile is less than just the fuel cost of a car that gets 50 miles per gallon at $3 per gallon!

Let's triple that cost, to account for times when the AEV is carrying no passengers, and for a very healthy profit. 18c per mile retail cost. That's still less than the fuel cost of a 16.7 mpg car! It's probably less than the fuel+maintenance+taxes/etc of any fully paid off car.

With these economics, large portions of people in western countries will probably forego car ownership entirely. Two-car families will become one-car families. Poor countries, like we saw with cell phones where they skipped the landline phase entirely, will probably skip the car-ownership phase entirely as well.

 

[UltradoomY]

I'm not sure and I am ready for a healthy amount of disagrees....but Really?

Does anyone here saying Tesla shouldn't, wouldn't or couldn't make their own fab have any history of what they have done????

Just 2 days ago (maybe 6) there was a prominent super computer executive on twitter dumbfounded that Tesla built their own super computer specifically for exactly what they wanted it to do with the excess ability to license it out after the fact.
He literally said "No one does that, or would attempt it!"

Tesla and Elon Musk et al, have done things no one thought possible (have you watched a Falcon 9 land on a moving ship??)
This encompasses the first principles and ideals of the company.

We should NOT expect any announcement of any in house FAB's being built until they are ready to move forward since they do not want to osbourne suppliers however, when announced (just like battery day) they will happily state - "We do not plan to abandon any suppliers, in fact we will buy everything you can sell us"

If possible, please remove the mental hurdles in attempting something like building a FAB, or a Robot, or a Starship and just let them do it, invest and reap the benefits to not only your personal wealth but to humanity for having moved forward buy a large leap.
Cheers.

 

[Todd Burch]

Troy has increased his Q3 Deliveries from 220k to 225k.
He as an odd assumption that Models 3&Y from Fremont will drop vs Q2.
Q2 - 111,520
Q3 - 95,907
That's a 15,613 drop in deliveries out of Fremont.

In response to a challenge on Twitter, he comments that production will be higher but that Tesla will likely build some inventory in Q3.
This does not sound logical based on the wait times we are seeing for new orders. Why build inventory when you have orders on hand?

So if you add the 15k difference to his 225k . . . . . .you get my 240k number. So we differ on one assumption.
Let's see if he continues to adjust his number up.

View attachment 710005

Have you read the latest notes from UBS’s meeting with Tesla Investor Relations (Martin Viecha)? See Tesla Daily’s latest Youtube video from Rob Maurer.

Among the points:

1. Most of the recent price increases were not yet visible in Q2 and will show up in Q3/Q4. Should add several hundred million straight profits to Q3 vs. Q2.

2. MIC cars sold to the western world (Europe) are the most profitable cars. There was a LOT of that in Q3.

3. High point for China demand starts in Oct, so no concerns for domestic demand there. (Perhaps leading to additional price increases in China?)

4. Elon sees opening up the Supercharger network in Europe as a revenue opportunity, so anticipate Tesla looking to bank on that starting in 2022. Thus Superchargers will directly become a revenue stream for Tesla.

5. Tesla is starting to feel FSD/AI will be more proprietary/exclusive tech into the future, vs previous views showed they felt it would be more of a commodity. This implies Tesla could have a longer high revenue stream with both exclusivity and/or selling FSD to other automakers for a longer time.

All of these things affect both long and short-term forecasts to the positive, although I imagine you’ve probably modeled for them all. Just curious if this new official info adjusts your forecasts at all. Certainly makes TSLA appear even more attractive as a longer-term investment…

 

[capster]

I wasn't advocating that you try selling options (although I believe that every investor should learn how to, since it's much simpler in practice than in theory). I was only speculating that (unlike with stocks where we're essentially powerless), the retail community might actually have enough critical mass to have an effect on the options market.

I get where you’re coming from but personally feel holding TSLA by retail is a powerful strategy from both the individual and the market perspectives.

For individuals, holding allows you to take a long term view. It also insulates you from the short term manipulations of those with access to higher execution speeds and more ways to slice and dice trades. While "simply" holding doesn’t make you invulnerable, it makes you far less vulnerable to extraneous influences than the options trader.

From a market perspective, recall the summer of 2018 when there was a concerted effort to "short-to-kill" Tesla. I held knowing of and aiming to combat this effort even though much of my position was down by half at that point. Those retail investors who did as I did, and a good number of them are here, helped Tesla weather a dangerous storm.

Powerless? I think not—these are not small things.

As I’ve said, I’m not against options (folks here have even influenced me to have level II trading enabled on one of my investment accounts, though I’ve not done any trading). I don’t trade because of the opportunity cost: I feel my attention is better allocated elsewhere than options trading demands.

tl;dr: vs

 

[StealthP3D]

Those of us who lived through 2000 and 2008 are forever tainted and gunshot. I literally wake up at 4:30am EST every morning to check if the market is crashing. I'm shocked every day that it isn't.

My finger is ALWAYS on the sell trigger. Sad way to have to live.

Sad indeed. but there is help. Study this chart of the S&P 500 Index over the last 43 years:

Can you make out a trend line here? The proven way to become wealthy is to work hard, save and invest and not worry about the ups and downs because they are not something you have any control over. By selecting the best companies and avoiding the failures like a plague you can do a lot better than this without worrying about trying to time the market.

Black Monday 1987 is visible as a little blip - it was the largest one day drop ever and people thought the world was coming to an end. I was wondering why everyone seemed so shocked. It was only 20% for the S&P 500 and around 23% for the DJIA. But, if you didn't sell it was a non-event. The way to manage stock market volatility is to reduce exposure to stocks as retirement nears. But if you have been a diligent investor your entire life you will have so much money by that time that you will be able to laugh off a 25% loss. A long-term perspective makes the game of life much easier to play.

 

[Krugerrand]

During my 45 year professional career I helped create, worked in or helped dismantle many joint ventures. Factually, more than 100, in many countries, at least a few on every permanently populated continent. None have been successful unless one side had absolute control and the other acted as a supplier or semi-passive investor.

Thus entities such as Airbus, Shell, SWIFT and the ones that have been structured to actually avoid governance issues by not really being quite JV's (e.g. Apple/Foxconn, Tesla/Panasonic) are not really exceptions to the rule. Even those have periodic crises that threaten their survival.

Frankly I think it would be quite plausible for Tesla to have relationships with OEM'S, public energy utilities, mining companies and others that could be durable and beneficial. For example, CATL seems quite close to that already. Probably there are a fair number of other suppliers and customers (mostly in TE, probably) already in that category. We will also see some emerging JV-like relationships with financial institutions including insurance companies.

As Tesla grows there will be more and more of those. It is not implausible for those to develop from Supercharger sharing, tier one suppliers beyond batteries (is LK/IDRA already there?) and more.
We don't really need to have the old-fashioned JV's to extract the benefits without enduring the pain.

Whether we like it or not the hugely complex supply chain issues are now being sources of conflict and outright business failures. Government policies play an outsized role in that (see UK today for reference). So too do business short-term thinking (see semiconductor crisis for reference).

Thus far Tesla has done a stellar job of developing and executing fast workarounds for such issues. That very fast reaction and manufacturing change to cope with unforeseen events distinguishes Tesla (and SpaceX) from nearly everyone else.

This quarter Tesla once again proven that it has manufacturing, design and process advantages oven nearly all competitors. Those would ahem been impossible if Tesla did not have very close connections with myriad outside entities. They don't call them JV's or anything like that.

Less us consider those things when we observe business volume and profit numbers from Tesla.

I actually believe Tesla has succeeded more because they’re willing to do it themselves as relying on others has brought on many of the issues.

We need more batteries. We’re telling the whole world we need more batteries. Who moved first? Tesla. It doesn’t count after the fact in my world.

We need to improve manufacturing processes. Make better use of factory space. Simplify the process. Make cars like Mattel makes toys. Who moved first? Tesla.

Make us space age doors. We tried, we failed. Never mind we’ll do it ourselves.

Build us safe and comfortable seats for cars. Pfft! Never mind we’ll do it.

More raw materials? Fine we’ll look into going directly to the mines.
We need special stainless steel - meh, we’ll come up with the formula ourselves. Oh, did we forget Tesla’s foundry?

Solar has to have battery storage and an integrated inverter and smart software - yup, we got this ourselves.

Chip shortage? Fine, we’ll just do some new software so we can use whatever chips we can get our hands on. Oh, it’s too expensive for Tesla to mfg their own chips. Uh, huh.

Insurance costs our customers too much. Fine, we’ll do that too.

And we’ll build our own AI stuff and Dojo and a Tesla bot and on the list goes.

I think it irks Elon to no end that he has to depend on others; others who move like snails, others who can’t deliver what they promise, others who don’t get it.

How many times has he said in frustration, we can only go as fast as the slowest part? We have to go faster.

No. As much as you think partnerships and relationships will grow in number and significance, I believe the opposite will happen simply because nobody to date has stepped up to the table and laid it all out. Everyone else is playing at it. Some playing better, but nobody risking everything for all except Elon and his companies.

 

[ZachF]

OK, here is a little chart I made... It's TTM revenue going back to 2007q4, adjusted for inflation:

Dotted lines are projections. Q3 assumes revenues roughly went in line with published YoY sales, and Q4 assumes a slight QoQ recovery in sales.

As you can see, most auto makers have been barely able to grow revenues beyond the rate of inflation.

Tesla will probably pass Nissan next year in size. possibly in late 2023 or almost certainly in 2024, Tesla will pass Honda/Ford/GM/BMW (who are all pretty much the same size now) for the #4 world automaker spot. I think Tesla takes the crown sometime in 2025. It'll probably be the most profitable automaker well before this.

 

[ZachF]

With Tesla likely to get $2b in profit this quarter (which is $8b annualized), here is the 10 year average of profits at other automakers (2011-2020):
(adjusting for inflation would increase these figures by about 10%)

$16,079m (6.4%) Toyota
$11,621m (4.6%) Volkswagen
$8,122m (4.8%) Daimler
$6,905m (6.5%) BMW
$6,110m (4.1%) GM
$5,824m (4.0%) Ford
$5,008m (4.0%) Honda
$2,740m (2.6%) Nissan

Remember, almost none of these automakers are beating inflation for revenue growth.

I think Tesla will get $12 billion next year, which is already more than the 10 year average for VW!

By 2023 it should easily be the world's most profitable automaker. I suspect after 2025 it will be making more profit than all of these automakers put together.

(EDIT- added in average net income as a percentage of average revenues in parenthesis)

 

[jkirkwood001]

I have bugged others about posting on Tesla's sales compared to other EV manufacturers. I personally don't care about Tesla "beating" other EVs. I personally care about Tesla displacing more ICEs off the roads.

We've seen some statistics - usually presented as text or in a table - but not the historical trends I think matter most. I absorb better visually. So I put a chart together: Global light vehicle sales.

This chart includes the top 12 sellers from 2020 compiled by the sources at bottom, plus Tesla Model 3 and Model Y (with sales labels). I tried to colour code by manufacturer - if you have a hard time deciphering, the legend lists the model in order of 2020 sales.

Obviously I'm looking for Tesla models to begin climbing past these fossils until they are top selling models globally. If any other EVs come close to the top 20 of global sales, power to them - I'll add them.

Please let me know any suggestions or corrections.

Sources:

The world’s best-selling cars | Autocar

2020 was memorable for all the wrong reasons – and the pandemic caused ructions to the car market as well, creating some winners as well as losers

www.autocar.co.uk

Best-selling car models worldwide 2023 | Statista

Three Toyota models were in the five most sold cars in the world, including one of these models recording over one million sales. Tesla also made the ranking.

www.statista.com

The world’s best-selling cars | Auto Express

We’re very familiar with the top selling models in the UK, but what about the global car market? Here are the world’s best-selling cars...

www.autoexpress.co.uk

https://www.marklines.com/en/vehicle_sales

World 2019: Discover the Top 1300 best-selling cars

The Toyota Corolla celebrates 15 straight years as the world’s best-seller. Consult 60 years of Worldwide Historical Data here. 29/04 update: Now with the Top 15 groups and Top 30 brands. 24/…

bestsellingcarsblog.com

Focus2move| Best selling cars in the World - Top 100 in 2017

Best selling cars in the World in the 2017 reports the global success of SUVs models with Toyota Rav4 and Volkswagen Tiguan escalating positions on top. The event of the year was the second place of Ford F-Series fourth model ever up 1 million

www.focus2move.com

 

[jkirkwood001]

I have bugged others about posting on Tesla's sales compared to other EV manufacturers. I personally don't care about Tesla "beating" other EVs. I personally care about Tesla displacing more ICEs off the roads.

We've seen some statistics - usually presented as text or in a table - but not the historical trends I think matter most. I absorb better visually. So I put a chart together: Global light vehicle sales.

This chart includes the top 12 sellers from 2020 compiled by the sources at bottom, plus Tesla Model 3 and Model Y (with sales labels). I tried to colour code by manufacturer - if you have a hard time deciphering, the legend lists the model in order of 2020 sales.

Obviously I'm looking for Tesla models to begin climbing past these fossils until they are top selling models globally. If any other EVs come close to the top 20 of global sales, power to them - I'll add them.

Please let me know any suggestions or corrections.
View attachment 718133

Sources:

The world’s best-selling cars | Autocar

2020 was memorable for all the wrong reasons – and the pandemic caused ructions to the car market as well, creating some winners as well as losers

www.autocar.co.uk

Best-selling car models worldwide 2023 | Statista

Three Toyota models were in the five most sold cars in the world, including one of these models recording over one million sales. Tesla also made the ranking.

www.statista.com

The world’s best-selling cars | Auto Express

We’re very familiar with the top selling models in the UK, but what about the global car market? Here are the world’s best-selling cars...

www.autoexpress.co.uk

https://www.marklines.com/en/vehicle_sales

World 2019: Discover the Top 1300 best-selling cars

The Toyota Corolla celebrates 15 straight years as the world’s best-seller. Consult 60 years of Worldwide Historical Data here. 29/04 update: Now with the Top 15 groups and Top 30 brands. 24/…

bestsellingcarsblog.com

Focus2move| Best selling cars in the World - Top 100 in 2017

Best selling cars in the World in the 2017 reports the global success of SUVs models with Toyota Rav4 and Volkswagen Tiguan escalating positions on top. The event of the year was the second place of Ford F-Series fourth model ever up 1 million

www.focus2move.com

Using monthly figures through September from MarkLines.com, I've projected sales through end of 2021. This favours Tesla's impressive ramp up, as well as its handling of the chip shortage.

The Model 3 is straight-line trending to be the 8th highest selling light vehicle in the world this year:

The biggest decline trends are:

• VW Golf (was 3rd highest seller in 2017, now 16th)
• Nissan Sentra / Sylphy
• Honda HR-V
• Honda Civic
• Ford F-150

Can't wait for CyberTruck to compete against that huge ICE truck market (3rd Ford F-150, 6th GM Silverado, 7th RAM Truck), and for the Model Y to ramp up and beat out the RAV4 (the only non-Tesla vehicle that has grown in sales despite the pandemic and chip shortage).

 

[jbcarioca]

This day I am thinking that, as other people state, Tesla is much more advanced than even our most optimistic views.

I offer these (not in any special order):
1. The paint shop: the robots seem likely to use far less paint than have the traditional paint shops. Just looking at the videos show very low paint usage. Of course the video array I have seen does not show primer supply. The Grüneheide water usage forecasts has been declining; at least some of that must be in the paint shop.
2. Front casting,rear casting assembly: Total parts count reduces from ~800 to somewhere below 20. There are analyses pending from a proprietary data service I have, and Sandy Munro will manage to tear a Grüneheide or Austin Model Y which will give many specifics. In the meantime, I think these will reduce Robin requirement by at least a dozen or so. That will also make nearly all attachments will self tapping screws, ideal for robotics as well.
3. Battery pack: excluding the 4680 benefits, the design probably ends out saving not only the ~300 pounds Elon spoke of, but act to further reduce parts counts and further adapting to automated assembly and installation. On balance these should reduce parts counts again by at least 20.
4. During the annual shareholder questions Elon mused about reducing factory size by increasing throughput and simplifying all processes. He did not make cost prognostications, but said Fremont would've about 50% more production volume.
5. All of these are yet to be quantified, but even after the first new Y teardowns nearly everyone will have ignored the massive continuous improvement in manufacturing that has total redesigns happening will maintaining stable visual. Key example: Model S refresh.

I asked my best source to estimate the consequences of all this:
1. Paint shop: Probably cheaper to build than traditional shops. Why? Vastly less material needed and construction costs probably half those of traditional paint shops. Operation is likely to use less than 75% the paint typically consumed, many fewer employees (no estimate) while reducing waste by 90% or so. This may decrease total vehicle costs by $150 or more, while saving substantial rework typically needed. There ismore about paint, including the ability to use better (e.g. harder and more resilient) paints than can normally be achieved due to reduced waste and pollution.
2.and 3. The two front and rear castings have been estimated by others at reducing total construction cost by roughly 20%. When combined with the battery pack it is quite reasonable that the entire constructions costs may be reduced by 1/3.

Following the Grüneheide tour and the other revelations recently my sources are quite astonished.
Just for a bit of context, here is Assembly magazines 2020 assembly plant of the year:

2020 Assembly Plant of the Year: There’s No Looking Back at Murakami

Every motorist uses rearview mirrors whenever they get behind the wheel. In fact, most people look at them every few seconds as they drive. However, few ever give those ubiquitous devices much thought.

www.assemblymag.com

They make mirrors, so are only tangentially connected.

In the end my astonished friend suggests that Tesla Grüneheide is set to produce Model Y for less than half what BMW spends for an X1. Frankly I have no idea but I'm positive that the order of magnitude is reasonable.

We all have noted that Tesla has been increasing Free Cash Flow, reducing inventory DOH, and growing far more than 50% per annum. In the process reducing capex!

All that has been happening by huge improvements in manufacturing process and product construction simplicity.

The easiest way to illustrate all these developments within Tesla we can compare the evolution of Model S:
2014 Model S P85D. 4936 pounds weight
2021 Model S Plaid 4941
Just reflect on the same weight for these two. Further the MSRP for mine were almost identical in US$, so no inflation at all.

Now the Model Y is undergoing far higher refinement in less time.
The above discusses costs, but weight reduction is maybe more consequential.
The weight reductions will help allow cheaper battery solutions, maybe even the new CATL Sodium ion cells. That alleviates supply issues and reduces costs further. Presumably 4680 form can be used with a wide variety of chemistries, thus reducing costs again.

After Grüneheide I think I have been understating the Tesla growth trajectory.

 

[Singuy]

I know you're being sarcastic, but I actually read through many of them, and they don't seem to do any kind of analysis that answers my questions.

Long story short, Tesla is a story about operating margins which dictates it as a car company, or a tech company.

Tesla is not valued as a car company because it's operating margins are much higher even at the early stage of growth. We are at 11% operating margin, hitting 13% this q. In comparison, F's operating margin last Q was negative, Nissan is at 1-3%. Toyota/GM are between 5-10%. These are car company operating margins.

Tesla's operating margins however are heading toward 20%+ because

1. FSD roll out. People will likely pay 10k or subscribe to FSD more as it's an actual software that provides value. It doesn't need to be robotaxi ready nor are buyers expecting it to be. The roll out also have Tesla realize more than 75% of all money collected vs only 50% today.

2. Increase production efficiencies: Fremont is Tesla's worst efficient production plant and also the highest in operating cost. Once Tesla have higher production moved away from Fremont via Berlin/Texas/Shanghai, we should see even more in operation savings.

3. Continue to simplify process on production: It takes Tesla today only 10hrs to make a Model 3 from raw material to completion. It takes the best car manufacturing company Toyota to make a car in 18 hours. Musk wants Tesla to reduce this 10hr number further, but as of right now you see where all the operational cost savings come more

4. As supply chain issues ease, energy will be less draggy on operation costs

Just to put things in perspective, Tesla is valued as a tech company because it has forward operating margins like a tech company. Car companies are in the mid single digits, companies like Apple are at 25%. Tesla will be among the techs as the years go by, except that Tesla's total addressable market will blow Apple's out of the water and ends up making a stupid amount of high revenue at 20m cars/year+50% FSD take rate vs what Apple can do. Apple's yearly revenue is 260 billion. Tesla will be hitting over a trillion in revenue at 20m cars plus whatever energy can do.

So Tsla's valuation is not all made up by apes being strong together. Q2 2021 opened the eyes of whales and analysts. Q3 will be Tesla shouting from the rooftops that they are not a car company.

 

[ammulder]

I've read up on manufacturing innovations at Tesla to reduce costs (Like the Octovalve and Gigapresses), so how easy would it be for other companies to copy Tesla and achieve similar cost savings, which would then pressure Tesla to lower prices & margins?

“The competition is coming.” We’ve heard this for years, that the OEMs are so good at making cars that one day they’d just wake up and eat Tesla’s lunch. But surely you heard about VW’s recent emergency meeting?

According to BI sources Herbert Diess and Brand CEO Ralf Brandstätter called a crisis meeting with all 120 top managers at the company, on Thursday, 8/30/2021.​

​

Diess stated the following:​

​

Compared to Tesla and Chinese manufacturers VW is too expensive, slow, unproductive, and not competitive.​

​

If everything remains as it is, VW will no longer be competitive.​

​

It is urgently necessary that a new course is set in Wolfsburg. Future competition with Tesla's new Giga factory will be brutal. The electric car pioneer sets new standards in car production.​

​

A Model 3 is built in 10 hours, more than 3 times as fast as a VW ID.3 in Zwickau. This puts Tesla in another dimension in terms of productivity and profitability.​

Yeah, those OEMs with their car-building expertise… (and bear in mind the quoted time for the Model 3 doesn’t include the front and rear castings that speed up Model Y production)

Tesla has made no secret of their octovalve or giant castings. Sandy Munro has torn down those cars, and he sells detailed reports to any OEM who will buy them. German OEMs have bought and imported Teslas strictly for competitive analysis and tear downs. Challenge: name one OEM who has implemented an octovalve or giant casting. Why not? Who knows. But surely if they had an easy way to make their EVs more cost-effective, they’d do it?

Another example: chip shortages. GM sales down 33% in Q3. Ford down 27% in Q3. Toyota down 22% in September. Factories closed all over the world. All because of chip shortages.

Tesla sales up 73%. How? From the Q2 update letter:

Our team has demonstrated an unparalleled ability to react quickly and mitigate disruptions to manufacturing caused by semiconductor shortages. Our electrical and firmware engineering teams remain hard at work designing, developing and validating 19 new variants of controllers in response to ongoing semiconductor shortages.​

Why don’t the OEMs just do that? Surely if they could put in some effort to accommodate changing chip suppliers and avoid idling factories, they would?

Can you give a counter-example of an OEM doing better at manufacturing EVs than Tesla in some area? (Any area?). About all I can come up with is the Lucid range/efficiency and the cost of some BYD models (e.g. Yuan Pro crossover for < $20k). But neither of those companies are the OEMs we’re talking about.

 

[PeterJA]

...He keeps linking CNN articles and his main arguments is that Chinese EV manufacturers bill beat Tesla price and quality and that nobody wants to own specifically a Tesla...

The "competition is coming" argument can be refuted with one sentence:

No competitor can match Tesla's rate of innovation in hardware AND software, products/services AND manufacturing, and vertical integration.​

If your listener asks for examples, you can choose from the following or add your own:

• Hardware: 18650 cell skateboard, 2170 cells, 4680 cells, structural battery pack, gigacastings, proprietary alloys for castings and Cybertruck exoskeleton, octovalve, carbon-fiber-wrapped motor, bioweapon defense mode, falcon wing doors, Supercharger versions 1-3, Autopilot, FSD Hardware 2-4, Dojo, Solar Roof, Powerwall, Megapack, medical ventilators, RNA vaccine printers, Bot
• Software: Autopilot, FSD, OTA updates, Sentry Mode, Dog Mode, Caraoke, in-car video games, Tesla app, Autobidder, Warp (Enterprise Resource Planning system), Tesla Network (forthcoming)
• Products/Services: cars, trucks, global charging network, FSD subscriptions, robotaxi service (forthcoming), auto insurance, home energy generation/storage, utility energy storage, virtual power-plants, electricity sales, Dojo as a service and humanoid robots (forthcoming)
• Manufacturing: gigacasting, Dry Battery Electrode, in-house automation team (Tesla Grohmann), Model 3 built 3 times faster than ID.3 (according to VW CEO Herbert Diess)
• Vertical Integration: in-house software design, chip design, materials engineering, glass engineering, control/power electronics design, battery engineering, battery recycling, seat manufacturing, charging infrastructure, sales/service infrastructure, auto insurance

If your listener asks why competitors can't catch up to Tesla, that too has a short answer:

Elon attracts and nurtures the smartest, most innovative engineers in the world with his corporate missions and culture (unique in the auto industry, according to Sandy Munro).​

In any race, there can be only one leader.

 

[heltok]

So how are the bears spinning Q3 numbers?

I have been following some bears over the years. What is consistent with them is that they believe they have always been right, which seems strange given that Tesla is not bankrupt yet, Elon is not in jail etc. Anyday now I guess.

Before they used to say that Tesla loses money on every sold car and will never make a profit. Then they said Tesla only made money because of tax credits but would never make profit without it. Now they are saying that the only reason Tesla makes profit is because of the FSD fraud. As FSD will never happen, Tesla will have to pay back customers and thus go bankrupt. I wonder what they will say when FSD has been delivered. I guess that NHTSA will cancel FSD and Tesla will go bankrupt. Because one thing will remain true, the bears have always been right.

They will probably always believe that compeition is coming, that Teslas have low build quality, that Elon lies about everything, that Autopilot is inferior to competition, that Tesla has squeezed out that final demand this quarter by some clever one time shenanigans and that Tesla is extremely overvalued at current valuation.

Imo what is sad to see is that previously they believed that Tesla was overvalued at $30B, now they believe that Tesla is overvalued at $900B and should have a fair value of say $100-200B. But they fail to see that their extremely overvalued at $30B estimation model must have been based on a flawed mental model.

 

[jhm]

This quote from Edwin Hubble regarding scientists, has always been a favorite of mine:

“A healthy skepticism, suspended judgment and disciplined imagination, not only about other people's ideas but also about their own."

I like to think that I possess an open mind to to new evidence; an openness to changing my beliefs once presented sound reasoning.

After ten years of separating signal from noise — especially as it relates to Tesla FUD vs reality — I fear I’ve grown to quick to dismiss Tesla bears.

But d?!$, they’ve been wrong for ten years.

We live in a time were bubble-think disinformation mediated by social media is literally an epidemic crisis. It's very important for society to understand how bubble-think works so as to safeguard from it. For instance, TSLAQ is an information bubble and exists at a social level, not individual level. I know at least one person, a co-worker, who was taken in by TSLAQ and lost a lot of money shorting Tesla. As an individual he has come to realize that shorting Tesla is a really dumb idea and he has moved on with his life. TSLAQ as a social bubble, however, rolls right along as if nothing has been learned. That is, people like my co-worker, who wake up to reality, are not really welcome to voice that within TSLAQ circles. Indeed, they are often driven out. So as someone moves past the cognitive limitations of TSLAQ what they have learned is ejected from the bubble. The bubble retains as much ignorance as it had before people like my co-worker woke up to reality. The issue is whether the the bubble can attract new uninformed members as quickly as members wise up and exit the bubble. If so, the bubble can persist a very long time. Additionally, those who remain the longest with the bubble are likely the least cognitively equipped person or otherwise motivated participants in disinformation, e.g., paid shills.

So is TMC a social bubble? Perhaps. Some of the dynamics are similar. Members with divergent views tend not to stick around for long. Certainly we have had notable members who have "woke up" to how Elon Musk cannot be trusted, poor Tesla service will destroy the company, etc. It is actually a healthy sign that we have these debates from time to time. At any rate, we cannot rule out the possibility that TMC could become a social bubble which is unhinged from reality. I do not believe this is presently the case however. The basic epistemological question we must always ask ourselves is, how would I know if I were wrong? Is there any external source of information that could persuade me that Tesla is on the wrong track? Indeed there are. We pour over SEC filings and other statements from Tesla. These are external sources of information. If Tesla were on the wrong path as evidenced by say quarterly filings, would we be able to modify our views of Tesla a going concern? I believe that for most of us the answer is yes. Personally, my investment thesis is based on Tesla being able to sustain 50% annual growth on average over many years. We see in Q3 that Tesla is able grow revenue 57% y/y, gross profit 77%, and deliveries 73%. So by multiple metrics we get robust confirmation that Tesla is indeed growing by about 50% annually. Had any of these metrics been below 40%, most of us would be very concerned and would have robust debate about whether this is just a short-term issue to be resolve in the coming year. If two-year or three-year growth were to slow below 40% CAGR, I think many of us would be able to admit that Tesla is no longer the growth engine it once was. We'd have to change our investment thesis away from one that was based on assumed 50% growth. (Tesla may still be a very good investment even with slower growth or not.) This is all quite intellectually healthy. I believe that TMC will be able to navigate such changes in the investment theses we hold.

On the other hand, TSLAQ seems unable to do this. Do they read the quarterly reports? Yes, many do. But is this for them an external source of credible information? Sadly, no. They do not view any statements from Tesla as credible. They operate with a hermeneutic of suspicion regarding Tesla's management. That is, they believe that management is trying to deceive them and the public at every turn. Hoaxes! Lies! Fraud! So when Tesla reports 73% growth in deliveries, they immediately hold that information is suspicion. The discount this in any number of ways. It might be an accounting trick. It might be cover for some worse fraud or deception. And on and on. This sort of cynical, undisciplined hyper-skepticism is really a form of disinformation. Essentially, it gives license to bubble-think members to utterly disregard Tesla as an external inform source. TSLAQ as group appears to lack any ability to take in external information without transforming it into their own disinformation. Even losing billions shorting Tesla is transformed into disinformation when they console themselves that the market price for Tesla is just a bubble, which ought to burst sometime soon. Again the less cognitively impaired ones will take their losses and walk away from the TSLAQ bubble, but those who remain will have learned nothing. Indeed those who remain will embraces increasingly bizarre delusions to suppress psychologically and sociologically all information contrary to their collective bubble-think.

Now are there Tesla bears who are not part of TSLAQ? I would hope so. We genuinely need there to be well informed participants who scrutinize Tesla. For such a person to be worth listening to, they have be willing to take SEC filings and other external sources of information at face value. They really ought to have genuine respect for Elon Musk and be willing to believe what Tesla's management has to say. Indeed Musk and Tesla's management generally often have many critical things to say about the company. If you listen carefully you will hear what risks management is aware of and probably mitigating in someway. There is little reason for cognitively competent bull and bears to disagree on what the real risks are. The substantial disagreement is on how likely and severe these risks may be and how likely management will be able to mitigate or work around these risks. For example, management is clear that Tesla is facing supply chain problems. This is real risk that both bulls and bear need to understand and accept. The bear could argue that these supply chain risks are too high and could imperil Tesla's future. Fair enough, bulls can also look at those same risks and conclude that management will work through those risks with agility and that the balance sheet is strong enough to financially sustain these headwinds. In confronting real risks, any of us can be bullish or bearish to some extent. And it is particularly healthy for investors to be able to acknowledge our doubts and worries as well as the reasons why we accept the risk/reward profile of the investment. My own opinion is that TMC is a place were we can process both beliefs and doubts regarding Tesla in a health, constructive and adaptive manner.

Cheers!

 

[The Accountant]

For those of you fixated on the P/E ratio, something to chew on . . . . .
TTM = Trailing Twelve Months
Model assumes:
- 890k deliveries in 2021 and 1.4m in 2022.
- Margins flat to Q3 2020 for all future quarters
- Modest growth in R&D and SG&A

Today the P/E ratio is at 291 and will likely go to 194 at year end using the current $900 share price (See Yellow boxes below).
By Q4 2022, the model shows $11.07 in GAAP EPS getting us to an 81 P/E Ratio at $900; at a $1800 share price, P/E is at 163 (see Orange boxes)
The table at the bottom shows the same numbers using Non-GAAP EPS for those of you who prefer that metric.