Musk Can’t Dodge Tesla Cash Woes Any Longer
bloomberg.com
bloomberg.com
So... are we living on the same planet? Does Musk seriously think that Tesla will have solved full autonomous driving, with no LIDAR, and have commercialized a functioning robotaxi service, by next year? This is so far outside of the realm of possibility that it's like saying he's going to Pluto next week.
I agree that his timeline for robotaxis is probably over optimistic, and that there are many unsolved problems. Self-driving isn't all they have to solve. They also have to solve complex and annoying problems such as having self-driving cars find the people they are supposed to pick up, and also having the cars somehow find charging, find parking, etc. Furthermore, Tesla's claim of 1 million robotaxis assumes that everyone who owns a Tesla with full self driving would want to rent them out as part of the Tesla Network. That's very unrealistic. Most people probably prefer having their car be always available and not subjecting it to potential damage/towing/fines (more driving, more risk).
Still, I wouldn't say Musk is ignorant about the state of self driving. They have self driving cars which they have demoed to people on their investor day. He just makes this probably incorrect assumption that it's all "just software" from here, and everything should be easy to fix. Software isn't easier than hardware. It could also be the case that changes do need to be made for the hardware in order to get high enough reliability, there is no guarantee that the hardware is completely right in its current iteration.
There’s an easy explanation. Musk knows that self driving is mostly hype at this point but he’s running out of cash and desperately needs a capital raise. If he can fool investors into thinking he’ll have self driving solved within a year maybe they’ll give Tesla the money it needs.
Here he is, on record, stating that he believes Tesla has essentially solved the problem ('game, set, and match'):
That’s 7 months, not 19.
(The rest is good :)
Maybe he inherited Jobs' reality distortion field?
In Elon's biography the author mentions that in all projects he was part of he would constantly give far optimistic delivery dates.
Most of us give overly optimistic delivery dates without intending to. Over time we learn that we have this habit, so we pad in some time we think is unnecessary...and still give overly optimistic delivery dates without intending to.
If you add someone INTENDING to give such poor estimates, the problem moves from the "expected and occasionally problematic but still joke-able" to the "just plain lies" category.
"I think we can do this by XX. Granted, I've been over-optimistic in the past"... is refreshing honesty, not "lies."
It's amazing to me that so many people interpret acknowledgement of one's own fallibility as lying.
I can't speak for others, but for myself I interpreted the bit about his bio saying this meant that it was the intention, not an honest assessment of what will occur despite intentions.
I mean, I'm TERRIBLE at estimation and despite all my efforts and awareness I still underestimate most everything. But when starting a company I wouldn't say "...and we'll have optimistic estimates!"
That said, I've not read the bio, and I may well have misunderstood the capsule summary. On the gripping hand, despite (or because of) all his undeniable brilliance at execution, Musk says and does a lot of things that are Not How I Would Do It, so who knows.
“The reasonable man adapts himself to the world: the unreasonable one persists in trying to adapt the world to himself. Therefore all progress depends on the unreasonable man.” -- George Bernard Shaw
When the debt load becomes high enough, it dominates everything else. Musk is getting to the point where he every late delivery costs investors more and more.
The only thing that SpaceX has done so far is prove that the traditional space industry was correct that you couldn't cost-effectively reuse rockets.
Seemed to work for Uber in Pheonix... until somebody died.
Tesla could replace Turo for Teslas fairly rapidly IMHO (and possibly Zipcar!). Supporting Lyft/Uber functionality would of course be more effort, but also doable. This isn't trying to go to the Mars (insert chuckle here). Even if you discount full autonomy, Tesla could collect a skim from every one of these transactions, while also collecting autopilot data from each trip.
Here's an open source rideshare platform: https://libretaxi.org/ TLDR Lots of dollars to capture besides for handing manufactured units over to customers. It's so silly people value Uber and Lyft as platforms so highly (as just mobile apps) while they have so little capability compared to Tesla, who not only has similar software engineering capabilities, but actually builds the cars and restricts their ability to join other platforms as deeply integrated components.
It's delusional stupidity, and no one should actually take Musk seriously.
Step 2) Car will Come to you driverless, but you still need to drive. This car will drive very slow during summon. Since no one is inside the car, the risk to human lives are reduced (but still exists for other people)
Step 3) Driverless, but limited to certain blocks, weather conditions
Step 4) A more expanded version.
But all of these appear years away.
It's not infeasible to train an automated driving system specifically suited to the streets of LA or wherever. Some place where it doesn't snow, doesn't rain often, and drivers/cyclists/pedestrians are fairly predictable (at least compared to someplace like Asia).
Alternatively, a robobus, that is to say an automated system that drives from one place to the other on a highway or interstate, seems to be mostly solved.
In both cases, if the vehicles were mostly autonomous but could also be controlled remotely by a human in ambiguous cases, they would still be vastly cheaper to operate than existing taxi/bus services.
Tesla just spent (probably) ~$100 Million or so developing a 14nm chip, already obsolete (NVidia has a 12nm chip already, Intel/MobilEye has 7nm incoming 2020, and who knows what Google/Waymo got up their sleeves. Those TPUs are fully proprietary and fully to Google/Waymo's advantage). 7nm is deployed and shipping, Tesla's already behind.
And now you're telling me that to "raise money", they're entering another highly competitive field full of companies who are literally willing to lose money over the next 5-years on this idea?
That's straight up madness. I'm sure autonomous taxis will eventually become a reality, but no company is going to make money in that field for 5 to 10 years. The other companies like Google / Waymo are going to do what Silicon Valley does best: loss lead for years and years to build a customer base, before raising prices and eventually making a sustainable business.
Tesla has already spent all of its cash and loans on Gigafactory 1, Gigafactory 2, and Gigafactory 3. Scratch that, Gigafactory 3 isn't even complete yet (and is estimated to be a few billion dollars alone in costs...).
At best, Tesla will have to enter the autonomous taxi industry offering goods at cost (or higher: trying to make a profit). That's innately going to put them severely behind Google / Waymo, who will loss lead their way to cheaper prices and more customers.
MobilEye EyeQ4 and EyeQ5 has no other purpose than self-driving. EyeQ5 is going to be 7nm and is launching 2020. A full ASIC for self-driving as well.
And no one knows what the heck Google / Waymo is doing. All we know is that its working, today, in Phoenix Arizona, where anyone can use Google / Waymo's taxi service TODAY. We also know that Google employes the same researchers who made TPUs that powered AlphaGo. They're very secretive about their hardware (for good reason!), but they're the elephant in the room with regards to self-driving.
This is false.
There are, to the best of anyone's knowledge, a handful of people in the Waymo One program (I'm fairly confident it's less than 10). Everyone in the Early Rider program is still under NDA. In order to be accepted to either, you have to apply. The application process being open to the public does not mean the service is public, anymore than the application process to Google being public means anyone can work at Google.
As to regards to how well it's working...they are definitely in the lead, and they do really have cars driving around, but all of them are still with safety drivers. Until they pull the safety drivers you can't really call them driverless and it shows a lack of faith in their product because it's not ready yet to actually be driverless.
Waymo lost their goodwill when they said they'd have the service you mentioned in 2018, basically pulled a bullshit PR event in order to "fulfill" their promise. It's pretty obvious though it was just so whoever was in charge could get some bonus attached to the timeline, very similar to how Google seems to launch products already - they do it so people can get promoted and then all the important people leave before the product is useful to anyone. It's no secret that almost the entire original team has already left and most of them have started competing against Waymo, so it seems they are confident they can take on Waymo and win - and they'd know better than anyone because they built Waymo.
And Waymo has since gone silent on when they'll expand their program, or pull the driver from the car, or pretty much anything. I agree it's a good idea for them to play their cards close to their chest, but compared to their past posturing that's a sign that it's not around the corner.
No one has ever seen a "Full self driving" car from Tesla, despite the fact that hundreds-of-thousands of people have paid $5000 for the promise of future hardware to be installed onto their car.
My point is: other companies are ahead, and have demonstrated capabilities above and beyond Tesla's 14nm chip team.
Volta architecture is much more general purpose than Tesla's.
If you're doing a custom ASIC hyper-focused on your application and you're not selling hundreds of millions of them, it doesn't make sense to lock yourself into paying of dev costs for cutting edge fabrication techniques with risk of yield problems and questionable per-unit economics.
You mean a cheaper and more industry established MobilEye EyeQ5 chip, with LiDAR capabilities, Tensor Units and all that good stuff.
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Let me ask you this: how many vehicles do you think Tesla will make in 2018 and 2019? A million? Two million?
Do remember, 2018 Tesla made only 244,920 cars. 2019 Q1 only had 70,000 cars, so Tesla is currently producing cars at a rate under 300,000 cars/year (maybe growing to 350,000 by the end of the year). Maybe Gigafactory 3 comes up in early 2020, and Tesla then makes 500k cars for 2020.
So... just about a million cars between 2018 to 2020, and I'm being quite generous on Tesla's growth potential here. Remember: not all of those cars having FSD or autopilot installed.
I'm not seeing how this 14nm chip is going to be a financially sound move for Tesla. They just don't make enough cars and they weren't watching out on industry standard chip upgrades.
Also, a side note, but maybe it was a bad idea for BMW to use Peugeot engines in the Mini... I've not heard good things about them... (Which is irrelevant to the point at hand, of course.)
Aside from some potential benefits down the road coming from proprietary chips I don't see why Tesla would do it. Also the use cases are so similar that the use of in-house chips will hardly be a competitive advantage. So why burn additional cash on it if you can't afford it?
Tesla, and Musk, are risking everything by loosing focus and discipline. Even at SpaceX with their in-house satellite is goeing that way now. No idea why you would do that either.
Thermal profile and power, instruction set and a dozen other things are more important.
Watch the autonomy day video on how the chip was built and why, will help a lot
I watched it, and I'm calling them out on it. They focused their entire presentation on NVidia and completely ignored Google/Waymo and Intel/MobilEye Q5 comparisons.
Autonomy day was an obvious hype-fest that ignored the competition. Tesla was only looking at NVidia Xavier or Pegasus, but ignores the real giants in the field.
The arguments in that presentation were exceptionally poor. There's no way a 500W chip could be a problem in a car with 300,000W motors attached and 1000W air conditioners / heaters. It was obvious to me when they were skewing their examples to be absurd corner cases to make a point: 12mph stop-and-go traffic for many hours?
Yeah, as if the 300,000W motor would like 12mph stop-and-go traffic anyway. Its not like regenerative brakes are much better than 50% recycling of the energy btw, the stop-and-go condition is going to wreak your mileage regardless.
A 500W chip can be powered by a 75kW-hr battery for 150 hours. That's nearly a whole week of life. The thought that a Model 3 or Model S car would be scrounging for efficiency in the ~100W magnitude is completely laughable.
They ignore google/waymo because they won't sell them the chip anyway.
You can't make money from self-driving Taxis if Google/Waymo simply offers a similar service for cheaper right next to you. And yes, Google/Waymo has the vertical integration thing all figured out too.
Now if you think that maybe Tesla's chip is useful for its M3 customers... sure. I strongly disagree with that fact, but you're certainly entitled to your opinion on that subject. My main issue is that Elon Musk is trying to sell this idea... that Tesla can actually raise money by going into self-driving taxis.
That's completely hogwash. Completely. There's not a chance of that at all. The other companies are too far ahead, and Tesla doesn't have enough cash to enter that fledgling industry.
Tesla isn't a tech company anymore, its a car company. It built a $2.5 Billion factory that can only produce cars, and its stuck with that (and its associated loans). Elon Musk can't just pivot into a new industry with all of these loans weighing down on his company.
Now, maybe if Elon Musk wanted to start a new company, one that wasn't burdened by all of the Gigafactory Debt, to tackle the self-driving problem... well... maybe that would work. But Tesla has already bet its life on wide-scale deployment of the Model 3. It doesn't have any other chances. It simply doesn't have the money to do anything else, or to pivot anymore.
Right, if, tesla currently has the advantage being ahead, they have self driving (at some level) currently deployed for masses.
Safety drivers are still necessary for both. But the number of times the safety-driver interacts in Waymo/Google's car is way way less.
EDIT: Actually, I'm not sure about Tesla's numbers. I heard 1 per 3 miles but I couldn't prove it through a google search. In any case, Tesla doesn't seem to be bragging about its disengagement rate, so I bet it isn't very good.
While giving as much as $30K/year of the revenue to each of the car owners.
First, the likes of nVidia have a much larger customer base and thus a better risk profile. Also, chips are their core competency. And second, running your own chip production is capital intensive, not so great when you are already in a tight financial situation.
Fabbing at 14nm is the only sensible thing for Tesla to do right now, and since they're able to do it to replace their existing Nvidia chip for lower cost, it seems quite sensible.
MobilEye is deployed in 313 car models across 27 manufacturers. They're going to have a 7nm chip next year, and are easily going to leapfrog Tesla's 14nm capabilities.
MobileEye plans to maybe have a 7nm chip sometime in 2020 (probably the end of the year) which might make it into year 2021 cars. So again, we're talking about ~2 years difference in deployment time for a less-tailored chip with a far more expensive development process. Maybe MobilEye can justify that (I'm not saying MobilEye is wrong to pursue 7nm), but it seems pretty clear Tesla pursued a logical plan to go with a 14nm process that is much cheaper to design for and is already available now at high quantities from multiple providers and reliable yields with zero technical risk on the chip fab side.
The main issue is that Tesla can't afford them. They have $2.2 Billion in cash remaining and are currently losing money at a rate of $700 Million/quarter.
Tesla's cash reserves are nose-diving and they're busy doing vanity projects like a self-driving ASIC, when their volume of cars being produced is well under 300k / year.
The volume simply isn't there yet to sustain this ASIC. 300k/year total car production, and not all of those cars would even have a self-driving capabilities installed. Tesla needs to work on expanding its Model 3 capabilities before ASICs make sense.
70,000 total vehicles produced Q1 2019. That's 280,000 vehicles this year if extrapolated over 4 quarters.
EDIT: Corrected below. MobilEye is using TSMC even though they're owned by Intel.
https://www.eetimes.com/document.asp?doc_id=1333990
TSMC 7nm has already deployed the iPhone A12, the iPad A12x, and AMD's Radeon VII. Its mature and ready for mass production.
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The problem with Tesla's 14nm chip is that their capabilities are about to be leap-frogged by a commercial-off-the-shelf solution in just a year. Note that the EyeQ5 is sampling TODAY. MobilEye is aiming at cars being deployed with the thing for 2020.
And thank you for the correction about Intel/MobilEye using TSMC instead. Of course, anyone can use TSMC, so there's less vertical integration advantage for Intel/MobilEye than I had previously expected.
So Tesla is planning to spend another $100 to $200 Million on this project? For another chip? That's 10% of its remaining cash (Tesla only has $2.2 Billion left)
I'm not convinced that Tesla has the cash for these projects.
But that might be a nice way to get outside funding for a new service that can buy a bunch of Teslas. That in turn would increase sales and, potentially, increase the stock. Kind of what Tesla did with Solar City, more or less. For me that is only postponing the time they hit a hard wall.
I bet there are more corner cases than just bad weather and other traffic participants.
Glare from the sun, stuff that looks like one thing but turns out to be another close up, curious people wanting a closer look at the marvellous robotic car. That's just from a short brainstorm.
You don't know that.
The only rational -non delusional- reason I see for the talk is if Musk does it to get better financing terms before the self driving hype dries down.
I think taxi services without driver are coming but the the secret sauce is remote human operator working together with high level of automation. Driver is the main cost of taxi service. If you get one operator to remotely oversee 20 highly autonomous vehicles and provide input when needed, the cost of taxi-service drops into a fraction of what it used to be and service is better than fully autonomous driving.
As soon as the car sees it cannot proceed properly, it parks somewhere or go in a safe situation and requests a remote human operator to intervene. Then the whole point is to have a call center sized so that you do not have to wait too much.
We're not there yet, and giving back the control to the passengers is also a possibility. However, in a world where passengers almost never drive, it might be safer to give the control to trained remote operators.
Agreed. This is just more of the usual Musk hype. Maybe he will get some geofenced taxi service going in a suburb of Phoenix, where the roads are wide and straight and the weather is always sunny.
> the secret sauce is remote human operator
New startup idea: Instead of paying people to mine WoW gold 14 hours a day, pay them to pilot taxis via a low-latency satellite link. "Hi, I'm 'Joe' from 'The Bronx,' and I will be your taxi driver today."
> If you get one operator to remotely oversee 20 highly autonomous vehicles
This doesn't work, because the situations that require human intervention will also require near-human reaction times. That's not possible for a single human herding 20 cars.
Automation must still react instantly to sudden situations (you need liars for this). Humans are there for difficult-to-navigate scenarios and stuff that robo-cars can't handle. Waymo is already testing this in geofenced areas.
Or what would be really cool would if Tesla could produce multiple car models... at the same time!
https://www.therobotreport.com/researchers-back-teslas-non-l...
It's fairly clear machine vision is going to surpass LIDAR in the near future (taking capability and cost into account), doesn't take a robotics expert to see that.
It's just a matter of time before AI can drive better than humans even if using similar vision. Especially in aggregate (e.g., factoring in distracted drivers).
I am not considering here situations where either system is impaired since that will lead to varied degrees of failure with both.
And you're oversimplifying a little, it goes far beyond just avoiding obstacles. You need to be able to anticipate, learn and adapt to completely new situations, understand consequences and things that aren't strictly related to what happens on the road. That's something even most mammals fail to do. Our computers are not there and they won't be for some time.
Garbage in garbage out. Don't skimp on your sensors.
I'm not convinced absolute speed is that important of a variable, when comparing to something much smaller dealing with closer distances, but some birds actually do reach highway speeds and beyond: https://www.worldatlas.com/articles/the-fastest-birds-in-the...
But the fastest relative to size might be the hummingbird, which can fly 30mph backwards: https://www.ponderweasel.com/what-bird-can-fly-backwards/
The Anna's hummingbird has been clocked at up to 50mph in a dive, or 385 body lengths per second. https://www.wired.co.uk/article/the-hummingbird-thats-faster...
How is it considered unacceptable? It has been acceptable for humans to drive in every country since 100+ years.
Anyway, the biggest problems with humans driving that cause accidents are distractions like smartphone usage, sleepiness, excessive speeding, tailgating, road rage, drunk driving, old age, being new to driving, being tired, medical problems like strokes, seizures, diabetic comas etc. which automated driving will solve.
VSLAM, visual SLAM, which is what you have to employ if relying largely on vision-only, is so far cruder than that.
I'm sure Tesla has some sensor fusion that also employs GPS and short-range radar/ultrasonar to help.
You can get some velocity and positional data through GPS, but it will have quite a lot of latency and is very coarse (at least the commercially accessible part).
SLAM is much, much easier to do with LIDAR since that will give you a point cloud 3D model. With VSLAM, you have to infer the depth data and build it up over time, and it's a much harder problem to solve reliably. OTOH, LIDAR's Achilles heel is, however, heavy rain/sleet/snow. Waymo has shown off using deep learning to filter the bulk of the noise out, but it looks like it's still early days there.
Vision isn't great for sleet/snow either, to be fair.
[1]: simultaneous localization and mapping
I look forward to the day when cars have giraffe-necks protruding from their roofs, mounted with stereo cameras...
But until then, the researchers actually just confirmed that front-mount cameras are only about a third as accurate as LIDAR.
And as a bonus, if the car flies off the road into the river, it can use a fishing pole style winch to pull your vehicle out of the water and place it back on the road.
The picture and the words in the article show cameras next to the rear view mirror.
""" Using two inexpensive cameras on either side of a vehicle’s windshield, Cornell researchers have discovered they can detect objects with nearly LiDAR’s accuracy and at a fraction of the cost."""
That being said, existing self-driving cars already have some cameras at that level without displaying the sort of accuracy the researchers found, which relates to the methodology issues other commenters have noted.
In any conceivable situation where you'd use this, it would actually be better to just use LIDAR.
Why don't you read the paper a bit -
https://arxiv.org/pdf/1812.07179.pdf
And then work out why they used the words "birds eye" that you found so upsetting.
The research paper, in a nutshell, was about transforming stereovisual images to psuedo-birds eye data, like roof-mounted LIDAR. This, theoretically, would result in about a 350% improvement over current vision-based methods...but still only 50% of that of existing LIDAR systems. In exchange, you just have to 1) convert the stereovisual data to a 3d point cloud, 2) transform the point cloud to birds-eye perspective, and 3) run the LIDAR systems on the point cloud, and 4) do that all in milli-seconds.
LiDAR literally will cost him money, so yeah, that's a conflict.
That he's doing bad PR is another point (that we can discuss also but is harder to comment on objectively)
I think its seriously deliverable.
So now it makes sense to ramp up in China, in Europe and Japan etc. This obviously takes upfront investment before the product can be produced. All companies with a popular product face this kind of financing hurdle.
The difference now is that the end game of the automotive industry is now a fair bit clearer than it was even a few years ago. Most of the pieces are on the table you just have to put them together. Musk understands this, it appears that most other automotive makers are still in denial.
Tesla will need a lot more financing before this game is done. Telsa is the current favorite, and up one set to nil, but with a lot of game left to play.
Tesla bet it's financial future into being able to mass produce Model 3 profitably in large quantities. The amount of debt Tesla has prevents them from retreating into smaller scale luxury cars. When Model 3 is in trouble, lets move to the taxi-scheme.
They have to dilute the stocks again and again and current owners see less of the (possible) future profits.
There will be some kind of economic slowdown or correction in the next few years. Tesla has maybe one more financing round left until the music stops.
If you're a retail investor looking for high risk/high reward stocks, Tesla was a rare exception. In most other cases, only large funds have access to growth companies like that. I'd like to see more IPOs like Tesla's, rather than reserving wealth growth only for those with tons of money.
In short, if you're not interested in taking advantage of an option, don't assume other people think the same way.
Also, the robotaxi is not some zany idea Musk randomly came up. It's been publicly on their website for 3 years now and in their internal road maps for long before that: https://www.tesla.com/en_CA/blog/master-plan-part-deux
It's really bizarre to see the constant condemnation of Musk, because he chooses to have an ambitions long-term plan and follow through with it.
Is that not true for all companies as they grow?
Tesla has executed very well on those plans and delivered very handsomely for investors.
Now you're saying, today they are different. Are they? Or is it just simple 20/20 hindsight? Did you happen to invest at $17 and sell at $350?
There was even more skepticism of them before their IPO (ie, the famous "Tesla Death Watch" series from 2008) and I think they were in a far, far more precarious position back then.
Though seeing what Tesla constantly has to deal with, if I was ever in a position to decide to IPO in the future I’d want to stay private for as long as possible.
I have some notable counters to that premise.
Square, $31.3 billion market cap. At IPO ~$5 billion.
Shopify, $27.8 billion market cap. At IPO ~$3 billion (already 9x after four years).
Splunk, $20 billion market cap. At IPO ~$5 billion.
Palo Alto Networks, $23.7 billion market cap. At IPO ~$5 billion.
Fortinet, $15.8 billion market cap. At IPO $1.5 billion.
ServiceNow, $50.3 billion market cap. At IPO ~$4.5 billion.
Atlassian, $26.5 billion market cap. At IPO ~$6.5 billion.
Twilio, $16.5 billion market cap. At IPO ~$4.5 billion.
Zendesk, $9.3 billion market cap. At IPO ~$1.7 billion.
Salesforce.com, $127 billion market cap. At IPO ~$3 billion. It hit 15x in about the same time as Tesla.
Netflix, $167 billion market cap. At IPO... a couple hundred million dollars. It hit 15x in eight years. This and CRM reach back a ways now, however you still could have easily purchased NFLX for sub $10 / share as recently as 2012.
And there are a bunch of tech-related companies that may yet produce 15x style net post IPO returns in the coming years. Such as HubSpot, which has a $7.6b market cap, versus ~$1.2b at IPO in 2014. Could have picked up ETSY at $7 / share (sub $900m market cap) well after its IPO, now $68 ($8.1b market cap).
I think Musk realized some time ago that Tesla was going to get close, but just shy of long term profitability. He’s looking for a way out that doesn’t involve him saying “uncle”.
That doesn't mean Ford is ten times as likely to go under - indeed the market cap's being the same means that buyers and sellers generally believe that Ford can carry ten times as much debt as Tesla with about the same risk.
Ford's sales are about 7.5X Tesla, and it's EV is about 4X Tesla.
Tesla's financials and market cap are not completely out of whack when compared to other car companies.
Tesla has literally never made a yearly profit in its life. Tesla hasn't even had positive yearly cash-flow for its entire life.
The best Tesla ever got was Q3 / Q4 2018, a very modest profit of a couple hundred-million dollars. But this was very quickly wiped out by Q1 2019 with a $700 Million loss and $1.4 Billion negative cash flow.
Tesla's financials are a complete disaster. Tesla's stock price has absolutely no bearing on its financials. Investors are chasing Tesla's future, they're hooked onto its story and 10-year plan. Tesla investors always ignore the finances of today.
So Uber / Lyft will fail at a later date than Tesla will fail. Note that Uber/Lyft can potentially become profitable by simply raising prices, but there's no easy way for Tesla to raise prices. (In fact, they haven't really deployed the promised $35,000 M3 yet in wide numbers. Tesla's customers are still expecting price cuts... to get to the $35k number)
I still think that traditional auto makers are in big trouble, some of them in far bigger trouble than Tesla. If the trend towards electric vehicles accelerates they are potentially sitting on mountains of stranded costs.