My name is Martin Vieca, VP of Investor Relations, and I'm
joined today by Elon Musk, FEI, Bafta, Necha and a number of
other executives. Our Q1 results were announced at
about 3:00 PM Central Time in the update deck, we published at
the same link as this webcast. During this call, we will
discuss our business outlook and make forward-looking statements.
These comments are based on our predictions and expectations as
of today. Actual events and results could
differ materially due to a number of risks and
uncertainties, including those mentioned in our most recent
filings with the SEC during the question and answer portion of
today's call. Please limit limit yourself to
one question and one follow up. Please use the raise hand button
to join the question queue. But before we jump into Q&A,
Elon has some opening remarks. Elon.
Thanks, Martin. So to recap, in Q1 we navigated
several unposting challenges as well as the ramp with the
updated Model 3 in Fremont. There was as as we all have
seen, the EV adoption rate globally is under pressure and
and a lot of other water manufacturers are pulling back
on E BS and pursuing plug in hybrids instead.
We believe this is not the right strategy and electric vehicles
will ultimately dominate the market.
Despite these challenges, the Telstra team did a great job
executing it, executing in a tough environment and energy
storage deployments. The Megapack in particular
reached an all time high in Q1 leading to record profitability
for the energy business and that that looks likely to continue to
increase in the quarters and years ahead.
It will increase, we actually know that it will so
significantly faster than the the car business as we expected.
We also continue to expand our AI training capacity in Q1, more
than doubling our training compute sequentially.
In terms of the new product road map, there's been a lot of talk
about our upcoming vehicle line in the next.
In the past several weeks, we've updated our future vehicle
lineup to accelerate the launch of new models.
Head of previously mentioned star production in the
second-half of of 2025. So we expect it to be more like
the early 2025 if not late this year.
These new vehicles including more affordable models, we'll
use aspects of the next generation platform as well as
aspects of our current platforms and we'll be able to produce on
the same manufacturing lines as our current vehicle lineup.
This, so it's not contingent on any new factory or massive new
production line. It'll be made on our current
production lines much more efficiently and and we think
this should allow us to get to over 3 million vehicles of of
capacity when realized to the full extent regarding FSD
version 12, which is the the pure AI based self driving
people that if you haven't experienced this, I strongly
urge you to try it out. It's profound and the rate of
improvement is is rapid. So we've and we've, we've now
turned that on for all cars with the cameras and inference
computer and everything from hardware 3 on in North America.
So it's been pushed out to I think around 1.8 million
vehicles and we're seeing about half of people use it so far and
that that percentage is increasing with each passing
week. So we now have over 300 billion
miles that have been driven with FSDV 12.
Since the launch of full self driving, supervised full self
driving, it's become very clear that the vision based approach
with end to end neural networks is the right solution for
scalable autonomy. And it's it's really how humans
drive. Our entire Rd. network is
designed for biological neural Nets and eyes.
So naturally cameras and digital neural Nets are the solution to
our current Rd. system. To make it more accessible,
we've reduced the subscription price to $99.00 a month.
So it's easy to try out. And as we've announced, we'll be
showcasing our purpose built robot taxi or cyber cap in
August. Yeah, regarding, regarding AI
compute, over the past few months we've been actively
working on expanding Tesla's core AI infrastructure.
For a while there we were training constrained in our
progress. We are at this point no longer
training constrained and so we're making rapid progress.
We've installed and and commissioned, meaning they're
actually working 35,000 H 100 computers or GPUs or GPU is
wrong with they need a new word. I always feel like a wince when
I say GPU because it's not GPU. That's G central graphics and
doesn't do graphics. But anyway, roughly roughly 35H1
hundreds are active and we expect that to be probably
85,000 or their bounce by the end of this year in training,
just for training, we are making sure that we're being as
efficient as possible in our training.
It's not just about the number of H1 hundreds, but how
efficiently they're used. So in conclusion, we're super
excited about our autonomy road map.
I think it should be obvious to anyone who's driving version 12
in a test that that is only a matter of time before we exceed
the reliability of humans and not much time with that.
And and we're really headed for an electric vehicle, an
autonomous future. And I'll go back to something I
said several years ago that in the future, gasoline, gasoline
cars that are not autonomous will be like riding a horse and
using a flip boat. And that will become very
obvious in in hindsight. We continue to make the
necessary investments that will drive growth and profits for
Tesla in the future. And I wanted to thank the Tesla
team for incredible execution during this period and look
forward to everything that we have planned ahead.
Thanks. Thank you very much and Abhay
Bap has some comments as well. Thanks.
You know, it's important to acknowledge what Elon said.
From our auto business perspective, we did see a season
decline in revenues quarter over quarter and there's a primarily
because of seasonality uncertain macroeconomic environment and
the main and the other reasons which Elon had mentioned
earlier. Auto margins declined from 18.9
to 18.5% excluding the impact of cyber truck.
The impact of pricing actions was largely offset by reductions
in per unit cost and the and the recognition of revenue from auto
part feature for certain vehicles in the US that
previously did not have that functionality.
Additionally, while we did experience higher cost due to
the ramp of Model 3 in Fremont and disruptions in Berlin, these
costs were largely offset by cost reduction initiatives.
In fact, if you exclude Cybertruck and Fremont and
Fremont Model 3 Ram cost, the revenue from Auto Park auto
margins improved slightly. Currently normalized Model Y
cost per vehicle in Austin and Berlin are already very close to
that of Fremont. Our ability to reduce costs
without sacrificing on quality was due to the amazing efforts
of the team in executing Tesla's relentless pursuit of efficiency
across the business. We've also witnessed that as
other OEMs are pulling back on their investments in EV, there
is increasing appetite for credits and that means a steady
stream of revenue for us. Obviously, seeing others pull
back from EV is not the future we want.
We would prefer it. The whole industry went all in
on the demand front. We've undertaken a variety of
initiatives, including lowering the price of both the purchase
and subscription options for FSD, launching extremely
attractive leasing specials for the Model 3 in the US for 299 a
month and offering attractive financing options in certain
markets. We believe that our awareness
activities paired with attractive financing will go a
long way in expanding our reach and driving demand for our
products. Our energy business continues to
make meaningful progress with margins reaching a record of
24.6%. We expect the energy storage
deployments for 2024 to grow at least 75% higher from 2023 and
accordingly this basis will begin contributing significantly
to our overall profitability. Note that there is a bit of
lumpiness in our storage deployments due to a variety of
factors that are outside of our control, so deployments may
fluctuate quarter over quarter. On the operating expense front,
we saw a sequential increase from our AI initiatives,
continued investment in future projects, marketing and other
activities. We had negative free cash flow
of 2.5 billion in the first quarter.
The primary driver of this was an increase in inventory from a
mismatch between bills and deliveries as discussed before
and our elevated spend on CapEx across various initiatives
including AI compute. We expect the inventory build to
reverse in the second quarter and free cash flow to return to
positive again. As we prepare the company for
the next phase of growth, we are to make the hard but necessary
decision to reduce our head count by over 10%.
The savings generated are expected to be well in excess of
1.1 excess of 1 billion on an annual 100 basis.
We are also getting hyper focus on CapEx efficiency and
utilizing our installed capacity in a more efficient manner.
The savings from these initiatives, including our cost
reductions, will help improve our overall profitability and
ultimately enable us to increase the scale of our investments in
AI. In conclusion, the future is
extremely bright and the journey to get there, while challenging,
will be extremely rewarding. Once again, I would like to
thank the whole Tesla team for delivering great results and we
can open it up to Q&A. Thank you.
OK, Let's start with investor Q&A.
The first question is what is the status of 4680?
What is the current output? Lars sure. 4680 production
increased about 1820% over from Q4, reaching greater than one KA
week for Cybertruck, which is about 7 GW hours per year.
As we posted on X, we expect to stay ahead of the Cybertruck
ramp with the cell production throughout Q2 as we ramp the
third of four lines in phase one while maintaining multiple weeks
of cell inventory to make sure we're ahead of the ramp because
we're ramping. COGS continues to drop rapidly
week over week driven by yield improvements throughout the
lines and production volume increases.
So our goal and we expect to do this is to beat supplier cost of
nickel based sales by the end of the year.
Thank you. The the second question is on
Optimus. So what is the current status of
Optimus? Are they currently performing
any factory tasks? When do you expect to start mass
production? We are able to do simple factory
tasks or at least I should say factory tasks in the lab.
The in terms of actually we do, we do think we will have Optimus
in limited production in the factory and the actual factory
itself doing useful tasks before the end of this year.
So, and then I think we, we may be able to sell it externally by
the end of next year. These are just just guesses.
As I've said before, I think Optimus will be more valuable
than everything else combined. Because if, if you've got a, a
sentient humanoid robot that is able to navigate reality and do
tasks at request, there is no meaningful limit to the size of
the economy. So that's, that's what's going
to happen. And I think Tesla is best
position of any humanoid robot maker to be able to reach volume
production with efficient inference on the robot itself.
The I mean, this perhaps is a point that is worth emphasizing.
Tesla's inference AI inference efficiency is vastly better than
anyone, any other company. There's no company even close to
the inference efficiency of Tesla.
We've we've had to do that because we were constrained by
the inference hardware in the car.
We'd never choice but that that will pay dividends in many ways.
Thank you. The third question is what is
the first current assessment of the pathway towards regulatory
approval for unsupervised FSD in the US and how should we think
about the appropriate safety threshold compared to human
drivers? Sure.
I can start. There are a handful of states
that already have adopted autonomous vehicle laws.
These states are paving the way for operations while the the
data for such operations guides A broader adoption of driverless
vehicles. I think a show can talk a little
bit about our safety methodology, but expect that
these States and the work ongoing as well as the data that
we're providing will pave the way for a broad based regulatory
approval in, in, in in the US at least and then other countries
as well. Yeah, it's actually been pretty
helpful that other autonomous car companies have been cutting
a path through the regulatory jungle, but the which is so
that's, that's actually quite helpful.
And they, they have obviously been operating in temperature
scope for a while. I think they got approval for
city of LA. So these, these approvals are
happening rapidly. I, I think if you've got at
scale, it's a statistically significant amount of data that
shows conclusively that the autonomous car has let's say
half the accident rate of a human driven car.
I think that's difficult to ignore because at that point
stopping autonomy means killing people.
So I actually do not think that there will be significant
regulatory barriers, provided there is conclusive data that
the autonomous car is safer than a human driven car.
And in my view this will be much like elevators.
Elevators used to be operated by a guy with a relay switch, but
sometimes that guy would get tired or drunk or just make a
mistake and cheer somebody in half between floors.
So now we just have, we just get in an elevator and press button.
We don't think about it. In fact, it's kind of weird if
somebody's standing there with relay switch.
That'll be how cars work. You just some in a car using
your phone. You get in, it takes you to a
destination, you get out you. Don't even think about it.
You don't even think about it. Just like an elevator, it takes
you to A to your floor. That's it.
Don't think about how the elevator is working or anything
like that. And, and something I should
clarify is that Tesla will be operating the fleet.
So you can think of like how Tesla think of Tesla, like under
some combination of Airbnb and Uber, meaning that you know,
there'll be some number of cars that Tesla owns itself and
operates in the fleet. There'll be some number of cars
and then there'll be a bunch of cars where they're owned by the
end user. But that end user can add or
subtract their car to the fleet whenever they want.
And they can decide if they want to only let the car be used by
friends and family or only by 5 star users or by anyone.
And at any, at any time, they could have the car come back to
them and be exclusively theirs, like an Airbnb.
You could rent out your guest room or not anytime you want.
So as our fleet grows, we have 7 million cars going to 9 million
cars going to, you know, eventually 10s of millions of
cars worldwide with a, with a, with a constant feedback loop.
Every time something goes wrong, that that gets added to the
training data and you get this training flywheel happening in
the same way that Google search has the sort of flywheel.
It's very difficult to compete with Google because people are
constantly doing searches and clicking and, and Google's
getting that feedback loop. It's the same with with Tesla,
but at A, at a scale that is maybe difficult to comprehend,
but ultimately it'll be 10s of millions.
I, I think there's also some potential here for an AWS
element down the road where if we've got very powerful
inference, you know, because we've got a hardware 3 in the
cars not, but now all cars are being made with hardware 4.
Hardware 5 is pretty much designed and should be in cars
hopefully towards the end of next year.
And there's there's the potential to have for the to to
run when the car is not moving to to actually run distributed
inference So kind of like AWS, but it distributed inference
like it takes a lot of computers to train an AI model, but many
orders 92 less compute to run it.
So if you can imagine the Future Past where there's a fleet of
100 million Teslas and on average they've got like maybe a
kilowatt of inference compute, that's 100 gigawatts of
inference compute distributed all around the world.
It's pretty hard to put together 100 gigawatts of AI compute.
And even in an autonomous future where the the car is perhaps
used instead of being used 10 hours a week is used 50 hours a
week, that still leaves over 100 hours a week where the car
inference computer could be doing something else and it
seems like it'll be a waste not to use it.
Actually, do you want to chime in on the air process and
safety? Yeah, we have like multiple
tiers validating the safety for like every in any given week we
train hundreds of neural networks that can produce, you
know, different trajectories for how to drive the car.
They repay them through the millions of clips that we have
already collected from our users and our own QA.
Those are like critical events, you know, like someone jumping
out in front or like other critical events that we have
gathered database or many, many years and we replay through all
of them to make sure that we are net improving safety.
And top of it, we have simulation systems that also try
to recreate this and test this in close to fashion.
Once all of this is validated, we give it to our own QA
reverse. We have hundreds of them in
different cities in San Francisco, Los Angeles, Austin,
New York, lot of different locations.
They are also driving the some collecting real world miles and
we have an estimate of what are the critical events, are they
net improvement compared to the previous week's bills.
And once we have confidence that the build is a net, net
improvement, then we start shipping to early users, like
2000 employees initially that they would like get the build
they would give feedback on like if it's an improvement or are
they noting some new issues that we did not capture in our own QA
process. And only after all of this is
validated, then we go to external customers.
And even when we go external, we have like live dashboards of
monitoring every critical event that's happening in the feed
sorted by, you know, the criticality of it.
So we are having a constant pulse on the build's quality and
the safety improvement along the way.
And then any failures like you don't alluded to, you get the
data back, add it to the training and that improves the
model in the next cycle. So we have this like constant
feedback loop of issues, fixes, evaluations and then rinse and
repeat. And especially with the new
virtual architecture, all of this is automatically improving
without requiring much engineering interventions in the
sense that people, engineers don't have to be creative in
like how they code the algorithms.
It's mostly learning on its own based on data.
So you see that OK, we failure or like this is how a person
shows this is how you drive this intersection or something like
that. They get the data back, we add
it to the neural network and it learns from that training it
automatically instead of some engineers saying that oh, here
you must rotate the steering wheel by this much or something
like that. There's no hard if it's
conditions, it's everything is neural network.
It's very soft, it's probabilistic.
So it will adapt its probability probability distribution based
on the new data. That it's getting, yeah.
And we, we do have some insight into how good the things will be
in like let's say three or four months, because we have advanced
models that are, are far more capable than what is in the car,
but have have some issues with them that we need to, to fix.
So they're like there'll be there'll be a step change
improvement in the capabilities of the car, but it'll have some
quirks that are that need to be addressed in order to release
it. As Shrock was saying, we have to
be very careful in what we release the fleet or to to
customers in general. So, so like if we look at say
12.4 and 12.5, which are really could arguably even be version
13 and version 14 because it's pretty close to total retrain of
the neural Nets and in each case or substantially different.
So we have been insight into where the where the models,
where, how the call, how well the call will perform in say
three or four months. Yeah.
It turns out like scaling loss. People in the AI community
generally talk about model scaling loss, where they
increase the model size a lot and then they have corresponding
gains in performance. But we have also figured out
scaling loss and other access. In addition to the model size
scaling, we can also data scaling.
You can increase the amount of data you use to train the neural
network and that also gives similar gains.
And you can also scale up by training compute.
You can train it for much longer and get or like one more GPUs or
more Dojo nodes and that also gives better performance.
And you can also have architecture scaling where you
come up with better architectures that for the same
amount of compute produce better results.
So a combination of model size scaling, data scaling, training
compute scaling and the architecture scaling, we, we can
basically like OK with the continuous scaling based on
these, this ratio, we can sort of predict future performance.
Obviously it takes time to do the experiments because it
takes, you know, few weeks to train, it takes few weeks to
collect 10s of millions of video clips and process all of them.
But you can estimate what's going to be the future progress
based on the trends that we have seen in the past and they're
generally help through based on the past data.
OK. Thank you very much.
Let's go to the next question, which is can we get an official
announcement of the timeline for the $25,000 vehicle?
I think we Elon mentioned it in the opening remarks, but as we
as you mentioned, we're updating our future vehicle line up to
accelerate the launch of our low cost vehicles in a more CapEx
efficient way. That's our mission to get the
cheap, the most affordable cars to customers as fast as
possible. These new vehicles we built on
our existing lines and open capacity and that's a major
shift to utilize all our capacity with marginal CapEx
before we go spend high CapEx to do anything.
Yeah, we'll talk about this more on August 8th.
So, but, but really the, the way to think of Tesla is, is almost
almost entirely in terms of solving autonomy and being able
to turn on that autonomy for a gigantic fleet.
And I think it it it might be the biggest asset value
appreciation in history when that day happens when you can do
unsupervised full self driving. 5 million cars.
Yeah, a little less. Well, Tesla was having Yeah,
yeah, you know, it'll be, it'll be 7 million cars, you know, in
a year or so. Yeah.
And then 10 million and then, you know it eventually we're
talking about 10s of millions of cars.
Not eventually. It's like pulling out of this.
Yeah, pulling in the decade. It's several 10s of millions of
cars I think. Thank you.
The next question is what is the progress of Cybertruck ramp?
I can take that one to Cybertruck at one KA week.
Just a couple weeks ago. This happened in the first four
to five months since we SOP D late last year.
Of course, volume production is what matters, that's what drives
costs. And so our costs are dropping.
But the ramp still faces like a lot of challenges with so many
new technologies, some supplier limitations, etcetera and will
continue to ramp this year just focusing on cost efficiency and
and quality. OK.
Thank you. The next question have any of
the legacy automakers contacted Tesla about possibly licensing
FSD in the future? We're in conversations with one
major automaker regarding licensing FSD.
Thank you. The next question is about the
robotaxi unveil. Elon already talked about that,
so we'll have to wait till August.
The following question is about the next generation vehicle.
We already talked about that. So let's go to the semi.
What is the timeline for scaling semi?
I think awesome. So we're finalizing the
engineering of the semi to enable like a super cost
effective high volume production with our learnings from our
fleet and pilot, you know our pilot fleet and Pepsi's fleet
which we were you know expanding this year marginally in parallel
as we showed in the the shareholders deck, we have
started construction on the factory in Reno.
Our first vehicles are planned for late 2025 with external
customers starting in 2026. OK, a couple more questions.
So our favorite, can we make FSD transfer permanent until FSD is
fully delivered with level 5 economy?
OK, next question, what is the getting, what is getting the
production ramp at Lathrop? Where do you see the Megapack
run rate at the end of the year, Mike?
Yeah, Yeah, Lathrop is ramping as planned.
We have our second GA line allowing us to increase our exit
rate from 20 GW hours per year to at the start of this year to
40 GW hours per year by the end of the year.
That's that Lions commissions, there's really nothing limiting
the ramps. It's, you know, given the longer
sale cycles for these large projects, we typically have
order visibility 12 to 24 months prior to ship dates.
So, so we're able to plan the build plan several quarters in
advance. So this allows us to ramp the
factory to align with the business and order growth.
And lastly, we'd like to thank our customers globally for their
trust and Tesla as a partner for these incredible projects.
OK. Thank you very much.
Let's go to analyst questions. The first question comes from
Tony Sakanagi from Bernstein. Tony, please go ahead and
unmute. Thank you for taking the
question. I I was just wondering if you
could elaborate a little bit more on kind of the new vehicles
that you talked about today. Are these like tweaks on
existing models giving that they're going to be running on
the same lines or these like new models and how should we think
about them, You know, in the context of like the Model 3
Highland update, what will these models be like relative to that?
And given the QuickTime frame, you know, Model 3 Highland is
required a lot of work and a lot of retooling.
Maybe you can help put that all in context.
Thank you. And I have a follow up please.
I think we've said all we we will on that front.
So what's your follow? It's a more personal one for
you, Elon, which is that you're leading many important companies
right now. Maybe you can just talk about
where your heart is at in terms of your interests and do you
expect to lessen your involvement with Tesla at any
point over the next three years? Well, as a constitutes the
majority of my work time and I work pretty much every day of
the week, it's rare for me to take a slightly afternoon
afternoon off. So I'm going to make sure Tesla
is very prosperous and it is like it is prosperous and it
will be very much so in the future.
OK. Thank you.
Let's go to Adam Jonas from Morgan Stanley.
Adam, please go ahead. Go ahead and unmute.
OK, great. Hey, Elon, So you, you and your
team on volume expect a 2024 growth rate notably lower than
that achieved in 2023. But what's your team's degree of
confidence on growth above 0 percent?
Or in other words, does that statement leave room for
potentially lower sales year on year?
No, I think we'll have higher sales this year than last year.
OK, my follow up Elon on future product.
If you had nailed execution, assuming that you nail execution
on your next Gen. cheaper vehicles, you know, more
aggressive giga castings. I don't want to say one piece,
but getting closer to one piece structural pack unbox 300 mile
range, $25,000 price point. Putting aside robotaxi, those
features unique to you, how long would it take your best Chinese
competitors to copy a cheaper and better vehicle that you
could offer a couple years from now?
How long would it take your best Chinese competitors to copy
that? Thanks.
I mean, I don't know what our competitors could do except
we've we've done relatively better than they have.
You know, if you look at the drop in our competitors in China
sales versus our drop in sales, our drop is less than theirs.
So we're doing, we're doing well.
But you know, I, I, I think, you know, Kathy Wood said it best
like really we should be thought of as an AI robotics company.
If, if you value Tesla as a, as just like a, an order company,
you would just have to fundamentally it's just the
wrong framework. And it will come to be if you,
if you ask the wrong question, then the right answer is
impossible. So I, I mean, I, if, if somebody
doesn't believe Tel's going to solve autonomy, I, I, I think
they should not be an investor in the company like that.
That is, but we will and we are. And then you you, you have a car
that goes from 10 hours of use a week, like an hour and a half a
day to probably 50, but it costs the same.
I, I think that's the key thing to remember, right?
Especially if you look at FSD supervised, if you didn't
believe in autonomy, they should, they should give you a
preview that this is coming. It's actually getting better day
by day. Yeah, if if you if you've not
tried the FSD 4.3 and like I said, 12.4 is going to be
significantly better than 12.5, even better than that and we
have visibility into those things, then you really don't
understand what's going on. It's not possible.
Yeah. And and that's why we can't just
look at just as a car company because a car company would just
have a car. But here we have more than a car
company because the cars can be autonomous.
And like I said, it's happening. Yeah, this is all in addition to
test the sorting. The overall AI community is just
like increasing like improving rapidly.
Yeah, yeah. I mean, we're putting the actual
auto in automobile. So, you know, so sort of like,
well, sort of like tell us about future horse carriages you're
making. I'm like, well actually it
doesn't need a horse. That's the whole point.
That's that's really the whole point.
OK. Thank you.
The next question comes from Alex Potter from Piper Sandler.
Alex, please go ahead and unmute.
Great. Thanks.
Yeah, So couldn't agree more. The thesis hinges completely on
AI, the future of AI, full self driving, you know, neural net
training, all of these things. In that context, Elon, you've
spoken about your desire to obtain 25% voting control of the
company. And I, I understand completely
why that would be so I'm not necessarily asking about that.
I'm asking if you've come up with any mechanism by which you
can ensure that you'll obtain that level of voting control.
Because if not, then the core part of the thesis could
potentially be at risk. So any additional commentary you
might have on that topic. Well, I think no matter what
tells the, you know, even if I kidnap my aliens tomorrow, Tesla
will solve autonomy maybe a little slower, but it would
solve autonomy for vehicles at least.
I don't know if it would win on with respect to Optimus or with
respect to future products, but it would.
But there's not momentum or Tesla to solve autonomy.
Even if I disappeared for for vehicles now there's there's a
whole range, a whole range of things we can do in the future.
Beyond that, I'd be more reticent with respect to
Optimus. You know, if we have a super
sentient humanoid robot that can follow indoors and you bet you
can't escape, you know, we're talking Terminator level risk,
then yeah, I'd be uncomfortable with, you know, if there's not
some meaningful level of influence over how that is
deployed. And you know, if, if there's
shareholders have an opportunity to ratify or re ratify the, the,
the sort of competition, I guess I can't say that, but that is a
fact. They have an opportunity.
OK, very good. And yeah, we'll see if, if, if
company generates a lot of positive cash flow, we can
obviously buy back shares. All right, that's, that's
actually all Very helpful context.
Thank you. Maybe one final question, I'll
pass it on OpEx reductions. Thank you for quantifying the
impact there. I'd be interested also in
potentially more qualitative discussion of what the
implications are for these headcount reductions.
What are the types of activities that you're presumably
sacrificing as a result of parting ways with with these
folks? Thanks very much.
So, you know, like we said, we've done these headcount
reductions across the board and you know, as companies grow over
time, you've, you know, there are certain redundancies,
there's some duplication of efforts which happens in certain
areas. So you need to go back and look
at where, where, where all these pockets are, get rid of it.
So we're basically going through that exercise wherein we're
like, hey, how do we, how do we set this company right for the
next phase of growth? And the way to think about it
is, you know, any tree which grows it needs pruning.
This is the pruning exercise which we went through.
And at the end of it will be much stronger and much more
resilient to deal with the future because the future is
really bright. Like I said in my opening
remarks, we just have to get through this period and get
there. Yeah, we're, we're not giving up
anything that it's significant that I'm worried of.
So we've just we've had a lot long period of prosperity from
2019 to now and you know so if a company sort of organizationally
is 5% wrong per year, you know that accumulates to 2530% of
inefficiency. We've made some corrections
along the way, but but it is, it is time to reorganize the
company for the next phase of growth.
And you really need to reorganize it just like a, you
know, a human when you restart off with one cell and kind of
zygote and, you know, blastocyst and you start growing arms and
legs and briefly you have a tail and, you know, so.
But you shed the tail. You.
Shed the tail hopefully. And then your baby and you, you
know, you basically you, you have to be different.
The Organism, a company is kind of like, you know, creature
growing and it, if you don't reorganize it for different
phases of growth, it will fail. You can't have the same
organizational structure if you're, you know, 10 cells
versus 100 versus 1,000,000 versus a billion versus a
trillion. You know, where humans are like
around 35 trillion cells doesn't feel like, it feels like, you
know, like one person, but, but you know, you're, you're
basically a walking cell colony of roughly 35 trillion depending
on your body mass and about three times that number in
bacteria. So anyway you you've got to
reorganize the the the company for a new phase of growth or it
will fail to achieve that growth.
Thank you. Let's go to Mark Delaney from
Goldman Sachs. Mark, please go ahead and
unmute. Yes, good afternoon.
Thanks very much for taking the question.
The company previously characterized potential FSD
licensing discussions as in the early phase and some OEMs had
not really been believing in it. Can you elaborate on how much
the licensing business opportunity you mentioned today
has progressed? And is there anything Tesla
needs to achieve with the technology in terms of product
milestones in order to be successful at reaching the
licensing agreement in your view?
But I think we just need to, it just needs to be obvious that
our approach is the right approach and I think it is.
I think we're now with 12.3. If you just have the car drive
you around, it is obvious that our solution with a relatively
low cost inference computer and standard cameras can achieve
self driving. No lidars, no radars, no
ultrasonics, nothing. Just no heavy integration work
for vehicle. Manufacturers, yeah, it's so it
really just be a case of, you know, having them use the same
cameras and adverse computer and licensing our software and but
but it's it's it's once it becomes obvious that if you
don't have this in a car, nobody wants your car.
Yeah, it's like it's a smart car.
And you know, I mean, I still remember like in the back when
Nokia was king of the hill. Yeah, cell phone, yeah.
Crushing and and and and I slowly come out with a
smartphone that was basically a brick with limited
functionality. And then, you know, the iPhone
and Android, but people still did not understand that all the
phones are going to be that way. There's not going to be any flip
phones if there'll be a niche product.
Or home phones. Yeah, not even exactly.
When was the last time you saw a home phone?
Is it like an acronym? Yeah, in a hotel.
Sometimes in a hotel. Yeah, the hotels have them,
Yeah. So if people don't understand
all cars will need to be smart cars or they or or you will not
sell this. The car will not, nobody will
buy it. Once that becomes obvious, I
think licensing becomes not optional, becomes a method of
survival. Yeah, it's license in order to
buy your car. I mean, one other thing which
I'll add is in the conversations which we've had with some of
these OEMs, I just want to also point out that they take a lot
of time in their product life cycle.
Yeah, they're talking about years before they will, you
know, put it in their product. They might, we might have a
licensing deal earlier than that, but it takes a while.
So this is where the big difference between us and them
is but. Yeah.
I mean really a deal sign now would result in it being in a
car in probably three years that.
Would be early. Yeah, that's like lightning
basically. So.
That's being an eager OEM. Yeah.
So I mean, I, I wouldn't be surprised if we do sanity.
I think we're good chance we do sign a deal this year, maybe
more than one. But yeah, it would be probably
three years before it's integrated with a car, even
though all you need is cameras and our parents computer.
So it's talking about a massive design change.
Yeah. And again, just to clarify, it's
not that work which we have to do, it's the work which they
have to do with the paper time. Yeah.
Yeah, very helpful. Thank you.
My follow up was to better understand Tesla's approach to
pricing going forward. Previously, the company had said
that the price reductions were driving incremental demand.
With how affordable the cars have become, especially for
vehicles that have access to IRA credits and some of the leasing
offers that Tesla has in place, do you still see meaningful
incremental price reductions as making sense from here for the
existing products? And can the company immediately
lower prices from here and also stay free cash flow positive on
an annual basis with the current product set?
Thanks. Yeah.
I, I think we, we can be free cash flow positive meaningfully,
yeah. I think Vibov said it in his
opening remarks like our cost down efforts, we basically we're
offsetting the price cut. So I was going to say, oh, like
we're trying to give it back to the customers.
Yeah. I mean, at the end of the day,
like for any given company, if you sell a great product at a
great price, the sale, if if you have a great product at a great
price, the sales will be excellent.
That's true of any arena. So over time, we do need to keep
making sure that we're that that's a great product at a
great price and moreover that that price is accessible to
people. So it's not you have to solve
both the value for money and the fundamental affordability
question. The fundamental affordability
question is sometimes overlooked.
If if somebody's earning 100 several $100,000 a year, they
they don't think of a car from a fundamental affordability
standpoint. But from vast majority of people
are living paycheck to paycheck. So it actually makes difference
if the if the cost per month for lease or financing is $10 one
way or the other. So it is important to keep
improving the affordability and to and to keep this is like
making the price more accessible.
Yeah, the the exactly make the price more accessible, the value
for money better and to keep keep improving that over time.
But also the main kick ass if people want to buy.
Yeah, it's got to be a great product at a great price.
And and the, the, the standards for what constitutes great
product at a great price keep keep increasing.
So there's like you can't just be static.
You have to keep saying keep making the car better, improving
the price but improving the cost of production and that's what
we're doing. Yeah.
And in fact, like I said in my opening remarks, also like the
revised, the updated Model 3 is a fantastic card.
I don't think people fully even understand the model of
engineering effort which has gone.
And Lars and team have actually put out videos explaining how
much the car is different when it looks and feels different.
Not only it looks and feels different, we've added so much
value to it. But you can lease it for like as
low as 299 a month, yeah. Without gas.
Yeah. All right.
The next question comes from George from Canaccord.
George, please go on on mute. Hi.
Thank you for taking my question.
First, could you please help? US understand some of the timing
of launching FSD and additional geographies including maybe
clarifying your recent comment about China.
Thank you. I mean like new markets, yeah,
we are. There are a bunch of marks where
we don't currently sell cars that we should be selling cars
in. We'll see some acceleration of
that. And FSD new.
Markets, yeah. So, so the thing about the the
the old, the the end to end neural net based autonomy is
that just like a human, it actually works pretty well
without modification in almost any market.
So we plan on with the approval of the regulators releasing it
as a supervised autonomy system in any market that work that
where we can get regulatory approval for that, which we
think includes China. So yeah, it's, it's a, you know,
just like a human, you can go rent a car in a foreign country
and you can drive pretty well. Obviously if you're, if you live
in that country, you'll drive better.
And so we, you know, we'll make the car drive better in in these
other countries with country specific training, but it can
drive quite well almost everywhere.
Yeah. The basics of driving are
basically the same everywhere, like in a car Is a car is a
traffic light or is there a nice?
Yeah, it understands that it shouldn't hit things no matter
where. It.
Is exactly there are some Rd. rules that you need to follow
and in China it's you shouldn't crossover a solid line to do a
lane change. US is a recommendation I think.
China, yeah, you get fine heavily if you do that.
We have to do some adoptions, but it's mostly smaller
adoptions, not like the entire change of stack or something
like that. Yeah.
Hey, George, do you have a follow up?
Yep. So my follow up has to do with
the first quarter deliveries. And I'm curious as to whether or
not you feel that supply constraints that you mentioned
throughout the release impacted the results.
And if you can, can you help us quantify that?
And is that why you have some confidence in unit growth in
2024? Yeah.
I think we did cover this a little bit in the opening
remarks to, you know, Q1 had a lot of different things which
were happening. You know, seasonality was a big
one, continued impression, you know, pressure from the
macroeconomic environment. We had attacks at our factory,
we had Red Sea attacks, we're ramping Model 3, we're ramping
model cyber truck. All these things are happening.
I mean, it almost feels like a culmination of all those
activities in a constraint period.
And that gives us that confidence that, hey, we don't
expect these things to recur. Yeah.
We think Q2 will be a lot better, yeah.
It's just one thing after another.
Our side of towns are crazy. Yeah, exactly.
It's just if you've got cars that are sitting on ships, they
obviously cannot be delivered to people.
And if you've got the, you know, excess demand for one for, you
know, Model 3 and Model Y in one market, but you don't have it
there, it's like it's, it's a quite a, it's, it's extremely
complex logistics situation. So you know that.
And I'd say also the we, we, we, we did over complicate the sales
process, which we've just in the past a week or so have greatly
simplified. So the IT just, it just, it
became far too complex to buy a Tesla, whereas it should just be
you can buy the card and under a minute.
So we're we're getting back to the you can buy a Tesla in under
a minute interface from what was quite complex.
OK, thank you. Let's go to Colin Rush from
Oppenheimer. Colin, go ahead and unmute,
please. Thanks so much, guys.
You know, given, you know, the pursuit of Tesla really is the
leader in AI for the physical world and your comments around
distributed inference, can you talk about what that approach
is, is unlocking beyond what's happening in the vehicle right
now? So do you want to say this one?
Yeah, I cannot mention like the car even when it's a full robot
taxi that's probably going to be used on 50 hours a week.
That's. That's my guess.
Like a third of the hours of the week, yeah.
It could be more or less, but then there's certainly going to
be some hours left for charging and cleaning and maintenance.
In that world, you can do a lot of other workloads.
Even right now we are seeing for example, these LLM companies
have this like batch workloads where they send a bunch of
documents and those are run through pretty large neural
networks, take a lot of, you know, compute to chunk through
those workloads. And now that we have already
paid for this compute in these cars, it might be wise to use
them and not let them be idle. Be like buying a lot of
expensive machinery and letting them be idle.
Like we don't want that. People want to use the computer
as much as possible and close to like basically 100% of the time
make effective use of it. That's right.
I think it's analogous to Amazon Web Services where, you know,
people didn't expect that AWS would be the most valuable part
of Amazon when it started out as a bookstore.
So that was on nobody's radar, but they they found that they
had excess compute because the compute needs would would spike
to extreme levels for brief periods of the year and then
they had idle compute for the rest of the year.
So then what should they do with pull that excess compute for the
rest of the year that's kind of monetize it.
Yeah, monetize it. So it seems like kind of a no
brainer to say, OK, if we've got millions and then 10s of
millions of vehicles out there where the computers are idle
most of the time, that we might as well have them do something
useful. Yeah, exactly.
And then I mean, if you get like to the 100 million vehicle
level, which I think we will at some point get to then and
you've got a kilowatt of usable compute and maybe you're on
hardware 6 or 7. By that time.
Then you really, I think you could have on the order of 100
gigawatts of usable compute, which which might be more than
anyone, more than any company, probably more than any company.
Yeah, probably because it takes a lot of intelligence to drive
the car anyway. And when when it's not driving
the car, you just put this intelligence to other users,
just solving the scientific problems.
Like a human. Or Anthony Dump.
Actually, someone else. We've already learned a lot
about deploying workloads to these nodes, yeah.
And unlike laptops and our cell phones, it is totally under test
of control, so it's easier to distribute the work product
across different nodes as opposed to, you know, asking
users for permission on their own cell phones would be very
tedious. Well, you, you just drain the
battery on the Yeah. Exactly.
The battery is also limited. So like technically I suppose
like Apple would have the most amount of distributed compute,
but but you can't use it because you can't get the, you can't
just run the phone at full power and drain the battery.
So the whereas for the car, even if you're a kilowatt level
reference computer, which is crazy power compared to a phone,
you know, if you've got a, if you're a 60 kWh pack, that's
it's still not not a big deal to run, right.
If you plugged in, whether you plugged in or not, you could be
plugged in or not plugged in. You know, you could run for 10
hours and use 10 kilowatt hours if you're kilowatt of compute
per hour. Yeah, we're together built in
liquid coal thermal management. Yeah, it's exactly.
That's for data centers. So it's already there in the
car. Exactly.
So it's distributed power generation.
It's just distributed access to power and distributed cooling,
and it's already paid for. Yeah, I mean that that
distributed power and cooling, people underestimate that costs
a lot of money, really big. Data.
It does, yeah. And the CapEx is shared by the
entire world, yes, sort of. Everyone owns a small chunk and
they get a small profit out of it maybe.
Yeah. Thanks so much guys.
And just my follow up is a little bit more mundane looking
at the the 4680 ramp. Can you talk about how?
Close you are. To target yields and when you
might start to accelerate incremental capacity expansions
on on that on that technology. You know, I, we, we're making
good progress on that, but I don't, I don't think it's super
important for at least the near term as, as, as Laura said, we,
we think it'll be, you know, exceed the competitiveness of
suppliers by the end of this year and then we'll continue to
improve. Yeah.
I mean, I think it's important to note also that like the ramp
right now is relevant to the Cybertruck ramp.
And so like we're not going to just randomly build 4680's once
we have a place to put them. And so we're going to, you know,
make sure we're prudent about that, but we also have a lot of
investments with all our cell suppliers and vendors.
They're great partners and they, you know, have done great
development work without us. And a lot of the advancements in
technology and chemistry we found 4680 they're also putting
into their cells. Yeah.
I mean, a big part of the 4680 it tells us during internal
cells was a hedge against what how what would happen without
suppliers because for a while there it was very difficult
because every big car maker put in massive battery orders.
And so the price is the price per kWh of of battery of lithium
ion batteries went to crazy numbers to crazy levels.
Bonkers. Yeah, just bonkers.
So like, OK, we've got to have some hedge here to deal with,
you know, cost per kilowatt hours numbers that were double
what we anticipated. If we have an internal cell
production, then we have that hedge against demand shocks.
There was too much demand. That's that's really the way to
think about it. It's not like we want to take on
a whole bunch of problems that just for the hell of it.
We we did this health program in order to address the the crazy
increase in cost per kWh from our suppliers due to gigantic
orders placed by every car maker on earth.
So. OK.
Thank you. And the last question comes from
Ben Kalo from Baird. Ben, go ahead and unmute and
you're still muted. Well, I once again would just
like to strongly recommend that anyone who is I guess thinking
about the Tesla stock should really drive FSD 12.3.
You'd really you, you can't. It's impossible to understand
the company if you do not do this.
All right, so since Ben is not unmuting, let's try Shreyas
Patel from Wolf Research. Final question.
Oh hey, thanks so much. Just.
You know, Elon, during the Investor day last year, you
mentioned that auto COGS per unit for the next Gen. vehicle
would decline by 50% versus the current three.
And Yi think that was implying something around $20,000 of
COGS, about 1/3 of that was coming from the unbox
manufacturing process. But I'm curious if you see an
opportunity that the other some of the other some of the other
drivers around powertrain cost reduction or material cost
savings, would those be largely transferable?
To some of the new products that you're that you're now talking
about, about introducing. Yeah, yeah, sure.
I mean, in short, yes, I mean, like, you know, unbox
manufacturing method is certainly great in
revolutionary, but with with it comes some risk because, you
know, it's new production lines, not but all the subsystems we
developed, whether it was powertrains, BAT, you know,
drive units, battery improvements in manufacturing
and automation, thermal systems, seating, integration of interior
components and reduction of LV controllers, all that's
transferable. And that's what we're doing, you
know, trying to get it into our products as fast as possible.
And so so I, yeah, I that engineering work, we're not
trying to just throw it away and, and put it, you know, in in
a coffin. We're going to take it and and
utilize it and utilize it to the best advantage of of the cars we
make and the future cars we make.
OK, great. And then just on, on that topic
of 4680 cells, I, I know you, you mentioned it, you really
thought of it more as like a hedge against, against, you
know, rising battery costs from other OEMs. But it seems, you
know, even today, you know, it, it, it seemed like you would
have a cost advantage against some of those other automakers.
And I'm wondering, you know, given the rationalizing of your
vehicle manufacturing plans that, that you're talking about
now, if there's an opportunity to maybe you know, convert the
4680 cells and, and, and maybe sell those to other automakers
and really generate an additional revenue stream.
I'm just curious if you have any thoughts about that.
Great. What what seems to be happening
is that the unless I'm missing something, the orders for
batteries from other water makers have declined
dramatically. So we're we're seeing much more
competitive prices for sales from our suppliers dramatically
more competitive than in the past.
It is clear that a lot of our suppliers have excess capacity.
Yeah. One, in addition to what Elon
said, this is currently all the way in addition to what Elon
said about 4680. What 4680 did for us from a
supply chain perspective was help us understand the supply
chain that's upstream of our cell suppliers.
So a lot of the deals that we had struck for 4680, we can also
supply those materials to our partners.
Help. Reducing the overall cost back
to Tesla. So we're we're basically
inserting ourselves in the upstream supply chain by doing
that. So that's also been beneficial
in reducing the overall pricing in addition to the excess
capacity that these suppliers. Have yeah, Now, I mean, this is
going to wax and wane, obviously.
So, you know, there's, there's going to be a boom and bust in,
in battery cell production, yeah, where production exceeds
supply and then supply exceeds production and back and forth,
kind of like on a DRAM or something.
But yeah, so, so it's like what what is true today will not be
true in the in the future. There's going to be somewhat of
a boom and bust cycle here. And then there are additional
complications by, you know, with government incentives like the
the Inflation Reduction Act, the IRA, Victoria's found like a
funny name for a found. My cool name.
Yeah, is it like the Irish Republican Army, the Internet
research agency from Russia independent retirement camp?
Yeah, exactly. Roth IRA and there's like 4
spider man situations which I which IRA wins.
So, but it does, it does complicate the incentive
structure so that there's, there, there is perhaps there's
the stronger demand for cells that are produced in the US than
outside the US, But then how long does that the IRA last, I
don't know. Which is why it's important that
we have both inland cells and other cells that hedge against
all of this. Yeah.
OK, thank you very much. That's all the time we have
today. But at the same time, I would
like to make a short announcement and I wanted to let
the investment community know that about a month ago, I met up
with Elon and Vaibhav and announced that I'll be moving on
from the world of investor relations.
I'll be hanging around for another couple of months or so,
so feel free to reach out anytime.
But after the seven-year Sprint, I'm going to be taking a break
and spending some good quality time with my family.
And I wanted to say that these seven years have been the
greatest privilege of my professional life.
I'll never forget the memories from I started literally at the
beginning of production hell and just watching the company from
the inside to see what it's become today.
And I'm especially super thankful to the people in this
room and dozens of people outside of this room that I've
worked for over the years. I think the the team strength
and teamwork at Tesla is unlike anything else I've seen in my
career. Elon, thank you very much for
this opportunity that I got back in 2017.
Thank you for seeking investor feedback and regularly and
debating it with me. Yeah, Well, I mean, the, the
reason I I reached out to you is because I thought your analysis
of Tesla was the best that I'd seen.
Thank you. So yeah, thank you for helping
Telsey get to where it is today. Over 7 years it's been a
pleasure working with you. Thank you so much.
And yeah, thank you for all the thousands of shareholders that
we've met over the the years and walked around factories and
loved all the interactions even with the even the tough ones.
And yeah, looking forward to the call the next three months, but
I'll be on the the other side listening in.
Thank you very much. Thanks.