Elon Musk's Tesla 2025 q3 investor relations

Elon Musk's Tesla 2025 q3 investor relations call

Episode Transcript

(00:01):
Hey, everybody. Welcome back to the Elon Musk
Podcast. This is a show where we discuss
the critical crossroads, the Shape, SpaceX, Tesla X, The
Boring Company and Neurolink. I'm your host, Will Walden.
Good afternoon, everyone, and welcome to Tesla's third quarter
2025 Q&A webcast. My name is Travis Axelrod, Head

(00:23):
of Investor Relations, and I'm joined today by Elon Musk,
Vaibhav Taneja and a number of other executives.
Our Q3 results were announced atabout 3:00 PM Central Time in
the update deck, we published atthe 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

(00:43):
predictions and expectations as of today.
Actual events or results could differ materially due to a
number of risks and uncertainties, including those
mentioned in our most recent filings with the SEC.
We urge shareholders to read ourdefinitive proxy statement,
which contains important information about the matters we
voted on at the 2025 Annual Meeting.

(01:05):
During the question and answer portion of today's call, please
limit yourself to one question and one follow up.
Please use the raise hand buttonto join the question queue.
Before we jump into Q&A, Elon has some opening remarks.
Elon. Thank you.
We're we're at a critical inflection point for Tesla and

(01:27):
our strategy going forward as webring AI into the real world.
I think it's important to emphasize that Tesla really is
the leader in real world AI. No one can do what we can do
with real world AII. Have pretty good insight into AI
in general I think. That Tesla has the.
Highest intelligence density of any AI out there in the car and

(01:51):
that is only going to get better.
And really just the beginning ofscaling at a, at a quite
massively full self driving and robo taxi and fundamentally
changing the nature of transport.
I think people just don't don't quite appreciate the degree to
which this will take off where the the it's honestly, it's

(02:12):
going to be like a shockwave. So it's it's because because the
cars are all out there, they're.You know, we have millions of
cars out there that with a software update become full self

(02:33):
driving cars. And, and you know, we're making
a couple million a year. And, and in fact, with the
advent of with, with what we seenow as as a clarity on achieving
full self driving, unsupervised full self driving, I should say

(02:54):
I feel confident in expanding Tesla's production.
So that is that is our intent toexpand as quickly as we can our
future production. So I was, I was resident to do
that until we had clarity on, onachieving unsupervised full self

(03:14):
driving. But at this point, I, I feel
like we've got clarity and it, it makes sense to expand
production as as fast as we reasonably can.
We're also making huge make making impact, impact on the
energy sector with, with batterystorage.

(03:38):
So with both Powerwall and especially with the Mega Pack,
we are dramatically improving the ability to generate more
energy from the grid. Let me sort of talk a little bit
about that, which is if you, if you look at total US energy

(03:58):
capability for example, there's roughly a terawatt of of
continuous power available in the US, but the average usage
over 24 hour cycle is only half a terawatt because of the.
Big difference between day and night usage.
If you buffer that buffer the energy with batteries, you can
effectively double the energy output in the United States just

(04:21):
with batteries building, no incremental power plants.
And it's very. Difficult to build power plants,
so they take a long time. There's a lot of permitting and
it's not an industry that's usedto moving fast.
So we see the potential there for Tesla battery packs to
greatly improve the, the energy output per year for any given

(04:45):
grid, US or otherwise. We're also on the cusp of, of
something really tremendous withoptimists, which I think is
likely to be or has potential tobe the biggest product of all
time. And it's it's a difficult

(05:09):
project. And it's worth noting that it's
not like it's it's just automatic.
I'm unaware of any robot programmed by Ford or GM or, you
know, and by US sort of car. Companies, people like I think
maybe think of Tesla as as a carcompany.
We mostly make cars and battery packs, but so it's not like it's

(05:32):
not just like an obvious. Fall off a log thing to make
Optimus, but but we do have the ingredients with of real world
AI and exceptional electrical mechanical engineering
capabilities and the ability to scale production, which I don't
think anyone else has all of those ingredients.

(05:57):
So yeah, with with version 14 ofthe of self driving.
Which people you can see the reactions of of people online,
they're quite amazed actually anyone in the US can get version
14 if they just go and select I want the advanced software in

(06:20):
their car. So if if you're listening right
now and you'd like to try it out, just go in in settings and
say I want the advanced softwareand you will get version 14.
And yeah, so on the Mega Pack front, we've we unveiled Mega

(06:41):
Block, Mega Pack 3. We also have exciting plans for
Mega. Pack 4, Mega Pack 4 will
incorporate a lot of the, a lot of what is normally in a
substation and be able to outputat probably 35 kilovolts

(07:04):
directly. So this, this greatly improves
our ability to deploy Megapack because it's not dependent on
building a substation of 335 KV or Megapack 4.
So that that'll be next. That's the that's the
engineering priority for Megapack.

(07:25):
And we look forward to unveilingOptimus V3, you know, probably
in Q1. I think it'll be ready for to,
to show off. And that that I think is going
to be quite remarkable. If you, it won't even seem like

(07:47):
a robot. It'll seem like a person in a
robot suit, which is kind of howwe started off with Optimus.
But it it'll seem so real that you'll need to like poke it, I
think to believe that it's actually a robot.
And and obviously, like the the real world intelligence we've

(08:09):
developed, we've developed for the car.
Most of that transfers to Optimus.
So it's a very good starting point.
In conclusion, we're excited about the, you know, updated
mission of Tesla, which is sustainable abundance.
So going beyond sustainable energy to say.

(08:31):
Sustainable abundance is the mission where we we believe with
with optimist and self driving. That you can actually create a
world where there is no poverty,where everyone has access to the

(08:54):
finest medical care. Optimist will be an incredible
surgeon, for example, and imagine if everyone had access
to an incredible surgeon. So, so I, I think there's, you
know, of course we need to make sure Optimus is safe and
everything, but, but I, I do think we're headed for a world

(09:18):
of sustainable abundance and that I'm excited to work with
the Tesla team to make that happen.
Great. Thank you very much.
Elon Vebub also has some openingremarks.
Thanks, Travis. Q3 was a special quarter at
multiple levels. We set new records not just for
deliveries and deployments, but also around a range of financial

(09:42):
metrics from total revenues, energy, gross profit, energy
margins to fresh free cash flow.This was the result of continued
confidence of our customers in our products and the relentless
efforts by the Tesla team. The strength and deliveries was
attributed to strong performanceacross all regions.
Greater China and APEC were up sequentially 33 and 29%

(10:06):
respectively. North America was up 28%, while
EMEA was up 25%. The base in deliveries was the
function of continued excitementaround the new Model Y We had
previously talked about 2025 being the year of the Y and have
since delivered on that promise with the new Model Y released in
Q1. Followed by Model Y, long

(10:28):
wheelbase and performance and more recently Standard Y in
North America and EMEA. We're now operating a robotaxi
in two markets, Austin and most Bay Area cities.
We've already expanded our coverage area in Austin three
times since the initial launch and are on pace to continue
expanding further. Unlike our competitors, our

(10:50):
robotaxi fleet blends in. The markets we operate in since
they don't have extra sensor sets or peripherals which make
them stick out. This is an under appreciated
aspect of our current vehicle offerings which are all designed
for autonomous driving. We feel that as experience, as

(11:11):
people experience the supervisedFSD at scale, the demand for our
vehicles, like Elon said, would increase significantly on the
FSD adoption front. We we've continued to see decent
progress. However, note that total paid
FSD customer base is still small, around 12% of our current
fleet. We're.

(11:32):
Moving or we're working with regulators in places like China
and EMEA to obtain approval so that we can get FSD in those
regions as well. Now covering a little bit on the
financial side, automotive revenues increased 29%
sequentially in line with the growth and deliveries.
While regulatory credits declined sequentially, we

(11:55):
entered into new contracts and continued delivery on previously
entered contracts. Our automotive margins excluding
credits increased marginally from 15% to 15.4, which was
attributed to improvements in material cost and better fixed
cost absorption due to higher volumes.

(12:16):
The energy storage business continue to deliver with record
deployments, gross profit and margins.
As discussed before, this business has a bigger impact
from tariffs as measured by percentage of COGS, since
currently all sales procured arefrom China while we're still
working on other alternatives. However, as the ramp of mega

(12:39):
factory Shanghai is happening, this is helping us avoid
tariffs. Because we are using this
factory to supply the non-us demand, like Elon said, you know
grid scale storage, the only waywe can get to electricity
fastest is by using storage. The other thing to keep in mind

(13:00):
is we are seeing headwinds in this business given the increase
in competition and tariffs, the total tariff impacts for Q3.
For both businesses was in excess of 400 million generally
split evenly between them. Services and other demonstrated
a marked improvement sequentially.

(13:20):
This was a function of improvements primarily in our
insurance and service center businesses.
Note that while small, our robotaxi costs are included
within services and other along with our other businesses like
paid supercharging, used car parts and merchandise sales
etcetera. Our operating expenses increase

(13:41):
sequentially, the largest increase included in
restructuring and other related to certain actions undertaken to
reduce cost and improve efficiency to convergence of our
ARAI chip design efforts. Additionally, we incurred legal
expenses related to proceedings in certain legal cases as well

(14:02):
as incremental cost incurred in preparation for our shareholder
meeting. Such costs are recorded within
STNA. Further, our employee related
spend is increasing especially in R&D as we have recently
granted various performance based equity awards to employees
working on AI initiatives and therefore such spend will

(14:24):
continue to increase going forward.
On other income, our other income decreased sequentially
primarily from mark to market adjustments on BTC holdings,
which was much smaller gain of 80 million in.
Q3 versus 284,000,000 in Q2. With the rest of the movement
attributable to FX movements in the quarter, our free cash flow

(14:46):
for the quarter was approximately 4 billion, which
was yet another record. Our total cash and investments
at the end of the quarter were over 41 billion.
On the CapEx front, while we areexpecting to be around 9 billion
for the current year, we're projecting the numbers to
increase substantially in 2026 as you prepare the company for

(15:08):
the next phase of growth in terms of not just our existing
businesses, but our bets around AI initiatives including
Optimus. In conclusion, note that
bringing AI into real world is hard, but we have never shield
away from doing what is hard. We are extremely excited about
the future and are laying down the foundation, the benefits of

(15:31):
which will be realized over years to come.
I would like to end by thanking the Tesla team, our customers,
our investors and supporters forthe continued belief in us.
Thank you very much, Vaibhav. Now let's go to
investorquestionsfromsay.com. The first question is what are
the latest robo taxi metrics? Fleet size, cumulative miles

(15:55):
rides, completed intervention rates, and when will safety
drivers be removed? What are the obstacles still
preventing unsupervised FSD frombeing deployed to customer
vehicles? I'll, I'll start.
Off with that and then Shark canelaborate.
But we we are expecting to have no safety drivers in at least

(16:19):
large parts of Austin by the endof this year.
So within a few months, we expect to have no safety drivers
at all in at least in parts of Boston.
We're obviously being very cautious about the deployment.
So, so our goal is to be actually paranoid about
deployment because obviously even one accident will be front

(16:40):
page headline news worldwide. So I guess it's better for us to
take a cautious approach here. But we do expect to have no, no
safety drivers in the car in Austin within a few months.
I think that's perhaps the most important data point.
And then we, we do expect to be operating Robotaxi in I think

(17:06):
about 8 to 10 metro areas by theend of the year.
You know, it depends on various regulatory approvals and, but
you, you can actually, I think most of our regulatory
applications are online. You can kind of see them because
they're they're public information.
But we expect to be operating inNevada and Florida and Arizona

(17:30):
by the end of the year. Ashok Yeah.
We we continue to operate our fleet in Austin without anyone
in the driver's seat and we havecovered more than a quarter
million miles with that. And then in the Bay Area where
we still have a person in the driver's seat.
So the regulations we cross morethan 1,000,000 miles.

(17:51):
So and we continue to see that the fleet robotaxi fleet works
really well. Customers are really happy and
there's no notable issues on thecustomer side via customers have
used FSE supervised for a total of 6 billion miles as of
yesterday. So that's like a big milestone.
And overall the safety continuesto be very good.

(18:14):
And as I mentioned, we are on ontrack to remove the person from
inside the car all together starting with Austin.
Great. The next question is what is the
demand and backlog for Megapack,Powerwall, solar or energy

(18:34):
storage systems? With the current AI boom, is
Tesla playing to supply power toother hyperscalers?
Thanks. Demand for Megapack and
Powerwall continues to be reallystrong into next year.
We received very strong positivecustomer feedback on our Mega
Black Mega block product, which will begin shipping next year

(18:55):
out of Houston. And we're seeing remarkable
growth in in the demand for AI and data center applications as
hyperscalers and utilities have seen the versatility of the
Megapack product to increase reliability and receive and and
relieve grid constraints. As Elon was talking about, we
we've also seen a surge in residential solar demand in the
US due to policy changes, which we expect to continue into the

(19:18):
first half of 2026 as we introduced a new solar lease
product. And we also began production of
our Tesla residential solar panel in our Buffalo factory and
we will be shipping that to customers starting Q1.
The panel has industry leading aesthetics and shape performance
and demonstrates our continued commitment to US manufacturing.

(19:42):
Great. Thank you, Mike.
Unfortunately, the next questionis related to future products.
This is not the appropriate venue to cover that, so we're
going to have to skip it. The question after that is what
are the present challenges in bringing Optimist to market
considering app control, software engineering, hardware
training, general mobility models, training task specific

(20:03):
models, training voice models, implementing manufacturing and
establishing supply chains. Yeah, I mean bringing office
Optimist market is an incrediblydifficult task.
To be clear. It's not like some walk in the
park at some point. I mean at this actually
technically Optimist can walk inthe park right now.

(20:25):
And we do have Optimist robots that walk around our offices at
our engineering headquarters in Palo Alto, CA basically 24 hours
a day, seven days a week. So any visitors that come by you
actually you can, you can stop to stop one of the Optimist
robots and ask it to take you somewhere and it'll literally

(20:46):
take you to that meeting room orthat location in the building.
So I don't want to downplay the difficulty of Optimist.
It's, it's an incredibly difficult thing, especially it's
difficult to create a, a hand that is as dexterous and capable
as the human hand, which is an incredible, the human hand is an

(21:07):
incredible thing that the more you study the human hand, the
more incredible you realize the human hand is and, and why you
need 5, you know, 4 fingers in the thumb.
Why the why the fingers have certain degrees of freedom.
You know why, why the, the various muscles are of different
strengths. The fingers are of different
lengths. And it turns out actually that

(21:31):
all that, those are all there for a reason.
And so making it, making it thatthe hand and, and forearm,
because most of the, most of theactuators, just like the human
hand, the muscles of that control your hand are actually
primarily in your forearm. The optimist hand and forearm is
an incredibly difficult engineering challenge.

(21:54):
It's, I'd say it's more difficult than the rest of, from
an electromechanical standpoint,the forearm and hand are, it's
more difficult than the entire rest of the robot.
So, but really in order to have a, a useful generalized robot,
you, you do need this, you do need an incredible hand and, and

(22:15):
then you need the real world AI and you need to be able to scale
up that production to have it berelevant, because it's not
relevant if it's just a few 100 robots.
But so you need to be able to make Optimus robots at volumes
comparable to vehicles, if not significantly higher.

(22:38):
So if you're trying to make a million or something per year,
I'm trying to make a million Optimus robots per year.
That manufacturing challenge is immense considering that the
supply chain doesn't exist. So with with cars, you've got an
existing supply chain. With computers, you've got an
existing supply chain. With, with a humanoid robot,

(22:59):
there is no supply chain. So in order to, to manufacture
that, Tesla actually has to be very vertically integrated and
manufacture very deep into the supply chain, manufacture the
parts internally because there just is no supply chain.

(23:20):
So this is this is the kind of thing where I'm like, if I put
myself in the position of a startup trying to make an
humanoid robot, I'm like, I don't know how to do it without
and an immense amount of manufacturing technology.
So that's that's why I think like Tesla's in almost a unique,
I think, I think unique positionwhen you consider manufacturing

(23:42):
technology, scaling real world AI and the and a truly dexterous
hand. Those are the generally the
things that are missing when youread about other robots that
they just don't have those threethings.
So now I think we can achieve all those things, those those

(24:04):
three things with an immense amount of work.
And, and that, that is that is the game plan.
So, you know, my, like my, you know, fundamental concern with
regard to how much voting control I have in Tesla is if I

(24:25):
go ahead and build this enormousrobot army, can I just be ousted
at some point in the future? That's my biggest concern.
If I that's, that, that is the, that is really the only thing
I'm trying to address with with this.
So it's called compensation, butit's not like I'm going to go
spend the money. It's just if we build this robot
on me. Do I have at least?

(24:48):
A strong influence over that robot on me.
It's not control, but a strong influence.
That's that's what it comes downto in a nutshell.
Like I don't feel comfortable building that robot on me if I
don't have at least a strong influence.
Great. Thank you.
We've already covered robotaxi expansion.

(25:10):
Unfortunately, the question after that is another future
product question. So we're going to have to skip
that. The next one though is can you
update us on the $16.5 billion Samsung chip deal?
And Taylor, given the importanceof semiconductors to autonomy
and Tesla's AI driven future, what gives you confidence
Samsung can fulfill AI 6 at Tesla's timelines and achieve

(25:30):
relatively better yields and cost versus TSTSMC?
OK, so I'm going to give quite along answer to this question
because I have to unpack this question and then and then
answer the unpacked version. So first of all.
I have nothing but great things to say about Samsung.

(25:51):
They're an amazing company and Samsung is worth noting this
manufacturer our AI4 computer and does a great job doing that.
So now with the, the AI5 and here's I, I need to make a point

(26:12):
of clarification relative to some comments I've made publicly
before, which is we're actually going to focus both TSMC and
Samsung initially on AI5. So the, the AI5 chip design by
Tesla is I, I think it's an amazing design.

(26:35):
I've spent almost every weekend for last last few months with
the chip design team working on AI5 and I, I don't hand out
praise easily, but I have to saythat I think, I think the Tesla
chip team is, is really designing an incredible chip

(26:56):
here. This is by some metrics, the AI5
chip will be 40 times better than the AI4 chip, not 40%,
forty times because we, we, we have a detailed understanding of
the entire software and hardwarestack.
So we're designing the hardware to address all of the pain

(27:20):
points and software. So I don't think there's, there
really isn't anyone that's doingthis the entire stack all the
way through real world, you know, calibrating against the
real world where you've got carsand robots in real world that
like we know what the chip needsto do and we know what, just as

(27:40):
importantly, we know what the chip doesn't need to do.
You know, to sort of give you some examples here with the AI
5:00, we, we deleted the the legacy GPU or the OR the
traditional GPU, which is it, it's in AI 4, but AI 5 does not

(28:03):
have, we just just deleted the legacy GPU because it basically
is a GPU. So we also deleted the image
signal processor. And there's, there's like a long
list of actually of deletions that are very important.

(28:25):
As a result of these deletions, we can actually fit AI5 in 1/2
reticle and. With with with good margin for
the traces from the memory to the the trip, the Tesla trip
accelerators. The ARM, the ARM CPU course and

(28:51):
and the PCI. Sort of the PCI blocks.
So this, this is a beautiful chip.
I've poured so much life energy into this.
Chip personally and I'm I'm confident this will be this is
going to be a winner next level.So it makes sense to have both

(29:17):
Samsung and TSMC focus on AI5 and so like the technically the
Samsung fab has slightly more advanced equipment than the
TSMC. Fab, these will be.
Both be made in in the US that in one TSMC in Arizona, Samsung
in Texas and but but it's it it we're going to make.

(29:43):
Starting off, just to be confident of having our, our,
our goal, explicit goal is to have an oversupply of AI5 chips.
Because if, if we, if we have too many AI5 chips for the cars
and, and and robots, we can, we can always put them in the data
center. So we already use AI4 for for

(30:06):
training in our in our data center.
So we use a combination of AI4 and NVIDIA hardware.
So we're not about to replace NVIDIA to be clear, but but but
we do use both in combination AIfour and NVIDIA hardware and the
AI5 excess production we can always put in in our data

(30:28):
centers. NVIDIA keeps keeps improving
that. The challenge that they have is
that they've got to satisfy a large range, a lot of
requirements from a lot of customers, but Tesla only has to
satisfy requirements from one customer with Tesla that that
makes the design job radically easier and means we we can

(30:49):
delete a lot of complexity from the chip.
Like I can't emphasize how important this is.
So like when when you look at the various logic blocks in the
chip, as you increase the numberof logic blocks, you also
increase the interconnections between the logic blocks.
So you can think of it like there's just highways, like how

(31:09):
many highways do you need to connect the various parts of the
chip? And especially if you're not
sure how much data is going to go between each, you know, logic
block on the chip, then you, youkind of end up having giant
highways going all over the place.
It's a very, it like it becomes an almost impossibly difficult
design problem. And Nvidia's done an amazing job

(31:31):
of dealing with almost an impossibly difficult set of
requirements. But in our case, we, we, we're
going for radical simplicity. And the net effect is that I, I,
I think AI 5 will be the best performance per Watt, maybe by a
factor of two or three and the best performance per dollar for

(31:54):
AI, maybe by a factor of 10. So you know, that's you know.
We'll have to. The proof's in the pudding, so
obviously we need to actually get this chip made and made it
scale, but that's what it looks like.

(32:15):
Great. Thank you, Elon, we've already
covered unsupervised FSD. So the next question is, instead
of trying to replace hardware 3 with hardware 4, why not give an
equal incentive to trade in for a new vehicle?
Yeah, not completely given on upon hardware three.
However, over the last year we've offered the customers the

(32:36):
option to transfer FSD to their new vehicle with which at times
you've been running some promotions if if they got FSD,
they can get better preferentialrates.
So we've been definitely taking care of this.
But we do want to solve autonomyfirst and then we'll come back
with a way to take care of thesecustomers.
These customers are very important.

(32:58):
They were the early adapters. For what it's worth.
My daily commuter is a hardware 3 car which I use FSD on a daily
basis, so we will definitely take care of you guys.
Great and thank you. Once the V14 release series is
fully done, we are planning on working on AV14 Lite version for

(33:22):
Hardware 3, probably expected inQ2 next year.
Awesome. Thanks Ashok.
Alrighty, our final question from say is how long until we
see self driving Tesla semi trucks and could you see this
technology replacing trains? Yeah.
So I guess I'll start with that.In terms of the semi production

(33:46):
plan and schedule, so the factory is is going on schedule.
We've, you know, completed the building and are installing the
equipment. Now we've got our fleet of
validation trucks driving on theroad.
We'll have larger builds towardsthe end of this year and then
our first online builds in the first part of next year ramping
into you know the Q2 timing withreal volume coming in the back

(34:06):
half of the year. So that's going quite well and
and that's the first step to obviously getting autonomous
trucks on the road. In terms of trains, you know,
they're really great for long point to point deliveries are
super efficient, but you know, that last mile, the load unload
can be better served for in shorter distances with
autonomous semis. And that would be great.

(34:28):
And so we do expect that to probably shift.
And as we, you know, really, as Elon said, change the way
transportation is considered. And so we're looking forward to
that timeline. And Ashok, I know you can can
take the the full self driving part.
Currently, the team is super focused on solving for passenger
vehicles autonomy. That said, the same technology
will extend quite easily to the semi truck once we have a little

(34:51):
bit of data from the semi trucks.
Great. And now we will move over to
analyst questions. The first question comes from
Emmanuel at Wolf. Emmanuel, please go ahead and
unmute yourself. Great.
Thanks so much. Hi, everybody.

(35:12):
So Ilan, you talked about expanding production of vehicles
as fast as possible. Now that you have confidence in
the unsupervised autonomy. How should we think about that
in the context of your existing capacity of 3,000,000 units?
Is that where you're hoping to get volume to?

(35:33):
What sort of timeline are we talking about?
And would this require, you know, some level of boosting or
incentivizing demand? Like would this basically be
prioritizing volume over near term profitability given the
longer term opportunity? Well, our.

(35:54):
Capacity isn't quite 3,000,000, but it, it, it will be 3,000,000
at some point. You know, aspirationally, you
know, it could be 3,000,000 within we could probably hit an
annualized rate of 3,000,000 within 24 months, I think maybe
less than 24 months. Bearing in mind like this,

(36:16):
there's an entire like supply chain, like a vast supply chain
that's got to also move in tandem with that.
So I think we're going to, we'regoing to expand production as
fast as, as, as, as we can and as fast as our suppliers can,
can, can sort of keep up with it.

(36:37):
And then we're going to think about where, where do we build
incremental factories beyond that, Like the single biggest
expansion in production will be the the Cyber Cab, which starts
production in Q2 next year. That's, that's really a vehicle
that's optimized for full autonomy, in fact does not have

(36:58):
a steering wheel or pedals and is really an engineering
optimization on minimizing cost per mile, if you like fully
considered cost per mile of operation.
So that's. You know, for the other, for
the, for other vehicles, they'restill, they still have a little
bit of the horseless carriage thing going on where you know,
obviously you've got if you're still, if you've got steering

(37:19):
wheels and pedals and. And and you're designing a car
that people might want to go, you know, very direct past
acceleration and tight cornering, like high performance
car, you know, cars. Then you're going to design a
different car than one that is optimized for a comfortable
ride, but doesn't expect to go, you know, past sort of 85 or 90

(37:40):
miles an hour. And it's just aiming for a
gentle ride the whole time. That's what cybercap is.
So yeah, so so it's do I think we'll sacrifice margins?
I don't think so. I think the demand will be
pretty naughty. But like here's the here's the

(38:02):
killer app. Really what it comes down to is
can you text? Can you text while you're in the
car? And if you tell someone yes that
the car is now so good, you can you can you can be on your phone
and text the entire time while you're in the car.
It's anyone who can buy the car will buy the car and A and a

(38:23):
story. So that's what everybody wants
to do. In fact, not everyone wants to
do they do do that. And that's why, in fact, the
reason you've seen like there's been an uptick in accidents very
much worldwide is because peopleare.
Texting and driving. So Autopilot actually

(38:44):
dramatically improves the safetyhere.
Because if somebody's looking down at their phone, they're not
driving very well. So that's, that's really the,
the game changer. And you know, we, we do see like
at this point, I feel, you know,essentially 100% confident.

(39:06):
I say not essentially 100% confident that we can set that
we can solve unsupervised full full self driving at a safety
level much greater than human. So we've released 14.1.
We've got a technology road map that's I think pretty amazing.

(39:27):
We'll be adding reasoning to thecar.
Our world simulator for for reinforcement learning is is
pretty incredible. Like our like our when you see
it that the Tesla reality Simulator it's you can't tell
the difference between the videothat's generated by the Tesla
reality simulator and the actualvideo looks exactly the same.

(39:52):
So that allows us to have a verypowerful reinforcement learning
loop to further improve the Tesla AI, we're going to be
increasing the parameter count by an order of magnitude that
that's not in 14.1. There are also a number of other
improvements to the AI just. That, that are that are quite

(40:16):
radical. So it's this, this car will feel
like it is a living creature. That's how good the the AI will
get with the AI4 computer with this before AI5 and then and
then AI5, like I said, is by some metrics 4040 times better.
But let's just say safely it's a10X improvement.

(40:40):
So it might almost be too much intelligence for a car.
I do wonder, like how much intelligence should you have in
a car? It might get bored actually.
And then one of the things I thought like, well, if we got
all these cars that maybe are bored, well, while they're,
while they're sort of, if they are bored, we, we could actually

(41:00):
have a giant distributed inference fleet and say like,
well, if they're not actively driving, let's just have a giant
distributed inference fleet. You know, at some point if, if
you've got like 10s of millions of cars in the fleet or maybe at
some point 100 million cars in the fleet.
And let's say they had at at that point, you know, like I

(41:25):
don't know, a kilowatt of inference capability of, you
know, high performance inferencecapability, that's 100 gigawatts
of inference distributed with, with power and cooling taken
with, with, with cooling and, and power conversion taken care
of. So that seems like a pretty

(41:49):
significant asset. Great.
Thanks, Elon. The next question comes from
Adam from Morgan Stanley. Adam, please feel free to unmute
yourself. Adam, go ahead and ask your
question. Seems like we might be having

(42:14):
some audio issues with Adam, so we'll come back to you.
The next question will then comefrom Dan from Barclays.
Hi, good evening. Thank you for taking the
question. Elon, I, I know that Tesla's
really focused on with master plan for bringing AI into the

(42:37):
physical world. And I think we've seen over the
past, you know, this willingnessfor Tesla to engage and, and go
into new markets, new Tams. So when you think about the
growth prospects, how do we define the areas that are really
within Tesla's core competency versus where do you draw the
line for markets or AI applications that are outside of

(43:02):
Tesla's core competency? Actually, I'm not sure what you
mean by AI applications outside of Tesla's core competency.
But and we, we kind of, we didn't have any of these core
competencies when we started. You know, so it's like we had 0

(43:22):
core competencies, total competency of 0 actually.
So, I mean, you can think of Tesla as like, I don't know, a
dozen start-ups in one company, you know, and, and I've
initiated every one of those start-ups.
So it's, it wouldn't used to make battery packs, so
stationary battery packs, but now we're due make them for the

(43:44):
home, make them for, you know, utility scale with power wall
mega pack. We've created the Supercharger
network globally. No one, no one else has created
a global Supercharger network. In fact, that North American
Supercharger network's so good at that, that basically that
yeah, every other manufacturer in North America is converted to

(44:04):
our standard and uses our the Tesla Supercharge network.
But if it was so easy, why don'tthey just do it?
And the chip design team startedthat from scratch.
The Tesla AI software team was started from scratch.

(44:24):
I literally just say, hey, we'regoing to start this thing I
posted on Twitter now X and then, you know, join us if you'd
like to build it. In fact, Ashok was, I believe,
the first person I interviewed for the the Tesla autopilot
team, which we now call the Tesla AI software team, which
because it is the AI software team.

(44:46):
So you know, it's core companies, competencies created
while you wait and you know, Optimus at scale.
It is the infinite money glitch.It's like this is a, it's
difficult to express the magnitude of like if you've got

(45:09):
something that like that, like if I.
Optimist, I think probably achieve 5X to the productivity
of a person per year because it can operate the 24/7.
It doesn't even need to charge. It can operate it tethered.
So it's plugged in the whole time and whatever.

(45:32):
So it it that's that's why I call it like if, if you're true
of sustainable abundance, we're working will be optional.
You know, there's there's a limit to how much, how much AI
can do in terms of enhancing theproductivity of humans, but
there is not really a limit to AI that is embodied.

(45:53):
That's why I call it the infinite money glitch.
I mean, one thing which I'll further add is I mean, people
forget like our first iteration of Autopilot was 10 years back.
So you know, Elon had started this way back in the day.
We've got the tweets to prove itexactly.
And then even even on the optimist side, right, as much as

(46:17):
people think, OK, this is a new thing, I still remember, was it
4 plus years back? We were in a finance meeting
with Elon and Elon said, hey, our car is a robot on wheels and
that's where we started developing.
In fact, most of the engineeringteam which is working on Optimus
has come from the vehicle side. And that's why, you know, when

(46:38):
we talk about manufacturing progress, we have the
wherewithal because the same engineers who worked in the back
in the day on drive units are working on actuators now.
So that's where we can do if there's any company which can do
it at scale, that is going to beus.
But we we also have actually added a lot of new engineers as
well to the team. So there's actually a lot of the

(47:01):
credit for the Optimus Engineering is, is actually also
new, new engineers, many of themthat are just out of college
actually. So the Optimus engineering team
is a. Very talented engineering team,
I'd say like wow, actually so and you know, the optimist

(47:25):
reviews at this point are the the engineering review and then
there's the manufacturing reviewbeing done.
It's simultaneously with an iterative loop between
engineering, design and and manufacturing, because then we
see. We, we.
We. We.
Designed something and we see like, oh man, that's really

(47:45):
difficult to make. We need to change that design to
make it easier to manufacture. So we've made radical
improvements to the design of Optimus while increasing the
functionality, but making it actually possible to manufacture
like I'd say Optimus 2 is almost.
Impossible to manufacture, frankly, but by two bipolars

(48:06):
point we've gone from, you know,a person in a robot outfit to
what what people have seen with Optimus 2.5 where it's doing
Kung Fu. You know, it was like after this
was at the at the Tron premiere doing Kung Fu, you know, just
out in the open, you know, like with Jared Leto, like there

(48:28):
wasn't nobody was controlling it.
It was just doing Kung Fu with Jared Leto, you know, at the
Tron premiere. You can see the videos online
and actually The funny thing is like a lot of people walked past
it thinking it was just a person.
Even though with Optimus 2.5, you can see that it has, you

(48:52):
know, a waist that's three inches wide that results in not
a human. So but the movements were so
human like that people didn't realize.
A lot of people didn't realize they were looking at a robot.
So, and what I'm saying is like Optimus 3 will be a giant
improvement on that and made it scale.

(49:17):
But like I said, a very difficult thing.
Yeah, the the optimist sort of engineering and manufacturing
reviews. And there's the Friday night
meeting with optimists, which sometimes goes till midnight.
And then my Saturday meeting is,is with the is, is the Saturday

(49:37):
afternoons with the the AI5 chipdesign team.
So those two things are crucial to the future of the company.
Great. And Dan, did you follow up?
Yeah. Just as a related, maybe you

(49:57):
could just talk about to what extent are the AI efforts at
Tesla and XAI complimentary or are they just different forms of
AI? Maybe you can just help
distinguish for the audience? Thank you.
Yeah, there there are different.Forms of AI so the you know the.

(50:20):
The ex AI so Grok is like a a giant model that that you could
not you could not possibly squeeze Grok onto a car, that's
for sure. It is a giant piece of a model.
It's with Grok. It's trying to say solve for
artificial general intelligence with a massive amount of AI
training compute and and inference compute.

(50:43):
So for example, for Croc 5 will actually only run effectively on
a GV300. That's, that's how much of A
beast that Croc 5 is. So, you know, whereas Tesla's,
you know, models are, I don't know, maybe about less than 10%

(51:04):
the size, maybe closer to 5% thesize of, of, of Croc.
So yeah, they're, they're they're, they're really coming
at the problem from very different angles.
X and Grok are are you know they're competing with.

(51:25):
You know, Google Gemini and opening I ChatGPT and that kind
of thing. So, and some of it's
complementary, for example, for grok voice, being able to
interact with grok in the car iscool Grok for you know, Optimus
voice recognition and voice generation is grok.

(51:49):
So that's that's helpful there. But they are.
Coming at it from kind of opposite ends of the spectrum.
Already, Adam, let's give it another try.
When you're ready, please unmuteyourself for the next question.

(52:09):
Already unfortunately still having audio issues, so we're
gonna move on to Walt from LightShed.
Walt, please go ahead and unmuteyourself can.
You hear me now? Yes, Perfect.
Thank you. Just getting back to Austin, if,

(52:33):
if you can remove the safety driver at year end, is the
limitation the Bay Area just regulatory or is it kind of the
market by market learning process?
And I guess similarly in the 8 to 10 markets that you mentioned
to get added, is the decision there to put, you know a safety
attendant in the passenger seat or the safety driver?
And is that like your step by step process to opening up a

(52:57):
market or is it really just the regulation in the individual
market? Well, it's, I think, I think
even if the regulators weren't making us do it, we'd still do
that as the, as the sort of right, sort of cautious,
cautious approach to a new market.
So just to make sure that we're being, you know, paranoid about
safety, I think it makes sense to have a sort of a sort of a

(53:21):
either safety driver or safety occupant in the car when we
first go to new markets. To just to confirm that there's
not something we're missing. Because all it.
Takes is like one in 10,000 trips to go wrong and and you've
got you've got an issue. So it's it just to make sure
like is is there some peculiarity about a city like a,

(53:42):
a very difficult intersection orI don't know, something that's
that's an unexpected challenge in in a city for that one in
10,000 situation. So, right, I think we, we, we
probably could just let her loose in the, in this, in these
cities, but we just don't want, we don't want to take a chance.

(54:03):
And, and, and like, you know, what we're talking about here
is, you know, maybe 3 months of safety driver in, in a new metro
to confirm that it's good. And then we take the safety
driver off that, that kind of thing.
OK. And then on, on FSD 14, it has a
different feel than 13 and it's also I think a little different
than what it feels like in in Austin.

(54:25):
Are you, is it basically def different development pass path
that you're doing in terms of the robotaxi stuff versus what
you're dropping to the early adopters?
And when you and when you push these new builds, is it that
you're you're looking for notable improvements in
intervention rates or is that largely solved and it's more
about adding the functionality like the parking, the Dr. modes

(54:46):
or or just the overall comfort? Now the the first priority when
we release a a major new software architecture of.
For autopilot is safety. So, so it's, it starts off with
safety, obviously safety prioritized and then we've, and
then we solve comfort thereafter, which is why I don't

(55:06):
recommend people take the, the initial version.
Like like that's why I say like,yeah, most people should wait
until 14.2 for before they actually download version 14
because by 14.2 we'll have addressed many of the comfort
issues. The priority is, is very much
safety 1st and then thereafter the comfort issues.

(55:29):
That's why most people are like,probably it'll be a little like
it'll be safe but jerky. And we just need time to kind of
smooth the rough edges and solvefor comfort in addition to
safety with a with a major news autopilot architecture change.

(55:52):
But it really is, I mean, I, I, I know what the, you know, the
road map is for the Tesla real world AI and, and a very
granular detail. Obviously Ashok is leading that.
And, and I mean, I spent a lot of time with the team going, you
know, in, in like excruciating detail here on, on what, what,

(56:17):
what we're doing to improve the real world AI.
And like I said this, this car is going to feel like it is a
living creature. And that's with AI 4 before even
AI 5. Yeah, the road map is super
accelerating like it's like so like waiting so much like
released all the stuff we're working on in terms of like, you
know, what we ship to customers versus robotaxi, it's mostly the

(56:41):
same. Obviously customers have
somewhat features like you know,they can choose the car wants to
park in a spot or driver or something like that, which is
not super relevant for Robotaxi.But there's only a few minor
changes like those ones. But the majority of the
algorithms and architecture, everything is the same between
those two platforms. Yeah.
But and as I mentioned earlier, like we'll be adding reasoning

(57:02):
to, I don't know, Shrek, is thatlike reasoning in like 14.3,
maybe 14.4, something like that?Yeah.
Or by end of this year for sure.Yeah, so with reasoning, it's
literally going to think about which parking spot to pick at
the. So it's going to say this is the
entrance, but actually probably there's not a parking spot right

(57:23):
at the entrance if it's a full, you know, if the if the parking
lot is fairly full, the probability of an open parking
spot right at the entrance is very low.
But actually what it'll simply do is drop you off at the
entrance of the store and then go find a parking spot.
But it's it's going to get very smart about figuring out a
parking. Spot it's going to spot.

(57:43):
Figure out it's going to spot Empty spots.
Much better than human. It's got 360° vision.
And it's gonna, yeah. Yeah, like I said, just it's.
It's gonna use reasoning to solve things.
And putting that all inside the computer that has a four is the
actual challenge. And that's what the team is

(58:03):
working on. Because obviously you can do
reasoning on the server that takes whatever, but then in car
you need to make real time decisions.
So putting on the computer that's in the car, that's the
challenge. Yeah, that's why I say like,
like I have a pretty good understanding of like AI, you
know, the, the sort of the, the giant model level with Grog and
with, with Tesla. And like I'm confident in saying

(58:25):
that Tesla has the, the Tesla AIhas the highest intelligence
density when you look at the, the intelligence per GB.
I think like Tesla, AI is probably an order of magnitude
better than anyone else and doesn't.
Have any choice because that that AI has got to fit in the AI
for computer. The but the the discipline of

(58:46):
having that level of AI intelligence density will pay
great dividends when you go to something that has an order of
magnitude, order of magnitude more capability like AI5.
Now you have that same intelligence density but but you
got 10 times more capability in the computer.
Great. The next question will come from

(59:08):
Colin at Oppenheimer. Colin, please unmute yourself
when you're ready. Alan, go ahead and unmute
yourself please. Thanks so much guys.
You know, I appreciate you bringing up the, the challenges
of hand dexterity and humanoids,you know, along with the
complexity of the supply chain and the, the vertical

(59:30):
integration you guys are pursuing.
You know, I'm just trying to harmonize the, the timeline for
the start of production, you know, next year with the current
state of the supply chain and what sounds like a fair amount
of work remaining on the dexterity before you can really
freeze the hardware design and and start to scale up
production. Well.

(59:51):
We're not the, the hardware design will not actually be
frozen even through startup production.
There'll be continued iteration because a bunch of the things
that you discover are very difficult to make.
You only find that pretty late in the game.
So we'll be doing rolling changes of of for the optimist
design even after startup production.

(01:00:12):
But I do think that the the you know, the new hand is.
An an incredible piece of engineering and you know,
that's, well, actually we'll have a production intent
prototype ready to show off in, you know, Q1, probably February

(01:00:32):
or March and then we're yeah. We're we're, we're going to be.
Building a, you know, million unit Optimus production line,
you know, hopefully with the production start towards the end
of next year, but that that production ramp will take a

(01:00:54):
while to get to annualized rate of 1,000,000 because it's going
to move as fast as the the slowest, dumbest, least lucky
thing out of 10,000 unique items.
But it, but it will, it will getto 1,000,000 units and then
ultimately, you know, we'll do Optimus 4.

(01:01:16):
That'll be, you know, 10 millionunits, Optimus 5, maybe 50 to
100 million units. I mean, it's really pretty
nutty. Yeah.
All righty, that is unfortunately all the time we
have for Q&A today. Before we conclude though,
Vaibhav has some closing remarks.

(01:01:39):
Thanks, Davis. I want to take the time to talk
about an extremely important vote which is being held on
November 6th. The meeting will shape the
future of Tesla and we are asking you as our shareholders
to support Elon's leadership through the two compensation
proposals and the re election ofIra, Kathleen and Joe to the

(01:02:01):
board. Note that it is a team sport and
here at Tesla, the board is an integral part of the winning
team. Shareholders are at the center
of everything we do at Tesla, and a special committee has laid
out a compensation package. Like Elon said, don't we don't
even want to call it a compensation package.
Yeah. So the point is that I just like

(01:02:23):
there needs to be enough voting control to give a strong
influence, but not not so much that I can't be fired if I go
insane. But I you know, and I think
that's sort of numbers in the mid 20s approximately.
As a company that has already gone public, there's no.
That we've investigated every possible way to how do you
achieve increased voting controlwithout, you know, is there some

(01:02:50):
way to have like a super voting stock?
But there there really isn't, isthere is no way to have a super
voting stock after you've gone public.
But for example, Google, Meta, you know, many other companies
have this, but they, they had itbefore they went public.
And so it sort of gets, I guess grandfathered in.

(01:03:12):
Tesla does not have that. So it's just like I said, I just
don't feel comfortable building a robot army here and not and
then, you know, being ousted because of some ASEAN
recommendations from ISS and Glass Lewis who have no freaking
clue. I.
Mean those guys are corporate terrorists and.

(01:03:35):
And the problem yeah. So let me like explain.
Like the core problem here is that so many of the index funds,
the passive funds vote along thelines of what whatever Glass
Lewis and ISS recommend. Now, they've made many terrible
recommendations in the past thatif those recommendations have

(01:03:56):
been followed, would have been extremely destructive to the
future of the company. But if you've got passive funds
that essentially defer responsibility for the vote to
Glass Lewis and ISS, then you can have extremely disastrous
consequences for a publicly traded company.
If if too much of the publicly traded company is controlled by

(01:04:19):
index funds, it's de facto controlled by Glass Lewis and
ISS. This is a fundamental problem
for corporate governance becausethey're not voting along the
lines that are actually good forshareholders.
That's the that's the big issue.I mean, that's what it comes

(01:04:41):
down to. ISS, Glass Lewis Corporate
Terrorism? Yeah.
And I would say, you know the special committee did an amazing
job in constructing this plan for the benefit of the
shareholders. There is no nothing which gets
passed on till the time shareholders make substantial
returns. So that's why, you know, in the

(01:05:02):
end, I would say, I would urge you to not only work on the
plan, but also work on all the three directors because of their
exceptional knowledge and experience.
And literally, you know, we at Tesla work with these directors
day in, day out. I mean, there is not even a
single day that one of the directors I haven't spoken to or

(01:05:26):
one of my colleague hasn't spoken to.
And we're the even the directorsout here are not just reading
out of. You know, PowerPoint
presentations, they're actually working with us day in, day out.
So again, I just urge you guys as shareholders to work along
the board's recommendation. Thank you guys.
Great. Thank you, Vaibhav.

(01:05:47):
We appreciate everyone's questions today.
We look forward to talking to you next quarter.
Thank you very much and goodbye.Hey, thank you so much for
listening today. I really do appreciate your
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(01:06:08):
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