Latest / Elon Musk Podcast / Tesla Q2 2023 Financial Results and Q&A Webcast

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Tesla Q2 2023 Financial Results and Q&A Webcast · Elon Musk Podcast

0:00
Good afternoon, everyone, and welcome to Tesla second quarter
0:02
2023 Q&A webcast. My name is Martin Vieca, VP of
0:05
Investor Relations, and I'm joined today by Elon Musk,
0:08
Zachary Kirkhorn and a number of other executives.
0:11
Our Q2 results were announced at about 3:00 PM Central Time in
0:14
the update deck we published at the same link as this webcast.
0:18
During this call, we will discuss our business outlook and
0:20
make forwardlooking statements. These comments are based on our
0:23
predictions and expectations as of today.
0:26
Actual events or results could differ materially due to a
0:28
number of recent uncertainties including those mentioned in our
0:31
most recent filings with the SEC.
0:34
During the question and answer portion of today's call, please
0:37
limit yourself to one question and one follow up.
0:40
Please use the raise hand button to join the question queue.
0:43
But before we jump into the Q&A, Elon has some opening remarks.
0:47
Elon. Thank you, Martin.
0:49
So just a Q2 recap. In Q2, we achieved record
0:53
vehicle production and deliveries and record revenue of
0:55
about $25 billion in a single quarter.
0:58
And Model Y became the best selling vehicle of any kind
1:01
globally in Q1, surpassing the lights of likes of Corolla and
1:06
Golf. So it was the number one vehicle
1:08
of any kind, including vehicles that are at a seller far lower
1:12
price. This is I think an incredible
1:15
achievement by the Tesla team and just a huge thank you to our
1:19
customers for their support. So and this came in spite of
1:24
high interest rates and a lot of macro uncertainty and
1:29
nonetheless we managed to achieve operating margin of
1:32
about 10%. We continue to target 1.8
1:38
million vehicle deliveries this year, although we expect that Q3
1:44
production will be a little bit down because we've got summer
1:47
shutdowns to for. A lot of factory upgrades, so
1:53
just probably a slight decrease in production Q3 for sort of
1:58
global factory upgrades in the long term autonomy, we think
2:05
it's gonna just drive volume through the ceiling next level
2:11
and our future Robotaxi products, dedicated Robotaxi
2:17
products. We think have like quasi
2:21
infinite demand so and we're the way we're gonna manufacture the
2:31
robot taxi is is also itself a revolution and so it's
2:35
revolutionary design made in a revolutionary way.
2:40
It'll be by by far the highest units per hour of of any vehicle
2:46
production ever so. Very, very excited about that.
2:52
With respect to Autopilot and Dojo, in order to build
2:55
autonomy, we also need to train our neural net with the data
2:59
from millions of vehicles. With the more, I mean this has
3:03
been proven over and over again, the more training data you have,
3:05
the better the results. And I mean there's times where
3:10
we see basically in a neural net, basically it's sort of at a
3:17
million training examples. It barely works at 2,000,000.
3:21
It's it slightly works at 3,000,000 it's like wow, OK
3:25
we're seeing something but then you get like 10 million training
3:27
examples. It's it's like it becomes
3:29
incredible. So you just there's just there's
3:33
just no substitute for massive amount of data and obviously
3:37
Tesla has more vehicles on the road that are collecting this
3:43
data than all of the companies combined by I think maybe even
3:47
an order of magnitude. So I think we might we might
3:50
have 90% of all or a very big number.
3:55
So you know the success in AI and dev is is a function of
4:01
talent sort of unique data and computer resources and and we
4:13
have outstanding capabilities in all three arenas.
4:20
And I really just don't know how anyone could do what we're doing
4:23
even if they had our software and had our computer if they did
4:26
not have the the the training data.
4:28
So Speaking of which, our training computer is designed to
4:33
significantly reduce the cost of neural net training.
4:37
It it is designed to it's it's it's so optimized for the kind
4:41
of training that we need which is a video training so.
4:46
You know would we just see that that the need for neural net
4:51
training being a quasi things is is just enormous.
4:58
So I think having having we we we we expect to use both NVIDIA
5:03
and Dojo to be clear. But there's there's we just see
5:09
demand for really fast training resources.
5:16
And we, we think we may reach in house your net, your net
5:20
training capability of 100 exaflops by the end of next
5:24
year. So to today over 300,000,000
5:30
miles have been driven using FSD beta.
5:33
That 300,000,000 mile number is gonna seem very small very
5:37
quickly. It'll soon be billions of miles,
5:42
then 10s of billions of miles. And that FSD will will go from
5:47
being better, from being as good as a human to them being vastly
5:51
better than a human. We see a clear path to full self
5:55
driving being 10 times safer than the average human driver.
6:01
So and between autopilot Georgia computer, our inference hardware
6:11
in the car which we calls. Sort of hardware 3-4, you know,
6:16
but it's really dedicated, it's it's, it's a high efficiency in
6:19
front of computer that's in the car.
6:20
And our optimist robot translates clearly at the
6:24
cutting edge of a ad development to with we continue to build
6:32
release candidates of the cyber truck on our final production
6:35
line in Austin. I'm actually here in Austin at
6:37
the Giga factory, this is the first truck that we're aware of
6:42
that will have 4 door. Was over 6 foot bed and 1 foot
6:46
into a 20 foot garage. So it's it's a it's a biggest on
6:50
the outside but it's even bigger on the inside.
6:52
So it's a I think that's one of the one of the elements of good
6:56
design is it should feel bigger on the inside than it looks on
7:00
the outside. And and this is this is no small
7:02
car but we we we really cared about the exterior dimensions of
7:07
the side truck down to the last millimeter.
7:10
So it's just we try to get right in the middle of the Goldilocks
7:13
zone, not too big, not too small and and then really maximize the
7:19
utility of the volume and we can't wait to start delivering
7:24
it later this year. Some some other highlights, our
7:28
global supercharging network now stands at over 50,000, roughly
7:33
50,000 connectors and over 5000 locations as I think a lot of
7:37
people are aware. The Tesla starting the the Tesla
7:43
charging standard which we made open source and it's now called
7:47
the North American charging standard.
7:49
We're we're deeply honored that Ford, GM, Mercedes and many
7:53
other O M's have signed up to use our connector and gain
8:00
access to our charging network. Yeah we we we strongly believe
8:06
in helping. Other car companies to
8:12
accelerate the EV revolution and just trying to do the right
8:16
thing in general. So that's a goal there.
8:24
Then it's only I think I want to emphasize like very, very
8:29
strongly. This is a very important point
8:32
is that tells that just as with the.
8:38
North American charging standard, although we're not
8:39
licensed in that case not licensing, we're just making it
8:42
available, but but we are very open to licensing our full self
8:47
driving software and hardware to other car companies and we are
8:51
already in discussions with early discussions with a major
8:56
OEM about using the Tesla FSD. So we're not trying to keep this
9:03
to ourselves, we're more than happy to to license it to
9:06
others. And lastly, our new lithium
9:10
refinery and catheter facility are progressing well.
9:15
Then in conclusion, we continue to focus on making as many
9:18
causes as we can while maintaining healthy financials.
9:22
Our artificial intelligence development is obviously
9:25
entering a new era and we're incredibly excited about what's
9:30
to come. Our other businesses such as
9:32
Megapack supercharging service. And what not all started to
9:36
become a meaningful contributor to overall profitability this
9:40
quarter. And then lastly, I'd just like
9:43
to profusely thank all of our employees who are making a lot
9:49
of extra effort during uncertain times.
9:51
Thank you very much for your hard work and impact you're
9:53
making. Thank you very much, Elon.
9:56
And I think Zach gets some opening remarks as well.
9:59
Yeah. Thanks, Martin.
10:01
As Elon mentioned, Q2 was another record quarter of
10:04
production and deliveries, as well as records and profit for
10:07
energy and services and other businesses.
10:09
Congratulations again to the Tesla team on the continued
10:12
progress as we navigate through a period of economic
10:16
uncertainty, rising interest rates, volatility and consumer
10:19
confidence and regulatory change.
10:21
I want to comment on our financial approach.
10:24
First, the single most important priority is to ensure we are
10:27
continuing to invest heavily in the core technologies that will
10:30
drive the long term value of the business.
10:33
This include increasing spending on a I related technologies such
10:36
as full self driving Optimus and Dojo as well as new products
10:40
such as Cybertruck, our next generation platform in the semi
10:44
as evidenced by the continued growth in our R&D spend.
10:47
This also includes continuing our investments in capacity
10:50
expansion. Not only in our vehicle
10:52
factories, but also our supercharging network, service
10:55
internal applications and battery processes as we continue
10:59
with meaningful capital expenditures to lay this
11:01
foundation for the future. 2nd, we continue to work towards our
11:04
goals of maximizing volumes on both our vehicle and energy
11:08
business, but most importantly doing so in a way that generates
11:12
the capital to continue our pace of R&D and capital investments.
11:16
This requires a strong focus on per unit COGS reductions in each
11:19
of our key businesses. As well as working capital
11:22
improvements on raw materials, working process inventory and
11:26
customer AR, all of which progressed appropriately in Q2.
11:30
If we look specifically at our automotive business, our gross
11:33
margin showed a modest reduction and remain healthy despite
11:37
action taken to further improve vehicle affordability.
11:40
Early in the quarter, we recognize we realize per unit
11:44
cost improvements in nearly every category including
11:46
material costs and commodities, manufacturing costs and
11:50
logistics. While also continuing to rapidly
11:52
increase the build rate in our Austin and Berlin factories.
11:56
For our energy business, we improved margins and gross
11:58
profit driven by cost reductions in deal economics, particularly
12:01
with Megapack. As a reminder, storage volumes
12:05
are typically volatile sequentially based on the types
12:07
of projects and their specific revenue recognition milestones.
12:12
As we look forward to the rest of the year, I want to reiterate
12:14
Elon's comments on Q3 volumes driven by plan down times for
12:18
factory upgrades. These upgrades will also carry
12:21
some amount of factory at all cost.
12:23
How however, we are working to minimize as much as possible.
12:26
It's also important to keep in mind the uncertainty in the
12:28
macro environment which can impact our execution positively
12:32
or negatively in the near term. Regardless, we continue to
12:35
remain dynamic with a focus on fundamental efficiency and a
12:39
long term outlook. Congratulations again to
12:42
everybody on a great quarter. Thank you very much, Zach, and
12:46
let's go to investor questions. The first, the first question on
12:48
licensing FSD, we've already answered.
12:50
So let's go to the second one. The second question is what is
12:53
the status of 4680 cells? How far are you from the specs
12:58
you laid out on Battery Day? When do you expect to achieve
13:01
what you laid out on Battery Day?
13:05
Yeah. First, I'll just start with a
13:06
little bit of a production update.
13:08
So in Texas 4680, cell production increased 80% Q2 over
13:13
Q1. And the team surpassed 10
13:15
million production cells produced here in Texas, so
13:17
Congrats to the team for that. Their focus on yield reduced our
13:21
scrap bill by 40% quarter over quarter and that resulted in a
13:25
25% reduction in cell COGS. Here in Texas, we're preparing
13:30
to launch our cyber truck cell, which is 10% higher energy
13:32
density than current production. That was accomplished through
13:35
process and mechanical design optimization as we scale cyber
13:39
cell production through the end of.
13:41
The year and early next, we should be in a comfortable place
13:44
on cost per cell against our battery energy density targets.
13:49
The cyber cell is at our expectations on a like for like
13:52
electrochemistry basis. We're yet to integrate silicon
13:56
or in house cathode production, both reviewed on battery day,
13:59
which do bring significant further energy density and cost
14:01
improvements, but that is a topic for another day.
14:05
Lastly, it is important to remember that most of what we
14:07
focused on a battery day was the Tesla engineered 4680 production
14:11
system and the improvements we strove to achieve on equipment
14:14
factory density, capital cost and utility cost reduction, all
14:18
of which we are realizing in our Texas scale up to date.
14:22
Thank you very much. The next question is, can you
14:26
talk more to the upcoming Tesla Energy products and how you're
14:30
thinking has evolved on the revenue model?
14:32
Given Tesla's AI capabilities, how do you see the long term mix
14:36
between hardware margin and recurring softer margin from
14:39
auto bidder as the segment accelerates?
14:44
We can't comment on future product road map, but I can
14:46
provide a quick energy Q2 update.
14:49
Megapack continues to show strong demand globally with
14:52
Lathrop ramping successfully to meet our contracted projects in
14:55
2023. As stated last quarter, Megapack
14:58
margins are in a reasonable place in line with our target
15:01
market vehicle target margins. The second final assembly line
15:05
at Lathrop is progressing on schedule, eventually doubling
15:08
Lathrop capacity ahead of our full factory ramp in 2024.
15:11
We have several exciting large projects in construction or
15:14
nearing completion, including the KES project in Hawaii, the
15:18
River Rena project in Australia, several projects in California
15:20
and one here at Gigafactory, Texas toward today actually.
15:24
We want to thank our customers, utilities and grid operators for
15:27
trusting us with these projects. On the auto bidder question, we
15:30
continue to grow auto bidder contracts in wholesale markets
15:33
like Australia, Texas, UK and California with over 6 kwatt
15:36
hours under Tesla's dispatch next year in the UK, Our project
15:40
performed best in the industry in Q2.
15:43
Auto bidder does have software margins and is an enabler for
15:46
hardware sales, but it's a relatively small contributor to
15:49
revenues given how much deployment growth on the
15:51
Megapack hardware side is occurring.
15:53
It's important to remember that these large projects, these
15:56
large capital projects have lifetimes of 20 years of
15:58
recurring revenues on an analyzed basis relative to
16:00
upfront CapEx are small. On the residential side, we have
16:04
some fun things happening. We recently surpassed a half
16:07
million power walls installed. Just this week we were launching
16:10
charge on solar, which allows test the power wall and vehicle
16:13
customers to charge their vehicles using their excess
16:15
solar and drive only on the sunshine that hits their roof.
16:19
Yesterday we began paying customers in Texas for
16:21
participating in our virtual power plant to provide grid
16:23
support to ERCOT. We expect these credits to lower
16:26
our median customers annual bill by a third and to increase these
16:30
credits over time as ERCOT expands market access.
16:33
And today we are expanding Tesla electric enrollment to new Model
16:35
3 owners in Texas, fall by all Texas vehicle customers over the
16:38
rest of the quarter unfortunately and somewhat
16:41
similar to Tesla insurance. Bringing Tesla Electric and VPP
16:45
capabilities to our customers requires working through a
16:47
fractured regulatory environment on a jurisdiction by
16:50
jurisdiction basis. In the long run, the value of
16:53
residential energy software and hardware will be driven by the
16:56
level of market access that utilities, market operators and
16:59
regulators permit. For power walls eligible to
17:02
provide the full stack of energy services like peaker, peaker
17:05
capacity and system buffering such as in Australia, we can
17:08
more than double the value of ownership relative to a typical
17:10
system today. Thank you very much.
17:14
The next question is, could you quantify the benefits to COGS
17:18
per unit from the IRA battery manufacturing incentives?
17:22
And secondly, battery raw material declines year to date?
17:27
All right. I can take that.
17:30
On the first part of the question for IRA manufacturing
17:33
incentives, we provided previous guidance that we expect these to
17:37
be. For the course of this year in
17:39
the range of 150 million to 250 million per quarter, we are
17:45
staying within that boundary as we got it previously.
17:47
So that was the case in Q2 as well.
17:50
I will note, I think we've mentioned this before that this
17:54
includes a 5050 sharing of credits for qualified sales from
17:59
our long term battery partner Panasonic on the commodity side.
18:05
We are continuing to see improvements there.
18:07
As we've discussed previously, Lithium is the most notable
18:10
improvement so far. I think I commented on this on
18:14
the last call because typically we see this coming about 1/4
18:18
before it actually is realized in our financials.
18:21
And also just as a reminder, we're not fully exposed to the
18:24
price of Lithium. Our supply chain team has done a
18:27
terrific job in partnership with another bunch of other companies
18:30
to put in place. Some long term agreements here,
18:34
but we do have some exposure that moves up and down.
18:38
We're also seeing benefits in aluminum and steel which I think
18:41
is great but not as large as the lithium impacts, but they
18:46
contribute nonetheless. So if we add up the total impact
18:49
of this in Q2 relative to prior quarter, it's about the same
18:53
size and magnitude as the IRA benefits that we also received,
18:58
you know just to put this in context.
19:01
As you look at COGS per unit sequentially from Q1 to Q2, I
19:05
think there's there's two things to keep in mind there.
19:08
The 1st is that our SX mix and for deliveries increased quite a
19:12
bit from Q1 to Q2. So as you think about
19:15
fundamental cost reductions, it's important to adjust for
19:19
that. And then secondly, you know as
19:22
we continue to work on reducing our Austin and Berlin costs
19:25
which we did quite a bit of that from Q1 to Q2.
19:29
These factories are still a slightly above Model Y
19:32
production costs elsewhere and in the quarter, our mix of
19:36
Austin and Berlin related builds increased.
19:39
And so that's something to consider as you model out the
19:43
impact on from Q1 to Q2 in terms of COGS per unit.
19:47
I do want to ask Karen if there's anything else on the
19:49
commodity side or just more generally you want to add here.
19:53
Yeah, As you mentioned Zach, we we've naturally been a little
19:56
bit hedged from the lithium position because the the long
19:58
term contracts we have in place. But we have seen reduction in
20:01
pricing across the board for all commodities that specifically go
20:05
into batteries such as nickel, cobalt and graphite.
20:09
And the reductions and pricing translate into thousands of
20:11
dollars. When you look at it from a
20:13
purvedaical impact. We're taking advantage of the
20:17
look historically low commodity pricing in certain areas to kind
20:20
of extend some of those fixed price contracts.
20:23
Through the end of the decade. So it's a playbook that will
20:25
continue to kind of go back to as we look to the future.
20:30
Thank you. And the next question on FSD.
20:33
Have you considered allowing FSD transferability as a lever to
20:37
allow existing customers to upgrade to a new Tesla instead
20:40
of being locked into an existing car due to the price of FSD?
20:45
Yeah, this is a question we get asked a lot.
20:49
So we're excited to announce that for Q3 we will be allowing
20:54
transfer of FSD. This is a one time amnesty.
21:00
So it needs to be you need to take advantage of it in Q3, but
21:06
or at least place the order in Q3 with within with within
21:08
reasonable delivery time frames. So yeah, yeah.
21:15
Yeah, I hope this makes people happy this one time thing.
21:23
Right. The next question, when will,
21:25
when will we give more information about the cyber
21:28
truck orders, estimated delivery schedules, pricing and
21:31
specifications? The demand is so is so far off
21:37
the hook, you can't even see the hook.
21:39
So that's really not an issue. I do want to emphasize that the
21:43
cyber truck. Has a lot of new technology in
21:46
it like a lie, it doesn't look like, it doesn't look like you
21:52
know any other vehicle because it is not like any other
21:54
vehicle. So and the production ramp will
21:58
move as fast as the slowest and least like the elements of the
22:02
of the entire supply chain and an internal production.
22:07
So you know, I wouldn't expect you know it.
22:13
I I hope it's smooth. You know we're certainly better
22:15
at production ramps than than you know we've got a lot of
22:19
experience with production ramps.
22:20
But you know first order to 1st order approximation is there's
22:24
like 10,000 unique parts and processes in in a you know in
22:30
the Cybertruck and if any one of it'll go as fast as the least
22:34
lucky, you know least well executed element of the 10,000
22:38
so. Always very difficult to predict
22:41
the ramp initially, but I think we'll be making them in high
22:45
volume next year and we will be delivering the car this year.
22:52
Thank you. The next question is critics of
22:55
Giga casting contended that process makes vehicles harder
22:58
and more costly to repair, essentially pushing costs onto
23:01
the customer. You share some details about the
23:04
initial repair experience with Giga cast vehicles.
23:06
That must be why everyone's copying us.
23:10
Yeah, thanks you. On.
23:11
This is Lars and Martin. That that's like, simply not
23:14
true. There's a misconception that
23:16
traditional bodies are easy to repair, but they're made of
23:19
multiple materials and multiple joining methods.
23:21
Spot welds and rivets have to be drilled out.
23:23
Panels and structural adhesive have to be chiseled out, dry
23:26
adhesive has to be removed, stampings cut, blah, blah, blah.
23:29
It's a crazy patchwork quilt. Yeah.
23:31
And so putting that back together means time and money.
23:33
Using an example of replacing a rear cast rail on a Model Y.
23:38
To do that versus like what we replaced it with from the Model
23:41
3, it's 1010 times cheaper and three times faster to do it with
23:44
the cash rail. My design team works with our
23:47
collision repair team since we're closed loop on this with
23:50
insurance and we design specific parts that are make it easier
23:53
and faster to repair, we have an incentive to do that because we
23:56
have our own insurance and our own body shops.
24:00
We expect that we'll continue to do this and collision repair
24:03
will continue to become cheaper and faster over time.
24:05
And we already made this available to all body shops or
24:07
our tests are approved Body Shop training.
24:10
Yeah, closing loop on collision repair and factoring that into
24:13
design is is a big deal. It's crucial.
24:15
I don't think anyone else can do it with that ecosystem that we
24:18
have. So, yeah and and we are actually
24:20
able to change the details of the casting with inserts and we
24:24
actually do do that all the time.
24:26
So because the the answer is actually wear out and.
24:29
Need to be replaced anyway, so we can actually make design
24:32
changes to the inserts and tweak the castings, but the the cast
24:36
basically cast the rear rear body or front body is lighter,
24:40
cheaper, better for noise, vibration, harshness, much
24:44
easier to manufacture and it's better in every way.
24:49
And that's why so many other car companies are copying us,
24:52
because probably they don't know.
24:55
They certainly put out a lot of fresh releases about it.
24:59
I think it's basically going to be how old cars are made in the
25:02
future. Thank you.
25:06
Next question, how many optimist bots have been made and when
25:10
will they be able to start performing useful tasks?
25:12
10 million, yeah. I think.
25:21
I think we're around 5:00 or 6 bots like, you know, there's an
25:26
we're. Like 10 I guess yeah it depends
25:29
on what how many are working and what phase.
25:32
But it's it's sort of yeah, like there's there's more more every
25:40
month the there's a lot of interesting things a lot of
25:47
interesting things about the option spot.
25:51
We found that there are actually no suppliers that can produce
25:54
the actuators. There are no off the shelf
25:58
actuators that work well for Human Aid Robot at any price.
26:02
Certainly not compelling. Yes, not a not a human robot
26:07
that can do something that, you know, the things that human
26:10
could do. So we've actually had to design
26:14
our own actuators that integrate the motor of the power
26:18
electronics, the controller. The sensors and really everyone
26:27
of them is custom design. So and then of course we'll be
26:34
using the same inference hardware as the car.
26:40
So you know and we are in designing these actuators,
26:46
designing them for volume production.
26:48
So they're not just lighter, tighter, more and more capable
26:52
any any other actuators that that we're aware of that exists
26:55
in the world. There's also actually
26:58
manufacturable. So we we should be able to make
27:01
them in volume. The the first optimist that is
27:07
that will have all of the test that designed actuators sort of
27:11
production candidate actuators integrated and and walking
27:16
should be. Around November ish so and then
27:22
we'll we'll we'll start wrapping up after that you know in terms
27:29
of when we'll be able to do some useful things like we'll first
27:34
be trying this out in our own factories and just proving out
27:37
its utility. But I I think I think we'll be
27:40
able to have it do something useful in our factories sometime
27:44
next year I I would be. Yeah, I'm pretty, pretty
27:49
confident of that. So yeah, and it's going well, I
27:58
should say. Another cool thing about
28:00
optimists is that, you know, there's just in the US alone,
28:03
there are two million amputees. And I was just talking to the
28:09
neural link team and by combining A neural link implant.
28:15
And a robotic armor leg. For someone that has has had
28:20
their arms, armor leg or all arms and legs amputated, we
28:25
believe we can give you basically a cyber body that is
28:30
incredibly capable $6 million man in real life before.
28:38
Don't worry it cost $6,000,000 sixty $1000 man.
28:45
Since I was impressive but it's it'll actually you know so that
28:49
that that actually could be a really I think would be
28:52
incredible to you know potentially help police people
28:55
around the world and and give them you know Obama like that is
29:03
as good maybe a long term better than a biological 1.
29:08
Thank you. The next question is how has the
29:11
order intake trended relatively to production levels during Q2
29:15
and how is it trended in the quarter to date period?
29:18
Conceptually, how does this decide when is it appropriate to
29:21
reduce prices or add other sales incentives to increase demand?
29:28
Yeah. I guess demand is roughly track
29:29
production. So which is what we aim for is
29:35
is. But we look at you know
29:37
something that that we have that really I think no other car
29:40
maker has is that we have real time demand and real time
29:44
production like so seven days a week you know I get an e-mail
29:51
order generated e-mail that shows output from all factories
29:55
and orders globally. So it's like a real time thing
29:59
on the pulse of earth basically and and we would you know.
30:06
We're just we're just course according to what the mood of
30:09
the of the public is. You know buying a new car is a
30:14
is a big decision for vast majority of people.
30:17
So you know anytime there's economic uncertainty people
30:21
generally pause on your car buying at least to see to see
30:25
what happens and you know and then obviously another challenge
30:30
is the the interest rate environment as interest rates
30:34
rise. The affordability of anything
30:37
bought with debt decreases, so effectively increasing the price
30:42
of the car. So when interest rates rise
30:45
dramatically, we actually have to reduce the price of the car
30:48
because the the, the interest payments increase the price of
30:52
the car. So and and this is at least at
30:57
least up until recently it was the, I believe the sharpest
31:00
interest rate rise in history. So we had to do something about
31:04
that. And if somebody's got a crystal
31:08
ball for the global economy, I really appreciate it.
31:11
If I got borrow that crystal ball.
31:14
Yeah, exactly. Damn.
31:15
Yeah, it should be. Not on Twitter.
31:19
So, I mean, one day it seems like the world economy is
31:24
falling apart and the next day everything's fine.
31:27
I I don't know what the hell is going on.
31:30
It'd be totally frank. I wish I did.
31:34
So I I mean that that's why that's why I say like I always
31:38
you know you know I on Twitter I posted like you know just really
31:42
advising because I, you know I care a lot about the the the the
31:47
sort of the small shareholders especially ones that have stuck,
31:51
stuck with us through through thick and thin.
31:53
I love you guys and so the. We we can't control these macro
32:00
shocks you know or the the manic depressive nature of the stock
32:04
market. So that's why I I recommend
32:06
against margin loans in times that are turbulent.
32:10
You know if times are not that turbulent actually a margin loan
32:13
can be a smart move within reason but but we're in I would
32:18
call it turbulent times. I like I have very high
32:23
confidence, confidence in the long term value of Tesla.
32:28
Like I I see it really, you know, see a path to a 10X these
32:33
days, like 5X increase in the value of the company, maybe a
32:40
10X and where things go along the way that the trials and
32:47
tribulations and the mood of the mood of the markets 1 cannot
32:51
predict. And so you know.
32:57
The the, the old adage of buy and hold is is right.
33:01
You know, for investment advice I say like identify companies
33:07
products you love See if they you know does it seem like
33:12
they'll continue to make good products or great products.
33:16
Buy that stock and hold it, that's it.
33:19
But you will win. The reason companies exist is to
33:25
make. Goods and services, ideally
33:27
great goods and services, they don't exist for any other
33:31
reason. They shouldn't.
33:33
So that's why I should buy a software company that makes me
33:36
likeson has a great future pipeline.
33:38
It's common sense actually And and then and then generally if
33:46
you see if if you provided, you're confident about what that
33:50
company's products or services are when the market panics.
33:56
Buy and when the market is, you know, overly exuberant, you can
34:01
sell. I'm not recommending yourself as
34:02
a bit, but yeah, I love sell high.
34:15
You know, Warren Buffett actually I think has saying I'm
34:17
paraphrasing him. But, you know, publicly traded
34:20
companies like it's like imagine you're living in your house and
34:24
some. A crazy manic depressive guy
34:27
comes and stands at the outside your house and yells property
34:31
prices at you. You know, and it's a different
34:35
price every day. The house is still the same
34:38
house, so this is the stock market, you know, Credit that
34:45
door about it. Thank you.
34:48
Let's go to the next question. With the emphasis of price cuts
34:51
to drive volume growth eating into automotive gross margin,
34:54
can investors expect to see automotive gross margin
34:57
stabilize or even rise due to efficiencies outpacing the cuts?
35:01
And if so, when? Where's that crystal ball again
35:10
if if, I mean it's like look the, the, the short term
35:15
variances in in. Gross margin and profitability
35:20
really are minor relative to the long term picture.
35:24
Autonomy will make all of these numbers look silly.
35:30
I'd recommend looking at Arc Invest.
35:31
I think their analysis is very good.
35:34
It's the best you know I mean and generally fin Twit or like
35:42
if the finance. There's the smart fans, people
35:45
on Twitter follow their accounts.
35:47
They're great. So that that's what that that's
35:55
that's in my view where you'll get the best, best info.
35:59
So you know, I strongly believe Tesla is epic long term
36:04
investment and don't swear when you know things go up and down.
36:09
In fact, if the market panics, buy.
36:13
If the market's a little too exuberant sell at the time but
36:16
but just generally like like I feel I I confident you know we
36:21
we will deliver a long term but can't control short term so and
36:24
and these the the autonomy is is really where it's at exactly.
36:30
I fully agree with you. I mean, I think the only thing
36:34
in the short term that matters is, is what I said in my opening
36:39
remarks. Which is, you know, are
36:41
regenerating enough money to continue to invest and you know,
36:44
the portfolio of products and technologies that the technical
36:48
teams are investing in right now.
36:52
This is intense. It's intense in terms of
36:55
investment. It's intense in terms of
36:57
potential. Frankly, I think it's ridiculous
36:59
that we have positive free cash flow in a capital intensive
37:03
business while investing massive amounts of money in new
37:07
technology. That is super hard.
37:10
And vertical integration, it's not even just like new products,
37:12
but also. Yeah, we actually make our shit,
37:19
yeah. And so.
37:20
Others but. And so, at least from my
37:29
perspective, what matters is continuing to generate the cash
37:32
to invest. You know that means continuing
37:36
to be hyper focused on near term cost reduction because
37:40
everything we do in near term cost reduction provides capital
37:43
to reinvest, hyper focused on working Capital Management of
37:48
which we've made quite a bit of progress there.
37:52
On the raw materials and whip side of that, we've been very
37:56
focused on accounts receivables as well to ensure that we can
38:00
continue to reinvest, reinvest the cash.
38:04
You know that this is what we're focused on.
38:06
Yeah. And you know, so there's you
38:08
know a set of this that we control.
38:11
You know, we have a pipeline of cost reductions.
38:14
We are getting tailwinds in the commodity space right now.
38:16
As Karen mentioned, that's helpful variability around
38:21
average selling prices. You know, goes back to Elon's
38:23
point, we don't control interest rates, We don't control macro
38:28
consumer sentiment. But we have an obligation to be
38:32
responsive to that to ensure that we're matching supply and
38:36
demand and keeping things balanced.
38:38
And so this is how we're managing the next handful of
38:40
quarters. You know soon enough these
38:44
quarters will be behind us. They won't be part of the
38:48
present value of future cash flows of the business.
38:51
And so we want to make sure we keep that view and make sure
38:54
that the long term of the business is exactly the way that
38:57
we want it to be. Alright, thank you very much.
39:02
And now let's go to analyst questions.
39:06
The first question comes from Dan Levi from Barclays.
39:09
Then feel free to unmute yourself.
39:14
Great. Good evening.
39:17
Thank you. Wanted to start first with the
39:21
with a question about your efforts in AI and Dojo.
39:24
It's pretty clear, it sounds like you're accelerating your
39:26
focus. Can you maybe provide us with a
39:30
sense of what the process is of refining a product, Is it more
39:34
machines and and maybe you could give us a sense of you know when
39:38
the the payout starts to when you start to see the payout and
39:42
what the resource outlay is. You know what should we expect
39:45
on the OpEx front as a result of this?
39:50
Sorry, are you saying how much are we gonna spend on Georgia
39:52
or? Yeah, it.
39:54
Warranty of Georgia. Yes.
39:58
Well, we're not going to be open loop on our Dojo expenditures.
40:01
So but I mean I think we, we will be spending you know the
40:07
north of a billion over the next year on on through the end of
40:11
next year, it's well over a billion dollars in Dojo.
40:15
And yeah, so I mean we've got a truly staggering amount of of
40:22
video data. To do training on and this is
40:25
another thing I don't like into in order to copy us you you also
40:28
need to spend billions of dollars on on training compute.
40:32
I mean it's like and it's it's also hard to you know you need
40:37
the data you need the training computer it's like think think
40:40
all things needed to actually achieve this at scale toward a
40:43
generalized solution for autonomy is it's this is this is
40:46
one of the hottest problems ever.
40:49
You know you see a lot of AI companies doing you know Llms
40:52
and and and and whatnot and I'm saying if they're they're so
40:55
great why can't they make yourself a great driving car
40:59
because it's harder that's why. So but I do think that's that's
41:07
I think there's some you know great great AI companies out
41:09
there but but but just fundamentally the the the
41:15
staggering amount of data we've got to process recovery process
41:17
somehow. And custom silicon is the best
41:21
way to do that. So that that's what Dojo is is
41:26
designed to do is is yeah optimized for for video training
41:33
it's it's not optimized for LMS it's optimized for video
41:36
training. With the with with video
41:40
training you have a a much higher ratio of compute to
41:45
memory bandwidth so. This you know whereas LMS tend
41:51
to be memory bandwidth choked. So that's that's it I mean but
41:58
like so we're also we have some we're using a lot of NVIDIA
42:03
hardware and continue to you know we'll actually take NVIDIA
42:08
hardware as fast as NVIDIA will deliver it to us.
42:11
Tremendous respect for Jensen and NVIDIA they've done an
42:16
incredible job. And and frankly, I don't know if
42:23
they could deliver us enough GPUs, we we we might not need
42:27
your Dojo, but they can't. So they got so many customers,
42:33
they've been kind enough to you know nonetheless prioritize some
42:37
about our GPU orders, but. Yeah, the, the, the sheer
42:44
magnitude of video training because like I said, we're not
42:47
trying to just get as good as human.
42:49
We want to get to, you know, 10 times better than human, maybe
42:52
100 times better than human. Right now I believe there's
42:56
something on the order of 1,000,000 automotive deaths per
42:58
year. And and then if you say
43:00
permanent serious injuries, I think it's probably closer to 10
43:04
million per year. And you know, so it matters if
43:09
you if you're, you know. Twice as good as as human 10
43:15
times. You know like 10 times better
43:18
than human would still mean 100,000 deaths and a million
43:22
severe permanent injuries. So it's like OK, well we'd
43:25
probably be 100 times better. So there's this really you know
43:28
it's a March of 9th and and we want to achieve as perfect
43:34
safety as possible and it's fast truly mind boggling amounts of
43:39
video and and and computer needed for that.
43:42
So and then I just, you know, I do think there's there's other
43:45
applications for for Dojo but we just desperately needed for
43:49
video training. Right.
43:51
Just to just to add to what Ilan mentioned, so you know the
43:55
numbers that he mentioned are you know between R&D spend and
43:59
capital spend and you know this is moving quickly you know and
44:05
so we provide a three-year outlook on our capital expense
44:09
we are considering. These these expenses in that
44:13
outlook and as that moves up and down, we'll continue to update
44:17
our guidance in the queue. Yeah, I wanna say that the the
44:21
the fundamental rate limiter on the progress of full self
44:24
driving is training. But that's if if we had more
44:28
training compute we would get it done faster.
44:32
So that's it, that's it. And and it's just difficult to
44:36
predict how quickly, yeah, we can execute on it.
44:40
Great, thank you. Just as as a follow up, I
44:45
recognize you know there there's incredible macro uncertainty
44:49
right now, but you're sticking with your near term your volume
44:53
target 50% kegger. As we just think about sort of
44:57
in the in the year ahead, you know cyber truck is going to be
45:00
some contribution. You know there's going to be
45:04
some help from further EV penetration growth but.
45:07
But to to what extent are you willing to sacrifice on pricing
45:12
to keep that 50% volume cager intact or you know, are you
45:18
thinking differently about margins versus your prior
45:21
commentary of willing to sacrifice on margins to get more
45:23
share? It's not like getting more fair,
45:27
it's just that you can think of every car that we that we sell
45:31
or produce that that that has. Full autonomy capability as
45:39
actually something that in the future may be worth as much as
45:42
five times what it is today because, you know, average
45:50
passenger bickle is doing like maybe 10 hours of driving a
45:53
week. You know, one if if it's sort of
45:55
1 if let's say it's 1 1/2 hours a day, on average that's 10
45:58
hours a week. Ish if you've got.
46:04
An autonomous if that that vehicle's able to operate
46:10
autonomously and and and use be used in some either either
46:16
dedicated autonomous or partially autonomous like like
46:18
Airbnb. Like some maybe sometimes you
46:21
allow your your card to be used by others sometimes you want to
46:24
use it exclusively. Just like you know Airbnb, you
46:27
know doing Airbnb with a room in your house.
46:33
You know that the the, the value is just tremendous.
46:35
So I think it's sort of it would be I I think it makes it does
46:40
make sense to sacrifice margins in favor of making more vehicles
46:43
because we think in the not too distant future they will have
46:48
have a dramatic valuation increase.
46:50
I think the Tesla fleet value increase at the point which we
46:54
can upload full self, you know full self driving and it's
46:56
approved by regulators. Will be the single biggest step
47:02
Change in asset value, maybe in history?
47:08
Thank you. Let's go to the next analyst.
47:10
The question comes from Emmanuel Rosner from Deutsche Bank.
47:15
Thank you very much. Two questions for me as well.
47:18
First following up on on the autonomy, so you know before you
47:23
start launching these dedicated Robo Taxi vehicles on, on
47:26
existing vehicles you're. Improving FSD, you know,
47:29
incrementally what is your latest targeted timing to
47:34
essentially release a non beta version or an ISOF version that
47:38
would trigger much higher take rates And would Tesla benefit
47:42
from lowering the price of FSD? Well obviously I you know.
47:56
As people have sort of made fun of me and perhaps the, you know,
48:00
quite fairly have made fun of me, my predictions about
48:03
achieving full self driving have been optimistic in the past.
48:11
The reason they've been optimistic is what it tends to
48:14
look like is the we'll make rapid progress with the new
48:18
version of. Of FSD but but then it will
48:23
curve over logarithmically so. So at first logarithmic curve
48:28
looks like you know just sort of fairly straight upward line
48:32
diagonal and up. And so if you extrapolate that
48:36
it then you you have a great thing but then because it's
48:39
actually logarithmic, it curves over and then there's been a
48:41
series of stacked logarithmic curves now.
48:48
I know, I don't know the the, the, the boy who cried FSD, but
48:53
I I man, I I think I think we'll be better than human by the end
48:58
of this year. That's not to say we're approved
49:04
by regulators and and I'm saying that that would be in the US
49:10
because we got to focus on one market 1st.
49:12
But I I think we'll be better than human by the end of this
49:14
year. I've been wrong in the past.
49:16
I may be wrong this time and that the the price of FSD.
49:22
So the the way thing is the price of FSD is actually very
49:24
low. It's not high When you go back
49:29
to what I say earlier the the the value of the car increases
49:32
dramatically if it is actually autonomous.
49:37
You know $15,000 is is actually a low price not a high price
49:43
and. Now we will offer you know and
49:48
we have, I think I think we do sort of offer FSD as a sort of
49:51
monthly subscription although like most people don't know
49:54
that. So I'd recommend like maybe
49:56
trying it out as a monthly subscription so you don't have
49:58
to go with the $15,000 thing. But I think yeah, yeah the the
50:07
obviously if if the car is worth several times it's original
50:10
price. $13,000 is actually a low price for FSD.
50:18
Thank you. And the next question comes from
50:20
William Stein from Trust. William, go ahead and unmute.
50:26
Great. Thank you very much for taking
50:28
my question. I'd like to ask about to stick
50:35
on this AI topic. We've read, you know, with great
50:39
interest the developments in Dojo today and you've spoken
50:43
about FSD, but you've also Elon, you've started this X dot AI
50:49
company and you know for investors that think that there
50:53
might be quite a bit of value in the AI features and products of
50:58
Tesla, it might be concerning to see you.
51:02
You know, pursuing another endeavor where AI is the focus.
51:04
So can you talk about how X dot AI might overlap, might perhaps
51:12
compete with Tesla or in other ways Perhaps it it enhances the
51:16
value of what Tesla does? Thanks very much.
51:21
Yeah, I think we'll actually enhance the the value of Tesla
51:26
there. There were just some.
51:30
Some of the world's best AI engineers and scientists that
51:33
were willing to join a startup, but they were not willing to
51:36
join a large sort of relatively established company like like
51:40
Tesla. So I was like that that's
51:42
actually how it got started. I was interviewing a few people
51:44
and they're like, no, we we want to do a startup.
51:46
I was like, and that's all I I couldn't, I couldn't convince
51:49
them to join Tesla. So, So I was like, OK, well, you
51:55
know, better to start up that. That I run that's then.
51:59
Then they go work somewhere else.
52:01
That's kind of the the genesis of of Xai and Xai is is focused
52:07
on a sort of AGI. Yeah so it's but I I'd like so I
52:15
think there will be some value that Xai brings to Tesla you
52:25
know also some of the best. For the very best people in the
52:27
world they they really just want to work on interesting problems.
52:29
If you take say you know our material science group you know
52:33
really what convinced the Charlie Coleman to leave Apple
52:37
we was very happy and well compensated and both at and both
52:43
you know the the the where we think is the best material
52:49
science group in the world was that he got to work at both
52:52
Tesla and SpaceX He he wasn't willing to.
52:55
Leave Apple, If it was just Tesla, but he was willing to do
52:58
it, it was Tesla and SpaceX. So sometimes you get the best
53:01
talent in the world. That's the kind of thing you
53:03
know you need to do. And that actually has been very
53:06
beneficial to Tesla so. If you know if I can squeeze one
53:11
more mundane question in, I I wonder if you think you can hit
53:17
the 1.8 million unit number with current pricing or do you
53:20
anticipate? Needing to continue to lower
53:24
prices because it seems like they've stabilized, the trends
53:27
have stabilized in the last maybe a month and a half.
53:29
Should we expect a sort of continued decreases or or more
53:34
stabilization for the rest of the year?
53:41
Sure. You know we have, we have a
53:43
really sort of we started the referral program which I think
53:47
will be quite effective. So you know, as as Zach was
53:51
saying earlier, we we don't control the macroeconomic
53:55
conditions. So if interest rates continue to
53:57
rise that reduces the affordability of cars, you know
54:02
and and for a lot of people they're really trying to balance
54:05
that just you know, barely breaking even every month.
54:08
In fact, if you look at the rise in credit card debt, they are in
54:10
fact not breaking even every month like credit card debt is,
54:14
is looking scary so. You know, we just don't control
54:22
the micro conditions. If American conditions are
54:24
stable, I think prices will be stable.
54:26
And if they're not stable, then we would have to lower prices,
54:31
yeah. Thank you.
54:34
Let's go to Colin Rush from Oppenheimer.
54:38
That's so much. Guys, you know is your.
54:41
Building out Dojo, implementing what really is gonna be a highly
54:45
complex set of software. Can you speak to the maturity of
54:48
the operating system and how much software you're expecting
54:52
to use in that system? This is a custom software stack
54:58
so but it is designed such that you can run at the high at a
55:06
high level pie torch. And jacks, so but then you know
55:14
we have to customize it to actually run on a custom
55:17
silicon. So this the software stack is a
55:22
combination of open source software and then and that tells
55:24
the software all the way to the bear silicon, which is the case
55:28
for the inference computer in the car so.
55:34
Okay, thanks so much. That's super powerful.
55:35
And then can you speak to how you're managing some of the
55:37
geopolitical risks relative to your capacity expansion?
55:41
You know, obviously as you guys continue to grow at this rate,
55:43
you're gonna be putting some folks out of business and you
55:46
know there's going to be some impacts around regional
55:49
economies. So just want to understand how
55:50
you're thinking about that in terms of some of your CapEx
55:53
plans and and how you're managing some of those
55:54
relationships with with different countries and regions?
56:03
You know, this is a period of unusual geopolitical risk.
56:09
So I think we're the best we can do is you know have factories
56:14
and many parts of the world such that if things get difficult in
56:19
one part of the world we you know, we can still keep keep
56:22
things going in the rest of the world.
56:27
Thank you. The next question comes from
56:30
Mark Delaney from Goldman Sachs. Thank you very much for taking
56:38
that question. Tesla has been making progress
56:40
reducing cost and did so again last quarter.
56:43
Can you give an update on when you think automotive COGS per
56:45
vehicle could be under the historical $36,000 per vehicle
56:48
level? And what are?
56:49
The key puts and takes to get there.
56:54
This is, I think it was asked this in the past.
56:56
This is very difficult to forecast.
56:58
You know there's a series of costs that we manage.
57:01
This here is a cost in which we don't control and so you know
57:05
particularly on the commodity side where labor, Costco
57:09
etcetera, it's just hard to say. Yeah, we saw very inflationary
57:15
like strong inflationary pressures for a while last year
57:19
and and now we're which obviously makes it very
57:23
difficult to reduce COGS you know now we're seeing.
57:28
What seemed to be deflationary pressures, certainly
57:30
deflationary deflation is a pressure, but we're seeing you
57:37
know commodity prices dropped, dropping as as was mentioned you
57:40
know as car mentioned a moment ago and.
57:46
I think, I mean what do you think it basically the trends
57:49
should be deflationary at the commodity level?
57:51
Definitely there's that. And then there's also the the
57:54
unit economics improve as volumes grow.
57:57
That's the other thing we're seeing as we're becoming a
57:59
bigger and bigger part of a lot of suppliers, economies of scale
58:02
come into play. There's equipment appreciation
58:04
that comes into play, equipment that was commissioned five to
58:07
seven years ago that used to be a part of the peace price that's
58:10
completely amortized. So we'll see situations where
58:13
peace price comes down. Because that equipment
58:16
contribution has gone away and then just we continued to have
58:19
this mentality of continuous improvement in terms of Labor
58:23
reducing labor, improving automation and and just continue
58:27
to get better at what we do. So we have seen I think every
58:29
quarter. We have seen an improvement, of
58:31
course, the commodity spiked up and down.
58:33
Yeah, just in. General the trend is towards
58:37
being more efficient. Yeah, and and totally agree.
58:40
Yeah, but lithium prices weren't absolutely insane there for a
58:43
while. Yeah, yeah.
58:44
And they're recovering now. About like 1/3 of what it used
58:46
to be. Yeah.
58:48
Yeah. And you know, we're still early
58:49
in the ramps. Well, not early in the ramp, but
58:52
early in the cost down curve of Austin and Berlin.
58:55
Yeah. So it takes time to work the
58:57
cost out at first it's a focused on ramp, ramp it brings cost.
59:01
Down quality and then yeah. And quality cost.
59:04
Yeah. And then once that stabilizes,
59:05
we can divert bandwidth to cost reduction.
59:08
And so Austin Berlin saw quite a decent amount of cost reduction
59:12
on a fundamental basis from Q1 to Q2.
59:15
We'll continue to do that work. That will be helpful.
59:18
And so we're just gonna keep shipping away at it, yeah.
59:22
Package is a big, big element to logistics too.
59:26
Logistics is normalizing, which is great.
59:28
QQ Bot utilization. Something that your team has
59:33
been very focused on, so every bit of it.
59:38
Yeah. It's hard.
59:39
Logistics is under appreciated. Yeah, the whole thing is like
59:45
that was one with tactics, wasn't one with logistics.
59:48
Yeah. And we've made tremendous
59:49
improvements in cost and on fronts on you know express
59:54
costs. We have down down Pre, Pandemic
59:58
Express cost levels now. And our goal is to go further
1:00:02
down. So, yeah, so when we look at our
1:00:06
progress from Q1 to Q2 on cost, the way that we look at
1:00:10
internally and normalize for the impacts of mix shift with Austin
1:00:14
and Berlin being a higher percentage of our mix, normalize
1:00:17
for S&X being a higher percentage of our mix in Q2
1:00:20
versus Q1, the sequential cost reduction, it might be the
1:00:24
largest we've had in a while. So anything is it's great work
1:00:28
on behalf of the Tesla team. And we just gotta keep it up.
1:00:32
To get game of pennies, it's like Game of Thrones with
1:00:35
pennies. Mark, do you have a follow up
1:00:39
question? I think you're muted.
1:00:42
Yep. Yeah.
1:00:43
Thank you very much for all the the details on that.
1:00:46
Maybe you could put a finer point on the downtime impact
1:00:49
that you you spoke about in your prepared comments in terms of
1:00:53
production impact and then also to what extent there's a margin
1:00:56
impact from those if? You have a phrase that you're
1:00:59
planning this quarter. Thank you.
1:01:06
Yeah, the the downtime. You know, we don't know exactly
1:01:11
the number of cars impacted because you know kind of the way
1:01:14
that we go into downtime windows for upgrades is, you know we set
1:01:18
aside a period of time, but then the team is challenged to go as
1:01:21
quickly as possible so that we can get the factories up and
1:01:24
running again and minimize that. So it's not, it's not profound
1:01:29
reduction, you know, hopefully it's quite small I think.
1:01:31
We're getting too much into Louise here.
1:01:33
I mean, like we're asking for a level of precision that is not
1:01:36
possible to answer. So let's move on.
1:01:40
Yeah. I think this is unfortunately
1:01:42
all the time we have for today. OK.
1:01:44
So we'll speak to you all in the next three months.
1:01:47
Thank. You very much thank you.