Tesla, Inc. (NASDAQ:TSLA) Q1 2024 Earnings Call Transcript

Tesla, Inc. (NASDAQ:TSLA) Q1 2024 Earnings Call Transcript April 23, 2024

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Martin Viecha: Tesla’s First Quarter 2024 Q&A Webcast. My name is Martin Viecha, VP of Investor Relations, and I’m joined today by Elon Musk, Vaibhav Taneja, and a number of other executives. Our Q1 results were announced at about 3.00 p.m. Central Time in the Update Deck we published at the same link as this webcast. During this call, we will discuss our business outlook and make forward-looking statements. These comments are based on our predictions and expectations as of today. Actual events and results could differ materially due to a number of risks and uncertainties, including those mentioned in our most recent filings with the SEC. During the question-and-answer portion of today’s call, please limit yourself to one question and one follow-up. Please use the raise hand button to join the question queue. But before we jump into Q&A, Elon has some opening remarks. Elon?

Elon Musk: Thanks, Martin. So to recap in Q1 we navigated several unforeseen challenges as well as the ramp of the updated Model 3 in Fremont. There was, as we all have seen, the EV adoption rate globally is under pressure and a lot of other auto manufacturers are pulling back on EVs and pursuing plug-in hybrids instead. We believe this is not the right strategy and electric vehicles will ultimately dominate the market. Despite these challenges, the Tesla team did a great job executing in a tough environment and energy storage deployments, the Megapack in particular, reached an all time high in Q1, leading to record profitability for the energy business, and that looks likely to continue to increase in the quarters and years ahead.

It will increase. We actually know that it will, so significantly faster than the car business as we expected. We also continue to expand our AI training capacity in Q1, more than doubling our training compute sequentially. In terms of the new product roadmap, there has been a lot of talk about our upcoming vehicle line in the next – in the past several weeks. We’ve updated our future vehicle lineup to accelerate the launch of new models ahead, previously mentioned startup production in the second half of 2025, so we expect it to be more like the early 2025, if not late this year. These new vehicles, including more affordable models, will use aspects of the next generation platform as well as aspects of our current platforms, and will be able to produce on the same manufacturing lines as our current vehicle lineup.

So it’s not contingent on any new factory or massive new production line. It’ll be made on our current production lines much more efficiently. And we think this should allow us to get to over 3 million vehicles of capacity when realized to the full extent. Regarding FSD Version 12, which is the pure AI-based self-driving, if you haven’t experienced this, I strongly urge you to try it out. It’s profound and the rate of improvement is rapid so – and we’ve now turned that on for all cars with the cameras and inference computer and everything from Hardware 3 on in North America. And so it’s been pushed out to, I think, around 1.8 million vehicles and we’re seeing about half of people use it so far and that percentage is increasing with each passing week.

So we now have over 300 billion miles that have been driven with FSD V12. Since the launch of full self-driving, supervised full self-driving, it’s become very clear that the vision-based approach with end to end neural networks is the right solution for scalable autonomy. It’s really how humans drive. Our entire road network is designed for biological neural nets and eyes. So naturally cameras and digital neural nets are the solution to our current road system. To make it more accessible, we’ve reduced the subscription price to $99 a month, so it’s easy to try out. And as we’ve announced, we’ll be showcasing our purpose-built robotaxi, or Cybercab, in August. Yes. Regarding AI compute, over the past few months, we’ve been actively working on expanding Tesla’s core AI infrastructure.

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Q&A Session

For a while there, we were training constrained in our progress. We are, at this point, no longer training constrained and so we’re making rapid progress. We’ve installed and commissioned, meaning they’re actually working 35,000 H100 computers or GPUs, GPU is wrong word, they need a new word. I always feel like a wince when I say GPU because it’s not – GPU stands – G stands for graphics, and it doesn’t do graphics. But anyway roughly 35,000 H100s are active, and we expect that to be probably 85,000 or thereabouts by the end of this year and training, just for training. We are making sure that we’re being as efficient as possible in our training. It’s not just about the number of H100s, but how efficiently they’re used. So in conclusion, we’re super excited about our autonomy road map.

I think it should be obvious to anyone who’s driving Version 12 and it tells that that it is only a matter of time before we exceed the reliability of humans and not much time with that. And we’re really headed for an electric vehicle, an autonomous future. And I’ll go back to something I said several years ago that in the future, gasoline cars that are not autonomous will be like riding a horse and using a flip phone. And that will become very obvious in hindsight. We continue to make the necessary investments that will drive growth and profits for Tesla in the future, and I wanted to thank the Tesla team for incredible execution during this period and look forward to everything that we have planned ahead. Thanks.

Martin Viecha: Thank you very much, and Vaibhav has some comments as well.

Vaibhav Taneja: Thanks. It’s important to acknowledge what Elon said, from our auto business perspective. We did see a seasonal decline in revenues quarter-over-quarter and those were primarily because of seasonality, uncertain macroeconomic environment and the other reasons, which Elon had mentioned earlier. Auto margins declined from 18.9% to 18.5%. Excluding the impact of Cybertruck, the impact of pricing actions was largely offset by reductions in per unit costs and the recognition of revenue from Autopark feature for certain vehicles in the U.S. that previously did not have that functionality. Additionally, while we did experience higher cost due to the ramp of Model 3 in Fremont and disruptions in Berlin, these costs were largely offset by cost reduction initiatives.

In fact, if we exclude Cybertruck and Fremont Model 3 ramp costs, the revenue from Autopark, auto margins improved slightly. Currently normalized Model Y cost per vehicle in Austin and Berlin are already very close to that of Fremont. Our ability to reduce costs without sacrificing on quality was due to the amazing efforts of the team, in executing Tesla’s relentless pursuit of efficiency across the business. We’ve also witnessed that as other OEMs are pulling back on their investments in EV, there is increasing appetite for credits, and that means a steady stream of revenue for us. Obviously, seeing others pull back from EV is not the future we want. We would prefer it the whole industry went all in. On the demand front, we’ve undertaken a variety of initiatives, including lowering the price of both the purchase and subscription options for FSD launching extremely attractive leasing specials for the Model 3 in the U.S. for $299 a month and offering attractive financing options in certain markets.

We believe that our awareness activities, paired with attractive financing, will go a long way in expanding our reach and driving demand for our products. Our Energy business continues to make meaningful progress with margins reaching a record of 24.6%. We expect the energy storage deployments for 2024 to grow at least 75% higher from 2023. And accordingly, this business will begin contributing significantly to our overall profitability. Note that there is a bit of lumpiness in our storage deployments due to a variety of factors that are outside of our control, so deployments may fluctuate quarter-over-quarter. On the operating expense front, we saw a sequential increase from our AI initiatives, continued investment in future projects, marketing and other activities.

We had negative free cash flow of $2.5 billion in the first quarter. The primary driver of this was an increase in inventory from a mismatch between builds and deliveries as discussed before, and our elevated spend on CapEx across various initiatives, including AI compute. We expect the inventory build to reverse in the second quarter and free cash flow to return to positive again. As we prepare the company for the next phase of growth, we had to make the hard but necessary decision to reduce our head count by over 10%. The savings generated are expected to be well in excess of $1 billion on an annual run rate basis. We are also getting hyper focused on CapEx efficiency and utilizing our installed capacity in a more efficient manner. The savings from these initiatives, including our cost reductions will help improve our overall profitability and ultimately enable us to increase the scale of our investments in AI.

In conclusion, the future is extremely bright and the journey to get there while challenging will be extremely rewarding. Once again, I would like to thank the whole Tesla team for delivering great results. And we can open it up to Q&A.

A – Martin Viecha: Okay. Let’s start with investor Q&A. The first question is, what is the status of 4680. What is the current output? Lars?

Lars Moravy : Sure. 4680 production increased about 18% to 20% from Q4 reaching greater than 1K a week for Cybertruck, which is about 7 gigawatt hours per year as we posted on X. We expect to stay ahead of the Cybertruck ramp with the cell production throughout Q2 as we ramp the third of four lines in Phase 1, while maintaining multiple weeks of cell inventory to make sure we’re ahead of the ramp. Because we’re ramping, COGS continues to drop rapidly week-over-week driven by yield improvements throughout the lines and production volume increases. So our goal, and we expect to do this is to beat supplier cost of nickel-based cells by the end of the year.

Martin Viecha: Thank you. The second question is on Optimus. So what is the current status of Optimus? Are they currently performing any factory tasks? When do you expect to start mass production?

Elon Musk: We are able to do simple factory tasks or at least, I should say, factory tasks in the lab. In terms of – we do think we will have Optimus in limited production in the natural factory itself, doing useful tasks before the end of this year. And then I think we may be able to sell it externally by the end of next year. These are just guesses. As I’ve said before, I think Optimus will be more valuable than everything else combined. Because if you’ve got a sentient humanoid robots that is able to navigate reality and do tasks at request, there is no meaningful limit to the size of the economy. So that’s what is going to happen. And I think Tesla is best positioned of any humanoid robot maker to be able to reach volume production with efficient inference on the robot itself.

I mean this perhaps is a point that is worth emphasizing Tesla’s AI inference efficiency is vastly better than any other company. There is no company even close to the inference efficiency of Tesla. We’ve had to do that because we were constrained by the inference hardware in the car, we didn’t have a choice. But that will pay dividends in many ways.

Martin Viecha: Thank you. The third question is, what is the current assessment of the pathway towards regulatory approval for unsupervised FSD in the U.S. And how should we think about the appropriate safety threshold compared to human drivers?

Elon Musk: Sure.

Lars Moravy: I can start. There are a handful of states that already have adopted autonomous vehicle laws. These states are paving the way for operations, while the data for such operations guides a broader adoption of driver-less vehicles. I think Ashok can talk a little bit about our safety methodology, but we expect that these states and the work ongoing as well as the data that we’re providing will pave a way for a broad-based regulatory approval in the U.S. at least and then in other countries as well?

Ashok Elluswamy: Yes. It’s actually been pretty helpful that other autonomous car companies have been cutting a path through the regulatory jungle, which is absurd. That’s actually quite helpful. And they have obviously been operating in San Francisco for a while. I think they got approval for City of LA. So these approvals are happening rapidly. I think if you’ve got at scale, a statistically significant amount of data that shows conclusively that the autonomous car has, let’s say, half the accident rate of a human-driven car, I think, that’s difficult to ignore because at that point, stopping autonomy means killing people. So I actually do not think that there will be significant regulatory barriers provided there was conclusive data that the autonomous car is safer than a human-driven car.

And in my view, this will be much like elevators. Elevators used to be operated by a guy with relay switch. But sometimes that guy would get tired or drunk or just make a mistake, and shatter somebody in half between floors. So we just get an elevator and press button, we don’t think about it. In fact, it’s kind of weird if somebody is standing there with a relay switch. And that will be how cars work. You just summon the car using your phone, you get in, it takes you to a destination, you get out.

Vaibhav Taneja: You don’t even think about it?

Elon Musk: You don’t even think about it. Just like an elevator, it takes you to your floor. That’s it. Don’t think about how the elevator is working or anything like that. And something I should clarify is that Tesla will be operating the fleet. So you can think of like how Tesla, think of it’s like some combination of Airbnb and Uber, meaning that there will be some number of cars that Tesla owns itself and operates in the fleet. There will be some number of cars and then there’ll be a bunch of cars where they’re owned by the end user. That end user can add or subtract their car to the fleet whenever they want, and they can decide if they want to only let the car be used by friends and family or only by 5-star users or by anyone at any time they could have the car come back to them and be exclusively theirs, like an Airbnb.

You could rent out your guest room or not, any time you want. So as our fleet grows, we have 7 million cars going to – 9 million cars going to, eventually tens of millions of cars worldwide. With a constant feedback loop, every time something goes wrong, that gets added to the training data and you get this training flywheel happening in the same way that Google Search has the sort of flywheel, it’s very difficult to compete with Google because people are constantly doing searches and clicking and Google is getting that feedback loop. It’s the same with Tesla. But at a scale that is maybe difficult to comprehend, but ultimately, it will be tens of millions. I think there’s also some potential here for an AWS element down the road where if we’ve got very powerful inference because we’ve got a Hardware 3 in the cars, but now all cars are being made with Hardware 4.

Hardware 5 is pretty much designed and should be in cars, hopefully towards the end of next year. And there’s a potential to run – when the car is not moving to actually run distributed inference. So kind of like AWS, but distributed inference. Like it takes a lot of computers to train an AI model, but many orders of magnitude less compute to run it. So if you can imagine future, perhaps where there’s a fleet of 100 million Teslas, and on average, they’ve got like maybe a kilowatt of inference compute. That’s 100 gigawatts of inference compute distributed all around the world. It’s pretty hard to put together 100 gigawatts of AI compute. And even in an autonomous future where the car is, perhaps, used instead of being used 10 hours a week, it is used 50 hours a week.

That still leaves over 100 hours a week where the car inference computer could be doing something else. And it seems like it will be a waste not to use it.

Martin Viecha: Ashok, do you want to chime in on the air process and safety?

Ashok Elluswamy: Yes, we have multiple tiers of validating the safety in any given week, we train hundreds of neural networks that can produce different trajectories for how to drive the car, we replay them through the millions of clips that we have already collected from our users and our own QA. Those are like critical events, like someone jumping out in front or like other critical events that we have gathered database over many, many years, and we replay through all of them to make sure that we are net improving safety. And on top of it, we have simulation systems that also try to recreate this and test this in closed loop fashion. And some of this is validated, we give it to our own QA drivers. We have hundreds of them in different cities, in San Francisco, Los Angeles, Austin, New York, a lot of different locations.

They are also driving this and collecting real-world miles, and we have an estimate of what are the critical events, are they a net improvement compared to the previous week’s builds. And once we have confidence that the build is a net improvement, then we start shipping to early users, like 2,000 employees initially that they would like it to build, they will give feedback on like if it’s an improvement there or they’re noting some new issues that we did not capture in our own QA process. And only after all of this is validated, then we go to external customers. And even when we go external, we have like live dashboards of monitoring every critical event that’s happening in the fleet sorted by the criticality of it. So we are having a constant pulse on the build quality and the safety improvement along the way.

And then any failures like Elon alluded to, we get the data back, add it to the training and that improves the model in the next cycle. So we have this like constant feedback loop of issues, fixes, evaluations and then rinse and repeat. And especially with the new V12 architecture, all of this is automatically improving without requiring much engineering interventions in the sense that engineers don’t have to be creative in like how they code the algorithms. It’s mostly learning on its own based on data. So you see that, okay, every failure or like this is how a person shows, this is how you drive this intersection or something like that, they get the data back. We add it to the neural network, and it learns from that trained data automatically instead of some engineers saying that, oh, here, you must rotate the steering wheel by this much or something like that.

There’s no hard inference conditions, it’s everything is neural network, it’s very soft, it’s probabilistic. So it will adapt its probability distribution based on the new data that it’s getting.

Elon Musk: Yes. We do have some insight into how good the things will be in like, let’s say, three or four months because we have advanced models that are far more capable than what is in the car, but have some issues with them that we need to fix. So they are like there’ll be a step change improvement in the capabilities of the car, but it will have some quirks that are – that need to be addressed in order to release it. As Ashok was saying, we have to be very careful in what we release the fleet or to customers in general. So like – if we look at say 12.4 and 12.5, which are really could arguably even be Version 13, Version 14 because it’s pretty close to a total retrain of the neural nets in each case are substantially different. So we have good insight into where the model is, how well the car will perform, in, say, three or four months.

Ashok Elluswamy: Yes. In terms of scaling laws, people in the AI community generally talk about model scaling laws where they increase the model size a lot and then their corresponding gains in performance, but we have also figured out scaling laws and other access in addition to the model side scaling, making also data scaling. You can increase the amount of data you use to train the neural network and that also gives similar gains and you can also scale up by training compute, you can train it for much longer or make more GPUs or more Dojo nodes and that also gives better performance, and you can also have architecture scaling where you count with better architectures that for the same amount of compute for produce better results.

So a combination of model size scaling, data scaling, training compute scaling and the architecture scaling, we can basically extract like, okay, with the continue scaling based on this – at this ratio, we can sort of predict future performance. Obviously, it takes time to do the experiments because it takes a few weeks to train, it takes a few weeks to collect tens of millions of video clips and process all of them, but you can estimate what’s going to be the future progress based on the trends that we have seen in the past, and they’re generally held true based on past data.

Martin Viecha: Okay. Thank you very much. I’ll go to the next question, which is, can we get an official announcement of the time line for the $25,000 vehicle?

Lars Moravy: I think we – Elon mentioned it in the opening remarks. But as you mentioned, we’re updating our future vehicle lineup to accelerate the launch of our low-cost vehicles in a more CapEx efficient way. That’s our mission to get the most affordable cars to customers as fast as possible. These new vehicles we built on our existing lines and open capacity, and that’s a major shift to utilize all our capacity with marginal CapEx before we go spend high CapEx to do anything.

Elon Musk: Yes. We’ll talk about this more on August 8. But really, the way to think of Tesla is almost entirely in terms of solving autonomy and being able to turn on that autonomy for a gigantic fleet. And I think it might be the biggest asset value appreciation history when that day happens when you can do unsupervised full self-driving.

Lars Moravy: 5 million cars?

Elon Musk: Yes.

Lars Moravy: A little less?

Elon Musk: Yes. It will be 7 million cars in a year or so and then 10 million and then eventually, we’re talking about tens of millions of cars. Not eventually, it’s like, yes, for the end of the decade, its several tens of millions of cars I think.

Martin Viecha: Thank you. The next question is, what is the progress of Cybertruck ramp?

Lars Moravy: I can take that one too. Cybertruck had 1K a week just a couple of weeks ago. This happened in the first four to five months since we SOP [ph] late last year. Of course, volume production is what matters. That’s what drives costs and so our costs are dropping, but the ramp still faces like a lot of challenges with so many new technologies, some supplier limitations, et cetera, and continue to ramp this year, just focusing on cost efficiency and quality.

Martin Viecha: Okay. Thank you. The next question, have any of the legacy automakers contacted Tesla about possibly licensing FSD in the future?

Elon Musk: We’re in conversations with one major automaker regarding licensing FSD.

Martin Viecha: Thank you. The next question is about the robotaxi unveil. Elon already talked about that. So we’ll have to wait till August. The following question is about the next-generation vehicle. We already talked about that. So let’s go to the semi. What is the time line for scaling semi?

Elon Musk: I think…

Lars Moravy: So we’re finalizing the engineering of the semi to enable like a super cost-effective high-volume production with our learnings from our fleet and our pilot fleet and Pepsi’s fleet, which we are expanding this year marginally. In parallel, as we showed in the shareholders’ deck, we have started construction on the factory in Reno. Our first vehicles are planned for late 2025 with external customers starting in 2026.

Martin Viecha: Okay. A couple more questions. So our favorite, can we make FSD transfer permanent until FSD is fully delivered with Level 5 autonomy?

Lars Moravy: Yes.

Martin Viecha: Okay. Next question, what is the getting the production ramp at Lathrop, where do you see the Megapack run rate at the end of the year. Mike?

Unidentified Company Representative: Yes. Yes, Lathrop is ramping as planned. We have our second GA line allowing us to increase our exit rate from 20 gigawatt hours per year to – at the start of this year to 40 gigawatt hours per year by the end of the year, that lines commissioned. There’s really nothing limiting the ramp. Its given the longer sales cycles for these large projects, we typically have order visibility 12 months to 24 months prior to ship dates. So we’re able to plan – the build plan several quarters in advance. So this allows us to ramp the factory to align with the business and order growth. Lastly, we’d like to thank our customers globally for their trust in Tesla as a partner for these incredible projects.

Martin Viecha: Okay. Thank you very much. Let’s go to analyst questions. The first question comes from Tony Sacconaghi from Bernstein. Tony, please go ahead and unmute.

Tony Sacconaghi: Thank you for taking the question. I was just wondering if you can elaborate a little bit more on kind of the new vehicles that you talked about today. Are these like tweaks on existing models, given that they’re going to be running on the same lines? Are these like new models? And how should we think about them in the context of like the Model 3 Highland update, what will these models be like relative to that? And given the quick time frame, Model 3 Highland has required a lot of work and a lot of retooling. Maybe you can help put that all in context. Thank you, and I have a follow-up, please.

Elon Musk: I think we’ve said, we were on that front. So what’s your follow-up?

Tony Sacconaghi: It’s a more personal one for you, Elon, which is that you’re leading many important companies right now. Maybe you can just talk about where your heart is at in terms of your interests and do you expect to lessen your involvement with Tesla at any point over the next three years?

Elon Musk: Tesla constitutes a majority of my work time and I work pretty much every day of the week. It’s rare for me to take a Sunday afternoon. So I’m going to make sure Tesla is quite prosperous. And it is – like it is prosperous and it will be very much so in the future.

Martin Viecha: Okay. Thank you. Let’s go to Adam Jonas from Morgan Stanley. Adam, please go ahead and unmute.

Adam Jonas: Okay. Great. Hey, Elon. So you and your team on volume expect a 2024 growth rate, notably lower than that achieved in 2023. But what’s your team’s degree of confidence on growth above 0%? Or in other words, does that statement leave room for potentially lower sales year-on-year?

Elon Musk: No, I think we’ll have higher sales this year than last year.