Tesla, Inc.

Ladies and gentlemen, thank you for standing by, and welcome to the Tesla Q3 2020 Financial Results and Q&A webcast. At this time, all participants are in a listen-only mode. After the speaker presentation, there will be a question and answer session. To ask a question during the session, you will need to press star 1 on your telephone. If you require any further assistance, please press star 0. I would now like to hand the conference over to your speaker, Mr. Martin Vieca, Senior Director and Vet of investor relations. Please go ahead, sir.

Thank you, Sherry, and good afternoon, everyone. And welcome to Tesla's third quarter 2020 Q&A webcast. I'm joined today by Elon Musk, Zachary Kirkhorn, and a number of other executives. Our Q3 results were announced at about 1 p.m. Pacific 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 or 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 press star 1 now if you would like to join the question queue. But before we jump into the Q&A, Elon has some opening remarks. Elon?

Thanks, Martin. All right, so Q3 was our best quarter in history. We achieved record production and deliveries, record revenue, record net income, both gap and ungap, and record free cash flow of $1.4 billion. This is really due to the amazing execution by the Tesla team. I could not be more proud to work with such a great group of people. Just really kick-ass performance throughout the world. Of course, we had Battery Day, so we hosted, showed our plans for how we can expand the future and improve core battery technology, core cell technology at the form factor level, chemistry level, and I think most significantly at the manufacturing technology level. A comment I've made in the past is that I think Tesla's long-term competitive strength will be primarily manufacturing. This is counterintuitive, but I'm quite confident this will be what happens. Anyway, so we presented what the team's been working on for a long time, batteries. We wanted to step back and really rethink batteries from scratch. First principle thinking, just look at the fundamental physics and say what, rather than compare to other parts of the market, just say from a physics standpoint, what's the limit of physics? What's the tonic ideal of a perfect cell? And how close can we get there? And that was our aspiration. And I think we've got a pretty good approach to it, which will only get better over time. And we went through all of the engineering solutions for every important part of battery design and production, and we'll continue to iterate on that and just recursively improve the core cell and battery technology. The result, we think, in a few years will be batteries that cost half as much and where the capital expenditures required are a third or less of what they are today. And we expect Giga Berlin will see our first battery cell production line at scale. Regarding the full self-driving beta release, the Autopilot team, again, just a really all-star team. I spent a lot of time with the Autopilot team, and there's a lot of really talented people in that team who've worked incredibly hard to get the beta release out. So I'd just really like to thank them for their hard work. It's just a very smart group of people. So I think we're starting very slow and very cautiously because the world is a complex, messy place. And so we put it out there last night, and then we'll see how it goes, and then probably release it to more people this weekend or early next week, and then just gradually step it up until – We have, hopefully, a wide release by the end of this year. And of course, as the system collects more data, it becomes more robust. So it's sort of like, how does Google as a search engine get better? It's because everyone is programming it by asking it questions all the time and clicking on particular links. So it's got this great feedback loop, and that makes it an extremely effective search engine. It's the same thing for autonomy. Having on the order of a million cars that are providing feedback and specifically feedback on strange corner case situations that you just can't even come up with in simulation, this is the thing that is really valuable. It's not like the obvious stuff. Obvious stuff you can do in simulation. Weird corner cases, only reality can give you that. But we're able to say, okay, we need to train the system on this corner case situation and look for examples so we can then train against those examples and improve some very esoteric corner case. And also important to emphasize that this is a generalized neural net based approach. There is no need for high definition maps or a cell phone connection. The car, the system is designed such that even if you have no connectivity whatsoever and you're in a place that you have never been to before and no Tesla has ever been there, the car should still be able to drive, just like a person. That is the system that we are developing and aiming to release this year. In terms of capacity build-out, we're making progress on three major factories. We're continuing to expand Shanghai significantly, which is going incredibly well. The Tesla China team is just incredibly good. We're super smart, work hard. I'm always amazed by how much progress the Tesla China team makes. It's beyond all reasonable expectations. And then we're under construction in Berlin and Austin. So also making good progress there. Yeah, it's overall going well. I should make a point that for Berlin and Austin, we do expect to start delivering cars from those factories next year, but because of the exponential nature of the spool-up of a manufacturing plant, especially one with new technology, it will start off very slow at first, and then the output will become very large. Just in general, manufacturing follows the S-curve, and I think sometimes people, if they haven't spent a lot of time manufacturing, kind of think that once you have a factory, you can just sort of turn it on and it's at capacity. But it will typically take about 12 to 18 months to reach capacity, and that is a very fast period of time, especially for new technology. So, yeah, I'd say 12 to 24 months even. So, generally what I see is the manufacturing capacity is underestimated in the beginning for quite some time. Then it's sometimes overestimated because this is an S-code. It goes exponential to linear to logarithmic. It's actually an incredibly hard thing, just bringing a production plant to volume technology. Because you can actually think of it like you've got, to a first-order approximation, 10,000 unique parts or processes, all of which operate on an S-curve, and with a bunch of uncertainty. And you can just slide 10,000 S-curves on an X-axis, and that's what bringing up a large automotive plant is like. And which one is the... the laggard, which one's the leader, it's very difficult to tell, and it's constantly changing. So it's really one of the most difficult challenges I've ever seen. So let's see. In conclusion, thank you. All we've achieved would not be possible without the incredible hard work of tens of thousands of Tesla employees and all the people at our suppliers as well. I'd like to thank our suppliers. We continue to grow as fast as we can while focusing on cost control and improving quality. And ultimately, the best company will be that which makes great products at an affordable price. And that is our goal. I think I've never felt more optimistic about the future of Tesla than I do today. Also, I thank investors who have stuck with us through thick and thin. This is... I think there's a lot more good stuff to come. All right, with that, we can move to questions.