Tesla’s AI Day is here. In a few minutes, Tesla watchers would be seeing executives like Elon Musk provide an in-depth discussion on the company’s AI efforts on not just its automotive business but on its energy business and beyond as well. AI Day promises to be yet another tour-de-force of technical information from the electric car manufacturer. Thus, it is no surprise that there is a lot of excitement from the EV community heading into the event.
Tesla has kept the details of AI Day behind closed doors, so the specifics of the actual event are scarce. That being said, an AI Day agenda sent to attendees indicated that they could expect to hear Elon Musk speak during a live keynote, speak with Andrej Karpathy and the rest of Tesla’s AI engineers, and participate in breakout sessions with the teams behind Tesla’s AI development.
Similar to Autonomy Day and Battery Day, Teslarati would be following along on AI Day’s discussions to provide you with an updated account of the highly-anticipated event. Please refresh this page from time to time, as notes, details, and quotes from Elon Musk’s keynote and its following discussions will be posted here.
Simon 19:40 PT – A question about the use cases for the Tesla Bot was asked. Musk notes that the Tesla Bot would start with boring, repetitive, work, or work that people would least like to do.
Simon 19:25 PT – A question about AI and manufacturing is asked and how it potentially relates to the “Alien Dreadnaught” concept. Musk notes that most of Tesla’s manufacturing today is already automated. Musk also noted that humanoid robots would be done either way, so it would be great for Tesla to do this project, and safely as well. “We’re making the pieces that would be useful for a humanoid robot, so we should probably make it. If we don’t someone else will — and we want to make sure it’s safe,” Musk said.
Simon 19:15 PT – And the Q&A starts. First question involves open-sourcing Tesla’s innovations. Musk notes that it’s pretty expensive to develop all this tech, so he’s not sure how things could be open-sourced. But if other car companies would like to license the system, that could be done.
Simon 19:11 PT – There will really be a “Tesla Bot.” It would be built by humans, for humans. It would be friendly, and it would eliminate dangerous, repetitive, boring tasks. This is still petty darn unreal. It uses the systems that are currently being developed for the company’s vehicles. “There will be profound applications for the economy,” Musk said.
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Simon 19:06 PT – New products! A whole Tesla suit?! After a fun skit, Elon says the “Tesla Bot” would eventually be real.
Simon 19:00 PT – What is crazy is that Dojo is not even done. This is just what it is today. Dojo is still evolving, and it is going to be way more powerful in the future. Now, it’s Elon Musk’s turn. What’s next for Tesla beyond vehicles.
Simon 19:00 PT – Venkataramanan teases the ExaPOD. Yet another revolutionary solution from Tesla. With all this, it is evident that Tesla’s approach to autonomy is on a whole other level. It would not be surprising if it takes Wall Street and the market a few days to fully absorb what is happening here.
Simon 18:55 PT – The specs of Dojo are insane. Behind its beastly specs, it seems that Dojo’s full potential lies in the fact that all this power is being used to do one thing: to make autonomous cars possible. Dojo is a pure learning machine, with more than 500,000 training nodes being built together. Nine petaflops of compute per tile, 36 terabytes per second of off-tile bandwidth. But this is just the tip of the iceberg for Dojo.
Simon 18:50 PT – Ganesh Venkataramanan, Project Dojo’s lead, takes the stage. He states that Elon Musk wanted a super-fast training computer to train Autopilot. And thus Project Dojo was born. Dojo is a distributed compute architecture connected by network fabric. It also has a large compute plane, extremely high bandwidth with low latencies, and big networks that are partitioned and mapped, to name a few.
Simon 18:45 PT – Milan Kovac, Tesla’s Director of Autopilot Engineering takes the stage. He notes that he would discuss how neural networks are run in the company’s cars. He notes that Tesla’s systems require supercomputers.
Simon 18:40 PT – Ashok notes that simulations have helped Tesla a lot already. It has, for example, helped the company identify pedestrian, bicycle, and vehicle detection and kinematics. The networks in the vehicles were traded to 371 million simulated images and 480 million cuboids.
Simon 18:35 PT – Ashok notes that these strategies ultimately helped Tesla retire radar from its FSD and Autopilot suite and adopt a pure vision model. A comparison between a radar+camera system and pure vision shows just how much more refined the company’s current strategy is. The executive also touched on how simulations help Tesla develop its self-driving systems. He states that simulations help when data is difficult to source, difficult to label, or in a closed loop.
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Simon 18:30 PT – Ashok returns to discuss Auto Labeling. Simply put, there is so much labeling that needs to be done that it’s impossible to be done manually. He shows how roads and other items on the road are “reconstructed” from a single car that’s driving. This effectively allowed Tesla to label data much faster, while allowing vehicles to navigate safely and accurately even when occlusions are present.
Simon 18:25 PT – Karpathy returns to talk about manual labeling. He notes that manual labeling that’s outsourced to third-party firms is not optimal. Thus, in the spirit of vertical integration, Tesla opted to establish its own labeling team. Karpathy notes that in the beginning, that Tesla was using 2D image labeling. Eventually, Tesla transitioned to 4D labeling, where the company could label in vector space. But even this was not enough, and thus, auto labeling was developed.
Simon 18:23 PT – The executive states that traffic behavior is extremely complicated, especially in several parts of the world. Ashok notes that this partly illustrated by parking lots and how they are actually complex. Summoning a car from a parking lot, for example, used to utilize 400k notes to navigate, resulting in a system whose performance left much to be desired.
Simon 18:18 PT – Ashok notes that when driving alongside other cars, Autopilot must not only think about how they would drive, they must also think about how other cars would operate. He shows a video of a Tesla navigating a road and dealing with multiple vehicles to demonstrate this point.
Simon 18:15 PT – Director of Autopilot Software Ashok Elluswamy takes the stage. He starts off by discussing some key problems in planning in both non-convex and high-dimensional action spaces. He also shows Tesla’s solution to these issues, a “Hybrid Planning System.” He demonstrates this by showing how Autopilot performs a lane change.
Simon 18:10 PT – Karpathy’s discussion notes that today, Tesla’s FSD strategy is a lot more cohesive. This is demonstrated by the fact that the company’s vehicles could effectively draw a map in real-time as it drives. This is a massive difference compared to the pre-mapped strategies employed by rivals in both the automotive and software field like Super Cruise and Waymo.
To solve several problems encountered over the last few years with the previous suite, Tesla re-engineered their NN learning from the ground up and utilized a multi-head route, camera calibrations, caching, queues, and optimizations to streamline all tasks.
(heavily simplified) pic.twitter.com/LG2TRgjxip
-— Teslascope (@teslascope) August 20, 2021
Simon 18:05 PT – The AI Director discusses how Tesla practically re-engineered their neural network learning from the ground-up and utilized a multi-head route. These include camera calibrations, caching, queues, and optimizations to streamline all tasks. Do note that this is an extremely simplified iteration of Karpathy’s discussion so far.
Simon 18:00 PT – Karpathy covers more challenges that are involved in even the basics of perception. Needless to say, AI Day is quickly proving to be Tesla’s most technical event right off the bat. That said, multi-camera networks are amazing. They’re just a ton of work, but it may very well be a silver bullet for Tesla’s predictive efforts.
Simon 17:56 PT – Karpathy showcases a video of how Tesla used to process its image data in the past. He shows a popular video for FSD that has been shared in the past. He notes that while great, such a system proved to be inadequate, and this is something that Tesla learned when it launched Smart Summon. While per-camera detection is great, the vector space proves inadequate.
Simon 17:55 PT – Karpathy noted that when Tesla designs the visual cortex in its car, the company is modeling it to how a biological vision is perceived by eyes. He also touches on how Tesla’s visual processing strategies have evolved over the years, and how it is done today. The AI Director also touches on Tesla’s “HydraNets,” on account of their multi-task learning capabilities.
Simon 17:51 PT – Karpathy starts off by discussing the visual component of Tesla’s AI, as characterized by the eight cameras used in the company’s vehicles. The AI director notes that AI could be considered like a biological being, and it’s built from the ground up, including its synthetic visual cortex.
Simon 17:48 PT – Elon Musk takes the stage. He apologizes for the event’s delay. He jokes that Tesla probably needs AI to solve these “technical difficulties.” The CEO highlights that AI Day is a recruitment event. He calls Tesla’s head of AI Andrej Karpathy. There’s no better person to discuss AI.
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Simon 17:45 PT – We’re here watching the AI Day FSD preview video and we can’t help but notice that… are those Waypoints?!
Simon 17:38 PT – Looks like we’ve got an Elon sighting! And a preview video too! Here we go, folks!
We’ve got an Elon sighting
— Rob Maurer (@TeslaPodcast) August 20, 2021
Simon 17:30 PT – A 30-minute delay. We haven’t seen this much delay in quite a bit.
Simon 17:20 PT – It’s a good thing that Tesla has great taste in music. Did Grimes mix this track?
Simon 17:15 PT – We’re 15 minutes in. “Elon Time” is going strong on AI Day. To be honest, though, this music would fit the “Rave Cave” in Giga Berlin this coming October.
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Simon 17:10 PT – A good thing to keep in mind is that AI Day is a recruitment event. Some food for thought just in case the discussions take a turn for the extremely technical. AI Day is designed to attract individuals who speak Tesla’s language in its rawest form. We’re just fortunate enough to come along for the ride.
Tesla Board Member Hiro Mizuno sums it up in this tweet pretty well.
Anybody passionate about real world AI !! https://t.co/ydaWQlkE4O
— HIRO MIZUNO (@hiromichimizuno) August 20, 2021
Simon 17:05 PT – I guess AI Day is starting on “Elon Time?” We’re on to the next track of chill music.
Simon 17:00 PT – And with 5 p.m. PST here, the music is officially live on the AI Day live stream. Looks like we’re in for some wait. Wonder how many minutes it would take before it starts? Gotta love this chill music though.
Simon 16:58 PT – While waiting, I can’t help but think that a ton of TSLA bears and Wall Street would likely not understand the nuances of what Tesla would be discussing today. Will Tesla go three-for-three? It was certainly the case with Battery Day and Autonomy Day.
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Made it pic.twitter.com/aAWqxgf0bP
— Johnna (@JohnnaCrider1) August 19, 2021
Simon 16:55 PT – T-minus 5 minutes. Some attendees of AI Day are now posting some photos on Twitter, but it seems like photos and videos are not allowed on the actual venue of the event. Pretty much expected, I guess.
Simon 16:50 PT – Greetings, everyone, and welcome to another Live Blog. This is Tesla’s most technical event yet, so I expect this one to go extremely in-depth on the company’s AI efforts and the technology behind it. We’re pretty excited.
Don’t hesitate to contact us with news tips. Just send a message to tips@teslarati.com to give us a heads up.
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Investor's Corner
SpaceX and Nvidia team up on Musk’s orbital AI bet
SpaceX revealed a new Nvidia satellite partnership, then Musk pledged an exclusive Nvidia hardware commitment.
SpaceX and Nvidia are now working together on the hardware that will power Musk’s orbital data center ambitions. SpaceX announced on X on Tuesday that it is partnering with Nvidia to design the compute payload for Starmind AI1, the first satellite in a planned constellation built to run AI workloads directly in orbit. Each Starmind satellite will carry Nvidia’s Rubin GPUs and Vera CPUs, according to the post, which included renderings of the payload design.
The announcement landed hours before SpaceX’s first earnings call as a public company, where Musk went further, saying the company has committed to building its AI infrastructure exclusively on Nvidia hardware. “We think the Vera Rubin architecture is the best architecture. We think it’s the best AI computer, and we greatly value our close cooperation and partnership on many levels with Nvidia,” Musk told investors on the call,. “So we’re exclusive to Nvidia.”
Musk said SpaceX plans to deploy Nvidia’s Vera Rubin NVL72 rackscale system, codenamed Kyber, both on the ground and in space. He set a target of 2 gigawatts of compute capacity online by the end of this year, scaling to roughly 10 gigawatts by the end of 2027.
SpaceX’s newest Starmind will make earth data centers obsolete
Starmind has been in development since Musk confirmed the name in June, following an xAI trademark filing that tipped off the project before SpaceX made it official. The idea is massive in scope and instead of moving data down to ground based servers, satellites equipped with onboard processors and large solar arrays would compute AI workloads in orbit and beam results back to Earth. SpaceX has already filed with the FCC for a constellation of up to one million satellites to support the effort, citing constant solar power and the absence of zoning restrictions as advantages over terrestrial data centers.
The Nvidia exclusivity marks a shift in tone from just two weeks ago, when Musk was busy knocking down a report that SpaceX had ordered $52 billion worth of Nvidia GPUs through Foxconn, calling it fake news at the time. The dollar figure in that rumor may have been wrong, but the underlying direction seems correct. SpaceX’s AI division already leases Colossus compute capacity to Anthropic and Google, and Tuesday’s earnings report showed AI revenue climbing sharply as those deals ramp up.
Nvidia shares rose roughly 3% in Tuesday trading on the news, while SpaceX stock climbed nearly 9% during the day before giving back gains after hours as investors digested the earnings report’s capital spending figures.
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SpaceX (NASDAQ: SPCX) reported a beat in revenues and EBITDA in its first earnings call report while also minimizing losses as its business continues to gain momentum.
After its IPO in July, SpaceX saw some tough losses on Wall Street due to a major selloff after a delay in its 13th Starship test flight. The ship launched later that week and completed what was arguably the most successful IFT operation in the Starship program’s history.
Nevertheless, the company is continuing on and reported some encouraging financials while also promoting what appears to be a robust outlook moving forward in its Space, AI, and Connectivity divisions.
SpaceX to report first-ever earnings today: here’s what to expect
Earnings Results
- Revenues: $7.8 billion reported vs. $6.7 billion expected
- Adjusted EBITDA: $3.5 billion vs. $2 billion expected
- Net loss of $541 million, an improvement of $467 million from net loss of $1.0 billion
Additionally, CFO Bret Johnsen had these comments:
“2026 has been a momentous year so far, and the second quarter demonstrated the true power of SpaceX. Revenue growth accelerated across all our business segments and we delivered strong operating leverage, with significant margin expansion led by our new AI compute agreements. Our unparalleled leadership in launch, Starlink subscriber growth, new enterprise and government partnerships, and best-in-class AI infrastructure underscore our ability to drive meaningful scale and deliver attractive returns. As a newly public company, we are delighted to welcome our broad base of shareholders and bondholders. We ended the second quarter with $100 billion of cash, cash equivalents, and marketable securities, and $47.5 billion in backlog. This financial strength gives us substantial capacity to invest in Starship, Starlink Broadband and Mobile satellites, and our AI platform, while maintaining a disciplined long-term capital allocation framework.”
Space Business Highlights
SpaceX shared some of its biggest Space Business Highlights for Q2:
- Space revenues grew 55% sequentially and 29% year-over-year to $962 million, driven by a higher number of large customer launches and a favorable customer shift compared to the prior year
- Total costs and expenses for the Space segment were up by $389 million year-over-year, as we continued to accelerate R&D investments in our Starship program, which we believe will reduce the cost to orbit by 99% or more relative to the historical average, and unlock significant revenue potential across all business segments
- Leading launch provider for the world with 78 launches and 1,041 metric tons of mass to orbit deployed over the six months ended June 30, 2026, primarily allocated to Connectivity for the deployment of our Starlink constellation
- Starship V3 development continued to advance towards full and rapid reusability:
- Completed Starship V3’s first suborbital mission in May, Flight 12, which achieved a successful lift off from our new Starbase pad, a precision landing of Starship’s upper stage, and deployment of modified V2 Starlink satellites
- Subsequent to the second quarter, completed Starship Flight 13 in July, which achieved all flight objectives including deploying 20 production V3 satellites, demonstrating in-space relight of a Raptor engine, and executing the softest ever splashdown of Starship, providing critical views of an intact heatshield
SpaceX will report its earnings today at 4:30 P.M. EDT.
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Elon Musk issued a second pointed warning to SpaceX short sellers on Tuesday, just hours before the company was set to release its first quarterly earnings as a publicly traded firm. Responding to a report highlighting elevated short interest, Musk wrote on X: “I try to warn them, but they just double down …”
The comment came as data from S3 Partners showed roughly 95 percent of available SPCX shares to borrow were on loan, translating to about 34 percent short interest as a percentage of the float. The stock has traded under pressure since its record-breaking IPO in June 2026, declining significantly from early peaks.
I try to warn them, but they just double down … 🤷♂️
— Elon Musk (@elonmusk) August 4, 2026
This marks the second such message from Musk in under three weeks.
On July 17, amid post-IPO volatility, he stated: “The survival probability of firms who maintain a significant short position in SpaceX over time is very low.” At that time, SPCX had fallen roughly 30 percent from its peak above a $2.6 trillion valuation, with short sellers reportedly realizing gains of about $8.7 billion.
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Musk’s warning aligned with optimistic analyses projecting that Starship-driven cost reductions could enable a multi-trillion-dollar space economy through applications such as orbital solar power, asteroid mining, data centers, and Mars-related projects, positioning SpaceX as critical infrastructure.
SpaceX is scheduled to report second-quarter results after the market close later today, followed by a webcast. Analysts anticipate revenue near $6.9 billion, reflecting growth in Starlink, launch services, and AI-related segments. The earnings release precedes a major lockup expiration on August 6 that could free hundreds of millions of insider shares.
Musk has a long track record of confronting short sellers, particularly regarding Tesla, where he has argued that persistent bearish positions underestimate transformative technologies. Critics view his optimism as overly ambitious given near-term stock fluctuations, while supporters see temporary dips as opportunities in a longer-term expansion of the space economy.
As SpaceX opens its books to public scrutiny for the first time, the high short interest and Musk’s repeated cautions set the stage for heightened market attention on the results and management’s commentary.
SpaceX and Nvidia team up on Musk’s orbital AI bet
SpaceX reports beat in first earnings while minimizing losses
