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.
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.
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.
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.
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.
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.
News
Tesla China’s new six-seat Model Y L already sold out through October
New Tesla Model Y L orders now show an estimated delivery date of November 2025 at the earliest.

Tesla’s new Model Y L is sold out for October in China, with new orders showing an estimated delivery date of November 2025 at the earliest.
The extended-wheelbase variant, launched in August and first delivered this month, has quickly become one of Tesla’s strongest-selling vehicles in its key overseas market.
Demand and expectations
Tesla China initially positioned the Model Y L for September deliveries, with Vice President Grace Tao confirming on Weibo that the vehicle would begin reaching customers this September. True to that promise, the first handovers of the vehicle started last week. Since its launch, the six-seat crossover has sold out its September and October allocations, hinting at healthy demand.
Industry estimates suggested that Tesla received more than 35,000 orders for the Model Y L on launch day alone. While some Model Y L orders may overlap with those of the standard Model Y, industry watchers have noted that the six-seat, extended wheelbase variant is expanding the company’s total addressable market by appealing to car buyers who need more space and seating.
Tesla China boost
The Model Y L’s strong momentum is significant as Tesla navigates a competitive Chinese EV sector. With deliveries now stretching into November, the new crossover could potentially lift Tesla’s quarterly sales performance and help maintain its relevance in a market dominated by fast-moving domestic brands.
Beyond China, the extended-wheelbase Model Y L may also serve as a strategic export product for markets where larger family vehicles are in demand. Its early sellout performance suggests that Tesla has tapped into a new growth lever within its most successful vehicle lineup. With a starting price of RMB 339,000 ($47,180), after all, the Model Y L has the makings of a true bang-for-the-buck vehicle.
News
Tesla targets Bay Area airports as next step for Robotaxi rollout
The update was initially reported by Politico, which cited records that it reportedly obtained.

Tesla has expressed interest in operating its Robotaxi ride-hailing service in three of Silicon Valley’s busiest airports, as per the company’s communications with California regulators.
The update was initially reported by Politico, which cited records that it reportedly obtained.
Key Robotaxi battleground
As per the publication, Casey Blaine, Tesla’s senior regulatory counsel, informed regulators in California that the electric vehicle maker was “initiating engagement with the following airports to secure the necessary approvals to conduct pick-ups/drop-offs: San Francisco International Airport, San Jose Mineta International Airport, and Oakland International Airport.”
High-traffic airports have long been a focal point for autonomous vehicle firms like Waymo, which recently secured permits to operate in San Jose and is progressing in San Francisco after a lengthy battle with labor groups. By pursuing airport access, Tesla seems to be hinting that it wants a share of the same market. Regulators confirmed that Tesla has opened discussions with each Bay Area airport, though no permits have been granted yet.
Regulator visit
California’s Public Utilities Commission, the state’s primary ride-hailing regulator, has reportedly engaged directly with Tesla in recent months. Agency officials reportedly visited Tesla’s Palo Alto offices to learn more about the company’s ride-hailing program and its technology. Agency spokesperson Terrie Prosper shared some insights about the matter.
“CPUC staff are aware of Tesla’s recently expanded Bay Area charter-party carrier service and associated app. As for any charter-party carrier regulated by the CPUC, staff engages to exchange information, promote safety, and monitor compliance with applicable rules and regulations. Among other things, we appreciate and expect Tesla and all carriers to properly and clearly represent its service to the public,” Proper noted.
Tesla has already allowed Bay Area riders to book trips through its Robotaxi app, which launched to select customers in July before opening publicly in September. Videos posted online show Tesla’s driverless cars are still operating with safety drivers, though Musk has suggested that the service could be fully driverless by the end of the year.
Elon Musk
Analyst: Elon Musk’s $1 trillion Tesla pay deal modest against robot market potential
Jonas highlighted Tesla’s longer-term ambitions in robotics as a key factor in his assessment.

Morgan Stanley analyst Adam Jonas, one of Wall Street’s most ardent Tesla (NASDAQ:TSLA) bulls today, has described Elon Musk’s newly proposed $1 trillion performance-based compensation package as a “good deal” for investors.
In a note shared this week, Jonas argued that the package helps align the interests of Musk and Tesla’s minority shareholders, despite its shockingly high headline number.
Future market opportunities
Jonas highlighted Tesla’s longer-term ambitions in robotics as a key factor in his assessment. “Yes, a trillion bucks is a big number, but (it) is rather modest compared to the size of the market opportunity,” Jonas wrote. He added that the humanoid robot market could ultimately surpass the size of today’s global labor market “by a significant multiple.”
“We have entertained scenarios where the humanoid robot market can exceed the size of today’s global labor market… by a significant multiple,” Jonas wrote, as shared on X by Tesla watcher Sawyer Merritt.
The analyst likened the arrival of AI-powered robotics to the transformative effect of electricity, noting that “contemplating future global GDP before AI robots is like contemplating global GDP before electricity.” The Morgan Stanley analyst’s insights align with the idea that as much as 80% of Tesla’s future valuation could be tied to its Optimus humanoid robot program.
Elon Musk’s pay package
Tesla’s board has tied Elon Musk’s proposed compensation package to some of the most ambitious targets in corporate history. The 2025 CEO Performance Award requires the automaker’s valuation to soar from roughly $1.1 trillion today to $8.5 trillion over the next decade, a level that would make Tesla the most valuable company in existence.
The plan also demands a leap in Tesla’s operating profit, from $17 billion in 2024 to $400 billion annually. It also ties the CEO’s compensation to a number of product milestones, including the delivery of 20 million vehicles in total, 10 million active Full Self-Driving subscriptions, 1 million Tesla Bots, and 1 million Robotaxis in operation. Tesla’s board emphasized that Musk’s leadership was fundamental to achieving such ambitious goals, with Chair Robyn Denholm noting the award would align the CEO’s incentives with long-term shareholder value.
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