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 domestic sales fell 4.8% in 2025, but it’s not doom and gloom
Despite the full-year dip, Tesla finished the year with record domestic sales in December.
Tesla posted 625,698 retail vehicle sales in China in 2025, marking a 4.8% year-on-year decline as the EV maker navigated an increasingly competitive EV market and a major production transition for its best-selling vehicle.
Despite the full-year dip, Tesla finished the year with record domestic sales in December.
Retail sales slip amid Model Y transition
Tesla’s 2025 retail sales in China were down from 657,102 units in 2024, when the company ranked third in the country’s new energy vehicle (NEV) market with a 6.0% share. In 2025, Tesla’s share slipped to 4.9%, placing it fifth overall, as noted in a CNEV Post report.
Part of the decline seemed tied to operational disruptions early in the year. Tesla implemented a changeover to the new Tesla Model Y in the first quarter of 2025, which required temporary production pauses at Giga Shanghai. That downtime reduced vehicle availability early during the year, weighing on the company’s retail volumes in China and in areas supplied by Giga Shanghai’s exports.
China remained one of Tesla’s largest markets, accounting for 38.24% of its global deliveries of 1.64 million vehicles in 2025. However, the company also saw exports from Giga Shanghai fall to 226,034 units, down nearly 13% year-on-year. It remains to be seen how much of this could be attributed to the Model Y changeover and how much could be attributed to other factors.
Strong December 2025 finish
While the full-year picture showed some contraction, Tesla closed 2025 on a high note. According to data from the China Passenger Car Association (CPCA), Tesla China delivered a record 93,843 vehicles domestically in China in December, its highest monthly total ever. That figure was up 13.2% from a year earlier and 28.3% higher than November.
The surge was driven in part by Tesla prioritizing domestic deliveries late in the year, allowing buyers to lock in favorable purchase tax policies. In December alone, Tesla captured 7.0% of China’s NEV market and a notable 12.0% share of the country’s battery-electric segment.
On a wholesale basis, Tesla China sold 851,732 vehicles in 2025, down 7.1% year-on-year. From this number, 97,171 were from December 2025 alone. Tesla Model 3 wholesale figures reached 312,738 units, a year-over-year decrease of 13.12%. The Tesla Model Y’s wholesale figures for 2025 were 538,994 units, down 3.18% year-over-year.
News
Tesla Robovan’s likely first real-world use teased by Boring Company President
As per the executive, the vehicle will be used to move large crowds through Las Vegas during major events.
The Boring Company President Steve Davis has shared the most likely first real-world use for Tesla’s Robovan.
As per the executive, the vehicle will be used to move large crowds through Las Vegas during major events.
Tesla Robovan for high-demand events
During a feature with the Las Vegas Review-Journal, Boring Company President Steve Davis stated that the Tesla Robovan will be used in Sin City once the Vegas Loop expands across the Strip and downtown and the fleet grows to about 1,200 Teslas.
At that scale, Robovans would primarily be deployed during predictable surges, such as game days and large shows, when many riders are traveling to the same destination at the same time.
“The second you have four (passengers) and you have to start stopping, the best thing you can do is put your smallest vehicle in, which is a car. But if you know people are going to the stadium because of a game, you’ll know an hour before, two hours before, that a lot of people are going to a game or a Sphere show, if you are smart about it, that’s when you put a high occupancy vehicle in, that’s when you put the Robovan in,” Davis said.
Vegas Loop expansion
Steve Davis’s Robovan comment comes amid The Boring Company’s efforts to expand the Vegas Loop’s airport service. Phase 1 of rides to Harry Reid International Airport began last month, allowing passengers to travel from existing Loop stations such as Resorts World, Encore, Westgate, and the Las Vegas Convention Center.
Phase 2 will add a 2.2-mile dual-direction tunnel from Westgate to Paradise Road. That section is expected to open within months and will allow speeds of up to 60 mph on parts of the route, while expanding the fleet to around 160 vehicles.
Future phases are expected to extend tunnels closer to airport terminals and add multiple stations along University Center Drive. At this point, the system’s fleet is expected to grow close to 300 Teslas. The final phase, an underground airport station, was described by Davis as the system’s “holy grail.” This, however, has no definite timeframe as of yet.
News
Tesla seeks engineer to make its iOS Robotaxi app feel “magical”
It appears that Tesla is hard at work in ensuring that users of its Robotaxi service are provided with the best user experience possible.
Tesla is hiring an iOS Engineer for its Robotaxi app team, with the job posting emphasizing the creation of polished experiences that make the service not just functional, but “magical.”
Needless to say, it appears that Tesla is hard at work in ensuring that users of its Robotaxi service are provided with the best user experience possible.
Robotaxi App features
As observed by Tesla community members, Tesla has gone live with a job listing for an iOS Engineer for its Robotaxi App. The job listing mentions the development of a “core mobile experience that enables customers to summon, track, and interact with a driverless vehicle. From requesting a ride to enabling frictionless entry, from trip planning to real-time vehicle status and media control.”
Interestingly enough, the job listing also mentioned the creation of polished experiences that make the Robotaxi more than just functional. “You will take full ownership of features—from architecture design to robust implementation—delivering delightful and polished experiences that make Robotaxi not just functional, but magical,” Tesla noted in its job listing.
Apple’s “magical” marketing
Tesla’s use of the word “magical” when referring to the Robotaxi app mirrors the marketing used by Apple for some of its key products. Apple typically uses the word when referring to products or solutions that transform complex technology into something that feels effortless, simple, and natural to daily life. Products such as the AirPods’ seamless pairing with the iPhone and FaceID’s complex yet simple-to-use security system have received Apple’s “magical” branding.
With this in mind, Tesla seems intent on developing a Robotaxi app that is sophisticated, but still very easy to use. Tesla already has extensive experience in this area, with the Tesla App consistently being hailed by users as one of the best in its segment. If Tesla succeeds in making the Robotaxi app worthy of its “magical” branding, then it wouldn’t be a surprise if the service sees rapid adoption even among mainstream consumers.
Tesla China’s domestic sales fell 4.8% in 2025, but it’s not doom and gloom
Tesla Robovan’s likely first real-world use teased by Boring Company President
