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.
Elon Musk said in late November that he’s “tried to warn” legacy automakers and “even offered to license Tesla Full Self-Driving, but they don’t want it,” expressing frustration with companies that refuse to adopt the company’s suite, which will eventually be autonomous.
Tesla has long established itself as the leader in self-driving technology, especially in the United States. Although there are formidable competitors, Tesla’s FSD suite is the most robust and is not limited to certain areas or roadways. It operates anywhere and everywhere.
The company’s current position as the leader in self-driving tech is being ignored by legacy automakers, a parallel to what Tesla’s position was with EV development over a decade ago, which was also ignored by competitors.
The reluctance mirrors how legacy automakers initially dismissed EVs, only to scramble in catch-up mode years later–a pattern that highlights their historical underestimation of disruptive innovations from Tesla.
Elon Musk’s Self-Driving Licensing Attempts
Musk and Tesla have tried to push Full Self-Driving to other car companies, with no true suitors, despite ongoing conversations for years. Tesla’s FSD is aiming to become more robust through comprehensive data collection and a larger fleet, something the company has tried to establish through a subscription program, free trials, and other strategies.
Tesla CEO Elon Musk sends rivals dire warning about Full Self-Driving
However, competing companies have not wanted to license FSD for a handful of speculative reasons: competitive pride, regulatory concerns, high costs, or preference for in-house development.
Déjà vu All Over Again
Tesla tried to portray the importance of EVs long ago, as in the 2010s, executives from companies like Ford and GM downplayed the importance of sustainable powertrains as niche or unprofitable.
Musk once said in a 2014 interview that rivals woke up to electric powertrains when the Model S started to disrupt things and gained some market share. Things got really serious upon the launch of the Model 3 in 2017, as a mass-market vehicle was what Tesla was missing from its lineup.
This caused legacy companies to truly wake up; they were losing market share to Tesla’s new and exciting tech that offered less maintenance, a fresh take on passenger auto, and other advantages. They were late to the party, and although they have all launched vehicles of their own, they still lag in two major areas: sales and infrastructure, leaning on Tesla for the latter.
I’ve tried to warn them and even offered to license Tesla FSD, but they don’t want it! Crazy …
When legacy auto does occasionally reach out, they tepidly discuss implementing FSD for a tiny program in 5 years with unworkable requirements for Tesla, so pointless. 🤷♂️
🦕 🦕
— Elon Musk (@elonmusk) November 24, 2025
Musk’s past warnings have been plentiful. In 2017, he responded to critics who stated Tesla was chasing subsidies. He responded, “Few people know that we started Tesla when GM forcibly recalled all electric cars from customers in 2003 and then crushed them in a junkyard,” adding that “they would be doing nothing” on EVs without Tesla’s efforts.
Companies laughed off Tesla’s prowess with EVs, only to realize they had made a grave mistake later on.
It looks to be happening once again.
A Pattern of Underestimation
Both EVs and self-driving tech represent major paradigm shifts that legacy players view as threats to their established business models; it’s hard to change. However, these early push-aways from new tech only result in reactive strategies later on, usually resulting in what pains they are facing now.
Ford is scaling back its EV efforts, and GM’s projects are hurting. Although they both have in-house self-driving projects, they are falling well behind the progress of Tesla and even other competitors.
It is getting to a point where short-term risk will become a long-term setback, and they may have to rely on a company to pull them out of a tough situation later on, just as it did with Tesla and EV charging infrastructure.
Tesla has continued to innovate, while legacy automakers have lagged behind, and it has cost them dearly.
Implications and Future Outlook
Moving forward, Tesla’s progress will continue to accelerate, while a dismissive attitude by other companies will continue to penalize them, especially as time goes on. Falling further behind in self-driving could eventually lead to market share erosion, as autonomy could be a crucial part of vehicle marketing within the next few years.
Eventually, companies could be forced into joint partnerships as economic pressures mount. Some companies did this with EVs, but it has not resulted in very much.
Self-driving efforts are not only a strength for companies themselves, but they also contribute to other things, like affordability and safety.
Tesla has exhibited data that specifically shows its self-driving tech is safer than human drivers, most recently by a considerable margin. This would help with eliminating accidents and making roads safer.
Tesla’s new Safety Report shows Autopilot is nine times safer than humans
Additionally, competition in the market is a good thing, as it drives costs down and helps innovation continue on an upward trend.
Conclusion
The parallels are unmistakable: a decade ago, legacy automakers laughed off electric vehicles as toys for tree-huggers, crushed their own EV programs, and bet everything on the internal-combustion status quo–only to watch Tesla redefine the industry while they scrambled for billions in catch-up capital.
Today, the same companies are turning down repeated offers to license Tesla’s Full Self-Driving technology, insisting they can build better autonomy in-house, even as their own programs stumble through recalls, layoffs, and missed milestones. History is not merely rhyming; it is repeating almost note-for-note.
Elon Musk has spent twenty years warning that the auto industry’s bureaucratic inertia and short-term thinking will leave it stranded on the wrong side of technological revolutions. The question is no longer whether Tesla is ahead–it is whether the giants of Detroit, Stuttgart, and Toyota will finally listen before the next wave leaves them watching another leader pull away in the rear-view mirror.
This time, the stakes are not just market share; they are the very definition of what a car will be in the decades ahead.
News
Waymo driverless taxi drives directly into active LAPD standoff
No injuries occurred, and the passengers inside the vehicle were safely transported to their destination, as per a Waymo representative.
A video posted on social media has shown an occupied Waymo driverless taxi driving directly into the middle of an active LAPD standoff in downtown Los Angeles.
As could be seen in the short video, which was initially posted on Instagram by user Alex Choi, a Waymo driverless taxi drove directly into the middle of an active LAPD standoff in downtown Los Angeles.
The driverless taxi made an unprotected left turn despite what appeared to be a red light, briefly entering a police perimeter. At the time, officers seemed to be giving commands to a prone suspect on the ground, who looked quite surprised at the sudden presence of the driverless vehicle.
People on the sidewalk, including the person who was filming the video, could be heard chuckling at the Waymo’s strange behavior.
The Waymo reportedly cleared the area within seconds. No injuries occurred, and the passengers inside the vehicle were safely transported to their destination, as per a Waymo representative. Still, the video spread across social media, with numerous netizens poking fun at the gaffe.
Others also pointed out that such a gaffe would have resulted in widespread controversy had the vehicle involved been a Tesla on FSD. Tesla is constantly under scrutiny, with TSLA shorts and similar groups actively trying to put down the company’s FSD program.
A Tesla on FSD or Robotaxi accidentally driving into an active police standoff would likely cause lawsuits, nonstop media coverage, and calls for a worldwide ban, at the least.
This was one of the reasons why even minor traffic infractions committed by the company’s Robotaxis during their initial rollout in Austin received nationwide media attention. This particular Waymo incident, however, will likely not receive as much coverage.
Tesla Model Y demand in China is through the roof, and new delivery dates show the company has already sold out its allocation of the all-electric crossover for 2025.
The Model Y has been the most popular vehicle in the world in both of the last two years, outpacing incredibly popular vehicles like the Toyota RAV 4. In China, the EV market is substantially more saturated, with more competitors than in any other market.
However, Tesla has been kind to the Chinese market, as it has launched trim levels for the Model Y in the country that are not available anywhere else. Demand has been strong for the Model Y in China; it ranks in the top 5 of all EVs in the country, trailing the BYD Seagull, Wuling Hongguang Mini EV, and the Geely Galaxy Xingyuan.
The other three models ahead of the Model Y are priced substantially lower.
Tesla is still dealing with strong demand for the Model Y, and the company is now pushing delivery dates to early 2026, meaning the vehicle is sold out for the year:
NEWS: New orders for all four Tesla Model Y trims in China are now officially sold out for 2025, as the factory’s remaining production capacity for the year has been fully allocated.
Estimated delivery dates for new orders now show January-February 2026. pic.twitter.com/Dfnu7yY58N
— Sawyer Merritt (@SawyerMerritt) December 1, 2025
Tesla experienced a 9.9 percent year-over-year rise in its China-made EV sales for November, meaning there is some serious potential for the automaker moving into next year despite increased competition.
There have been a lot of questions surrounding how Tesla would perform globally with more competition, but it seems to have a good grasp of various markets because of its vehicles, its charging infrastructure, and its Full Self-Driving (FSD) suite, which has been expanding to more countries as of late.
Tesla Model Y is still China’s best-selling premium EV through October
Tesla holds a dominating lead in the United States with EV registrations, and performs incredibly well in several European countries.
With demand in China looking strong, it will be interesting to see how the company ends the year in terms of global deliveries.
Elon Musk and Tesla try to save legacy automakers from Déjà vu
Waymo driverless taxi drives directly into active LAPD standoff
