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 FSD (Supervised) fleet passes 8.4 billion cumulative miles
Tesla’s Full Self-Driving (Supervised) system has now surpassed 8.4 billion cumulative miles.
The figure appears on Tesla’s official safety page, which tracks performance data for FSD (Supervised) and other safety technologies.
Tesla has long emphasized that large-scale real-world data is central to improving its neural network-based approach to autonomy. Each mile driven with FSD (Supervised) engaged contributes additional edge cases and scenario training for the system.
The milestone also brings Tesla closer to a benchmark previously outlined by CEO Elon Musk. Musk has stated that roughly 10 billion miles of training data may be needed to achieve safe unsupervised self-driving at scale, citing the “long tail” of rare but complex driving situations that must be learned through experience.
The growth curve of FSD Supervised’s cumulative miles over the past five years has been notable.
As noted in data shared by Tesla watcher Sawyer Merritt, annual FSD (Supervised) miles have increased from roughly 6 million in 2021 to 80 million in 2022, 670 million in 2023, 2.25 billion in 2024, and 4.25 billion in 2025. In just the first 50 days of 2026, Tesla owners logged another 1 billion miles.
At the current pace, the fleet is trending towards hitting about 10 billion FSD Supervised miles this year. The increase has been driven by Tesla’s growing vehicle fleet, periodic free trials, and expanding Robotaxi operations, among others.
With the fleet now past 8.4 billion cumulative miles, Tesla’s supervised system is approaching that threshold, even as regulatory approval for fully unsupervised deployment remains subject to further validation and oversight.
Tesla’s Full Self-Driving (Supervised) system has now surpassed 8.4 billion cumulative miles.
The figure appears on Tesla’s official safety page, which tracks performance data for FSD (Supervised) and other safety technologies.
Tesla has long emphasized that large-scale real-world data is central to improving its neural network-based approach to autonomy. Each mile driven with FSD (Supervised) engaged contributes additional edge cases and scenario training for the system.
The milestone also brings Tesla closer to a benchmark previously outlined by CEO Elon Musk. Musk has stated that roughly 10 billion miles of training data may be needed to achieve safe unsupervised self-driving at scale, citing the “long tail” of rare but complex driving situations that must be learned through experience.
The growth curve of FSD Supervised’s cumulative miles over the past five years has been notable.
As noted in data shared by Tesla watcher Sawyer Merritt, annual FSD (Supervised) miles have increased from roughly 6 million in 2021 to 80 million in 2022, 670 million in 2023, 2.25 billion in 2024, and 4.25 billion in 2025. In just the first 50 days of 2026, Tesla owners logged another 1 billion miles.
At the current pace, the fleet is trending towards hitting about 10 billion FSD Supervised miles this year. The increase has been driven by Tesla’s growing vehicle fleet, periodic free trials, and expanding Robotaxi operations, among others.
With the fleet now past 8.4 billion cumulative miles, Tesla’s supervised system is approaching that threshold, even as regulatory approval for fully unsupervised deployment remains subject to further validation and oversight.
Elon Musk
Elon Musk fires back after Wikipedia co-founder claims neutrality and dubs Grokipedia “ridiculous”
Musk’s response to Wales’ comments, which were posted on social media platform X, was short and direct: “Famous last words.”
Elon Musk fired back at Wikipedia co-founder Jimmy Wales after the longtime online encyclopedia leader dismissed xAI’s new AI-powered alternative, Grokipedia, as a “ridiculous” idea that is bound to fail.
Musk’s response to Wales’ comments, which were posted on social media platform X, was short and direct: “Famous last words.”
Wales made the comments while answering questions about Wikipedia’s neutrality. According to Wales, Wikipedia prides itself on neutrality.
“One of our core values at Wikipedia is neutrality. A neutral point of view is non-negotiable. It’s in the community, unquestioned… The idea that we’ve become somehow ‘Wokepidea’ is just not true,” Wales said.
When asked about potential competition from Grokipedia, Wales downplayed the situation. “There is no competition. I don’t know if anyone uses Grokipedia. I think it is a ridiculous idea that will never work,” Wales wrote.
After Grokipedia went live, Larry Sanger, also a co-founder of Wikipedia, wrote on X that his initial impression of the AI-powered Wikipedia alternative was “very OK.”
“My initial impression, looking at my own article and poking around here and there, is that Grokipedia is very OK. The jury’s still out as to whether it’s actually better than Wikipedia. But at this point I would have to say ‘maybe!’” Sanger stated.
Musk responded to Sanger’s assessment by saying it was “accurate.” In a separate post, he added that even in its V0.1 form, Grokipedia was already better than Wikipedia.
During a past appearance on the Tucker Carlson Show, Sanger argued that Wikipedia has drifted from its original vision, citing concerns about how its “Reliable sources/Perennial sources” framework categorizes publications by perceived credibility. As per Sanger, Wikipedia’s “Reliable sources/Perennial sources” list leans heavily left, with conservative publications getting effectively blacklisted in favor of their more liberal counterparts.
As of writing, Grokipedia has reportedly surpassed 80% of English Wikipedia’s article count.
News
Tesla Sweden appeals after grid company refuses to restore existing Supercharger due to union strike
The charging site was previously functioning before it was temporarily disconnected in April last year for electrical safety reasons.
Tesla Sweden is seeking regulatory intervention after a Swedish power grid company refused to reconnect an already operational Supercharger station in Åre due to ongoing union sympathy actions.
The charging site was previously functioning before it was temporarily disconnected in April last year for electrical safety reasons. A temporary construction power cabinet supplying the station had fallen over, described by Tesla as occurring “under unclear circumstances.” The power was then cut at the request of Tesla’s installation contractor to allow safe repair work.
While the safety issue was resolved, the station has not been brought back online. Stefan Sedin, CEO of Jämtkraft elnät, told Dagens Arbete (DA) that power will not be restored to the existing Supercharger station as long as the electric vehicle maker’s union issues are ongoing.
“One of our installers noticed that the construction power had been backed up and was on the ground. We asked Tesla to fix the system, and their installation company in turn asked us to cut the power so that they could do the work safely.
“When everything was restored, the question arose: ‘Wait a minute, can we reconnect the station to the electricity grid? Or what does the notice actually say?’ We consulted with our employer organization, who were clear that as long as sympathy measures are in place, we cannot reconnect this facility,” Sedin said.
The union’s sympathy actions, which began in March 2024, apply to work involving “planning, preparation, new connections, grid expansion, service, maintenance and repairs” of Tesla’s charging infrastructure in Sweden.
Tesla Sweden has argued that reconnecting an existing facility is not equivalent to establishing a new grid connection. In a filing to the Swedish Energy Market Inspectorate, the company stated that reconnecting the installation “is therefore not covered by the sympathy measures and cannot therefore constitute a reason for not reconnecting the facility to the electricity grid.”
Sedin, for his part, noted that Tesla’s issue with the Supercharger is quite unique. And while Jämtkraft elnät itself has no issue with Tesla, its actions are based on the unions’ sympathy measures against the electric vehicle maker.
“This is absolutely the first time that I have been involved in matters relating to union conflicts or sympathy measures. That is why we have relied entirely on the assessment of our employer organization. This is not something that we have made any decisions about ourselves at all.
“It is not that Jämtkraft elnät has a conflict with Tesla, but our actions are based on these sympathy measures. Should it turn out that we have made an incorrect assessment, we will correct ourselves. It is no more difficult than that for us,” the executive said.
Tesla FSD (Supervised) fleet passes 8.4 billion cumulative miles
Elon Musk fires back after Wikipedia co-founder claims neutrality and dubs Grokipedia “ridiculous”
