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 Model 3 named New Zealand’s best passenger car of 2025
Tesla flipped the switch on Full Self-Driving (Supervised) in September, turning every Model 3 and Model Y into New Zealand’s most advanced production car overnight.
The refreshed Tesla Model 3 has won the DRIVEN Car Guide AA Insurance NZ Car of the Year 2025 award in the Passenger Car category, beating all traditional and electric rivals.
Judges praised the all-electric sedan’s driving dynamics, value-packed EV tech, and the game-changing addition of Full Self-Driving (Supervised) that went live in New Zealand this September.
Why the Model 3 clinched the crown
DRIVEN admitted they were late to the “Highland” party because the updated sedan arrived in New Zealand as a 2024 model, just before the new Model Y stole the headlines. Yet two things forced a re-evaluation this year.
First, experiencing the new Model Y reminded testers how many big upgrades originated in the Model 3, such as the smoother ride, quieter cabin, ventilated seats, rear touchscreen, and stalk-less minimalist interior. Second, and far more importantly, Tesla flipped the switch on Full Self-Driving (Supervised) in September, turning every Model 3 and Model Y into New Zealand’s most advanced production car overnight.
FSD changes everything for Kiwi buyers
The publication called the entry-level rear-wheel-drive version “good to drive and represents a lot of EV technology for the money,” but highlighted that FSD elevates it into another league. “Make no mistake, despite the ‘Supervised’ bit in the name that requires you to remain ready to take control, it’s autonomous and very capable in some surprisingly tricky scenarios,” the review stated.
-->At NZ$11,400, FSD is far from cheap, but Tesla also offers FSD (Supervised) on a $159 monthly subscription, making the tech accessible without the full upfront investment. That’s a game-changer, as it allows users to access the company’s most advanced system without forking over a huge amount of money.
News
Tesla starts rolling out FSD V14.2.1 to AI4 vehicles including Cybertruck
FSD V14.2.1 was released just about a week after the initial FSD V14.2 update was rolled out.
It appears that the Tesla AI team burned the midnight oil, allowing them to release FSD V14.2.1 on Thanksgiving. The update has been reported by Tesla owners with AI4 vehicles, as well as Cybertruck owners.
For the Tesla AI team, at least, it appears that work really does not stop.
FSD V14.2.1
Initial posts about FSD V14.2.1 were shared by Tesla owners on social media platform X. As per the Tesla owners, V14.2.1 appears to be a point update that’s designed to polish the features and capacities that have been available in FSD V14. A look at the release notes for FSD V14.2.1, however, shows that an extra line has been added.
“Camera visibility can lead to increased attention monitoring sensitivity.”
Whether this could lead to more drivers being alerted to pay attention to the roads more remains to be seen. This would likely become evident as soon as the first batch of videos from Tesla owners who received V14.21 start sharing their first drive impressions of the update. Despite the update being released on Thanksgiving, it would not be surprising if first impressions videos of FSD V14.2.1 are shared today, just the same.
-->Rapid FSD releases
What is rather interesting and impressive is the fact that FSD V14.2.1 was released just about a week after the initial FSD V14.2 update was rolled out. This bodes well for Tesla’s FSD users, especially since CEO Elon Musk has stated in the past that the V14.2 series will be for “widespread use.”
FSD V14 has so far received numerous positive reviews from Tesla owners, with numerous drivers noting that the system now drives better than most human drivers because it is cautious, confident, and considerate at the same time. The only question now, really, is if the V14.2 series does make it to the company’s wide FSD fleet, which is still populated by numerous HW3 vehicles.
News
Waymo rider data hints that Tesla’s Cybercab strategy might be the smartest, after all
These observations all but validate Tesla’s controversial two-seat Cybercab strategy, which has caught a lot of criticism since it was unveiled last year.
Toyota Connected Europe designer Karim Dia Toubajie has highlighted a particular trend that became evident in Waymo’s Q3 2025 occupancy stats. As it turned out, 90% of the trips taken by the driverless taxis carried two or fewer passengers.
These observations all but validate Tesla’s controversial two-seat Cybercab strategy, which has caught a lot of criticism since it was unveiled last year.
Toyota designer observes a trend
Karim Dia Toubajie, Lead Product Designer (Sustainable Mobility) at Toyota Connected Europe, analyzed Waymo’s latest California Public Utilities Commission filings and posted the results on LinkedIn this week.
“90% of robotaxi trips have 2 or less passengers, so why are we using 5-seater vehicles?” Toubajie asked. He continued: “90% of trips have 2 or less people, 75% of trips have 1 or less people.” He accompanied his comments with a graphic showing Waymo’s occupancy rates, which showed 71% of trips having one passenger, 15% of trips having two passengers, 6% of trips having three passengers, 5% of trips having zero passengers, and only 3% of trips having four passengers.
The data excludes operational trips like depot runs or charging, though Toubajie pointed out that most of the time, Waymo’s massive self-driving taxis are really just transporting 1 or 2 people, at times even no passengers at all. “This means that most of the time, the vehicle being used significantly outweighs the needs of the trip,” the Toyota designer wrote in his post.
-->Cybercab suddenly looks perfectly sized
Toubajie gave a nod to Tesla’s approach. “The Tesla Cybercab announced in 2024, is a 2-seater robotaxi with a 50kWh battery but I still believe this is on the larger side of what’s required for most trips,” he wrote.
With Waymo’s own numbers now proving 90% of demand fits two seats or fewer, the wheel-less, lidar-free Cybercab now looks like the smartest play in the room. The Cybercab is designed to be easy to produce, with CEO Elon Musk commenting that its product line would resemble a consumer electronics factory more than an automotive plant. This means that the Cybercab could saturate the roads quickly once it is deployed.
While the Cybercab will likely take the lion’s share of Tesla’s ride-hailing passengers, the Model 3 sedan and Model Y crossover would be perfect for the remaining 9% of riders who require larger vehicles. This should be easy to implement for Tesla, as the Model Y and Model 3 are both mass-market vehicles.
Tesla Model 3 named New Zealand’s best passenger car of 2025
Tesla starts rolling out FSD V14.2.1 to AI4 vehicles including Cybertruck
