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 parked 50+ Cybercabs outside its Texas Factory with some crash tested
Dozens of Tesla Cybercabs have been spotted at Giga Texas crash testing facility ahead of launch.
Drone footage captured by longtime Giga Texas observer Joe Tegtmeyer shows over 50 units of Tesla Cybercab at the Austin factory campus, including several units clustered by Tesla’s on-site crash testing facility.
The outbound lot at Gigafactory Texas sits just outside the factory exit and serves as the primary staging area where finished vehicles are held before being loaded onto transport carriers or dispatched for validation testing. On any given day, the lot holds a mix of Model Y and Cybertruck units alongside the growing Tesla Cybercab fleet, as can be seen in the drone footage captured by Joe Tegtmeyer.
Roughly 50 Cybercab units are visible across the campus, parked in tight organized rows. Most of the units visible still carry steering wheels and pedals, temporary additions Tesla included to satisfy current safety regulations while the vehicles accumulate real-world data ahead of full regulatory approval for a steering wheel-free design. Tesla operates dedicated Crash Labs at both its Giga Texas and Fremont facilities that are purpose-built for controlled structural crash tests. Historically, automakers begin intensive crash testing roughly one to two months before volume production kicks off. The Cybertruck followed almost exactly that pattern. The Cybercab appears to be on the same track facility that we first saw back in October 2025. The first production Cybercab rolled off the Giga Texas line on February 17, 2026. Volume production is now targeted for April. Musk previously wrote on X that “the early production rate will be agonizingly slow, but eventually end up being insanely fast,” and separately stated Tesla is targeting at least 2 million Cybercab units per year. Commercial robotaxi service in Austin is targeted for late 2026.
Firmware
Tesla 2026 Spring Update drops 12 new features owners have been waiting for
Tesla announced its Spring 2026 software update, and it’s the most feature-dense seasonal release the company has put out. The update covers twelve named changes spanning FSD, voice AI, safety lighting, dashcam storage, and pet display customization, among other things.
The centerpiece for owners with AI4 hardware is a redesigned Self-Driving app. The new interface lets owners subscribe to Full Self-Driving with a single tap and view ongoing FSD usage stats directly in the vehicle.
Grok gets its biggest in-car upgrade yet. The update adds a “Hey Grok” hands-free wake word along with location-based reminders, so a driver can now say “remind me to pick up groceries when I get home” without touching the screen. Grok first arrived in vehicles in July 2025, but each update has pushed it closer to genuine daily utility. Musk framed the broader vision clearly at Davos in January, saying Tesla is “really moving into a future that is based on autonomy.”
On safety, the update introduces enhanced blind spot warning lights that integrate directly with the cabin’s ambient lighting, building on the blind spot door warning that arrived in update 2026.8.
Dog Mode has been renamed Pet Mode and now lets owners choose a dog, cat, or hedgehog icon and add their pet’s name to the display.
Dashcam retention now extends up to 24 hours, up from the previous one-hour rolling loop, with a permanent save option for any clip. Weather maps now show rain and snow with better color differentiation and include the past hour of precipitation data along the route.
Tesla has now established a clear rhythm of two major OTA pushes per year. As with last year’s Spring update, that cycle started taking shape in 2025 with adaptive headlights and trunk customization. The 2025 Holiday Update then added Grok to the vehicle for the first time. This Spring follows that structure: the Holiday update introduces new architecture, and the Spring update broadens it across the fleet.
Two notable features still did not make it. IFTTT automations, which launched in China earlier this year, were held back from this North American release for unknown reasons, and Apple CarPlay remains absent, reportedly still delayed by iOS 26 and Apple Maps compatibility issues.
Below is the full list of feature updates released by Tesla.
— Tesla (@Tesla) April 13, 2026
News
Tesla launches new Model Y interior option
Produced at Gigafactory Shanghai, the update applies to all five-seat Premium Model Y configurations and started being seen on customer deliveries this week. The move marks the first major interior refresh for the compact crossover since its global debut.
Tesla has rolled out a striking new interior choice for its best-selling Model Y in China, replacing the long-familiar white cabin with a fresh option: Zen Grey.
Produced at Gigafactory Shanghai, the update applies to all five-seat Premium Model Y configurations and started being seen on customer deliveries this week. The move marks the first major interior refresh for the compact crossover since its global debut.
The Zen Grey interior swaps the classic black-and-white contrast for a softer, more unified palette. Seats, door panels, and center console trim now feature a warm light-grey tone that covers far more surface area than before.
Previously, black accents on the console, door handles, and lower dashboard are now color-matched in the same pebbled vegan leather, creating a brighter, less clinical cabin.
Tesla describes the material as durable and easy to maintain while delivering a noticeably more premium feel. Early photos and videos from Chinese owners show the new shade reflecting natural light beautifully, giving the spacious Model Y an even airier, more inviting atmosphere without sacrificing the minimalist design customers expect:
🚨 First look at Tesla’s new Zen Grey interior, which differs slightly in tone and in placement compared to the now discontinued White Interior https://t.co/rRRuEOrbm4 pic.twitter.com/p7uyNfO3xY
— TESLARATI (@Teslarati) April 13, 2026
The change is not an added-cost upgrade but a direct replacement for the discontinued white interior on Shanghai-built vehicles. Customers configuring a new Model Y in China, Hong Kong, or Macau now see Zen Grey as the default light-colored choice.
The update also flows to export markets supplied by Giga Shanghai, including Australia, New Zealand, South Korea, Japan, and the Philippines. Tesla has used its Chinese factory as an innovation hub before, and executives appear to be testing broader appeal with this subtler, warmer tone that avoids the high-maintenance reputation sometimes associated with bright white leather.
Beyond the interior, the refreshed Model Y from Shanghai includes minor exterior tweaks such as blacked-out badges on some trims and optional dark 20-inch wheels.
These changes arrive as Tesla faces stiff competition from domestic EV makers in its largest market. By refreshing the Model Y’s cabin without raising prices, the company is signaling continued commitment to value and constant improvement.
With over 1.2 million Model Y units already on Chinese roads, the Zen Grey launch gives existing owners a fresh talking point and new buyers another reason to choose Tesla. As deliveries ramp up this month, the updated interior is expected to become the dominant light-colored choice across the Asia-Pacific region.
Tesla has not yet confirmed whether the Zen Grey will reach Fremont, Austin, or Berlin-built Model Ys, but Shanghai’s track record suggests the option could spread quickly if customer feedback remains strong.














