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 gets a massive order for the Semi: 370 units and $100M
WattEV, a leading provider of electric freight operations and charging infrastructure in the United States, has announced one of the largest deployments of electric Class 8 trucks in California history: an order for 370 Tesla Semi vehicles.
Tesla just got a massive order for the Semi, and it is its largest by a long shot.
WattEV, a leading provider of electric freight operations and charging infrastructure in the United States, has announced one of the largest deployments of electric Class 8 trucks in California history: an order for 370 Tesla Semis.
Valued at approximately $100 million, this marks the state’s biggest single electric truck order to date and signals accelerating momentum for zero-emission long-haul freight.
Credit: Tesla
Deliveries are set to begin with the first 50 Tesla Semis in 2026, with the full fleet operational by the end of 2027. More than 300 of these trucks will support a joint program with the Port of Oakland, helping electrify drayage and regional freight routes. The initiative aligns with California’s ambitious goals to transition to carbon-neutral freight operations.
Salim Youssefzadeh, CEO of WattEV, said at the annual ACT Expo industry event that the Semi was the easiest choice:
“We selected the Tesla Semi based on cost, performance, and availability after issuing a public request for proposals…With the Tesla Semi now entering mass production and drawing strong reviews from fleet operators nationwide, WattEV’s vertically integrated model – combining vehicle deployment, megawatt-class charging infrastructure, and full-service leasing – offers a turn-key path for carriers without any capital risk.”
Critical to the rollout are new Megawatt Charging System (MCS) hubs in Oakland, Fresno, Stockton, and Sacramento. These stations will deliver up to 300 miles of range in roughly 30 minutes—comparable to a traditional diesel fill-up. The Oakland depot, where WattEV recently broke ground, will serve as a cornerstone for northern and central California corridors, connecting ports to inland hubs and beyond.
This deployment builds on WattEV’s existing experience. The company has already logged millions of electric miles in Southern California, including early Tesla Semi deployments at the Ports of Long Beach and Los Angeles. By combining high-efficiency electric trucks with strategically placed fast-charging depots, WattEV aims to prove that battery-electric long-haul trucking can match—or exceed—diesel economics while slashing emissions.
The order arrives as Tesla ramps up Semi production at its Nevada factory, targeting higher volumes in 2026. Fleet operators nationwide have praised the Semi’s real-world performance, including strong torque, low operating costs, and advanced safety features. For California, the project supports air quality improvements around ports and highways while demonstrating scalable infrastructure for heavy-duty electrification.
Industry observers see this as a pivotal step toward broader adoption. With diesel trucks facing rising fuel and regulatory costs, turnkey electric solutions like WattEV’s could accelerate the shift. As the first 50 Semis hit the road in 2026, they will not only move freight but also help build the charging network that paves the way for even larger fleets.
This landmark order underscores Tesla’s growing footprint in commercial trucking and California’s leadership in sustainable transportation. For WattEV and its partners, it’s more than a vehicle purchase—it’s the foundation of a zero-emission freight network connecting Northern and Central California.
News
Tesla begins factoring international designs in Full Self-Driving visualization
Tesla has begun incorporating region-specific vehicle designs into its Full Self-Driving (FSD) visualization system, marking a quiet but meaningful step toward global readiness. In software update 2026.14, released as part of the Spring Update, European Tesla owners are now seeing flat-fronted, cab-over European-style semi-trucks rendered accurately on their center displays.
Tesla has begun factoring international designs into its Full Self-Driving (Supervised) visualizations, marking a tremendous step in how the company plans to roll out its driver assistance tech in areas outside North America.
Tesla has begun incorporating region-specific vehicle designs into its Full Self-Driving (FSD) visualization system, marking a quiet but meaningful step toward global readiness. In software update 2026.14, released as part of the Spring Update, European Tesla owners are now seeing flat-fronted, cab-over European-style semi-trucks rendered accurately on their center displays.
The change, first spotted by Not a Tesla App, adds a second 3D model alongside the traditional North American long-nose semi-trucks that have been standard until now. Vehicles can detect and display both styles depending on what’s in front of them, and the feature requires no FSD subscription—every Tesla owner in Europe sees it immediately.
The European semi-truck visualization was actually added to the vehicle software back in October alongside roughly fifteen new visual assets.
Tesla held it in reserve, activating it only once fleet data confirmed the AI could recognize these trucks with high confidence. This mirrors recent rollouts for horses and golf carts, where Tesla similarly waited for reliable detection before enabling the graphics. The result is a more realistic on-screen representation tailored to local roads, where cab-over designs dominate heavy transport.
The significance of this update extends far beyond a simple graphics tweak, which is really what people need to be paying attention to. These small, incremental steps forward continue to show Tesla’s intent for global expansion.
For the first time, Tesla is explicitly factoring international vehicle designs into its visualization engine, signaling a deliberate push to make FSD feel native in international markets.
In Europe, where cab-over semis are commonplace, seeing an accurate rendering builds immediate driver trust—the critical bridge between the car’s AI perception and the human behind the wheel. Accurate visualizations reinforce that the system truly understands its surroundings, reducing range anxiety and skepticism that have slowed autonomous adoption abroad.
Regulators in the EU have repeatedly emphasized human-AI transparency; by customizing visuals to match local reality, Tesla strengthens its case for broader FSD approvals and smoother regulatory reviews.
This move also highlights Tesla’s data-driven engineering philosophy. Rather than rushing generic models worldwide, the company is leveraging its global fleet to learn regional nuances before flipping the switch.
It accelerates FSD’s international expansion while improving safety—misidentified vehicles could erode confidence or, in edge cases, affect decision-making. For a company aiming to deploy robotaxis and unsupervised FSD globally, tailoring visualizations to European, Asian, or other markets is no longer optional; it’s foundational.
Early European owners report the change feels more intuitive, making the car’s “mind” easier to read in daily traffic.
As Tesla continues enabling the remaining visual assets added last year, the pattern is clear: localization is now baked into the FSD roadmap. What began as a small graphics update in Europe could soon appear in other regions, turning the visualization display into a truly worldwide language of autonomy.
With this step, Tesla isn’t just showing trucks differently—it’s proving it’s serious about making FSD work everywhere, one culturally accurate pixel at a time.
Tesla has quietly rolled out one of its most practical software updates yet — and it could add real dollars to every used Model 3, Y, S, and X on the road.
Starting with the latest Tesla app version, owners now receive an official “Certification of Repaired HV Battery” whenever Tesla performs a major high-voltage battery repair or full replacement. The digital certificate appears directly in the vehicle’s Service History tab inside the Tesla app.
It’s permanent, verifiable, and downloadable as a PDF, so sellers can hand it over to buyers in seconds.
For years, the used EV market has suffered from one glaring problem: nobody could prove what happened to the battery.
Service invoices often vanish when a car changes hands. Third-party battery-health scans are expensive and inconsistent. Buyers, staring at a car with 80,000 miles and an 8-year warranty ticking down, would negotiate hard — or walk away entirely — because the battery is the single most expensive part of any Tesla.
That uncertainty routinely shaved thousands off resale values and slowed the entire secondhand market.
Now Tesla has eliminated the guesswork. The new certificate, which was spotted by Tesla App Updates, logs exactly what work was done, when, and by whom. It lives inside the car’s digital profile forever, exactly where any future owner will look. No more digging through old emails or hoping the previous owner kept paperwork.
— Tesla App Updates (iOS) (@Tesla_App_iOS) May 5, 2026
The outlet describes why the update is so important:
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Official Digital Certificates: The string “Certification of Repaired HV Battery” confirms that if your vehicle undergoes a major battery repair or replacement, Tesla will now issue an official, verifiable digital certificate documenting the work.
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Service History Integration: Strings such as viewRepairedBatteryCert and repairedBatteryCertId indicate that this document won’t be lost in an old email thread. It will be permanently anchored to your vehicle’s profile inside the app’s Service History tab.
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Easy Exporting: The service_history_repaired_battery_cert_download_fail error state indicates you will be able to download this certificate directly to your phone as a file (likely a PDF) to share with others.
Sellers who have already replaced packs under warranty are especially excited; they can now prove the vehicle received a fresh Tesla battery without any gray-area questions.
The timing couldn’t be better. As more Teslas roll off 8-year/100,000- or 120,000-mile battery warranties, the used market is exploding. Lenders, insurers, and even auction houses have quietly asked for better battery documentation for years. Tesla’s certificate hands it to them on a silver platter.
For current owners, the feature adds peace of mind and protects long-term value. For buyers, it removes the single biggest risk in any used EV purchase. And for Tesla itself, it quietly strengthens the entire ownership ecosystem — making vehicles more liquid, more desirable, and more valuable over time.
In an industry obsessed with range numbers and 0-60 times, Tesla just proved that sometimes the biggest innovation is a simple line in the Service History tab. One small certificate, one giant step for used-EV confidence.
Tesla gets a massive order for the Semi: 370 units and $100M
Tesla begins factoring international designs in Full Self-Driving visualization
