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.
In a notable intersection of Big Tech powerhouses, Meta, led by Mark Zuckerberg, has partnered with Canadian energy infrastructure giant Enbridge on a significant renewable energy initiative that will rely on battery technology from Elon Musk’s Tesla.
The project, which was announced this week, marks another step in Meta’s aggressive push to power its expanding data center operations with clean energy, dispelling many of the complaints people have about them.
This new development is located near Cheyenne, Wyoming, and will feature a 365-megawatt (MW) solar farm paired with a 200 MW/1,600 megawatt-hour (MWh) battery energy storage system, also known as BESS. Tesla is providing the batteries for the project, valued at roughly $200 million.
The story was originally reported by Utility Dive.
This Wyoming project represents the first phase of Enbridge and Meta’s joint “Cowboy Project.” Once operational, it will deliver power to Meta’s regional data centers through Cheyenne Light, Fuel, and Power under Wyoming’s Large Power Contract Service tariff.
This tariff, originally developed in collaboration with Microsoft and Black Hills Energy, is designed specifically for large loads like data centers. It ensures that the renewable supply serves hyperscale customers without impacting retail electricity rates for other users.
The battery system will operate under a long-term tolling agreement, providing dispatchable capacity that enhances grid reliability. During periods of high demand, the utility can access the backup generation, addressing one of the key challenges of integrating large-scale renewables with the explosive growth of data center electricity demand driven by artificial intelligence.
This latest collaboration builds on prior joint efforts between Enbridge and Meta in Texas, including the 600 MW Clear Fork Solar, 152 MW Easter Wind, and 300 MW Cone Wind projects. Together with the Wyoming initiative, the companies have now partnered on roughly 1.6 gigawatts (GW) of combined solar, wind, and storage capacity.
The deal highlights the intensifying demand for reliable, low-carbon power from technology giants. Meta has committed to supporting its data center growth with renewable energy, joining peers like Microsoft and Google in seeking large-scale solutions. Enbridge’s Allen Capps described the project as “one of the larger utility-scale battery installations supporting U.S. data center operations and growth.”
The involvement of Tesla’s battery technology adds an intriguing layer, linking two of the world’s most prominent tech leaders—Zuckerberg and Musk—in the clean energy transition.
As data centers continue to drive unprecedented electricity load growth across the United States, projects like this one illustrate how hyperscalers are turning to strategic partnerships with traditional energy players and innovative storage solutions to meet both sustainability goals and reliability needs.
SpaceX has decided to stand down from what was supposed to be the first test launch of Starship’s v3 rocket tonight after a minor issue with a hydraulic pin delayed the flight once more.
The company scrubbed its first test flight of the upgraded Starship v3 on May 21 in the final minutes of the countdown. SpaceX CEO Elon Musk quickly took to social media platform X, explaining that a hydraulic pin on the launch tower’s “chopsticks” arm failed to retract properly.
Musk added that the company would fix the issue this evening. SpaceX will attempt another launch tomorrow night at 5:30 p.m. CT, 6:30 p.m. ET, and 3:30 p.m. PT.
The hydraulic pin holding the tower arm in place did not retract.
If that can be fixed tonight, there will be another launch attempt tomorrow at 5:30 CT. https://t.co/DJAdvDYQpH
— Elon Musk (@elonmusk) May 21, 2026
The countdown for Starship Flight 12 — featuring the taller and more capable V3 stack with Booster 19 and Ship 39 — had been progressing smoothly until the late-stage issue surfaced. The Mechazilla tower arm, designed to secure the vehicle on the pad and eventually catch returning boosters, could not complete its retraction sequence.
SpaceX teams immediately began troubleshooting the hydraulic system for an overnight repair.
Starship V3 introduces several significant upgrades over earlier versions. These include greater propellant capacity, more powerful Raptor 3 engines, larger grid fins, enhanced heat shielding, and an improved fuel transfer system.
We covered the changes that were announced just days ago by SpaceX:
SpaceX unveils sweeping Starship V3 upgrades ahead of May 19 launch
The changes are intended to increase payload performance, support higher flight rates, and advance the vehicle toward operational missions, including Starlink deployments, NASA Artemis lunar landings, and future crewed Mars flights. The debut flight from Starbase’s new Launch Pad 2 marked an important milestone in scaling up the fully reusable Starship system.
This stand-down highlights the intricate challenges of preparing the world’s most powerful rocket for flight. Despite extensive pre-launch checks, a single component in the ground support equipment can force a scrub.
The incident aligns with Starship’s proven iterative development approach. Previous test flights have encountered both successes and setbacks, each providing critical data that refines hardware and procedures. Some outlets may call some of these flights “failures,” when in reality, they are all opportunities for SpaceX to learn for the next attempt.
With V3, SpaceX aims to reduce ground-system dependencies and increase launch cadence to meet ambitious long-term goals.
The Tesla Model Y became the first-ever car to reach a legendary Norwegian milestone, surpassing 100,000 new registrations after gaining a reputation as one of the most popular vehicles in the country and the world.
As of May 20, Norwegian authorities have registered 100,224 units of the electric SUV, according to data from local outlet Opplysningsrådet for veitrafikken (OFV).
By population, roughly one in every 29 passenger cars on Norwegian roads is now a Model Y, underscoring its rapid rise as a national favorite.
Since the first deliveries in August 2021, the Model Y has transformed from a newcomer to a staple in Norwegian traffic.
Tesla back on top as Norway’s EV market surges to 98% share in February
Geir Inge Stokke, the Managing Director of OFV, described the achievement as “remarkable,” noting that few single models have gained such traction so quickly. “Tesla Model Y has hit the Norwegian market spot on, and the numbers illustrate how fast the EV market has developed here,” Stokke said.
The Model Y’s success reflects Norway’s aggressive push toward electrification. Nearly nine out of ten units, 87.6 percent, to be exact, are privately registered, with the remaining 12.4 percent on company plates. Owners span the country, from major cities to smaller municipalities, proving it is no longer just an urban or niche vehicle but a true “people’s car.
Who is Buying Tesla Model Ys in Norway?
Typical Model Y drivers are men in their early 40s. The average registered user age is 44, with 83 percent male and 17 percent female. Stokke noted that household usage often extends beyond the primary registrant, broadening the vehicle’s real-world appeal.
Geographically, adoption concentrates in urban centers with strong charging infrastructure. Oslo leads with 16,861 registrations (16.82 percent of the national total), followed by Bergen (7,450), Bærum (4,313), and Trondheim (4,240).
The top five municipalities—Oslo, Bergen, Bærum, Trondheim, and Asker—account for 35,463 units, or about 35 percent of all Model Ys. Yet the vehicle’s presence outside big cities highlights its broad acceptance.
Growth Trajectory and Popularity
Tesla built a lot of sales momentum in a short amount of time. In 2021, registrations closed out at 8,267, but more than doubled to more than 17,000 units in 2022 and more than 23,000 units in 2023. 2025 was the company’s strongest year yet, as Tesla managed to record 27,621 registrations.
Through 2026, Tesla already has 7,036 registrations.
Tesla’s Global Success with the Model Y
Tesla has tasted so much success with the Model Y; it has been the best-selling car in the world three times, it has dominated EV sales in numerous countries, and contributed to a mass adoption of electric vehicles across the planet.
As Stokke emphasized, the Model Y’s journey from newcomer to icon mirrors Norway’s broader success story. With robust incentives that push sales, excellent infrastructure, and consumer eagerness to transition to sustainable powertrains, the country continues setting global benchmarks in sustainable mobility.
The Tesla Model Y stands as a shining example of how quickly change can happen when conditions align.
Elon Musk called it Epic: The full story of SpaceX’s Starship Flight 12
Zuckerberg’s Meta taps Musk’s Tesla for massive clean energy project
