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LIVE Blog: Tesla AI Day

(Credit: Tesla)

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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.

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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.

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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.

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(Credit: Tesla)

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.

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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.

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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.

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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.

(Credit: Tesla)

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.

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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!

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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.

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Tesla Board Member Hiro Mizuno sums it up in this tweet pretty well.

Simon 17:05 PT – I guess AI Day is starting on “Elon Time?” We’re on to the next track of chill music.

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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.

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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. 

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Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla seeks approval to test FSD Supervised in new Swedish city

Tesla has applied to conduct local Full Self-Driving (Supervised) testing in the city of Jönköping, Sweden.

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Credit: Grok Imagine

Tesla has applied to conduct local Full Self-Driving (Supervised) testing in the city of Jönköping, Sweden.

As per local outlet Jönköpings-Posten, Tesla has contacted the municipality with a request to begin FSD (Supervised) tests in the city. The company has already received approval to test its Full Self-Driving (Supervised) software in several Swedish municipalities, as well as on the national road network.

Sofia Bennerstål, Tesla’s Head of Public Policy for Northern Europe, confirmed that an application has been submitted for FSD’s potential tests in Jönköping.

“I can confirm that we have submitted an application, but I cannot say much more about it,” Bennerstål told the news outlet. She also stated that Tesla is “satisfied with the tests” in the region so far.

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The planned tests in Jönköping would involve a limited number of Tesla-owned vehicles. Trained Tesla safety drivers would remain behind the wheel and be prepared to intervene if necessary.

Tesla previously began testing in Nacka municipality after receiving local approval. At the time, the company stated that cooperation between authorities, municipalities, and industry enables technological progress and helps integrate future transport systems into real-world traffic conditions, as noted in an Allt Om Elbil report.

If approved, Jönköping would become the latest Swedish municipality to allow local Full Self-Driving (Supervised) testing.

Tesla’s Swedish testing program is part of the company’s efforts to validate its supervised autonomous driving software in everyday traffic environments. Municipal approvals allow Tesla to gather data in urban settings that include roundabouts, complex intersections, and mixed traffic conditions.

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Sweden has become an increasingly active testing ground for Tesla’s driver-assistance software in Europe, with regulatory coordination between local authorities and national agencies enabling structured pilot programs.

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Microsoft partners with Starlink to expand rural internet access worldwide

The update was shared ahead of Mobile World Congress.

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Credit: Starlink/X

Microsoft has announced a new collaboration with Starlink as part of its expanding digital access strategy, following the company’s claim that it has extended internet connectivity coverage to more than 299 million people worldwide.

The update was shared ahead of Mobile World Congress, where Microsoft detailed how it surpassed its original goal of bringing internet access to 250 million people by the end of 2025.

In a blog post, Microsoft confirmed that it is now working with Starlink to expand connectivity in rural and hard-to-reach regions.

“Through our collaboration with Starlink, Microsoft is combining low-Earth orbit satellite connectivity with community-based deployment models and local ecosystem partnerships,” the company wrote.

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The partnership is designed to complement Microsoft’s existing work with local internet providers and infrastructure companies across Africa, Latin America, and India, among other areas. Microsoft noted that traditional infrastructure alone cannot meet demand in some regions, making low-Earth orbit satellite connectivity an important addition.

Kenya was cited as an early example. Working with Starlink and local provider Mawingu Networks, Microsoft is supporting connectivity for 450 community hubs in rural and underserved areas. These hubs include farmer cooperatives, aggregation centers, and digital access facilities intended to support agricultural productivity and AI-enabled services.

Microsoft stated that 2.2 billion people globally remain offline, and that connectivity gaps risk widening as AI adoption accelerates.

Starlink’s expanding constellation, now numbering more than 9,700 satellites in orbit, provides near-global coverage, making it one of the few systems capable of delivering broadband to remote regions without relying on terrestrial infrastructure. 

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Starlink is expected to grow even more in the coming years as well, especially as SpaceX transitions its fleet to Starship, which is capable of carrying significantly larger payloads compared to its current workhorse, the Falcon 9.

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Tesla expands US LFP battery supply with LG Energy Solution deal: report

The report was initially published by TheElec, citing industry sources.

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Credit: Tesla

LG Energy Solution (LGES) will manufacture lithium iron phosphate (LFP) energy storage system (ESS) batteries for Tesla at its Lansing, Michigan facility. 

The report was initially published by TheElec, citing industry sources.

LG Energy Solution’s Lansing plant, formerly known as Ultium Cells 3, was previously operated as a joint venture with General Motors. LGES acquired GM’s stake in May 2025 and now fully owns the site. With a production capacity of 50 GWh per year, it is one of the company’s largest facilities in North America.

LG Energy Solution is converting part of the Lansing factory to produce LFP batteries for energy storage systems. Equipment orders for the new lines have already been placed, and mass production is reportedly expected to begin in the second half of next year.

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Last July, LG Energy Solution disclosed a 5.94 trillion won battery supply agreement running from August 2027 to July 2030. While the company did not name the customer, industry sources pointed to Tesla as the buyer.

Tesla has primarily used CATL’s prismatic batteries for its Megapack systems. The move to source prismatic LFP cells from LG Energy Solution’s U.S. plant could then be seen as part of Tesla’s efforts to bolster its North American supply base for its energy storage business.

For the Lansing conversion, LG Energy Solution reportedly plans to use electrode equipment originally ordered under its Ultium Cells venture with General Motors. Suppliers reportedly include CIS and Hirano Tecseed for electrode systems, TSI for mixing equipment, CK Solution for heat exhaust systems, A-Pro for formation equipment, and Shinjin Mtech for assembly kits.

Tesla currently manufactures energy storage products at facilities in California and Shanghai, though another Megafactory that produces the Megapack is also expected to be built in Texas. As per recent reports, the Texas Megafactory recently advanced with a major property sale.

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