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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.

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.

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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.

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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.

(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.

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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.

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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.

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.

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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.

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.

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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.

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.

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.

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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. 

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’s Robotaxi expansion shape was truly a warning to competitors

Tesla might have made a joke with its first Robotaxi service area expansion, but it was truly a serious warning to its competitors.

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Tesla’s Robotaxi expansion occurred for the first time on Monday, and while the shape of its new service area might be “cocky,” it surely is not a joke. It’s a warning to competitors.

Robotaxi skeptics and Tesla opponents are sitting around throwing hate toward the company’s expansion appearance. Some called it “unserious,” and others say it’s “immature.” The reality is that it has a real meaning that goes much further than the company’s lighthearted and comical attitude toward things.

For context, Tesla has routinely used the number 69 as a way to price things it sells. 420 is another, an ode to cannabis culture. A few years back, it actually priced its Model S flagship sedan at $69,420. The first rides of the Robotaxi fleet were priced at $4.20. They are now being increased to $6.90.

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Some call it childish. Others call it fun. The truth is, nobody is doing it this way.

Tesla updates Robotaxi app with several big changes, including wider service area

But today’s expansion of the Robotaxi service area in Austin is different. Tesla did not expand its shape to different neighborhoods or areas of the City of Austin. It did not expand it by broadening the rectangle that was initially available. Instead, it chose a different strategy, simply because it could:

Tesla could have done anything. It could have expanded in any direction, in any way, but it chose this simply because it has gotten Robotaxi to the point that it can broaden its service area in any direction. It chose this shape because it could.

Other companies might not have the same ability. Of course, many companies probably would not do this even if it could, simply because of the optics. Tesla doesn’t have those concerns; it has been open about its ability to be funny, and yes, immature, at times.

But in reality, it was a stark warning to competitors. “We can go anywhere in Austin, at any time, and we’re confident enough to make a joke about it.”

Tesla’s Robotaxi geofence in Austin grows, and its shape is hard to ignore

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As Tesla is already aiming to expand to new states and high-population areas, and with applications filed in Arizona and California, Robotaxi will be in new regions in the coming weeks or months.

For now, it remains in Austin, and Tesla is sending a message to other companies that it is ready to go in any direction. The driverless Robotaxi fleet, bolstered by billions of miles of data, is ready to roam without anyone at the wheel.

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Tesla Robotaxi has already surpassed Waymo in this key metric

Tesla Robotaxi has already overtaken Waymo in Austin in one key metric, but there’s still more work to do.

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Credit: @HanChulYong/X

Tesla Robotaxi has already surpassed Waymo in one extremely important key metric: size of service area.

Tesla just expanded its service area in Austin on Monday morning, pushing the boundaries of its Robotaxi fleet in an interesting fashion with new capabilities to the north. Yes, we know what it looks like:

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The expansion doubled Tesla Robotaxi’s potential travel locations, which now include the University of Texas at Austin, a school with over 53,000 students.

The doubling of the service area by Tesla has already made its travel area larger than Waymo’s, which launched driverless rides in October 2024. It became available to the public in March 2025.

According to Grok, the AI agent on X, Tesla Robotaxi’s current service area spans 42 square miles, which is five square miles larger than Waymo’s service area of 37 square miles.

The service area is one of the most important metrics in determining how much progress a self-driving ride-hailing service is making. Safety is the priority of any company operating a ride-hailing network, especially ones that are making it a point to use autonomy to deploy it.

However, these companies are essentially racing for a larger piece of the city or cities they are in. Waymo has expanded to several different regions around the United States, including Arizona and Los Angeles.

Tesla is attempting to do the same in the coming months as it has already filed paperwork in both California and Arizona to deploy its Robotaxi fleet in states across the U.S.

As the platform continues to show more prowess and accuracy in its operation, Tesla will begin to expand to new areas, eventually aiming for a global rollout of its self-driving service.

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Tesla Megapacks arrive for massive battery replacing coal plant

Tesla Megapacks have started arriving on-site to the Stanwell Battery Project, just as Queensland prepares to wind down the Stanwell coal plant.

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Credit: Tesla

The first of over 300 Tesla Megapacks have arrived to the site of a massive battery energy storage system (BESS) being built in Australia, dubbed the Stanwell Battery Project after a coal plant it’s set to replace.

In a press release last week, the Stanwell Battery Project announced that the first Tesla Megapack 2XL units had arrived to the site, which is located outside of Rockhampton in Queensland, Australia. The project will eventually feature 324 Megapack units, set to arrive in the coming months, in order to support the 300MW/1,200MWh battery project.

“The Stanwell Battery is part of the diversification of our portfolio, to include cleaner and more flexible energy solutions,” said Angie Zahra, Stanwell Central Generation General Manager. “It is just one part of the 800 MW of battery energy storage capacity we have in our pipeline.

“Capable of discharging 300 MW of energy for up to four hours (1,200 MWh), our mega battery will be one of the largest in Queensland.”

Credit: Stanwell

READ MORE ON TESLA MEGAPACKS: Tesla Lathrop Megafactory celebrates massive Megapack battery milestone

The state is working with government-owned company Yurika to facilitate construction, and the process is expected to create roughly 80 jobs. The project is expected to come fully online in May 2027, with initial commissioning of the Megapacks aiming for November 2025.

The Stanwell Battery is set to replace the nearby Stanwell coal generation plant, which the government is planning to wind down starting in 2026 as part of efforts to reach an 80 percent renewable energy generation ratio by 2035. Meanwhile, the government is also set to begin winding down the Tarong and Callide coal plants, while several other Megapack projects are being built or coming online. o ya

Tesla currently has two Megapack production facilities, located in Lathrop, California, in the U.S. and another that came online earlier this year in Shanghai, China. The Shanghai Megafactory shipped its first units to Australia in March, while both factories are expected to be capable of producing 10,000 Megapack units per year upon reaching volume production.

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xAI receives more Tesla Megapacks for Colossus 2

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