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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 expands Robotaxi in a way that was long anticipated

Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.

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Credit: Grok Imagine

Tesla has expanded Robotaxi in a way that was long anticipated, and it does not have to do with a new, larger geofence in a city where it already offered its partially autonomous ride-hailing suite, or a new city altogether.

Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.

Tesla has taken a major step forward in its autonomous ride-hailing ambitions with the official launch of the Tesla Robotaxi app for Android users. Released on the Google Play Store on April 24. Titled simply “Tesla Robotaxi,” the app is now available to download directly from Tesla.

This rollout fulfills a long-anticipated expansion that opens the service to hundreds of millions of Android smartphone users who were previously unable to access it on iOS alone.

The app delivers a streamlined, driverless ride experience powered by Tesla’s automated driving technology.

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Users sign in with a Tesla Account, view the current service area map within the app, enter a destination, and receive an estimated fare and arrival time before confirming the ride. When a Model Y from the Robotaxi fleet arrives, riders confirm the license plate, enter the vehicle, fasten their seatbelt, and tap “Start Ride” on either the app or the vehicle’s touchscreen.

During the trip, passengers have access to all the same controls that iOS users do, and can adjust climate settings, seat positions, and music while tracking progress on an in-app map. The interface also allows drop-off changes or support requests if needed. After the ride, users exit, close the doors, and submit feedback.

This Android availability directly broadens the rider base for Robotaxi in its initial service areas. Unfortunately, Android users are used to being subject to delayed launches of new features available to Tesla owners.

By removing the iOS-only barrier, Tesla instantly expands the addressable market, enabling far more people to summon and use the autonomous vehicles already operating on public roads.

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The move is a foundational requirement for scaling ride volume and gathering the real-world data needed to refine the unsupervised Full Self-Driving system that powers every trip.

For the Robotaxi program itself, the launch signals steady operational progress. It prepares the service for higher utilization rates as the fleet grows and supports the transition from limited early deployments to a more robust network.

Tesla expands Unsupervised Robotaxi service to two new cities

Tesla has indicated that users outside current service areas can sign up at the company’s website for future notifications, pointing to a deliberate, phased geographic rollout.

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Looking ahead, the company plans to incorporate Cybercab vehicles to increase fleet capacity and efficiency while continuing to expand service territories. With the Android app now live, Tesla has removed a key adoption hurdle and positioned Robotaxi for the next phase of growth in autonomous urban transportation.

The infrastructure is now in place to support significantly larger rider demand as production and deployment accelerate.

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UPDATE: SpaceX’s Falcon Heavy that launched a Tesla into space is back on a mission

SpaceX Falcon Heavy returns after 18 months away to deliver a satellite that only it could carry.

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UPDATE: 10:29 a.m. et: SpaceX is standing down from today’s Falcon Heavy launch of the ViaSat-3 F3 mission due to unfavorable weather. A new target date will be shared once confirmed.

After an 18-month absence, SpaceX’s Falcon Heavy is returning to mission on Monday morning when it’s scheduled to lift off from Launch Complex 39A at Kennedy Space Center at 10:21 a.m. EDT.

The mission is called ViaSat-3 F3, and the heavy satellite payload needs to reach geostationary orbit, sitting 22,236 miles above Earth where its speed matches the planet’s rotation. Getting a satellite that heavy to that altitude demands more thrust than a single-core Falcon 9 can deliver.

This marks the Falcon Heavy’s 12th flight overall since its debut in February 2018, and its first since NASA’s Europa Clipper mission in October 2024.

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Arguably, the most exciting element for spectators will be watching the booster recoveries in action when the two side boosters, B1072 and B1075, will attempt simultaneous landings at Landing Zone 2 and the newer Landing Zone 40 at Cape Canaveral Space Force Station, while the center core will be expended over the ocean.

SpaceX wins its first MARS contract but it comes with a catch

Following satellite deployment, expected roughly five hours after launch, ViaSat-3 F3 will spend several months traveling to its final orbital slot before undergoing in-orbit testing, with service entry expected by late summer 2026

As Teslarati reported, NASA awarded SpaceX a $175.7 million contract on April 16, 2026, to launch the ESA Rosalind Franklin Mars rover aboard a Falcon Heavy no earlier than late 2028, which would mark the first time SpaceX has ever sent a payload to Mars. That contract came on top of an already deep pipeline that includes the Roman Space Telescope, the Dragonfly Saturn mission, and multiple national security payloads.

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SpaceX executed 165 missions in 2025 and now accounts for approximately 85% of all global orbital launches. With Starlink surpassing 10 million subscribers and an IPO targeting a $1.75 trillion valuation still ahead, Monday’s launch is one more data point in a company that has quietly become the backbone of both commercial and government space access worldwide.

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Tesla launches solution to end Supercharger fights once and for all

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Credit: Tesla

Tesla is launching its solution to end Supercharger fights once and for all, eliminating any confusion on who is to charge next at a congested location.

Last year, a notable incident at a Tesla Supercharger led to a fight, and it all stemmed from a disagreement over who arrived at the location first.

Congestion at Tesla Superchargers is a pretty infrequent occurrence for most of us, but there are more congested and popular areas where wait times can be extensive. An unfortunate growing pain of EV ownership is the plain fact that chargers are not as available as gas pumps, and there are, at times, lines to charge.

This can cause tensions to flare and people to get entitled when visiting Superchargers. Nobody wants to spend hours at a Supercharger, but now, there will be no more confusion when there is a queue, and that’s thanks to Tesla’s new Virtual Queue for Superchargers.

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Tesla is finally starting to build out the Virtual Supercharger Queue, according to Not a Tesla App, but it still relies on drivers to make it work.

When a driver is near a Supercharger that is full, a message will pop up on the Tesla App, using the driver’s location to determine their eligibility to join the virtual queue.

The app states:

“While the app is closed, Tesla uses your location to notify you of accurate wait times at Superchargers when you arrive.”

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Another message within the app states:

“There is a waitlist to charge. Are you sure you want to start a charging session now?”

This sounds as if it will require drivers to act appropriately and only plug in when the app prompts them to do so, by letting them know it is their turn.

The app will notify the driver of their position in the queue, as well as how many vehicles are ahead of them.

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Tesla launches first ‘true’ East Coast V4 Supercharger: here’s what that means

The company announced a while back that it would be working on a solution for this issue. Personally, I’ve only had to wait at a Supercharger for a charge on one occasion, and there was a line of between 3 and 10 cars during this singular occurrence.

There were no conflicts or arguments about who had arrived first, but there was some discussion between several drivers during my time there about who was to charge first. Throw a non-Tesla EV into the mix, one that can only charge at a pull-in spot, and that causes even more of a complication.

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