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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 Semi hauls fresh Cybercab batch as Robotaxi era takes hold

A Tesla Semi was filmed hauling Cybercab units out of Giga Texas for the first time.

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A Tesla Semi loaded with Cybercab units was recently filmed leaving Gigafactory Texas, marking what appears to be the first documented delivery run of Tesla’s autonomous two-seater. The footage shows multiple Cybercabs secured on a flatbed trailer being hauled by a production Tesla Semi, a truck rated for a gross combination weight of 82,000 lbs. The location is consistent with Giga Texas in Austin, where Cybercab production has been ramping since February 2026.

The sighting follows a wave of Cybercab activity at the Austin facility. In late April, drone operator Joe Tegtmeyer spotted approximately 60 Cybercabs parked in two organized groups in the factory’s outbound lot, the largest concentration observed to date. Units being staged in an outbound lot is a standard pre-delivery step, and the Semi footage is the logical next frame in that sequence.


This is not the first time Tesla has used its own Semi to move Tesla products. When the Semi was unveiled in 2017, Musk noted it would be used for Tesla’s own operations, and over the years Semi prototypes were spotted carrying cargo ranging from concrete weights to Tesla vehicles being delivered to consumers. In 2023, a Semi was photographed transporting a Cybertruck on a trailer ahead of that vehicle’s delivery launch.

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The Cybercab itself was first revealed publicly at Tesla’s “We, Robot” event on October 10, 2024, at Warner Bros. Studios in Burbank, where 20 pre-production units gave attendees rides around the studio lot. Musk stated at the event that Tesla intends to produce the Cybercab before 2027. The first production unit rolled off the Giga Texas line on February 17, 2026, with Musk posting on X: “Congratulations to the Tesla team on making the first production Cybercab.”

Tesla’s annual production goal is 2 million Cybercabs per year once multiple factories reach full design capacity, with the company targeting a price under $30,000 per unit. Tesla has confirmed plans to expand its robotaxi service to seven cities in the first half of 2026, including Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas, building on the unsupervised service already running in Austin. Musk has said he expects robotaxis to cover between a quarter and half of the United States by end of year.

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Cybertruck

Tesla Cybertruck too safe for even Musk’s biggest critics to ignore

Krassenstein’s decision reveals that superior safety isn’t a partisan issue. For parents prioritizing family protection over personal or political grudges, the Cybertruck has become too safe to ignore.

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Credit: Tesla

The Tesla Cybertruck is an extremely polarizing vehicle because of its potential symbolism as a political stance instead of just a pickup truck — or at least that is what many would want you to believe.

Of course, the Cybertruck is an icon of Tesla culture, and it is one of those things that never has a middle ground: you love it, or you don’t.

But maybe there is an establishment of that “grey area” happening.

In a striking illustration of engineering triumph over political tribalism, prominent Elon Musk critic Brian Krassenstein has purchased a Tesla Cybertruck, openly citing its exceptional safety as the deciding factor for his family.

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The announcement on X triggered predictable backlash, yet it underscores a growing reality: the Cybertruck’s safety credentials are proving impossible for even Musk’s fiercest detractors to dismiss.

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Krassenstein, who has repeatedly clashed with Musk over issues ranging from content moderation and “wokeness” to public health figures, made no attempt to hide his reservations. In his May 6 post, he acknowledged the coming criticism: “I might get hate for this too but I bought a Cybertruck.”

He stressed that the decision had “nothing to do with Elon or politics,” pointing instead to practical advantages—his existing Tesla charger, eligibility for Full Self-Driving upgrades, a returning-owner discount, and crucially, the vehicle’s strong safety profile.

With gasoline prices hovering near $5 a gallon in some areas, he also highlighted the environmental benefit of switching from a polluting combustion engine.

The numbers, data, and awards validate Krassenstein’s choice.

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The 2025 Cybertruck earned the Insurance Institute for Highway Safety’s (IIHS) elite Top Safety Pick+ award—the only pickup truck to achieve this highest rating. It delivered “Good” scores across every crashworthiness category, including the challenging updated moderate overlap front crash test, while excelling in crash avoidance and mitigation systems.

The National Highway Traffic Safety Administration (NHTSA) awarded it a perfect 5-star overall rating, with top marks in frontal, side, and rollover categories. No other pickup truck holds both distinctions simultaneously.

Tesla Cybertruck crash test rating situation revealed by NHTSA, IIHS

Beyond lab results, the Cybertruck’s stainless-steel exoskeleton and ultra-rigid structure have demonstrated remarkable real-world resilience. Owners have reported surviving high-speed collisions with minimal cabin intrusion.

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In one widely discussed incident, a Cybertruck endured a 70 mph sideswipe on the interstate; the driver reported barely feeling the impact while the other vehicle was heavily damaged.

Tesla’s crash demonstrations and independent analyses consistently show how the vehicle’s design prioritizes occupant protection through a fortified passenger cell rather than traditional crumple zones, giving families superior safeguarding in many common crash scenarios.

The online pile-on following Krassenstein’s post focused on aesthetics, politics, and perceived hypocrisy rather than the data. Critics called the angular truck “ugly” or accused him of selling out.

Yet his purchase highlights an inconvenient truth for polarized discourse: when objective safety metrics—IIHS awards, NHTSA ratings, and documented crash performance—point decisively toward one vehicle, even Musk’s biggest critics are forced to confront its merits.

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Krassenstein’s decision reveals that superior safety isn’t a partisan issue. For parents prioritizing family protection over personal or political grudges, the Cybertruck has become too safe to ignore.

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SpaceXAI signs agreement with Anthropic for massive AI supercomputer access

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Credit: SpaceX

SpaceXAI announced today that it had signed an agreement with Anthropic to give the company access to its Colossus 1 data center in Memphis, Tennessee.

It is a monumental deal as Anthropic will gain access to all of the compute at the plant, delivering more than 300 megawatts of power and over 220,000 NVIDIA GPUs within the month.

Anthropic’s Claude AI account on X announced the partnership:

We’ve agreed to a partnership with SpaceX that will substantially increase our compute capacity. This, along with our other recent compute deals, means that we’ve been able to increase our usage limits for Claude Code and the Claude API.”

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The company is also:

  • Doubling Claude Code’s 5-hour rate limits for Pro, Max, and Team plans;
  • Removing the peak hours limit reduction on Claude Code for Pro and Max plans; and
  • Substantially raising its API rate limits for Opus models.

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SpaceX also published its own release on the new agreement, noting that it is “the only organization with the launch cadence, mass-to-orbit economics, and constellation operations experience to make orbital compute a near-term engineering program rather than a research concept.”

CEO Elon Musk also commented on the partnership and shed light on intense meetings he had with senior members of Anthropic last week, stating, “nobody set on my evil detector.”

This has turned the argument that SpaceX is as much an AI company as a space exploration company into a very valid argument:

SpaceX is following in Tesla’s footsteps in a way nobody expected

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Nevertheless, this is an incredibly valuable and important move in the grand scheme of things. AI scaling is fundamentally bottlenecked by compute, and demand for Claude has surged, bringing terrestrial power grids, land, and cooling operations hitting limits everywhere.

Anthropic has been aggressively signing multiple large-scale deals to be competitive in the space, including:

  • Up to 5GW with Amazon
  • 5GW with Google and Broadcom
  • Strategic $30b Azure deal with Microsoft/NVIDIA
  • $50b U.S. infrastructure investment with Fluidstack

Access to Colossus 1 gives Anthropic immediate relief on NVIDIA GPU capacity. For SpaceXAI, it turns its rapid buildout into revenue. It also showcases its ability to deliver at world-leading speed and scale.

Most importantly, it plants the seed that its much larger vision, orbital AI compute, is totally viable.

Starlink V3 satellites could enable SpaceX’s orbital computing plans: Musk

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Within the month, Anthropic will begin using 100 percent of Colossus 1’s compute, directly expanding capacity for Claude Pro and Max subscribers and the API. This means fewer limits, faster responses, and support for heavier workloads.

In the long term, meaning 2026 and beyond, there will be a continued rollout of other multi-GW deals Anthropic has signed, and an early exploration of orbital compute with SpaceXAI.

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