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.
News
Tesla VP explains latest updates in trade secret theft case
Tesla reportedly caught Matthews copying the tech into machines that were sold to competitors, claiming they lied about doing so for three years, and continued to ship it. That is when Tesla chose to sue Matthews in July 2024 in Federal court, demanding over $1 billion in damages due to trade secret theft.
Tesla Vice President Bonne Eggleston explained the latest updates in a trade secret theft case the company has against a former manufacturing equipment supplier, Matthews International.
Back in 2024, Tesla had filed a lawsuit against Matthews International, alleging that the firm stole trade secrets about battery manufacturing and shared those details with some of Tesla’s competitors.
Early last year, a U.S. District Court Judge denied Tesla’s request to block Matthews International from selling its dry battery electrode (DBE) technology across the world. The judge, Edward Davila, said that the patent for the tech was due to Matthews’ “extensive research and development.”
The two companies’ relationship began back in 2019, as Tesla hired Matthews to help build the equipment for its 4680 battery cell. Tesla shared confidential software, designs, and know-how under strict secrecy rules.
Fast forward a few years, and Tesla reportedly caught Matthews copying the tech into machines that were sold to competitors, claiming they lied about doing so for three years, and continued to ship it. That is when Tesla chose to sue Matthews in July 2024 in Federal court, demanding over $1 billion in damages due to trade secret theft.
Now, the latest twist, as this month, a Judge issued a permanent injunction—a court order banning Matthews from using certain stolen Tesla parts or designs in their machines. Matthews is also officially “liable” for damages. The exact amount would still to be calculated later.
Bonne Eggleston, a VP for Tesla, said on X today that Matthews is a supplier who “exploited customer IP through theft or deception,” and has no place in Tesla’s ecosystem:
Buyer beware: Matthews International stole Tesla’s DBE technology and is now subject to an injunction and liable for damages.
During our work with Matthews, we caught them red-handed copying our technology—including proprietary software and sensitive mechanical designs—into… https://t.co/Toc8ilakeM
— Bonne Eggleston (@BonneEggleston) March 10, 2026
Tesla calls this a big win and warns other companies: “Buyer beware—don’t buy from thieves.”
Matthews hit back with a press release claiming victory. They say an arbitrator ruled they can keep selling their own DBE equipment to anyone and rejected Tesla’s request for a total sales ban. They call Tesla’s claims “nonsense” and insist their 20-year-old tech is independent. Both sides are spinning the same narrow ruling: Matthews can sell their version, but they’re blocked from using Tesla’s specific secrets.
What are Tesla’s Current Legal Options
The case isn’t over—it’s moving to the damages phase. Tesla can:
- Push forward in court or arbitration to calculate and collect huge financial penalties (potentially $1 billion+ if willful theft is proven).
- Enforce the permanent injunction with contempt charges, fines, or even jail time if Matthews violates it.
- Challenge Matthews’ new patents that allegedly copy Tesla’s work, asking courts to invalidate them or add Tesla as co-inventor.
- Seek extra damages, lawyer fees, and possibly punitive awards under the federal Defend Trade Secrets Act and California law.
Tesla could also refer evidence to federal prosecutors for possible criminal trade-secret charges (rare but serious). Settlement is always possible, but Tesla’s fiery public response suggests they want full accountability.
This isn’t just corporate drama. It shows why trade secrets matter even when Tesla open-sources some patents, confidential know-how shared in trust must stay protected. For the EV industry, it’s a reminder: steal from your biggest customer, and you risk losing everything.
News
Tesla Cybercab includes this small but significant feature
The Cybercab is Tesla’s big plan to introduce fully autonomous ride-sharing in a seamless fashion. In fact, the Full Self-Driving suite was geared toward alleviating the need to manually drive vehicles.
Tesla Cybercab manufacturing is strikingly close, as the company is still aiming for an April start date. But small and significant features are still being identified for the first time as production units appear all over the country for testing and for regulatory events, like one yesterday in Washington, D.C.
The Cybercab is Tesla’s big plan to introduce fully autonomous ride-sharing in a seamless fashion. In fact, the Full Self-Driving suite was geared toward alleviating the need to manually drive vehicles.
This was for everyone, including the disabled, who are widely reliant on ride-sharing platforms, family members, and medical shuttles for transportation of any kind. Cybercab aims to change that, and Tesla evidently put a focus on those riders while developing the vehicle, evident in a small but significant feature revealed during its appearance in the Nation’s Capital.
Tesla Cybercab display highlights interior wizardry in the small two-seater
Tesla has implemented Braille within the Cybercab to make it easier for blind passengers to utilize the vehicle. On both the ‘Stop/Hazard Lights’ button and the Door Releases, Tesla has placed Braille so that blind passengers can navigate their way through the vehicle:
The hazard lights button will be used as an emergency stop. Smart pic.twitter.com/vkYBioqmKm
— Whole Mars Catalog (@wholemars) March 10, 2026
We have braille on the interior door releases as well
— Eric (@EricETesla) March 11, 2026
This is a great addition to the Cybercab, especially as Full Self-Driving has been partially pointed at as a solution for those with disabilities that would keep them from driving themselves from place to place.
It truly is a great addition and just another way that Tesla is showing they are making this massive product inclusive for everyone out there, including those who have not been able to drive due to not having vision.
The Cybercab is set to enter mass production sometime in April, and it will be responsible for launching Tesla’s massive plans for an autonomous ride-sharing program.
Elon Musk
Tesla and xAI team up on massive new project
It is the latest move by a Musk company to automate, streamline, and reduce the manual, monotonous, and tedious work currently performed by humans through AI and robotics development. Digital Optimus will be capable of processing and actioning the past five seconds of a real-time computer screen video and keyboard and mouse actions.
Elon Musk teased a massive new project, to be developed jointly by Tesla and xAI, called “Digital Optimus” or “Macrohard,” the first development under Tesla’s investment agreement with xAI.
Musk announced on X that Digital Optimus will “be capable of emulating the function of entire companies.”
Macrohard or Digital Optimus is a joint xAI-Tesla project, coming as part of Tesla’s investment agreement with xAI.
Grok is the master conductor/navigator with deep understanding of the world to direct digital Optimus, which is processing and actioning the past 5 secs of…
— Elon Musk (@elonmusk) March 11, 2026
It is the latest move by a Musk company to automate, streamline, and reduce the manual, monotonous, and tedious work currently performed by humans through AI and robotics development. Digital Optimus will be capable of processing and actioning the past five seconds of a real-time computer screen video and keyboard and mouse actions.
Essentially, it will be an AI version of a desk worker in many capacities, including accounting, HR tasks, and others.
Musk said:
“Grok is the master conductor/navigator with deep understanding of the world to direct digital Optimus, which is processing and actioning the past 5 secs of real-time computer screen video and keyboard/mouse actions. Grok is like a much more advanced and sophisticated version of turn-by-turn navigation software. You can think of it as Digital Optimus AI being System 1 (instinctive part of the mind) and Grok being System 2. (thinking part of the mind).”
Its key applications would be used for enterprise automation, simulating entire companies, high-volume repetitive tasks, and potentially, future hybrid use with the Optimus robot, which would handle physical tasks, while Digital Optimus would handle the clerical work.
The creation of a digital AI suite like Digital Optimus would help companies save time and money, as well as become more efficient in their operations through massive scalability. However, there will undoubtedly be concerns from people who are skeptical of a fully-integrated AI workhorse like this one.
From an energy consumption perspective and just a general concern for the human workforce, these types of AI projects are polarizing in nature.
However, Digital Optimus would be a great digital counterpart to Tesla’s physical Optimus robot, as it would be a hyper-efficient addition to any company that is looking for more production for less cost.
Musk maintains that there is no other company on Earth that will be able to do this.
Tesla VP explains latest updates in trade secret theft case
Tesla Cybercab includes this small but significant feature
