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 makes latest move to remove Model S and Model X from its lineup
Tesla’s latest decisive step toward phasing out its flagship sedan and SUV was quietly removing the Model S and Model X from its U.S. referral program earlier this week.
Tesla has made its latest move that indicates the Model S and Model X are being removed from the company’s lineup, an action that was confirmed by the company earlier this quarter, that the two flagship vehicles would no longer be produced.
Tesla has ultimately started phasing out the Model S and Model X in several ways, as it recently indicated it had sold out of a paint color for the two vehicles.
Now, the company is making even more moves that show its plans for the two vehicles are being eliminated slowly but surely.
Tesla’s latest decisive step toward phasing out its flagship sedan and SUV was quietly removing the Model S and Model X from its U.S. referral program earlier this week.
The change eliminates the $1,000 referral discount previously available to new buyers of these vehicles. Existing Tesla owners purchasing a new Model S or Model X will now only receive a halved loyalty discount of $500, down from $1,000.
The updates extend beyond the two flagship vehicles. New Cybertruck buyers using a referral code on Premium AWD or Cyberbeast configurations will no longer get $1,000 off. Instead, both referrer and buyer receive three months of Full Self-Driving (Supervised).
The loyalty discount for Cybertruck purchases, excluding the new Dual Motor AWD trim level, has also been cut to $500.
NEWS: Tesla has removed the Model S and Model X from the referral program.
New owners also no longer get a $1,000 referral discount on a new Cybertruck Premium AWD or Cyberbeast. Instead, you now get 3 months of FSD (Supervised).
Additionally, Tesla has reduced the loyalty… pic.twitter.com/IgIY8Hi2WJ
— Sawyer Merritt (@SawyerMerritt) March 6, 2026
These adjustments apply only in the United States, and reflect Tesla’s broader strategy to optimize margins while boosting adoption of its autonomous driving software.
The timing is no coincidence. Tesla confirmed earlier this year that Model S and Model X production will end in the second quarter of 2026, roughly June, as the company reallocates factory capacity toward its Optimus humanoid robot and next-generation vehicles.
With annual sales of the low-volume flagships already declining (just 53,900 units in 2025), incentives are no longer needed to drive demand. Production is winding down, and Tesla expects strong remaining interest without subsidies.
Industry observers see this as the clearest sign yet of an “end-of-life” phase for the vehicles that once defined Tesla’s luxury segment. Community reactions on X range from nostalgia, “Rest in power S and X”, to frustration among long-time owners who feel perks are eroding just as the models approach discontinuation.
Some buyers are rushing orders to lock in final discounts before they vanish entirely.
Doug DeMuro names Tesla Model S the Most Important Car of the last 30 years
For Tesla, the move prioritizes efficiency: fewer discounts on outgoing models, a stronger push for FSD subscriptions, and a focus on high-margin Cybertruck trims amid surging orders.
Loyalists still have a narrow window to purchase a refreshed Plaid or Long Range model with remaining incentives, but the message is clear: Tesla’s lineup is evolving, and the era of the original flagships is drawing to a close.
News
Tesla Australia confirms six-seat Model Y L launch in 2026
Compared with the standard five-seat Model Y, the Model Y L features a longer body and extended wheelbase to accommodate an additional row of seating.
Tesla has confirmed that the larger six-seat Model Y L will launch in Australia and New Zealand in 2026.
The confirmation was shared by techAU through a media release from Tesla Australia and New Zealand.
The Model Y L expands the Model Y lineup by offering additional seating capacity for customers seeking a larger electric SUV. Compared with the standard five-seat Model Y, the Model Y L features a longer body and extended wheelbase to accommodate an additional row of seating.
The Model Y L is already being produced at Tesla’s Gigafactory Shanghai for the Chinese market, though the vehicle will be manufactured in right-hand-drive configuration for markets such as Australia and New Zealand.
Tesla Australia and New Zealand confirmed the vehicle will feature seating for six passengers.
“As shown in pictures from its launch in China, Model Y L will have a new seating configuration providing room for 6 occupants,” Tesla Australia and New Zealand said in comments shared with techAU.
Instead of a traditional seven-seat arrangement, the Model Y L uses a 2-2-2 layout. The middle row features two individual seats, allowing easier access to the third row while providing additional space for passengers.
Tesla Australia and New Zealand also confirmed that the Model Y L will be covered by the company’s updated warranty structure beginning in 2026.
“As with all new Tesla Vehicles from the start of 2026, the Model Y L will come with a 5-year unlimited km vehicle warranty and 8 years for the battery,” the company said.
The updated policy increases Tesla’s vehicle warranty from the previous four-year or 80,000-kilometer coverage.
Battery and drive unit warranties remain unchanged depending on the variant. Rear-wheel-drive models carry an eight-year or 160,000-kilometer warranty, while Long Range and Performance variants are covered for eight years or 192,000 kilometers.
Tesla has not yet announced official pricing or range figures for the Model Y L in Australia.
News
Tesla Roadster patent hints at radical seat redesign ahead of reveal
A newly published Tesla patent could offer one of the clearest signals yet that the long-awaited next-generation Roadster is nearly ready for its public debut.
Patent No. US 20260061898 A1, published on March 5, 2026, describes a “vehicle seat system” built around a single continuous composite frame – a dramatic departure from the dozens of metal brackets, recliner mechanisms, and rivets that make up a traditional car seat. Tesla is calling it a monolithic structure, with the seat portion, backrest, headrest, and bolsters all thermoformed as one unified piece.
The approach mirrors Tesla’s broader manufacturing philosophy. The same company that pioneered massive aluminum castings to eliminate hundreds of body components is now applying that logic to the cabin. Fewer parts means fewer potential failure points, less weight, and a cleaner assembly process overall.
Tesla ramps hiring for Roadster as latest unveiling approaches
The timing of the filing is difficult to ignore. Elon Musk has publicly targeted April 1, 2026 as the date for an “unforgettable” Roadster design reveal, and two new Roadster trademarks were filed just last month. A patent describing a seat architecture suited for a hypercar, and one that Tesla has promised will hit 60 mph in under two seconds.
The Roadster, originally unveiled in 2017, has been one of Tesla’s most anticipated yet most delayed products. With a target price around $200,000 and engineering ambitions to match, it is being positioned as the ultimate showcase for what Tesla’s technology can do.
The patent was first flagged by @seti_park on X.
Tesla Roadster Monolithic Seat: Feature Highlights via US Patent 20260061898 A1
- Single Continuous Frame (Monolithic Construction). The core invention is a seat assembly built from one continuous frame that integrates the seat portion, backrest portion, and hinge into a single component — eliminating the need for separate structural parts and mechanical joints typical in conventional seats.
- Integrated Flexible Hinge. Rather than a traditional mechanical recliner, the hinge is built directly into the continuous frame and is designed to flex, and allowing the backrest to move relative to the seat portion. The hinge can be implemented as a fiber composite leaf spring or an assembly of rigid linkages.
- Thermoformed Anisotropic Composite Material. The continuous frame is manufactured via thermoforming from anisotropic composite materials, including fiberglass-nylon, fiberglass-polymer, nylon carbon composite, Kevlar-nylon, or Kevlar-polymer composites, enabling a molded-to-shape monolithic structure.
- Regionally Tuned Stiffness Zones. The frame is engineered with up to six distinct stiffness regions (R1–R6) across the seat, backrest, hinge, headrest, and bolsters. Each zone can have a different stiffness, allowing precise ergonomic and structural tuning without adding separate components.
- Linkage Assembly Hinge Mechanism. The hinge incorporates one or more linkage assemblies consisting of multiple interlocking links with gears, connected by rods. When driven by motors or actuators, these linkages act as a flexible member to control backrest movement along a precise, ergonomically optimized trajectory.
- Multi-Actuator Six-Degree-of-Freedom Positioning System. The seat uses four distinct actuator pairs, all controlled by a central controller. These actuators work in coordinated combinations to achieve fore/aft, height, cushion tilt, and backrest rotation adjustments simultaneously.
- ECU-Based Controller Architecture. An Electronic Control Unit (ECU) and programmable controller manage all seat actuators, receive user input via a user interface (touchscreen, buttons, or switches), and incorporate sensor feedback to confirm and maintain desired seat positions, essentially making this a software-driven seat system.
- Airbag-Integrated Bolster Deployment System. The backrest bolsters (216) are geometrically shaped and sized to guide airbag deployment along a specific, pre-configured trajectory. Left and right bolsters can have different shapes so that each guides its respective airbag along a distinct trajectory, improving occupant protection.
- Ventilation Holes Formed into the Backrest. The continuous frame includes one or more ventilation holes formed directly into the backrest portion, configured to either receive airflow into or deliver airflow from the seat frame — enabling passive or active thermal comfort without requiring separate ventilation components.
- Soft Trim Recess for Tool-Free Integration. The headrest and backrest portions together define a molded recess, specifically designed to receive and secure a soft trim component (foam, fabric, or cushioning) directly into the continuous frame, eliminating the need for separate attachment hardware and simplifying final assembly.












