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.
Ahead of its highly anticipated unveiling, Tesla’s upcoming Roadster received a new patent that aims to keep it grounded while enabling white-knuckle speeds.
The patent, which was granted on September 29, is titled “Electric Car Fan,” bluntly stating its design but not its purpose, which is further detailed in the text of the application. Interestingly, it comes two weeks before the Roadster event, which was delayed due to unfavorable weather on Thursday, which could cause issues, as Tesla revealed the event must be held outdoors.
🚨 The design uses electrically driven ducted fans, typically shown as a row of four at the rear, powered by the vehicle’s high-voltage battery.
The fans pull air from an underbody inlet, route it through ducts, and expel it from a larger rear outlet that functions as a… https://t.co/CHQB9u9UA3 pic.twitter.com/QVXmWTdggh
— TESLARATI (@Teslarati) September 29, 2026
The purpose is to solve a problem that is relatively unique to high-performance electric cars. Instant motor torque is useless if the tires cannot plant that force, and conventional wings and underbody tunnels generate downforce only when air is already rushing past the car. At launch, in slow corners, and under hard braking from modest speed, passive aerodynamic additions contribute essentially very little to downforce.
Tesla’s filing says that its fans can produce the downforce needed, independent of vehicle velocity, then ease off so the same hardware does not pile on drag at highway speeds, an issue that can come from excessive body modifications.
The hardware outlined in the patent is a ducted-fan package that is placed into the rear of the vehicle. An underbody inlet between the rear wheels feeds a duct that rises to a wide outlet in the diffuser. In that outlet are four axial fans, which are divided by vertical strakes. They will pull air from under the floor and press the chassis onto the pavement.
The language in the patent claims it can cut drag rather than add to it while simultaneously increasing downforce.
Tesla Roadster event requires restricted airspace, and the FAA obliges
The fans run from the high-voltage battery and a vehicle control system, so output can be modulated rather than left on as a fixed penalty.
There are additional strengths that can come from this design, like extra tire load at low speed, which can contribute to even more face-melting acceleration rates, decrease stopping distance, and sharper turn-in before a wing has air to work with. Adjustable fan speed lets the car add grip only when needed, so it can be catered to the force of a turn or acceleration.
These designs were previously used, and banned, in some competitive settings. The Brabham BT46B was banned in F1 competition for using a similar fan design and being labeled as too effective.
Tesla still lists the Roadster as having a sub-two-second 0-60 MPH time and a 250-plus-MPH top speed, and there are expectations for a SpaceX cold-gas thruster package that could not only increase acceleration but potentially cause the vehicle to hover.
It is important to note that a patent is not a production part, and packaging four fans in a rear diffuser, managing noise, and potential debris are all things Tesla must consider. With that being said, the patent being granted shows Tesla is designing the Roadster to go fast, but it is also attempting to use unique strategies to combat any issues it might have at those speeds.
Tesla (NASDAQ: TSLA) showrooms have been picked clean ahead of the end of the third quarter of the year, as demand looks to be strong and delivery estimates for new vehicles are pushed into late 2026 and early 2027.
Tesla appears to have sold out of many of its Model 3 and Model Y trim levels in the United States, as only the Model Y RWD and Model Y All-Wheel-Drive are available for delivery before the end of the year.
Additionally, many showrooms are either completely empty or void of all but just one demo unit within the buildings themselves in an effort to bolster what could be one of Tesla’s best quarters in vehicle deliveries in recent memory.
I’m at Tesla right now and when I walked into their showroom I was shocked to see it basically empty.
I asked one of the people working there where all of the cars are “Gone – it’s the end of the quarter and we’ve sold out of everything… including the display vehicles”So… pic.twitter.com/rN7s3gE6sJ
— Devin Olsen (@DevinOlsenn) September 25, 2026
All the cars are gone from Tesla Century City!
All they have is Model Y L, a self-driving video playing on the background. I guess the best product is no product. Either that or they just sold the showroom cars. pic.twitter.com/mzCjWaXwww
— Whole Mars Catalog (@wholemars) September 26, 2026
Show room is empty. I asked and they have sold the demo cars too. Delivery numbers better be outstanding! pic.twitter.com/jq5N28Q6tZ
— Electric Brawl (@3lectricBrawl) September 22, 2026
Additionally, when I spoke to the guys at Tesla Mechanicsburg two weeks ago, when I returned the Model Y L, their third hauler of the week had just arrived, and every vehicle on it, along with every vehicle in their delivery lot, was accounted for and had a name attached to it for delivery.
Talking to the guys at the Mechanicsburg showroom on Friday, they couldn’t believe they had ANOTHER hauler coming in of cars for delivery—and each was accounted for
No car just sitting in inventory. They’re expecting a BIG quarter, and this is more than just the Y L https://t.co/ce801GkKVv
— TESLARATI (@Teslarati) September 21, 2026
Tesla saw a 25 percent increase in deliveries in Q2 compared to the same quarter the year before. The vast majority of the 480,126 units it delivered, 467,762 vehicles to be exact, were the Model 3 and Model Y.
In Q3 2025, Tesla delivered 497,099 vehicles, once again a figure that was dominated by the company’s two mass-market vehicles. Analysts have unusually wide predictions for this quarter, likely because so many firms missed the Q2 delivery figure by such a substantial margin; Wall Street predicted 408,000 cars, while Tesla delivered 480,000.
Goldman Sachs has Tesla slotted for 435,000 deliveries in Q3, while JPMorgan said it anticipates 482,000. The median guess is about 449,000 deliveries for Q3.
Interested in ordering a Tesla? Use my referral code for three free months of Full Self-Driving (Supervised) here.
Tesla’s Automatic Collision Evasion feature can be seen in one of the first owner videos of it in action.
Tesla owner Spencer (@scotsrule08) posted on Monday that the feature “worked flawlessly,” saying FSD reengaged itself just as he was about to hit a curb. Ashok Elluswamy, who leads Tesla’s AI team, shared the clip and wrote, “A guardian angel always looking out for you.”
The video arrives in the middle of a staged rollout. Tesla first shipped Automatic Collision Evasion with FSD (Supervised) v14.3.9 in software update 2026.27.6 earlier this month, which Teslarati covered as it reached cars. Update 2026.27.10, which began going out on September 19, carried the feature improvements with FSD v14.3.10, according to release notes tracked by Not a Tesla App. The newer 2026.27.11 build is now reaching another wave of vehicles.
The new Automatic Collision Evasion feature worked flawlessly! FSD reengaged itself just as I was about to hit a curb.
Kudos @Tesla_AI team! 👏 pic.twitter.com/Fbp15HhpL2
— Spencer (@scotsrule08) September 28, 2026
The feature only runs on HW4 vehicles, and it requires an active FSD purchase or subscription with both FSD (Supervised) and Automatic Emergency Braking enabled. HW3 owners receive FSD v14.2 Lite in the same updates, but that build does not include collision evasion.
Tesla’s release notes describe two triggers. The first is an imminent frontal collision that braking alone may not prevent, in which case the car can activate FSD to steer, brake or accelerate around the hazard. That scenario is limited to highways below 85 mph, with no pedestrians or cyclists detected and no slippery road surface. The second covers a driver who appears inattentive, such as reaching into the back seat, or who seems to have switched off FSD by accident. Spencer’s curb clip appears to fall into that second category.
Tesla plans big safety improvements for Full Self-Driving v15
Once the system takes over, the accelerator is muted and light brake input will not cancel the maneuver. Drivers need to apply firm, deliberate steering force to take back control, and the car chimes to hand control back once the danger has passed.
Elluswamy recently noted that earlier hazard prediction, faster reaction time and better collision avoidance would arrive with FSD v15, the next major version.
Tesla Roadster’s new patent preps white-knuckle speeds, keeping it grounded
Tesla showrooms picked clean ahead of Q3 end as demand looks strong
