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.
Tesla Full Self-Driving is set to receive improvements to address its two biggest issues, according to a company engineer.
Director of Engineering at Tesla AI, Phil Duan, revealed in a post on X that improvements to both pothole avoidance and navigation “are coming,’ something we have heard many times in the past. However, there are a few things that seem to hint that things might be different this time around.
Improvements on both are coming.
— Phil Duan (@pduan) October 1, 2026
Pothole avoidance, navigation, speed control, and left lane camping are some of the most prevalent and frequently mentioned shortcomings of the Full Self-Driving suite. These are a few of the biggest issues that have kept Tesla Full Self-Driving as a Supervised suite, meaning drivers must remain attentive during operation.
Pothole Avoidance
Pothole avoidance was first mentioned as an “Upcoming Improvement” with the Tesla Full Self-Driving v14.3 update back in early April of this year. It was listed alongside “Expand reasoning to all behaviors beyond destination handling.”
It’s been six months since we first saw pothole avoidance explicitly mentioned, and it has not moved beyond that and joined the main release notes yet.
Tesla has not shed any light on why pothole avoidance has been such an issue for it to solve, but it also has issues identifying large bumps much of the time, so its modeling of sudden changes in road conditions is likely pretty weak at this particular point. I’ve had more issues with large bumps than potholes, personally, but both are issues that need to be resolved.
This is that big bounce that I mentioned in the quoted post.
It’s just a tad too drastic to take at the speed FSD wants to go over it. You can see me quickly swipe down into Sloth, but I intervened. https://t.co/K20PK9ysBg pic.twitter.com/81Oc82ZJcZ
— TESLARATI (@Teslarati) August 2, 2026
It makes sense that things might be pretty close to being released to the public, as we are going on such an extensive period of time between it being mentioned and it actually being deployed.
Navigation
Navigation is likely the most painful part of using Full Self-Driving, as it routinely takes strange routes, has trouble with local rules (like Except Right Turn Stop Signs in Pennsylvania), and sometimes does not realize that maneuvers it is suggesting are against the law. Turning out of my neighborhood, you cannot turn left, yet my Model Y still suggests it roughly 70 percent of the time when I’m leaving.
However, Tesla might be close to a breakthrough on this. With the Summer Update, Tesla added “Preferred Routes” alongside “Automatic Navigation.”
Preferred Routes prioritized roads that the driver had actually taken before, instead of always defaulting to what the vehicle believes is the most efficient path. This has already solved many of my issues. Formerly, I would turn off the Online Routing setting, and that would eliminate most of my complaints with routing, but then you lose out later on the Live Traffic Visualization.
Tesla’s Navigation has improved tremendously thanks to the Preferred Routes release with the Summer Update, but it still could use some polishing, as it still suggests strange routes from time to time, and it also has a lot of issues getting out of a parking lot. I find that those truly confuse FSD sometimes.
News
SpaceX’s midnight spy satellite launch quietly set a new record
Falcon Heavy launched its first NRO mission while SpaceX landed four boosters in one day.
SpaceX closed out one of its busiest days ever with a midnight Falcon Heavy launch from Florida, and the rocket’s two side boosters came home to finish off a landing record the company had never set before.
Falcon Heavy lifted off from Launch Complex 39A at NASA’s Kennedy Space Center at 11:54 p.m. ET Thursday carrying NROL-97, a classified payload for the National Reconnaissance Office. It was the first time the NRO has flown on Falcon Heavy after 22 missions on Falcon 9, and the first NRO mission bought through the National Security Space Launch Phase 3 Lane 2 contract awarded in 2025, according to Spaceflight Now.
Falcon Heavy lifts off from pad 39A in Florida for the 14th time! pic.twitter.com/uuZLKNTdD7
— SpaceX (@SpaceX) October 2, 2026
Roughly eight minutes after liftoff, side boosters B1104 and B1072 touched down at Landing Zones 1 and 2 at Cape Canaveral Space Force Station, setting off double sonic booms across Brevard County. B1104 was flying for the second time and B1072 for the fourth. Both last flew on August 30 on NASA’s Nancy Grace Roman Space Telescope, making NROL-97 the quickest turnaround between Falcon Heavy missions to date. The brand new center core, B1106, was expended in the Atlantic so the payload could reach its high energy orbit, and SpaceX’s mission page noted the fairing had previously flown on the NROL-95 mission in July.
The two landings capped a record for SpaceX. Earlier Thursday, Falcon 9 booster B1101 returned to Landing Zone 40 after sending the Crew-13 astronauts to the International Space Station, and another Falcon 9 launched the Transporter-18 rideshare with 130 payloads from Vandenberg Space Force Base in California. Spaceflight Now reported it was the first time SpaceX has landed four boosters in a single day, wrapping up the triple header Teslarati previewed on Wednesday.
Falcon Heavy’s side boosters land on LZ-1 and LZ-2 pic.twitter.com/dBPcNeggFx
— SpaceX (@SpaceX) October 2, 2026
The mission also brought Landing Zone 1 back for what may be its final landing. SpaceX first landed an orbital class booster there in December 2015, but its lease on the former Launch Complex 13 site ended in 2025 as the company moved Florida landings to new pads at its own launch complexes. With LZ-40 already holding the Crew-13 booster, SpaceX brought LZ-1 back into service for one more night. Launch tracker Next Spaceflight listed NROL-97 as the final expected landing at the site.
NROL-97 adds to a fast growing stack of national security work for SpaceX. The company has flown four Space Force missions from Vandenberg since mid August, several believed to carry Starshield satellites, pushing its Pentagon contract total for 2026 past $8 billion. Elon Musk was also named this week to help lead the Pentagon’s Project Meridian study on the future of warfare.
The Florida doubleheader stood out for another reason. The Space Coast saw only one launch in all of September as SpaceX shifts more of its East Coast infrastructure toward Starship, which reached orbit for the first time on Flight 14 just three days earlier.
Tesla (NASDAQ: TSLA) reported strong delivery figures that beat Wall Street guesses, and they were revealed alongside the company’s second-best quarter in terms of energy deployments ever.
Tesla announced this morning that it delivered 486,532 cars in Q3, while producing 464,391, exceeding analyst consensus, which sat around 462,000 units.
Meanwhile, Tesla reported 13.7 GWh of energy storage deployed for the quarter. That’s the second-best quarter Tesla has ever reported on that side of things.
🚨 Tesla delivered 486,532 vehicles in Q3, beating expectations at 464,391.
Big Q from the Tesla team, also 13.7 GWh of energy was deployed. pic.twitter.com/olioLWgG7a
— TESLARATI (@Teslarati) October 2, 2026
Vehicle Deliveries
Deliveries were strong, and it was another quarter when Tesla had the opportunity to outshine the Wall Street pundits who are quick to criticize and slow to give credit. Tesla saw a slight decrease in deliveries compared to Q3 2025, but Tesla still had the $7,500 EV Tax Credit to use to help incentivize consumers to pick an EV.
A small decrease of 2.1 percent is pretty telling because it shows Tesla does not need massive federal credits to convince consumers to purchase its vehicles.
It was also the company’s third-best performance all-time in terms of deliveries, trailing that of Q3 2025 with 497,099 deliveries and Q4 2024, when the company handed over 495,570 cars.
We reported several days ago that Tesla Showrooms across the United States were completely bare of inventory or unclaimed units. Many locations also removed Demo Drive units, which had been bought by customers looking to take delivery sooner.
Tesla showrooms picked clean ahead of Q3 end as demand looks strong
Energy Generation
Tesla’s Energy Generation performance in Q3 was also very strong, as the company deployed 13.7 GWh of energy storage over the past three months. The only quarter when Tesla reported stronger energy deployment figures was Q4 2025, when 14.2 GWh of energy storage was deployed.
Tesla’s Q3 performance in energy generation has continued to grow each quarter, with the company increasing its deployments by ten-fold since Q3 2021, when just 1.3 GWh was deployed.
It is also nearly double what it was in Q3 2024, when the company reported 6.9 GWh. This is one of Tesla’s quickest-growing divisions, and it flies under the radar with fans and analysts, as many are focused on self-driving or the vehicles themselves.
Tesla Stock
Shares rose 5.07 percent to $372.06 at just after 10 a.m. on the East Coast. This is a rarity for Tesla after a strong delivery report, as positive news usually brings the stock down. Many quarters with extremely robust delivery reports have not been as kind to the Teslanaires of the world.
Tesla says fixes on Full Self-Driving’s two biggest issues are on the way
SpaceX’s midnight spy satellite launch quietly set a new record
