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
Why SpaceX is finishing another space-internet system that isn’t Starlink
SpaceX launched three final O3b mPower satellites Sunday, finishing a lesser known SES satellite network.
SpaceX had an 87 minute window opening at 2:49 p.m. Eastern on Sunday to fly a Falcon 9 out of Cape Canaveral carrying the final three satellites for SES’s O3b mPower constellation, a project that has taken more than a decade to finish since Boeing and SES first signed SpaceX on for the work.
Unlike the thousands of Starlink satellites SpaceX has stacked into orbit over the years, O3b mPower flies in a different neighborhood entirely. The three new satellites, tagged F11, F12 and F13, are headed for medium Earth orbit at roughly 5,000 miles up, more than ten times higher than Starlink’s shell around 340 miles but still a small fraction of the 22,000 miles where old school geostationary satellites sit. That middle position is the whole point, because a satellite that far out needs far fewer siblings to blanket the globe than a low orbit constellation does. Essentially, SES only needed 13 satellites total to build a network offering quick, steady service that used to require thousands of spacecraft.
With most people having heard plenty about Starlink and almost nothing about O3b mPower, SES and SpaceX already blend the two networks for some customers. Both SpaceX and SES sell satellite broadband, but they’re aimed at different buyers. Starlink is built for volume, direct to consumers, RVs, homes, small businesses, plus a growing aviation and maritime business. O3b mPower skips consumers entirely and sells enterprise grade connectivity to airlines, cruise lines, offshore energy operators, telecoms needing backhaul, and governments, priced and provisioned more like a dedicated circuit.
A 2023 partnership lets cruise ships combine Starlink’s speed with O3b mPower’s steady capacity depending on what a ship needs at a given moment. Sunday’s completed 13 satellite constellation effectively finishes the medium orbit half of that pairing, years after.
Sunday’s mission was already a something on SpaceX’s manifest well before O3b mPower entered the picture. This flight marked its 29th trip to orbit, a history that includes two crewed Axiom missions, the European Space Agency’s Euclid telescope and 22 separate Starlink batches. SpaceX has landed boosters on the droneship A Shortfall of Gravitas so often that Sunday’s touchdown attempt, if it went as planned, was set to be the 661st successful Falcon booster landing to date.
For a company that pushed the Starlink constellation past 11,000 satellites back in August, almost entirely through bulk launches from California, Sunday’s flight was a reminder that SpaceX’s schedule still has room for someone else’s satellites too. SES gets a finished network built for a narrower set of customers, and Falcon 9 gets one more line on an already long resume.
Elon Musk
Tesla gives the Roadster an official “Go for launch” demonstration date
Tesla teased an October 1 Roadster reveal, reviving years of delayed SpaceX thruster hover promises.
Tesla teased an October 1 event date for its next generation Roadster, posting an image on X Saturday that shows the car lit up like it is sitting on a launch pad, with the date “10.01” stamped across the bottom and the caption “Go for launch.” A countdown clock on Tesla’s Roadster order page now points to the same date, which falls on a Thursday. The company has not said where the event will happen or whether it will be streamed at the moment. Stay with us @Teslarati for live updates.
Go for launch pic.twitter.com/Khu03eiZ04
— Tesla (@Tesla) September 12, 2026
Tesla has since sent formal invitations to reservation holders confirming the event will take place in Waco, Texas, about 90 minutes north of its Austin headquarters, based on a digital ticket shared on X by Sawyer Merritt. Tesla did not name the exact venue, though Waco sits close to SpaceX’s McGregor, Texas, rocket test site, previously reported as the planned location for a Roadster thruster demonstration. The invite sets the reveal for 8:30 p.m. Eastern on October 1, requires RSVPs by midnight on September 16, and limits entry to guests 21 and older. Invitations are non-transferable.
The tease follows nine years of a project defined by unimaginable specs along with slipped dates. Musk first showed the second generation Roadster in November 2017 as a surprise reveal at the end of the Tesla Semi event, promising a 0 to 60 mph time under two seconds, a top speed above 250 mph, 620 miles of range from a 200 kWh battery, and production starting in 2020. At last November’s shareholder meeting, Musk set an April 1 demo date and joked the choice gave him “deniability” if it slipped again, which it did, moving first to late April, then to “a month or so,” then to August.
Tesla Roadster SpaceX Package’s 1.1-second 0-60 mph launch visualized in concept video
Whatever Tesla shows on October 1 is expected to center on the SpaceX developed thruster package Musk has described since 2018. Internally code named A71, a nod to the Lockheed SR-71 Blackbird, the system reportedly uses cold gas thrusters fed by a composite overwrapped pressure vessel, the same tank design SpaceX uses on Falcon 9. Musk has said a thruster equipped Roadster could hit 60 mph in about 1.1 seconds under roughly 2.75 g of launch force, well past the 1.9 second figure quoted for the standard car. That version reportedly will not be street legal and has reportedly been discussed as a limited run sold through a track only program.
The standard Roadster is still expected to carry the original $200,000 base price and $250,000 Founders Series tier, both set when Tesla opened $50,000 and $250,000 reservations in 2017. Tesla VP of Vehicle Engineering Lars Moravy has confirmed production will happen at Gigafactory Texas, with Musk targeting 2027 or 2028, 12 to 18 months after whatever the company demonstrates next month.
Tesla is planning to roll out some pretty significant safety and accident avoidance features with Full Self-Driving version 15, which will be the next major FSD deployment from the company.
Tesla AI lead Ashok Elluswamy used a near-miss this week to preview what the company says is the next leap in Full Self-Driving.
In response to a driver whose car had swerved away from another vehicle pulling out of a parking lot, Elluswamy wrote that he was glad the owner was safe and that “even earlier prediction of hazards, even faster reaction time and overall significantly better safety and collision avoidance” would arrive with FSD v15.
Glad you are safe. Even earlier prediction of hazards, even faster reaction time and overall significantly better safety and collision avoidance coming as part of the next big upgrade (v15).
— Ashok Elluswamy (@aelluswamy) September 11, 2026
The comment landed as Tesla continues to treat software as the primary safety upgrade path. v15 is described internally as a larger architectural step, with a much bigger neural network and tighter coupling between prediction and control.
The company has already begun using early v15 software in some robotaxi operations while rolling out safety features such as Automatic Collision Evasion into current customer cars, allowing the driving stack to intervene even when the driver is in manual control.
Tesla is rolling out a new FSD version with a massive safety addition
Tesla’s published telemetry is the backbone of its safety argument. In recent North American Vehicle Safety Report data, vehicles with FSD (Supervised) engaged traveled roughly 5.1 million to 5.7 million miles between major collisions, defined as airbag-deployment events.
Tesla’s estimate of the U.S. average over the same period is about 699,000 miles per comparable crash. That is the comparison Tesla often frames as roughly seven times fewer major collisions.
A tighter comparison uses the same Tesla fleet. Cars driven manually with active safety features such as automatic emergency braking still recorded a major collision about every 2.1 million miles. Against that baseline, FSD’s advantage shrinks to roughly 2.4 to 2.7 times fewer severe crashes, which independent researchers argue is the more apples-to-apples figure.
European data released in 2026 pointed in the same direction: Tesla reported FSD as 3.5 times safer than manual driving in the Netherlands and 4.1 times fewer collisions than manually driven Teslas with active safety across more than 100 million kilometers in five approved countries.
Those numbers do not settle every debate. NHTSA’s Standing General Order still shows Tesla accounting for the large majority of U.S. Level 2 driver-assist crash reports, in part because the fleet logs far more assisted miles than rivals. Critics also note that Tesla’s “U.S. average” mixes crash definitions and driving mix.
Even so, Tesla’s own same-car comparisons, plus lower rates of automatic emergency braking and harsh maneuvers when FSD is engaged, are the evidence Elluswamy is pointing to when he says v15 will push prediction and collision avoidance further. The claim is not that software already eliminates risk. It is that each major version is meant to widen the gap between the system and an unaided human driver.
Why SpaceX is finishing another space-internet system that isn’t Starlink
Tesla gives the Roadster an official “Go for launch” demonstration date
