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.
Elon Musk
Tesla CEO Elon Musk teases insane capabilities of next major FSD update
Tesla CEO Elon Musk teased the insane capabilities of the next major Full Self-Driving update just hours after the company rolled out version 14.2 to owners.
Tesla Full Self-Driving v14.2 had some major improvements from the previous iteration of v14.1.x. We were on v14.1.7, the most advanced configuration of the v14.1 family, before Tesla transitioned us and others to v14.2.
However, Musk has said that the improvements coming in the next major update, which will be v14.3, will be where “the last big piece of the puzzle finally lands.”
14.3 is where the last big piece of the puzzle finally lands
— Elon Musk (@elonmusk) November 21, 2025
There were some major improvements with v14.2, most notably, Tesla seemed to narrow in on the triggers that caused issues with hesitation and brake stabbing in v14.1.x.
One of the most discussed issues with the past rollout was that of brake stabbing, where the vehicle would contemplate proceeding with a route as traffic was coming from other directions.
We experienced it most frequently at intersections, especially four-way stop signs.
Elon Musk hints at when Tesla can fix this FSD complaint with v14
In our review of it yesterday, it was evident that this issue had been resolved, at least to the extent that we had no issues with it in a 62-minute drive, which you can watch here.
Some owners also reported a more relaxed driver monitoring system, which is something Tesla said it was working on as it hopes to allow drivers to text during operation in the coming months. We did not test this, as laws in Pennsylvania prohibit the use of phones at any time due to the new Paul Miller’s Law, which took effect earlier this year.
However, the improvements indicate that Tesla is certainly headed toward a much more sentient FSD experience, so much so that Musk’s language seems to be more indicative of a more relaxed experience in terms of overall supervision from the driver, especially with v14.3.
Musk did not release or discuss a definitive timeline for the release of v14.3, especially as v14.2 just rolled out to Early Access Program (EAP) members yesterday. However, v14.1 rolled out to Tesla owners just a few weeks ago in late 2025. There is the potential that v14.3 could be part of the coming Holiday Update, or potentially in a release of its own before the New Year.
News
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
Tesla rolled out Full Self-Driving version 14.2 yesterday to members of the Early Access Program (EAP). Expectations were high, and Tesla surely delivered.
With the rollout of Tesla FSD v14.2, there were major benchmarks for improvement from the v14.1 suite, which spanned across seven improvements. Our final experience with v14.1 was with v14.1.7, and to be honest, things were good, but it felt like there were a handful of regressions from previous iterations.
While there were improvements in brake stabbing and hesitation, we did experience a few small interventions related to navigation and just overall performance. It was nothing major; there were no critical takeovers that required any major publicity, as they were more or less subjective things that I was not particularly comfortable with. Other drivers might have been more relaxed.
With v14.2 hitting our cars yesterday, there were a handful of things we truly noticed in terms of improvement, most notably the lack of brake stabbing and hesitation, a major complaint with v14.1.x.
However, in a 62-minute drive that was fully recorded, there were a lot of positives, and only one true complaint, which was something we haven’t had issues with in the past.
The Good
Lack of Brake Stabbing and Hesitation
Perhaps the most notable and publicized issue with v14.1.x was the presence of brake stabbing and hesitation. Arriving at intersections was particularly nerve-racking on the previous version simply because of this. At four-way stops, the car would not be assertive enough to take its turn, especially when other vehicles at the same intersection would inch forward or start to move.
This was a major problem.
However, there were no instances of this yesterday on our lengthy drive. It was much more assertive when arriving at these types of scenarios, but was also more patient when FSD knew it was not the car’s turn to proceed.
Can report on v14.2 today there were ZERO instances of break stabbing or hesitation at intersections today
It was a significant improvement from v14.1.x
— TESLARATI (@Teslarati) November 21, 2025
This improvement was the most noticeable throughout the drive, along with fixes in overall smoothness.
Speed Profiles Seem to Be More Reasonable
There were a handful of FSD v14 users who felt as if the loss of a Max Speed setting was a negative. However, these complaints will, in our opinion, begin to subside, especially as things have seemed to be refined quite nicely with v14.2.
Freeway driving is where this is especially noticeable. If it’s traveling too slow, just switch to a faster profile. If it’s too fast, switch to a slower profile. However, the speeds seem to be much more defined with each Speed Profile, which is something that I really find to be a huge advantage. Previously, you could tell the difference in speeds, but not in driving styles. At times, Standard felt a lot like Hurry. Now, you can clearly tell the difference between the two.
It seems as if Tesla made a goal that drivers should be able to tell which Speed Profile is active if it was not shown on the screen. With v14.1.x, this was not necessarily something that could be done. With v14.2, if someone tested me on which Speed Profile was being used, I’m fairly certain I could pick each one.
Better Overall Operation
I felt, at times, especially with v14.1.7, there were some jerky movements. Nothing that was super alarming, but there were times when things just felt a little more finicky than others.
v14.2 feels much smoother overall, with really great decision-making, lane changes that feel second nature, and a great speed of travel. It was a very comfortable ride.
The Bad
Parking
It feels as if there was a slight regression in parking quality, as both times v14.2 pulled into parking spots, I would have felt compelled to adjust manually if I were staying at my destinations. For the sake of testing, at my first destination, I arrived, allowed the car to park, and then left. At the tail-end of testing, I walked inside the store that FSD v14.2 drove me to, so I had to adjust the parking manually.
This was pretty disappointing. Apart from parking at Superchargers, which is always flawless, parking performance is something that needs some attention. The release notes for v14.2. state that parking spot selection and parking quality will improve with future versions.
Any issues with parking on your end? 14.1.7 didn’t have this trouble with parking pic.twitter.com/JPLRO2obUj
— TESLARATI (@Teslarati) November 21, 2025
However, this was truly my only complaint about v14.2.
You can check out our full 62-minute ride-along below:
Elon Musk
SpaceX issues statement on Starship V3 Booster 18 anomaly
The incident unfolded during gas-system pressure testing at the company’s Massey facility in Starbase, Texas.
SpaceX has issued an initial statement about Starship Booster 18’s anomaly early Friday. The incident unfolded during gas-system pressure testing at the company’s Massey facility in Starbase, Texas.
SpaceX’s initial comment
As per SpaceX in a post on its official account on social media platform X, Booster 18 was undergoing gas system pressure tests when the anomaly happened. Despite the nature of the incident, the company emphasized that no propellant was loaded, no engines were installed, and personnel were kept at a safe distance from the booster, resulting in zero injuries.
“Booster 18 suffered an anomaly during gas system pressure testing that we were conducting in advance of structural proof testing. No propellant was on the vehicle, and engines were not yet installed. The teams need time to investigate before we are confident of the cause. No one was injured as we maintain a safe distance for personnel during this type of testing. The site remains clear and we are working plans to safely reenter the site,” SpaceX wrote in its post on X.
Incident and aftermath
Livestream footage from LabPadre showed Booster 18’s lower half crumpling around the liquid oxygen tank area at approximately 4:04 a.m. CT. Subsequent images posted by on-site observers revealed extensive deformation across the booster’s lower structure. Needless to say, spaceflight observers have noted that Booster 18 would likely be a complete loss due to its anomaly.
Booster 18 had rolled out only a day earlier and was one of the first vehicles in the Starship V3 program. The V3 series incorporates structural reinforcements and reliability upgrades intended to prepare Starship for rapid-reuse testing and eventual tower-catch operations. Elon Musk has been optimistic about Starship V3, previously noting on X that the spacecraft might be able to complete initial missions to Mars.








