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 Robotaxi has a highly-requested hardware feature not available on typical Model Ys
These camera washers are crucial for keeping the operation going, as they are the sole way Teslas operate autonomously. The cameras act as eyes for the car to drive, recognize speed limit and traffic signs, and travel safely.
Tesla Robotaxi has a highly-requested hardware feature that is not available on typical Model Ys that people like you and me bring home after we buy them. The feature is something that many have been wanting for years, especially after the company adopted a vision-only approach to self-driving.
After Tesla launched driverless Robotaxi rides to the public earlier this week in Austin, people have been traveling to the Lone Star State in an effort to hopefully snag a ride from one of the few vehicles in the fleet that are now no longer required to have Safety Monitors present.
BREAKING: Tesla launches public Robotaxi rides in Austin with no Safety Monitor
Although only a few of those completely driverless rides are available, there have been some new things seen on these cars that are additions from regular Model Ys, including the presence of one new feature: camera washers.
With the Model Y, there has been a front camera washer, but the other exterior “eyes” have been void of any solution for this. For now, owners are required to clean them manually.
In Austin, Tesla is doing things differently. It is now utilizing camera washers on the side repeater and rear bumper cameras, which will keep the cameras clean and keep operation as smooth and as uninterrupted as possible:
🚨 Tesla looks to have installed Camera Washers on the side repeater cameras on Robotaxis in Austin
pic.twitter.com/xemRtDtlRR— TESLARATI (@Teslarati) January 23, 2026
Rear Camera Washer on Tesla Robotaxi pic.twitter.com/P9hgGStHmV
— TESLARATI (@Teslarati) January 24, 2026
These camera washers are crucial for keeping the operation going, as they are the sole way Teslas operate autonomously. The cameras act as eyes for the car to drive, recognize speed limit and traffic signs, and travel safely.
This is the first time we are seeing them, so it seems as if Safety Monitors might have been responsible for keeping the lenses clean and unobstructed previously.
However, as Tesla transitions to a fully autonomous self-driving suite and Robotaxi expands to more vehicles in the Robotaxi fleet, it needed to find a way to clean the cameras without any manual intervention, at least for a short period, until they can return for interior and exterior washing.
Tesla made a dramatic change to the Online Design Studio to show its plans for Full Self-Driving, a major part of the company’s plans moving forward, as CEO Elon Musk has been extremely clear on the direction moving forward.
With Tesla taking a stand and removing the ability to purchase Full Self-Driving outright next month, it is already taking steps to initiate that with owners and potential buyers.
On Thursday night, the company updated its Online Design Studio to reflect that in a new move that now lists the three purchase options that are currently available: Monthly Subscription, One-Time Purchase, or Add Later:
🚨 Check out the change Tesla made to its Online Design Studio:
It now lists the Monthly Subscription as an option for Full Self-Driving
It also shows the outright purchase option as expiring on February 14 pic.twitter.com/pM6Svmyy8d
— TESLARATI (@Teslarati) January 23, 2026
This change replaces the former option for purchasing Full Self-Driving at the time of purchase, which was a simple and single box to purchase the suite outright. Subscriptions were activated through the vehicle exclusively.
However, with Musk announcing that Tesla would soon remove the outright purchase option, it is clearer than ever that the Subscription plan is where the company is headed.
The removal of the outright purchase option has been a polarizing topic among the Tesla community, especially considering that there are many people who are concerned about potential price increases or have been saving to purchase it for $8,000.
This would bring an end to the ability to pay for it once and never have to pay for it again. With the Subscription strategy, things are definitely going to change, and if people are paying for their cars monthly, it will essentially add $100 per month to their payment, pricing some people out. The price will increase as well, as Musk said on Thursday, as it improves in functionality.
I should also mention that the $99/month for supervised FSD will rise as FSD’s capabilities improve.
The massive value jump is when you can be on your phone or sleeping for the entire ride (unsupervised FSD). https://t.co/YDKhXN3aaG
— Elon Musk (@elonmusk) January 23, 2026
Those skeptics have grown concerned that this will actually lower the take rate of Full Self-Driving. While it is understandable that FSD would increase in price as the capabilities improve, there are arguments for a tiered system that would allow owners to pay for features that they appreciate and can afford, which would help with data accumulation for the company.
Musk’s new compensation package also would require Tesla to have 10 million active FSD subscriptions, but people are not sure if this will move the needle in the correct direction. If Tesla can potentially offer a cheaper alternative that is not quite unsupervised, things could improve in terms of the number of owners who pay for it.
News
Tesla Model S completes first ever FSD Cannonball Run with zero interventions
The coast-to-coast drive marked the first time Tesla’s FSD system completed the iconic, 3,000-mile route end to end with no interventions.
A Tesla Model S has completed the first-ever full Cannonball Run using Full Self-Driving (FSD), traveling from Los Angeles to New York with zero interventions. The coast-to-coast drive marked the first time Tesla’s FSD system completed the iconic, 3,000-mile route end to end, fulfilling a long-discussed benchmark for autonomy.
A full FSD Cannonball Run
As per a report from The Drive, a 2024 Tesla Model S with AI4 and FSD v14.2.2.3 completed the 3,081-mile trip from Redondo Beach in Los Angeles to midtown Manhattan in New York City. The drive was completed by Alex Roy, a former automotive journalist and investor, along with a small team of autonomy experts.
Roy said FSD handled all driving tasks for the entirety of the route, including highway cruising, lane changes, navigation, and adverse weather conditions. The trip took a total of 58 hours and 22 minutes at an average speed of 64 mph, and about 10 hours were spent charging the vehicle. In later comments, Roy noted that he and his team cleaned out the Model S’ cameras during their stops to keep FSD’s performance optimal.
History made
The historic trip was quite impressive, considering that the journey was in the middle of winter. This meant that FSD didn’t just deal with other cars on the road. The vehicle also had to handle extreme cold, snow, ice, slush, and rain.
As per Roy in a post on X, FSD performed so well during the trip that the journey would have been completed faster if the Model S did not have people onboard. “Elon Musk was right. Once an autonomous vehicle is mature, most human input is error. A comedy of human errors added hours and hundreds of miles, but FSD stunned us with its consistent and comfortable behavior,” Roy wrote in a post on X.
Roy’s comments are quite notable as he has previously attempted Cannonball Runs using FSD on December 2024 and February 2025. Neither were zero intervention drives.
Tesla Robotaxi has a highly-requested hardware feature not available on typical Model Ys
Tesla makes big Full Self-Driving change to reflect future plans
