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 executive moves on after 13 years: ‘It has been a privilege to serve’
“It is challenging to encapsulate 13 years in a single post. The journey at Tesla has been one of continuous evolution. From the technical intricacies of designing, building, and operating one of the world’s largest AI clusters to impactful contributions in IT, Security, Sales, and Service, it has been a privilege to serve,” Jegannathan said in the post.
Tesla executive Raj Jegannathan is moving on from the company after 13 years, he announced on LinkedIn on Monday.
“It is challenging to encapsulate 13 years in a single post. The journey at Tesla has been one of continuous evolution. From the technical intricacies of designing, building, and operating one of the world’s largest AI clusters to impactful contributions in IT, Security, Sales, and Service, it has been a privilege to serve,” Jegannathan said in the post.
After starting as a Senior Staff Engineer in Fremont back in November 2012, Jegannathan slowly worked his way through the ranks at Tesla. His most recent role was Vice President of IT/AI Infrastructure, Business Apps, and Infosec.
However, it was reported last year that Jegannathan had taken on a new role, which was running the North American sales team following the departure of Troy Jones, who had held the position previously.
While Jegannathan’s LinkedIn does not mention this position specifically, it seemed to be accurate, considering Tesla had not explicitly promoted any other person to the role.
It is a big loss for Tesla, but not a destructive departure. Jegannathan was one of the few company executives who answered customer and fan questions on X, a unique part of the Tesla ownership experience.
Tesla to offer Full Self-Driving gifting program: here’s how it will work
It currently remains unclear if Jegannathan was removed from the position or if he left under his own accord.
“As I move on, I do so with a full heart and excitement for what lies ahead. Thank you, Tesla, for this wonderful opportunity!” he concluded.
The departure marks a continuing trend of executives leaving the company, as the past 24 months have seen some significant turnover at the executive level.
Tesla has shown persistently elevated executive turnover over the past two years, as names like Drew Baglino, Rohan Patel, Rebecca Tinucci, Daniel Ho, Omead Afshar, Milan Kovac, and Siddhant Awasthi have all been notable names to exit the company in the past two years.
There are several things that could contribute to this. Many skeptics will point to Elon Musk’s politics, but that is not necessarily the case.
Tesla is a difficult, but rewarding place to work. It is a company that requires a lot of commitment, and those who are halfway in might not choose to stick around. Sacrificing things like time with family might not outweigh the demands of Tesla and Musk.
Additionally, many of these executives have made a considerable amount of money thanks to stock packages the company offers to employees. While many might be looking for new opportunities, some might be interested in an early retirement.
Tesla is also in the process of transitioning away from its most notable division, automotive. While it still plans to manufacture cars in the millions, it is turning more focus toward robotics and autonomy, and these plans might not align with what some executives might want for themselves. There are a wide variety of factors in the decision to leave a job, so it is important not to immediately jump to controversy.
News
Lemonade launches Tesla FSD insurance program in Oregon
The program was announced by Lemonade co-founder Shai Wininger on social media platform X.
Tesla drivers in Oregon can now receive significant insurance discounts when using FSD, following the launch of Lemonade’s new Autonomous Car insurance program.
The program was announced by Lemonade co-founder Shai Wininger on social media platform X.
Lemonade launches FSD-based insurance in Oregon
In a post on X, Wininger confirmed that Lemondade’s Autonomous Car insurance product for Tesla is now live in Oregon. The program allows eligible Tesla owners to receive roughly 50% off insurance costs for every mile driven using Tesla’s FSD system.
“And… we’re ON. @Lemonade_Inc’s Autonomous Car for @Tesla FSD is now live in Oregon. Tesla drivers in Oregon can now get ~50% off their Tesla FSD-driven miles + the best car insurance experience in the US, bar none,” Wininger wrote in his post.
As per Lemonade on its official website, the program is built on Tesla’s safety data, which indicates that miles driven using FSD are approximately twice as safe as those driven manually. As a result, Lemonade prices those miles at a lower rate. The insurer noted that as FSD continues to improve, associated discounts could increase over time.
How Lemonade tracks FSD miles
Lemonade’s FSD discount works through a direct integration with Tesla vehicles, enabled only with a driver’s explicit permission. Once connected, the system distinguishes between miles driven manually and those driven using FSD, applying the discount automatically to qualifying miles.
There is no minimum FSD usage requirement. Drivers who use FSD occasionally still receive discounted rates for those miles, while non-FSD miles are billed at competitive standard rates. Lemonade also emphasized that coverage and claims handling remain unchanged regardless of whether a vehicle is operating under manual control or FSD at the time of an incident.
The program is currently available only to Teslas equipped with Hardware 4 or newer, running firmware version 2025.44.25.5 or later. Lemonade also allows policyholders to bundle Tesla insurance with renters, homeowners, pet, or life insurance policies for additional savings.
News
Tesla exec: Preparations underway but no firm timeline yet for FSD rollout in China
The information was related by Tesla China Vice President Grace Tao in a comment to local media.
Tesla has not set a specific launch date for Full Self-Driving in China, despite the company’s ongoing preparations for a local FSD rollout.
The information was related by Tesla China Vice President Grace Tao in a comment to local media.
Tesla China prepares FSD infrastructure
Speaking in a recent media interview, the executive confirmed that Tesla has established a local training center in China to support the full adaptation of FSD to domestic driving conditions, as noted in a report from Sina News. However, she also noted that the company does not have a specific date when FSD will officially roll out in China.
“We have set up a local training center in China specifically to handle this adaptation,” Tao said. “Once officially released, it will demonstrate a level of performance that is no less than, and may even surpass, that of local drivers.”
Tao also emphasized the rapid accumulation of data by Tesla’s FSD system, with the executive highlighting that Full Self-Driving has now accumulated more than 7.5 billion miles of real-world driving data worldwide.
Possible 2026 rollout
The Tesla executive’s comments come amidst Elon Musk’s previous comments suggesting that regulatory approval in China could arrive sometime this 2026. During Tesla’s annual shareholder meeting in November 2025, Musk clarified that FSD had only received “partial approval” in China, though full authorization could potentially arrive around February or March 2026.
Musk reiterated that timeline at the World Economic Forum in Davos, when he stated that FSD approval in China could come as early as February.
Tesla’s latest FSD software, version 14, is already being tested in more advanced deployments in the United States. The company has also started the rollout of its fully unsupervised Robotaxis in Austin, Texas, which no longer feature safety monitors.
Tesla executive moves on after 13 years: ‘It has been a privilege to serve’
Lemonade launches Tesla FSD insurance program in Oregon
