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 Giga Berlin makes big move amid strong sales and demand
“We currently have very good sales figures and have therefore revised our production plans for the third and fourth quarters upwards.”

Tesla is making a big move at its factory in Germany, known as Giga Berlin, as managers at the plant have indicated the company plans to increase its production rate for the remainder of the year.
Giga Berlin is responsible for manufacturing Model Y vehicles for several markets worldwide, including those outside of Europe. It was opened in March 2022, and it recently built its 500,000th Model Y in March and its 100,000th new Model Y just three weeks ago.
Due to some encouraging sales figures in the markets it provides vehicles for, Tesla said it is planning to increase production at the factory for the remainder of the year.
Andrè Thierig, plant manager at Giga Berlin, said to German news outlet DPA on Sunday that market data has encouraged a move to be made regarding the production at the factory:
“We currently have very good sales figures and have therefore revised our production plans for the third and fourth quarters upwards.”
It is interesting to see this kind of narrative from Thierig, especially as data has shown Tesla has struggled in various markets, including Germany, this year.
Sales drops have been reported, but other markets are holding strong, especially those in Northern Europe, such as Norway, where the Model Y saw a nearly 39 percent increase in sales in August compared to the same month the previous year.
Gigafactory Berlin supplies vehicles for other markets, such as Canada, Australia, and New Zealand, which are strategically important to avoid tariffs. It also builds cars for the Middle East.
Thierig reiterated this point during the interview with DPA:
“We supply well over 30 markets and definitely see a positive trend there.”
Elon Musk
Tesla analyst says Musk stock buy should send this signal to investors
“With Musk’s (Tesla stock) purchase, combined with the upward momentum for delivery expectations and robotaxi rollout, we are becoming more bullish.”

Tesla CEO Elon Musk purchased roughly $1 billion in Tesla shares on Friday, and analysts are now breaking down the move as the stock is headed upward.
One of them is William Blair analyst Jed Dorsheimer, who said in a new note to investors on Monday that Musk’s move should send a signal of confidence to stock buyers, especially considering the company’s numerous catalysts that currently exist.
Elon Musk just bought $1 billion in Tesla stock, his biggest purchase ever
Dorsheimer said in the note:
“With Musk’s (Tesla stock) purchase, combined with the upward momentum for delivery expectations and robotaxi rollout, we are becoming more bullish. This purchase is Musk’s first buy since 2020. To us, this sends a strong signal of confidence in the most important part of Tesla’s future business, robotaxi.”
Musk putting an additional $1 billion back into the company in the form of more stock ownership is obviously a huge vote of confidence.
He knows more than anyone about the progress Tesla has made and is making on the Robotaxi platform, as well as the company’s ongoing efforts to solve vehicle autonomy. If he’s buying stock, it is more than likely a good sign.
Tesla has continued to expand its Robotaxi platform in a number of ways. The project has gotten bigger in terms of service area, vehicle fleet, and testing population. Tesla has also recently received a permit to test in Nevada, unlocking the potential to expand into a brand-new state for the company.
In the note, Dorsheimer also touched on Musk’s recent pay package, revealing that William Blair recently met with Tesla’s Board of Directors, who gave the firm some more color on the situation:
“We recently participated in a meeting with Tesla’s board of directors to discuss the details of Musk’s performance package. The board is confident of its position in the Delaware case and anticipates a verdict by end of year. It does not expect a similar situation to occur under new Texas jurisdiction. Musk has the board’s full support, and we expect he’ll get more than enough shareholder support for this to pass with flying colors.”
Tesla stock is up over 6 percent so far today, trading at $421.50 at the time of publication.
News
Morgan Stanley’s Adam Jonas dubs Tesla FSD a “game changer” after marathon drive
Jonas reported that FSD handled more than 99% of the miles.

Morgan Stanley’s analyst Adam Jonas shared a notable endorsement of Tesla’s Full Self-Driving (FSD) software after completing a 1,400-mile round trip from New York to Michigan in his Model Y.
Jonas reported that FSD handled more than 99% of the miles, calling the system “a game changer” for long-distance driving.
Hands-free experience
Jonas drove his 2021 Tesla Model Y equipped with Hardware 3 and FSD Supervised v12.6.4, and he used the system nearly the entire trip. “Having your hands off the wheel and feet off the pedals for nearly 12 hours of driving is a real game changer that is hard to appreciate without experiencing it for yourself,” he noted.
He explained that outside of two heavy downpours, one on the Pennsylvania Turnpike and another in suburban Detroit, plus some light maneuvering in fast food parking lots, FSD handled the drive without any human intervention. “FSD made no mistakes or close calls that I recall. The system handles highways very safely and confidently. I cannot imagine buying another EV without FSD.”
Broader implications
Jonas added that he has used FSD consistently over the past 18 months, and the $8,000 he paid for the feature feels like a bargain considering the value. He also praised Tesla’s Supercharging network, which supported his trip without issue.
Jonas has been one of Wall Street’s most closely followed voices on Tesla, and his comments add weight to the ongoing debate about the role of autonomy in the company’s future. His current price target for Tesla stock stands at $410. During Morgan Stanley’s 13th Annual Laguna Conference, he echoed similar experiences with Tesla’s software, emphasizing that FSD “probably drove well over 99% of the miles” on his recent trips.
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