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 aims to combat common Full Self-Driving problem with new patent
Tesla writes in the patent that its autonomous and semi-autonomous vehicles are heavily reliant on camera systems to navigate and interact with their environment.
Tesla is aiming to combat a common Full Self-Driving problem with a new patent.
One issue with Tesla’s vision-based approach is that sunlight glare can become a troublesome element of everyday travel. Full Self-Driving is certainly an amazing technology, but there are still things Tesla is aiming to figure out with its development.
Unfortunately, it is extremely difficult to get around this issue, and even humans need ways to combat it when they’re driving, as we commonly use sunglasses or sun visors to give us better visibility.
Cameras obviously do not have these ways to fight sunglare, but a new patent Tesla recently had published aims to fight this through a “glare shield.”
Tesla writes in the patent that its autonomous and semi-autonomous vehicles are heavily reliant on camera systems to navigate and interact with their environment.
The ability to see surroundings is crucial for accurate performance, and glare is one element of interference that has yet to be confronted.
Tesla described the patent, which will utilize “a textured surface composed of an array of micro-cones, or cone-shaped formations, which serve to scatter incident light in various directions, thereby reducing glare and improving camera vision.”
The patent was first spotted by Not a Tesla App.
The design of the micro-cones is the first element of the puzzle to fight the excess glare. The patent says they are “optimized in size, angle, and orientation to minimize Total Hemispherical Reflectance (THR) and reflection penalty, enhancing the camera’s ability to accurately interpret visual data.”
Additionally, there is an electromechanical system for dynamic orientation adjustment, which will allow the micro-cones to move based on the angle of external light sources.
This is not the only thing Tesla is mulling to resolve issues with sunlight glare, as it has also worked on two other ways to combat the problem. One thing the company has discussed is a direct photon count.
CEO Elon Musk said during the Q2 Earnings Call:
“We use an approach which is direct photon count. When you see a processed image, so the image that goes from the sort of photon counter — the silicon photon counter — that then goes through a digital signal processor or image signal processor, that’s normally what happens. And then the image that you see looks all washed out, because if you point the camera at the sun, the post-processing of the photon counting washes things out.”
Future Hardware iterations, like Hardware 5 and Hardware 6, could also integrate better solutions for the sunglare issue, such as neutral density filters or heated lenses, aiming to solve glare more effectively.
Elon Musk
Delaware Supreme Court reinstates Elon Musk’s 2018 Tesla CEO pay package
The unanimous decision criticized the prior total rescission as “improper and inequitable,” arguing that it left Musk uncompensated for six years of transformative leadership at Tesla.
The Delaware Supreme Court has overturned a lower court ruling, reinstating Elon Musk’s 2018 compensation package originally valued at $56 billion but now worth approximately $139 billion due to Tesla’s soaring stock price.
The unanimous decision criticized the prior total rescission as “improper and inequitable,” arguing that it left Musk uncompensated for six years of transformative leadership at Tesla. Musk quickly celebrated the outcome on X, stating that he felt “vindicated.” He also shared his gratitude to TSLA shareholders.
Delaware Supreme Court makes a decision
In a 49-page ruling Friday, the Delaware Supreme Court reversed Chancellor Kathaleen McCormick’s 2024 decision that voided the 2018 package over alleged board conflicts and inadequate shareholder disclosures. The high court acknowledged varying views on liability but agreed rescission was excessive, stating it “leaves Musk uncompensated for his time and efforts over a period of six years.”
The 2018 plan granted Musk options on about 304 million shares upon hitting aggressive milestones, all of which were achieved ahead of time. Shareholders overwhelmingly approved it initially in 2018 and ratified it once again in 2024 after the Delaware lower court struck it down. The case against Musk’s 2018 pay package was filed by plaintiff Richard Tornetta, who held just nine shares when the compensation plan was approved.
A hard-fought victory
As noted in a Reuters report, Tesla’s win avoids a potential $26 billion earnings hit from replacing the award at current prices. Tesla, now Texas-incorporated, had hedged with interim plans, including a November 2025 shareholder-approved package potentially worth $878 billion tied to Robotaxi and Optimus goals and other extremely aggressive operational milestones.
The saga surrounding Elon Musk’s 2018 pay package ultimately damaged Delaware’s corporate appeal, prompting a number of high-profile firms, such as Dropbox, Roblox, Trade Desk, and Coinbase, to follow Tesla’s exodus out of the state. What added more fuel to the issue was the fact that Tornetta’s legal team, following the lower court’s 2024 decision, demanded a fee request of more than $5.1 billion worth of TSLA stock, which was equal to an hourly rate of over $200,000.
Delaware Supreme Court Elon Musk 2018 Pay Package by Simon Alvarez
News
Tesla Cybercab tests are going on overdrive with production-ready units
Tesla is ramping its real-world tests of the Cybercab, with multiple sightings of the vehicle being reported across social media this week.
Tesla is ramping its real-world tests of the Cybercab, with multiple sightings of the autonomous two-seater being reported across social media this week. Based on videos of the vehicle that have been shared online, it appears that Cybercab tests are underway across multiple states.
Recent Cybercab sightings
Reports of Cybercab tests have ramped this week, with a vehicle that looked like a production-ready prototype being spotted at Apple’s Visitor Center in California. The vehicle in this sighting was interesting as it was equipped with a steering wheel. The vehicle also featured some changes to the design of its brake lights.
The Cybercab was also filmed testing at the Fremont factory’s test track, which also seemed to involve a vehicle that looked production-ready. This also seemed to be the case for a Cybercab that was spotted in Austin, Texas, which happened to be undergoing real-world tests. Overall, these sightings suggest that Cybercab testing is fully underway, and the vehicle is really moving towards production.
Production design all but finalized?
Recently, a near-production-ready Cybercab was showcased at Tesla’s Santana Row showroom in San Jose. The vehicle was equipped with frameless windows, dual windshield wipers, powered butterfly door struts, an extended front splitter, an updated lightbar, new wheel covers, and a license plate bracket. Interior updates include redesigned dash/door panels, refined seats with center cupholders, updated carpet, and what appeared to be improved legroom.
There seems to be a pretty good chance that the Cybercab’s design has been all but finalized, at least considering Elon Musk’s comments at the 2025 Annual Shareholder Meeting. During the event, Musk confirmed that the vehicle will enter production around April 2026, and its production targets will be quite ambitious.
Tesla aims to combat common Full Self-Driving problem with new patent
Delaware Supreme Court reinstates Elon Musk’s 2018 Tesla CEO pay package
