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.
Tesla is pushing back against the unfair reporting of accidents involving its vehicles. Many media outlets were quick to jump to conclusions about a fatal accident involving a Tesla in Katy, Texas, that happened recently.
The driver of the vehicle, which slammed into a brick house and killed a woman inside, stated the car was operating on Autopilot. Tesla CEO Elon Musk and Head of AI Ashok Elluswamy both challenged that claim, with Elluswamy revealing last night that the system was overridden by the driver, who pressed the accelerator pedal “all the way to 100%.”
Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration
The car reached a speed of 73 MPH during the crash, Elluswamy detailed, and stated that the accelerator pedal was even pressed after the crash.
The story has been spread throughout the media with either incomplete or incorrect reporting, with some stories still not updated nearly 24 hours after Musk and Elluswamy posted answers about the crash on X.
The reporting has been a thorn in the side of Tesla for several years. Vehicle accidents involving Teslas are usually reported with the manufacturer’s name in the headline, while other companies are free of criticism when their cars are involved in accidents.
Here’s an example of that:
So you don’t report the vehicle’s make when it isn’t a Tesla, but you do report it when it is a Tesla?
The vehicle in your post above is a Hyundai Ioniq 5 EV. pic.twitter.com/4WT3sZ2DHm
— Sawyer Merritt (@SawyerMerritt) February 17, 2026
Many media outlets stated the car was in “self-driving mode” or “Autopilot mode” when the car crashed. The truth is, now that Tesla has chimed in, that the driver had manually overriden the system by pressing the accelerator. Elluswamy commented on the unfair reporting:
“This blatantly irresponsible reporting does more harm to people than they realize.
Using Tesla self-driving is far safer than manual driving, and this was measured over 10B miles.
Planting such FUD in the minds of general public, who might not know the all the facts, might prevent them from using this technology that makes them safer.”
This blatantly irresponsible reporting does more harm to people than they realize.
Using Tesla self-driving is far safer than manual driving, and this was measured over 10B miles.
Planting such FUD in the minds of general public, who might not know the all the facts, might…
— Ashok Elluswamy (@aelluswamy) June 22, 2026
The damage these headlines do to Tesla and the self-driving car movement is unexplainable. Most people do not realize the safeguards that are in place with Tesla’s self-driving functions; many people who have used it know the car would never travel at that speed in a residential area, not even on the most aggressive “Mad Max” setting.
It is important to remember that Tesla Full Self-Driving is not autonomous, and the company never claimed it was. Drivers are still responsible for paying attention and remaining vigilant. They must be able to take over at all times.
Tesla Supercharging is getting yet another layer of gamification, as the company is rolling out a new competition that could win Free Supercharging miles.
Tesla is ramping up its efforts to make vehicle ownership more engaging through gamification. In June 2026, the company announced the 2026 Free Supercharging Competition, building on the Charging Passport feature introduced the previous year. This initiative turns Supercharging into a competitive, collectible adventure while offering substantial real-world incentives.
🚨 Tesla is taking its gamification of Supercharging a step further with the launch of the 2026 Free Supercharging Contest:
“In January 2027, Tesla will celebrate nine outstanding Supercharger users from 2026 by awarding them free Supercharging for their Tesla vehicle for as… pic.twitter.com/CPPYJLJwFD
— TESLARATI (@Teslarati) June 23, 2026
The Charging Passport, rolled out late last year, functions like a digital travel log or a year-in-review for Tesla owners. These types of things are used by many platforms, including Spotify and Apple Music, which show listeners what type of taste they had for the year.
Accessed in the Tesla App under the ‘Charging’ section, it displays a map of visited Superchargers, key stats, such as total energy charged (kWh), number of unique sites, total charging sessions, top charging day, and miles added. Owners earn collectible Charging Badges in categories, which include:
- Charging Milestones – for total energy, consecutive weeks of Supercharging, or unique sites visited
- Iconic Chargers – for Flagship Locations or stations near famous landmarks
- Special Events – limited-time badges for specific experiences. These badges appear within 24 hours of qualifying activity and provide a fun, shareable recap of an owner’s Supercharging journeys. Milestone progress resets annually, allowing fresh challenges each year
The 2026 contest elevates this gamification by rewarding top performers with lifetime free Supercharging. All Supercharging sessions from January 1 to December 31, 2026, count toward the competition. To participate, owners must enable “Share Charging Data with Tesla App” in vehicle settings and open the 2026 Charging Passport in the app at least once before January 1, 2027.
Nine winners will be selected — three per region (Americas, Asia-Pacific, and EMEA, with some countries excluded for regulatory reasons) — one in each of three categories:
- Longest Trip: Longest continuous streak of unique Supercharger locations where each new site is visited within 24 hours of the previous session’s start time
- Most Unique Supercharger Sites Visited: Highest number of distinct locations
- Most Energy Supercharged: Highest total in kWh charged at Superchargers
A unique site is defined as shown in the Tesla app or vehicle navigation. Repeat visits during a streak are allowed but do not extend the count. Ties are broken by total energy charged. Ineligible participants include vehicles already receiving free Supercharging, commercial-use vehicles (taxi, rideshare, delivery), Tesla employees and their immediate families, and residents of certain excluded countries.
Winners receive free Supercharging on the winning vehicle for as long as they own or lease it.
This contest is part of Tesla’s broader gamification strategy. The Safety Score has long rewarded safe driving habits with a numerical rating that can influence insurance rates or feature access. The referral program incentivizes owners with credits or free Supercharging months for successful referrals.
In-app statistics, streaks, and community features further encourage engagement. Older third-party apps even awarded “mayor” titles for frequenting specific Superchargers.
By combining digital badges, competitive leaderboards, and high-value rewards, Tesla boosts network utilization, gathers usage data, and fosters deeper owner loyalty. The 2026 Free Supercharging Competition invites enthusiasts to plan epic road trips while turning everyday charging into a rewarding pursuit. With the Passport already proving popular, expect heightened activity across the Supercharger network throughout the year.
Tesla is atop the American-Made Index from Cars.com for the sixth-straight year, as the Model 3 and Model Y took the top two spots, respectively.
Last year, the Model 3, Model Y, Model S, and Model X took the top four spots, respectively. The company has routinely performed well in the Index. However, Tesla discontinued its flagship Model S and Model X earlier this year, which took the two cars out of the ranking.
Cybertruck is not considered due to its curb weight being above the 8,500-pound threshold, which eliminates it from being required to have more detailed assembly information.
Cars.com uses five main categories to develop its rankings:
- Location(s) of final assembly
- Percentage of U.S. and Canadian parts
- Countries of origin for all available engines
- Countries of origin for all available transmissions
- U.S. manufacturing workforce
These five major factors are then put into a 100-point scale. The vehicles with the highest scores sit atop the list. The Model 3 edged out the Model Y.
🇺🇸 The Tesla Model 3 and Tesla Model Y have been put atop the American-Made Index from https://t.co/PXZ0g1pPb6, meaning they are the most American vehicles you can possibly buy.
This is the SIXTH-STRAIGHT year a Tesla has been listed as the most American-made vehicle: pic.twitter.com/HyraOmaxSL
— TESLARATI (@Teslarati) June 23, 2026
Tesla uses a strong domestic strategy to build its cars and parts domestically. It relies on intense vertical integration that reduces its dependence on global suppliers, keeping more value and jobs in the United States.
This strategy has helped Tesla gain a strong reputation for domestically produced vehicles and parts. However, it helps it with more than just awards like this one. Keeping a supply chain local has also helped insulate Tesla more than others from tariffs and supply chain disruptions.
This year’s American-Made Index from Cars.com studied nearly 400 vehicles from the 2026 model year. Tesla was the only manufacturer to have an EV inside the Top 10. The Kia EV9 was the next EV to make the list, scoring the 17th position.
The Hyundai IONIQ 5 was 21st, and the final EV to make the list was the Cadillac LYRIQ in 77th.
Tesla pushes back against unfair reporting of accidents
Tesla gets another layer of gamification with Free Supercharging on the line
