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.
A Texas man has been arrested and charged with manslaughter after his Tesla crashed into a home last month, striking a woman inside and killing her. The driver, Michael Butler, claimed the vehicle was in self-driving mode, but information from Tesla shows that Butler overrode the system.
Butler was arrested on Wednesday and booked at the Harris County, Texas, jail. He remained in custody through Thursday and Friday; he did not enter a plea, and his next court hearing is scheduled for Monday.
Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration
There are a handful of new clues in the case that could clear Tesla of any wrongdoing, especially as the woman who was killed’s family, the Avilas, filed a wrongful death lawsuit against Tesla and Butler, seeking at least $1 million in damages.
Charging documents from the Harris County prosecutor now show that Butler, who was working DoorDash the evening of the accident, had been using Full Self-Driving mode without incident through the duration of multiple deliveries that evening.
In the moments leading up to the crash, while in FSD and approaching a left turn, Butler pressed the accelerator pedal, overriding FSD’s speed control, and continued to push it until it reached 100 percent. This caused rapid acceleration; the brake pedal was never pressed, and there is no data to show that Butler aimed to turn away from the curb or house.
The charging documents state:
“I noted that the brake pedal was never pressed in the final minute before the crash. I also did not see any data to indicate that the driver attempted to turn away from the curb that he eventually struck. Further, I observed that no mechanical error was detected or recorded by the vehicle before BUTLER and the Tesla struck the curb.”
Additionally, a forensic analysis of Butler’s phone showed that he searched Google around the time of the crash with queries questioning why FSD was “too timid,” “not aggressive enough,” and even searched, “FSD is not aggressive enough for city driving.”
The documents outlined this:
“Investigator Veal also informed me that he had received BUTLER’s cell phone from Deputy Amad and that HDAO digital forensics team had completed a data extraction and download of the phone. Multiple Google searches related to Tesla had been made from BUTLER’s phone in the months leading up the crash. I noted multiple searches in May of 2026 indicating an apparent frustration with Tesla’s FSD mode, including the following searches: “Tesla fsd not aggressive enough 2026 model,” “Tesla fsd not [sic) aggressive enough 2026,” “FSD is not aggressive enough for city driving,” and “tesla fsd too timid.”‘
Tesla had claimed just after the crash that its internal data showed Butler had overridden the system’s speed control and pressed the accelerator completely, causing the vehicle to travel at an excessive rate of speed. Eventually, the car slammed into Avila’s house, killing her.
Butler has now been formally charged with Manslaughter, a felony.
Tesla shocked with its quarterly delivery report yesterday by reporting it delivered 480,126 vehicles in the second quarter of 2026, a 25 percent year-over-year jump that crushed Wall Street estimates of roughly 400,000–408,000 units. Production reached 451,758, with Model 3 and Model Y accounting for the vast majority.
The result ended two years of annual delivery declines and drew down inventory, signaling demand that outpaced earlier production.
Tesla bears had long warned that the expiration of the U.S. federal EV tax credit would hammer demand. Without the $7,500 incentive, they argued, American buyers would balk at higher effective prices, leading to a sharp slowdown.
Will Tesla thrive without the EV tax credit? Five reasons why they might
That narrative has not played out as predicted. While U.S. EV sales faced broader headwinds, Tesla’s global numbers held firm, underscoring the company’s ability to offset domestic pressure through other levers.
There are several plausible factors that explain Tesla’s strength during this quarter. Let’s take a look at them:
Rising Gas Prices
Rising gas prices provided a powerful tailwind, especially in the U.S.
Geopolitical tensions tied to the Iran conflict pushed fuel costs higher earlier in the year, amplifying the lifetime savings of electric vehicles. Even as oil prices later moderated, the psychological and financial impact lingered, encouraging fleet operators and private buyers to accelerate EV purchases. European sales rebounded sharply, helping drive the quarter’s outperformance.
Full Self-Driving Adoption
Advances in Full Self-Driving (FSD) supervised software also appear to have boosted appeal. Tesla expanded FSD availability in select European markets and continued refining the system.
No complaints from me because I finally got to enjoy this drive on FSD; I usually like to manually drive down this mountain https://t.co/RBFniRPSR0 pic.twitter.com/XQ5sOpN1Yg
— TESLARATI (@Teslarati) June 26, 2026
For tech-oriented buyers, the promise of future autonomy and enhanced driver-assistance features adds perceived value beyond the car itself. This differentiation helps Tesla stand out in a crowded market where competitors focus primarily on hardware and basic range.
Pricing Strategy, Affordable Configurations
Tesla’s offerings and its pricing strategy during Q2 further stimulated demand. Tesla introduced lower-cost versions of the Model 3 and Model Y, widening accessibility without sacrificing core margins.
These moves countered affordability concerns and attracted buyers who had been waiting on the sidelines. Combined with attractive financing and leasing options, the pricing strategy converted interest into actual orders more effectively than many analysts expected.
Broad European Recovery
Supported by government incentives, corporate fleet electrification, and easing political headwinds around CEO Elon Musk, Tesla was supplied additional momentum through stronger registration numbers throughout Europe.
Strong exports from the Shanghai Gigafactory and a production ramp at Giga Berlin ensured supply met this resurgent demand. Corporate buyers, in particular, accelerated transitions to EVs to meet sustainability targets, providing a steady volume base.
These elements created a virtuous cycle that delivered the strong deliveries report. While bears correctly flagged the loss of the U.S. tax credit as a risk, Tesla’s diversified playbook demonstrated that it could remain resilient against those headwinds. The Q2 beat suggests the company remains adept at navigating shifting market conditions, even as competition intensifies.
A Tesla Semi was involved in a fatal collision on U.S. Highway 50 in Dayton, Nevada, on Sunday, June 28, 2026, marking the first known fatal crash involving the electric Class 8 truck. The incident occurred around 7:20 a.m. at the intersection with Traditions Parkway, approximately 40 miles east of Reno and close to Tesla’s Gigafactory Nevada.
According to the Lyon County Sheriff’s Office and the Nevada State Police Highway Patrol, a semi-truck struck two passenger vehicles stopped at a traffic signal. The truck hit the vehicles from behind. Two people were pronounced dead at the scene, and a third person suffered life-threatening injuries and was flown to a hospital, Forbes reported.
Preliminary statements gathered at the scene by the Lyon County Sheriff’s Office suggested the truck driver may have fallen asleep at the wheel. However, the Nevada Highway Patrol, which is leading the investigation, stated that the official cause has not yet been determined.
Additional information is expected to be released early the following week. The truck was seized for evidence as part of the ongoing probe.
Responders at the scene included deputies from the Lyon County Sheriff’s Office, personnel from the Nevada Highway Patrol, Central Lyon County Fire Department, and the Nevada Department of Transportation. The crash led to the temporary closure of U.S. 50 in both directions.
The Tesla Semi is Tesla’s battery-electric heavy-duty truck, produced at the nearby Gigafactory in Nevada. Authorities initially described the vehicle as a semi-truck; its make was subsequently confirmed through reporting and scene identification; an interesting bit of information here, as the Semi is not yet available publicly and many do not know that Tesla builds electric trucks.
The investigation remains active, with no further official details on contributing factors or vehicle systems released as of early July 2026.
This incident highlights ongoing scrutiny of commercial vehicle safety on Nevada highways, particularly involving fatigue. Law enforcement continues to gather evidence and witness statements.
Texas man charged in fatal Tesla crash where he blamed Autopilot
Tesla’s strong Q2 deliveries: Four key drivers behind the surprise
