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 Full Self-Driving is going to be getting a major parking upgrade. That’s according to CEO Elon Musk, who detailed a crafty new feature that will improve parking preferences, removing a layer of human input.
Musk said that upcoming releases of Full Self-Driving will “remember your parking preferences.” It will go to the location you prefer, based on where you’ve parked in the past, instead of taking the first spot available, which is where the suite is currently.
The CEO went on to explain that destination parking is “by far” the biggest reason for intervention during FSD operation. We’d have to believe this is true; many takeovers in my Model Y, which runs the latest version of FSD as it is in the Early Access Program, are due to parking because it chooses a spot I do not want to be in.
Many times, as soon as I enter a parking lot, I take over and park manually. I prefer to park away from the entrance of wherever I am, away from cars. Too many lessons learned over the years from people with free-swinging doors.
Upcoming releases of FSD will remember your parking preferences, so that the car goes to the right location at your home, office, school drop off, etc.
Destination parking is by far the biggest reason people now intervene with FSD. Critical safety interventions are extremely…
— Elon Musk (@elonmusk) June 17, 2026
We’d imagine these new updates will also solve things like parking orientation. Let’s say when you arrive at work, you always park in the third spot in the third row, and you prefer to back in. It seems as if Musk is implying that your car will now do this, learning from takeovers and aiming to eliminate the need to manually park whenever possible.
This is a major upgrade because parking is a major shortcoming of FSD currently. We’ve requested things like manual input of parking preferences, choosing to park far away, first available, or away from cars, for example.
This is a big reason Parking Preferences with Supervised FSD will be so valuable.
If possible, parking a little further away and being distant from people like this is worth it. https://t.co/1YqQLgnfTz pic.twitter.com/3Ac71KQiQ3
— TESLARATI (@Teslarati) June 7, 2026
However, some have used the option of dropping a pin at the location you’d like to park at your destination. This has worked some of the time, but FSD will still choose to park in whatever it sees first.
Musk did not give a timetable for when the improvements would be released, but it is likely to come soon. Tesla has been releasing a new FSD version every few weeks, so we may not have to wait long to test it.
In a remarkable demonstration of how advanced vehicle technology can intersect with family care and rapid response, a Tesla Model Y equipped with Full Self-Driving (FSD) Supervised helped save a driver’s life during a severe heart attack. The incident, which occurred on November 15, 2025, highlights the life-saving potential of Tesla’s connected ecosystem.
John Brandt, 55, was driving his new 2026 Model Y Launch Edition on Interstate 20 from Atlanta toward Birmingham early that morning. He had recently received the FSD v14.1.3 update. Around 3:50 a.m., he began experiencing severe chest pain. Barely conscious and unable to safely control the vehicle, John managed to call his son, Jack Brandt.
FSD Supervised remained engaged, keeping the car steadily on course while John reached out for help.
As an authorized driver on his father’s Tesla account, Jack quickly sprang into action from his own phone. He located Tanner Medical Center in Carrollton, Georgia—a facility equipped for cardiac emergencies—via Google Maps and shared the destination directly through the Tesla app.
A Model Y driver started experiencing a medical emergency with chest pain mid-drive & called his son.
His son then remotely rerouted the car – which had FSD Supervised enabled – to the nearest hospital & let them know the vehicle was en route. ER staff were standing by on… pic.twitter.com/yi1tHISK9y
— Tesla North America (@tesla_na) June 16, 2026
The Model Y responded immediately, rerouting: it took the next exit, turned around on I-20, navigated local roads, and pulled directly up to the emergency room entrance. Jack also alerted hospital staff that a heart attack patient was en route in a Tesla.
Doctors diagnosed John with a massive STEMI heart attack, requiring immediate intervention on three blocked arteries. They later confirmed that without the swift reroute, John likely would not have survived—whether he had pulled over to wait for an ambulance or attempted to continue driving. He received life-saving treatment and is now recovering fully.
Tesla shared the story on X, including an interview video featuring John and Jack reflecting on the event. John described the terrifying onset of symptoms, while Jack detailed the ease of remote intervention thanks to the app’s features. Only authorized users with vehicle access can change navigation destinations, adding a layer of security and family coordination.
This case underscores Tesla’s emphasis on connectivity and supervised autonomy. Features like remote navigation allow loved ones to assist in real-time emergencies, while FSD handles complex driving tasks reliably. Tesla notes that FSD Supervised requires active driver supervision and is not fully autonomous; this was a specific incident, not a general emergency protocol.
The story has resonated widely, with many praising Tesla’s technology for bridging gaps in critical moments. Jack previously shared details on social media in February 2026, and Tesla’s recent post has amplified its reach. As vehicles become smarter and more connected, such integrations could redefine personal safety on the road—turning cars into proactive partners in health crises.
For Tesla owners, the incident serves as a powerful reminder to add trusted family members as authorized drivers and explore FSD capabilities. While no technology replaces professional medical care, this blend of AI-assisted driving and seamless app control proved invaluable. John’s survival stands as a testament to innovation that prioritizes human life.
In a bold declaration on X, xAI CEO Elon Musk announced that its model will be capable of creating full movies by the end of the year. Quoting an xAI post showcasing a stunning AI-generated trailer for Homer’s The Odyssey, Musk simply stated: “Full movies by the end of the year.”
The quoted video, created entirely with the newly released Grok Imagine Video 1.5, demonstrates the rapid strides in AI video generation. Crafted by creator David Thompson, the 2-minute-plus trailer reimagines the ancient epic in the style of a 1970s classical Hollywood blockbuster. It features 36 meticulously consistent shots that form a cohesive narrative world.
Full movies by the end of this year https://t.co/kkBrngWA0X
— Elon Musk (@elonmusk) June 17, 2026
Its realistic nature is truly mind-blowing, and it’s pretty amazing to think that it cool to think it could create an entire movie soon.
The trailer reimagines The Odyssey as a whole, and opens with a concept board outlining the vision: a retelling of the story using 35mm film aesthetics, classical framing, and other elements.
There are a handful of things that truly outline Grok’s capabilities:
- Scale and Physics: A bloodied Spartan helmet rests on a sandy battlefield amid smoke, marching armies, and flocks of birds. Horses gallop, chariots charge, and warriors clash with believable weight and motion.
- Emotional Depth and Dialogue: Close-ups capture intense expressions, as characters deliver lines like a warrior’s grief-stricken speech on a rocking ship.
- Cinematic Workflow: It’s hard to believe AI created this trailer, as editing and suspense are clearly detailed in this trailer
Now, why is this a big deal? AI has been a real threat to the way movies have been made over the past several decades. It’s no secret that the various AI platforms out there are becoming more capable, but Musk has said that he believes things would be “watchable” by the end of this year, and by the end of 2027, Grok would be able to create “really good” movies.
There are several issues that remain, most notably the ability to remain cohesive throughout the length of a film, energy requirements, copyright questions for training data, and artistic intent. Hollywood has created some of the greatest cinematic masterpieces over the past 100 years, but 2026 could be the year AI not only assists but also independently authors cinema.
Tesla Full Self-Driving is getting a major parking upgrade, Elon Musk says
Tesla Full Self-Driving and App Connectivity save life in medical emergency
