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 Full Self-Driving shows confident navigation in heavy snow
So far, from what we’ve seen, snow has not been a huge issue for the most recent Full Self-Driving release. It seems to be acting confidently and handling even snow-covered roads with relative ease.
Tesla Full Self-Driving is getting its first taste of Winter weather for late 2025, as snow is starting to fall all across the United States.
The suite has been vastly improved after Tesla released v14 to many owners with capable hardware, and driving performance, along with overall behavior, has really been something to admire. This is by far the best version of FSD Tesla has ever released, and although there are a handful of regressions with each subsequent release, they are usually cleared up within a week or two.
Tesla is releasing a modified version of FSD v14 for Hardware 3 owners: here’s when
However, adverse weather conditions are something that Tesla will have to confront, as heavy rain, snow, and other interesting situations are bound to occur. In order for the vehicles to be fully autonomous, they will have to go through these scenarios safely and accurately.
One big issue I’ve had, especially in heavy rain, is that the camera vision might be obstructed, which will display messages that certain features’ performance might be degraded.
So far, from what we’ve seen, snow has not been a huge issue for the most recent Full Self-Driving release. It seems to be acting confidently and handling even snow-covered roads with relative ease:
FSD 14.1.4 snow storm Ontario Canada pic.twitter.com/jwK1dLYT0w
— Everything AI (@mrteslaspace) November 17, 2025
I found the steepest, unplowed hill in my area and tested the following:
• FSD 14.2.1 on summer tires
• FSD 14.2.1 on winter tires
• Manual drivingBut I think the most impressive part was how FSD went DOWN the hill. FSD in the snow is sublime $TSLA pic.twitter.com/YMcN7Br3PU
— Dillon Loomis (@DillonLoomis) December 2, 2025
Well.. I couldn’t let the boys have all the fun!
Threw the GoPro up and decided to FSD v14.2.1 in the snow. Roads were not compacted like the other day, a little slippery, but overall doable at lower speeds. Enjoy the video and holiday music 🎶
Liked:
Took turns super slow… pic.twitter.com/rIAIeh3Zu3— 🦋Diana🦋 (@99_Colorado) December 3, 2025
Moving into the winter months, it will be very interesting to see how FSD handles even more concerning conditions, especially with black ice, freezing rain and snow mix, and other things that happen during colder conditions.
We are excited to test it ourselves, but I am waiting for heavy snowfall to make it to Pennsylvania so I can truly push it to the limit.
News
Tesla hosts Rome Mayor for first Italian FSD Supervised road demo
The event marked the first time an Italian mayor tested the advanced driver-assistance system in person in Rome’s urban streets.
Tesla definitely seems to be actively engaging European officials on FSD’s capabilities, with the company hosting Rome Mayor Roberto Gualtieri and Mobility Assessor Eugenio Patanè for a hands-on road demonstration.
The event marked the first time an Italian mayor tested the advanced driver-assistance system in person in Rome’s urban streets. This comes amid Tesla’s push for FSD’s EU regulatory approvals in the coming year.
Rome officials experience FSD Supervised
Tesla conducted the demo using a Model 3 equipped with Full Self-Driving (Supervised), tackling typical Roman traffic including complex intersections, roundabouts, pedestrian crossings and mixed users like cars, bikes and scooters.
The system showcased AI-based assisted driving, prioritizing safety while maintaining flow. FSD also handled overtakes and lane decisions, though with constant driver supervision.
Investor Andrea Stroppa detailed the event on X, noting the system’s potential to reduce severe collision risks by up to seven times compared to traditional driving, based on Tesla’s data from billions of global fleet miles. The session highlighted FSD’s role as an assistance tool in its Supervised form, not a replacement, with the driver fully responsible at all times.
Path to European rollout
Tesla has logged over 1 million kilometers of testing across 17 European countries, including Italy, to refine FSD for local conditions. The fact that Rome officials personally tested FSD Supervised bodes well for the program’s approval, as it suggests that key individuals are closely watching Tesla’s efforts and innovations.
Assessor Patanè also highlighted the administration’s interest in technologies that boost road safety and urban travel quality, viewing them as aids for both private and public transport while respecting rules.
Replies on X urged involving Italy’s Transport Ministry to speed approvals, with one user noting, “Great idea to involve the mayor! It would be necessary to involve components of the Ministry of Transport and the government as soon as possible: it’s they who can accelerate the approval of FSD in Italy.”
News
Tesla FSD (Supervised) blows away French journalist after test ride
Cadot described FSD as “mind-blowing,” both for the safety of the vehicle’s driving and the “humanity” of its driving behaviors.
Tesla’s Full Self-Driving (Supervised) seems to be making waves in Europe, with French tech journalist Julien Cadot recently sharing a positive first-hand experience from a supervised test drive in France.
Cadot, who tested the system for Numerama after eight years of anticipation since early Autopilot trials, described FSD as “mind-blowing,” both for the safety of the vehicle’s driving and the “humanity” of its driving behaviors.
Julien Cadot’s FSD test in France
Cadot announced his upcoming test on X, writing in French: “I’m going to test Tesla’s FSD for Numerama in France. 8 years I’ve been waiting to relive the sensations of our very first contact with the unbridled Autopilot of the 2016s.” He followed up shortly after with an initial reaction, writing: “I don’t want to spoil too much because as media we were allowed to film everything and I have a huge video coming… But: it’s mind-blowing! Both for safety and for the ‘humanity’ of the choices.”
His later posts detailed FSD’s specific maneuvers that he found particularly compelling. These include the vehicle safely overtaking a delivery truck by inches, something Cadot said he personally would avoid to protect his rims, but FSD handled flawlessly. He also praised FSD’s cyclist overtakes, as the system always maintained the required 1.5-meter distance by encroaching on the opposite lane when clear. Ultimately, Cadot noted FSD’s decision-making prioritized safety and advancement, which is pretty remarkable.
FSD’s ‘human’ edge over Autopilot
When asked if FSD felt light-years ahead of standard Autopilot, Cadot replied: “It’s incomparable, it’s not the same language.” He elaborated on scenarios like bypassing a parked delivery truck across a solid white line, where FSD assessed safety and proceeded just as a human driver might, rather than halting indefinitely. This “humanity” impressed Cadot the most, as it allowed FSD to fluidly navigate real-world chaos like urban Paris traffic.
Tesla is currently hard at work pushing for the rollout of FSD to several European countries. Recent reports have revealed that Tesla has received approval to operate 19 FSD test vehicles on Spain’s roads, though this number could increase as the program develops. As per the Dirección General de Tráfico (DGT), Tesla would be able to operate its FSD fleet on any national route across Spain. Recent job openings also hint at Tesla starting FSD tests in Austria. Apart from this, the company is also holding FSD demonstrations in Germany, France, and Italy.
Tesla Full Self-Driving shows confident navigation in heavy snow
Tesla hosts Rome Mayor for first Italian FSD Supervised road demo
