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.
Elon Musk
Tesla FSD in Europe vs. US: It’s not what you think
Tesla FSD is approved in the Netherlands, but the European version differs from what US drivers use.
On April 10, 2026, the Dutch vehicle authority RDW granted Tesla the first European type approval for Full Self-Driving Supervised, making the Netherlands the first country on the continent to authorize Tesla’s semi-autonomous system for customer use on public roads.
As Teslarati reported, the RDW approval followed 18 months of testing, more than 1.6 million kilometers driven on EU roads, 13,000 customer ride-alongs, and documentation covering over 400 compliance requirements. Tesla Europe had been running public demo drives through cities like Amsterdam and Eindhoven since early 2026, giving passengers their first experience of the system on European streets.
The European version of FSD is not the same software US drivers use. The RDW’s own statement is direct, noting that the software versions and functionalities in the US and Europe “are therefore not comparable one-to-one.” We’ve compile a table below that captures the most significant differences between US-based Tesla FSD vs. European Tesla FSD that’s based on what regulators and Tesla have publicly confirmed.
| Feature | FSD US | FSD Europe (Netherlands) |
| Regulatory framework | Self-certification, post-market oversight | Pre-market type approval required (UN R-171 + Article 39) |
| Hands requirement | Hands-off permitted on highway | Hands must be available to take over immediately |
| Auto turning from stop lights | Available — navigates intersections, turns, and traffic signals autonomously | Available in EU build — confirmed in Amsterdam demo footage handling unprotected turns and signalized intersections |
| Driving modes | Multiple profiles including a more aggressive “Mad Max” mode | EU build is more conservative by default and errs on the side of restraint when it cannot confirm the limit |
| Summon | Available — Smart Summon navigates parking lots to driver | Status unclear — not confirmed as part of the RDW-approved feature set; urban FSD approval targeted separately for 2027 |
| Driver monitoring | Camera-based eye tracking | Stricter continuous monitoring with more frequent intervention alerts |
| Software version | FSD v14.3 | EU-specific builds that must be separately validated by RDW |
| Geographic restriction | US, Canada, China, Mexico, Australia, NZ, South Korea | Netherlands only; EU-wide vote pending summer 2026 |
| Subscription price | $99/month | €99/month |
| Full urban FSD scope | Available | Partial — separate urban application planned for 2027 |
The approval comes as Tesla is under real pressure to grow FSD subscriptions globally. Musk’s 2025 CEO compensation package, approved by shareholders, includes a milestone requiring 10 million active FSD subscriptions as one condition for his stock awards to vest. Tesla hit one million subscriptions during its Q4 2025 earnings call, which is a meaningful start, but still a long way from the target. Opening Europe as a market for subscriptions, rather than just hardware sales, directly accelerates that number.
Tesla has said it anticipates EU-wide recognition of the Dutch approval during summer 2026, which would extend FSD access to Germany, France, and other major markets through a mutual recognition process without each country repeating the full 18-month review. That timeline is Tesla’s projection, not a confirmed regulatory outcome. As Musk acknowledged at Davos in January 2026, “We hope to get Supervised Full Self-Driving approval in Europe, hopefully next month.”
News
Tesla’s troublesome Auto Wipers get a major upgrade
Tesla has quietly deployed a major over-the-air (OTA) update across its entire fleet, implementing a new patent that could finally solve one of the most complained-about features in its vehicles: the Auto Wipers.
One of Tesla’s most complained-about features is that of the Auto Wipers, but they have recently received a major upgrade that impacts every vehicle in the company’s fleet, a company executive confirmed.
Tesla has quietly deployed a major over-the-air (OTA) update across its entire fleet, implementing a new patent that could finally solve one of the most complained-about features in its vehicles: the Auto Wipers.
Confirmed by senior Tesla AI engineer Yun-Ta Tsai on April 10, the improvement is based on patent US 20260097742 A1. It introduces an “energy balance model” that adds a tactile, physics-driven layer to the existing camera-based system—without requiring any new hardware.
🚨 Tesla has already implemented a new patent that improves the accuracy of the Auto Wiper system https://t.co/QjjKHKxSNv pic.twitter.com/mEbd04oJAu
— TESLARATI (@Teslarati) April 10, 2026
Tesla drivers have griped about auto wipers since the company ditched traditional rain sensors in favor of Tesla Vision around 2018.
Owners routinely report the wipers failing to activate in light drizzle or mist, leaving windshields streaked and visibility dangerously reduced. Just as often, they formerly blasted into high-speed mode on dry, sunny days, screeching across glass and risking scratches or premature blade wear.
This is a rare occurrence anymore, but many owners still report the feature having the wipers perform at the incorrect speed or frequency when precipitation is falling.
Tesla has tried repeatedly to fix the problem through software alone.
Early “Deep Rain” initiatives and the 2023 Autowiper v4 update used multi-camera video and refined neural networks, with Elon Musk promising “super good” performance. The 2024.14 update added manual sensitivity boosts, and later FSD versions claimed further gains. Yet complaints persisted.
Elon Musk apologizes for Tesla’s quirky auto wipers, hints at improvements
Vision systems struggle with edge cases—glare, bugs, reflections, or faint mist—because they rely purely on visual inference rather than physical detection
The new patent takes a different approach. The car’s computer constantly measures electrical power delivered to the wiper motor. It subtracts predictable losses—internal motor friction, linkage drag, and aerodynamic resistance—leaving only the friction force between the rubber blade and windshield glass.
Water lubricates the glass, sharply reducing friction; dry or icy surfaces increase it dramatically. This real-time “tactile” data acts as an independent check on the camera’s visual cues, instantly shutting down false triggers on dry glass and fine-tuning speed for actual rain.
The system can also detect ice and auto-activate defrost heaters, while long-term friction trends alert drivers when blades need replacing.
By fusing vision with precise motor-load physics, Tesla has created a hybrid sensor that is both elegant and cost-free. Owners have waited years for reliable auto wipers; this OTA rollout may finally deliver them.
News
Tesla Roadster unveiling set for this month: what to expect
As Tesla finally edges toward production and an updated reveal, enthusiasts aren’t asking for compromises; they’re demanding the original vision be honored. Here are five clear expectations that will come with the vehicle’s unveiling, which is still set for later this month, hopefully.
The Tesla Roadster has been the ultimate carrot on a stick since its 2017 unveiling. Promised as the fastest production car ever made, with 0-60 mph in under two seconds and a top speed over 250 mph, it has endured years of delays.
As Tesla finally edges toward production and an updated reveal, enthusiasts aren’t asking for compromises; they’re demanding the original vision be honored. Here are five clear expectations that will come with the vehicle’s unveiling, which is still set for later this month, hopefully.
Performance and Safety Do Not Go Hand in Hand, and That’s the Point
The Roadster is not a family sedan or a daily commuter. It is a no-holds-barred supercar meant to embarrass six-figure exotics on track days. Tesla should resist the temptation to load it with every passive-safety nanny and electronic guardian that dulls the raw feedback drivers crave.
Owners want to feel the road, not be shielded from it. Strip away unnecessary electronic limits so the car can deliver the visceral thrill Elon Musk originally described. Safety ratings will still be strong because of Tesla’s structural excellence, but the Roadster’s mission is speed, not coddling.
He said late last year:
“This is not a…safety is not the main goal. If you buy a Ferrari, safety is not the number one goal. I say, if safety is your number one goal, do not buy the Roadster…We’ll aspire not to kill anyone in this car. It’ll be the best of the last of the human-driven cars. The best of the last.”
Musk was clear that this will not be a car that will be the safest in Tesla’s lineup, but that’s the point. It’s not made for anything other than pushing the limits.
Tesla Needs to Come Through on a HUGE Feature
The Roadster unveiling would be wildly disappointing if it were only capable of driving. Tesla has long teased the potential ability to float or hover, and they need to come through on something that is along those lines.
The SpaceX cold-gas thruster package was never a joke. Musk, at one time, explicitly said owners could opt for a set of thrusters capable of lifting the car off the ground for short hops or dramatic launches. That feature is what separates the Roadster from every other hypercar on the planet.
If the production version arrives without it—or with a watered-down “maybe later” version—enthusiasts will feel betrayed. Deliver the thrusters, make them functional, and let the Roadster literally hover above the competition.
An Updated Design Might Be Warranted
It’s been nine years since Tesla first rolled off the next-gen Roadster design and showed it to the world.
The 2017 concept still looks sharp, but eight years is an eternity in automotive styling. The sharp lines and aggressive stance now compete against the angular Cybertruck and the next-generation vehicles rolling out of Fremont and Austin.
Tesla Roadster patent hints at radical seat redesign ahead of reveal
A subtle refresh, maybe with sharper headlights, revised aero elements, and modern materials, would keep the Roadster feeling current without losing its identity. Fans don’t want a complete redesign, just enough evolution to prove Tesla still cares.
Self-Driving Isn’t a Necessity for the Tesla Roadster
Full Self-Driving hardware and software belong in the Model 3, Model Y, and the upcoming robotaxi—not in a two-seat rocket built for canyon carving. The Roadster’s entire appeal is the direct connection between driver, steering wheel, and asphalt.
Offering FSD as standard would dilute the purity that separates it from every other Tesla. Make autonomy an optional delete or simply omit it. Let the Roadster remain the purest driving machine in the lineup, because that’s what it is all about.
Tesla Needs to Come Through on the Unveiling Timeline
The last thing Tesla needs right now is another complaint about not hitting timelines or expectations. This unveiling has already been pushed back one time, from April 1 to “probably in late April.”
Repeated delays have tested even the most patient fans. Whatever date the company now sets for the next major reveal or start of production must be met. No more “next year” promises. The Roadster has waited long enough. When it finally arrives, it must feel worth every extra month.
If Tesla hits these five marks, the Roadster won’t just be another fast car—it will be the machine that redefines what a Tesla can be. The world is watching.
Tesla FSD in Europe vs. US: It’s not what you think
Tesla’s troublesome Auto Wipers get a major upgrade
