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Tesla AI Day News Roundup: Optimus, FSD Beta & Dojo updates

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Tesla AI Day has officially kicked off. Guests have started entering the venue already.

AI Day is an event mainly held to recruit talented people and welcome them to Tesla. However, it is still a Tesla event, so everyone expects some product surprises and updates, specifically about the company’s humanoid robot, Optimus, Dojo, and Full Self-Driving.

Teslarati will be closely following the event. This is our news roundup for 2022 AI Day, covering key information Tesla reveals at the event.

Photos and Videos aren’t allowed during the event from attendees. However, guests were able to capture some cool photos of a Tesla Semi with Cybertruck graffiti, a literal fork on the road, and some other cool set ups around the premises.

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Tesla’s former AI Head, Andrej Karpathy, has brought out the (metaphorical) popcorn. His brief “comment” hints that AI Day 2022 might be as exciting as everyone anticipates.

Elon Musk set some expectations about Optimus, reminding everyone that during AI Day 2021, Tesla’s humanoid bot was just “a guy in a robot suit.” Musk also laid out the topics for AI Day 2022, saying that Tesla will talk about Autopilot and Dojo, too.

Optimus Takes the Stage

Tesla didn’t waste any time and brought out Optimus immediately. According to a Tesla mechanical engineer, AI Day 2022 is the first time Optimus has been “let out”– so to speak– without any external support.

“This is literally the first time the robot has walked on stage without a tether, on stage tonight,” Musk added. “The robot can actually do a lot more than we showed you. We just don’t want it to fall on its face.”

Tesla reveals videos of Optimus or in this case “Bumble-Cee” doing “work” around the Tesla office. Optimus carried a box from one area to another, watered plants, and even worked at the factory for a bit. The Tesla bot’s vision is very similar Autopilot.

Tesla also revealed Optimus’ potential final unit one production design. “Our goal is to make a useful humanoid robot as soon as possible,” said Elon Musk. The Tesla CEO also shared that Tesla aims to make Optimus’ price less than $20,000 or cheaper than a car.

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Tesla is using some of the technology in its car in Optimus’ body as well, such as the battery pack, cooling system and more. The company also uses that same technology it uses for its cars to simulate Optimus’ movements and reactions to external collisions.

Tesla is basing Optimus’ body design on the human body. The company has been closely studying the structure of the human body while making the humanoid robot’s overall design. For instance, Tesla designed Optimus’ hands with the idea that factories worldwide are designed ergonomically, or optimized for the human hand. Teslarati briefly covered the significance of robots’ hands in a previous article, linked below.

FSD Beta Updates

The Tesla FSD Beta now has 160,000 customers, compared to 2,000 customers in 2021. Tesla is expected to release v.10.69.2.3 after AI Day, although a precise roll out date has not be announced yet.

Tesla explained the progress its made with Full Self-Driving Beta. The Tesla FSD experts explained how the Full Self-Driving makes decision to AI day guests and the role that customer data played to refine the software. The company also explained occupancy and the role it plays with 3D mapping and providing a birds-eye-view for the car. Tesla is working hard to optimize its video model training as well.

Tesla also talked a lot about its FSD Lane Networks during AI Day 2022. In the past few weeks, Teslarati has received reports from FSD testers, who specifically brought up issues with lane selection. To see “under the hood”–so to speak–somewhat explains the lane issues FSD testers experience on the road.

After multiple test loops and drives, there’s really just one main problem remaining for me at this point on 10.69.2, it’s significant, and that is lane selection,” noted long-time FSD tester Les. 

Tesla has developed a new auto-labeling machine to help with 3D labeling. The FSD experts explained how the software uses other clips to fill out the picture under certain conditions when the camera shows an unclear picture.

Tesla also talked a bit about simulation. The experts showed how it could simulate worlds or environments, using the data gathered from its fleet. It revealed a simulation of San Francisco that was created within two weeks by one employee. Tesla may update a simulated world quickly and as updated develop.

Dojo Updates

Tesla’s goal with Dojo is to build a single accelerator. A key step to realizing its goals was its training tile, which it unveiled during AI Day 2021. Tesla has been trying to figure out how to make its Dojo design scalable and has run into challenges along the way. However, the company’s “fail fast” mindset has helped it push through road blocks and move forward.

The Dojo team showed images of a Cybertruck and Semi running on Mars using stable diffusion achieved through Dojo.

Tesla experts explained that Dojo reduced work that would usually take months to a single week.

Tesla plans to build its first Exapod by 2023, which is expected to significantly increase its autolabeling output . It will be the first Exapod of 7 that Tesla plans to build in Palo Alto.

Tesla ended AI Day 2022 by answering questions from attendees. Tesla hopes that through their thorough explanations during the event, the company would be seen as more than an automaker. And, of course, Tesla hopes that its AI Day 2022 presentation also entices talented individuals to join the company.

The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101

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Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Tesla urges New Jersey owners to oppose new bill that could block Robotaxi

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Credit: Grok

Tesla has launched a direct campaign targeting its customers in New Jersey, sending emails that warn of pending legislation that could effectively block true driverless technology in the state.

The email focuses on Senate Bill S.1677 and Assembly Bill A.3968, measures intended to create a three-year autonomous vehicle pilot program but laden with requirements that Tesla argues make unsupervised Robotaxis impossible.

According to the email, the bills impose “restrictions so severe that true driverless deployment would remain illegal.” Specific hurdles include mandates for human safety drivers during operations, multimillion-dollar insurance minimums, reportedly $5 million, and thresholds like 100,000 miles of demonstrated safe autonomous driving before any driverless approval.

Tesla contends these are arbitrary barriers that ignore real-world performance data and favor entrenched competitors over innovative technologies like its Full Self-Driving (FSD) system.

The push comes as Tesla has started expanding Robotaxi operations in states like Texas, where unsupervised vehicles are already providing rides in several cities. New Jersey, by contrast, risks falling behind. The company highlights in the email communication that more than 94 percent of serious crashes result from human error, meaning impairment, distraction, or fatigue. These are all problems that Robotaxis eliminate entirely.

In 2025, New Jersey recorded 582 traffic deaths, underscoring the human cost of delayed adoption.

Tesla’s outreach stresses the transformative potential of robotaxis. For families, they could offer safer school runs without drowsy or distracted drivers. For seniors and people with disabilities, robotaxis promise independence and reliable mobility.

In areas with limited public transit, they could deliver affordable, on-demand transportation, reducing congestion, emissions, and overall transportation costs. Economically, the company warns that restrictive rules could cost New Jersey jobs, innovation investment, and billions in potential growth as autonomous ride-hailing scales elsewhere.

Supporters of the legislation, including Sen. Andrew Zwicker, describe the pilot as a cautious framework with strong safety oversight, including incident reporting, expert task forces, and restrictions in sensitive zones like school areas. They view it as balancing innovation with public protection.

Tesla and pro-AV advocates counter that the bill lacks technology neutrality, creates insurmountable entry barriers for commercial deployment, and prioritizes process over outcomes — effectively functioning as a de facto ban on services like Robotaxi.

This latest clash echoes Tesla’s past battles in New Jersey over direct vehicle sales. The email directs owners to Tesla’s advocacy platform, where they can send customized messages to legislators calling for amendments: outcome-based safety standards, open competition, and clear pathways for fully driverless commercial operations.

As hearings approach, Tesla’s campaign frames the issue as a choice between protecting the status quo and embracing life-saving progress. With robotaxi technology already proving itself in permissive states, New Jersey owners are being asked to ensure their state doesn’t lock out the future of transportation.

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Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest

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Credit: TESLARATI

Turn-by-turn navigation is not new technology.

For over two decades, drivers have relied on Garmin, TomTom, and later smartphone apps like Google Maps and Waze to receive precise, reliable directions. These systems have guided millions safely through unfamiliar cities, highways, and backroads with remarkable effectiveness. They handle real-time traffic, construction detours, and complex intersections with minimal fuss.

Yet Tesla, the company that promised revolutionary Full Self-Driving (FSD), continues to struggle with this foundational capability. As FSD (Supervised) v14.3.4 has started rolling out to cars this week, navigation remains its glaring Achilles’ heel, undermining the entire autonomous vision.

Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much

Tesla’s FSD excels in many driving behaviors—smooth acceleration, confident lane changes in ideal conditions, and responsive handling of visible obstacles. However, when it comes to following a route accurately, the system falters repeatedly.

Owners report wrong turns, missed exits, inefficient routing through local roads instead of highways, phantom speed limit errors, and even directing vehicles to building rear entrances. Interventions for navigation issues often outnumber those for core driving maneuvers. Tesla has begun surveying owners specifically about these errors, acknowledging the problem after years of complaints.

Navigation is perhaps my biggest complaint when it comes to FSD, because sometimes, we do know better. Some of us have been living in our areas for our entire lives, but even those who have not have years or even decades of experience driving on local roads. We might know a little better about routing.

But the navigation mistakes are more than just FSD potentially taking a slightly different route that may or may not save you a few minutes. Sometimes, they’re genuinely mind-boggling.

This isn’t just annoying; it cascades into broader failures. A flawed route plan confuses the AI’s decision-making, leading to hesitant behavior, unnecessary disengagements, or dangerous maneuvers like attempting impossible U-turns or ignoring clear ramps. In a system meant to operate with minimal supervision, unreliable navigation erodes trust.

More often than not, false or plain incorrect navigation is what causes me to interrupt FSD operation. Unfortunately, I believe the latest FSD version is the worst example of it, and it leads me to believe that Tesla might be making some changes; they’ve just made them in the wrong direction.

It makes you wonder: Why is a company that has done so much with the progress of FSD and autonomy struggling so much with navigation, something that is not new and has been around a long time?

Multiple Data Sources

First, Tesla’s navigation relies on a fragile patchwork of multiple data sources—Google Maps, TomTom, OpenStreetMap, Valhalla, and its own fleet-derived data—stitched together rather than a single authoritative map. When these conflict on lane geometry, road status, or turn details, the system hesitates or chooses incorrectly.

Traditional GPS providers maintain centralized, regularly validated databases with professional curation and rapid updates. Tesla’s hybrid approach, while innovative in crowdsourcing, introduces inconsistencies that a purely vision-based or end-to-end AI approach may not easily reconcile in real time.

Persistent Learning

FSD seems to struggle with persistent learning from driver interventions.

Unlike consumer apps that quickly adapt to repeated corrections or user preferences (e.g., avoiding certain routes or remembering habitual detours), Tesla’s FSD often fails to internalize fixes on the same trip or across similar scenarios. Owners note making the same manual override multiple times without the routing engine updating its behavior meaningfully.

This stems from the neural architecture prioritizing real-time perception and control over long-term route memory and personalization, making navigation feel rigid and “opinionated” compared to the adaptive logic in Waze or Google Maps.

I noticed that when I asked Grok to try and get me home a certain way (a way that FSD routinely took in the past because it was the most efficient), it had to place a waypoint between my location at the time and my house. When I went to edit the waypoint out, as Grok had placed it for a way to get FSD to get off the highway at the right exit, it was stumped again, rerouted, and took a longer way home.

Reasoning, Scaling, and Intuition

Third, scaling navigation for unsupervised or robotaxi ambitions requires not just accuracy but adaptability and user-like reasoning. Current FSD often defaults to single routes that ignore driver preferences or real-world nuances like time-of-day traffic patterns. It fails to match the intuitive, context-aware planning that traditional systems have refined over the years.

Resolving navigation is critical for several reasons. Practically, it is the backbone of any autonomous journey: without trustworthy routing, the car cannot reliably reach destinations, rendering FSD useless for robotaxis or hands-free commutes. Safety depends on it—mismatched plans create hesitation in merges or intersections, increasing accident risk.

Economically, Tesla’s valuation and future hinge on FSD delivering unsupervised driving; persistent navigation flaws delay regulatory approval and erode consumer confidence. For owners who paid premiums for FSD, these issues represent unfulfilled promises. While it is unlikely Tesla will lose too many customers due to bad navigation, some will be frustrated with the constant need for human input.

Tesla has achieved miracles in electric vehicles and battery tech. Mastering turn-by-turn—technology Garmin nailed in the early 2000s—should not be this hard. By investing in tighter data integration, faster learning loops from interventions, and more intuitive routing algorithms, Tesla could close this gap.

Until then, FSD’s navigation struggles highlight a humbling truth: even the most ambitious innovator must sometimes master the basics before conquering the future.

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Tesla Cybertruck driver gets pickup seized for ‘legitimate concerns’ in UK

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A Tesla Cybertruck driver in the United Kingdom had their all-electric pickup seized by local police in the Greater Manchester area after the department cited “legitimate concerns.”

Last Thursday, police saw the pickup on the roads and decided to pull the driver over. Greater Manchester Police said:

“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a collision with the Cybertruck.”

The Cybertruck in question was, according to the BBC, registered and insured abroad and was confiscated. The driver, who is a UK resident, was reported.

The Greater Manchester Police Department then added:

“The Tesla Cybertruck is not road-legal in the UK and does not hold a certificate of conformity.”

The Cybertruck cannot be legally driven in the UK because it has no UK Type Approval for operation in the country. This is due to some safety concerns, which are related to its angular shape and design. The stainless steel exoskeleton has sharp edges and projections that violate UK/EU rules on pedestrian protection.

Tesla has considered creating what it referred to as an “international version” that would be approved for operation in Europe. However, there has been no real movement on that front by the company, as it has been focused on the Robotaxi rollout primarily.

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