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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 piggybacks recent Supercharger feature with update that takes it further

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Credit: Tesla

Tesla has introduced an enhanced visualization in its Supercharger navigation system, building directly on the Site Maps feature rolled out a few months ago.

This latest software update adds detailed 3D icons that represent specific vehicle models parked at charging stalls, offering drivers a more precise view of site occupancy and layout.

The Site Maps debuted in Tesla’s 2025 Holiday Update, providing 3D overviews of select Supercharger locations with real-time stall availability.

Tesla supplements Holiday Update by sneaking in new Full Self-Driving version

Drivers could see which spots were open, occupied, or out of service when navigating to supported stations.

Now, the system takes this capability further by rendering accurate representations of Tesla vehicles, including distinctions between models such as the Model 3, Model Y, Model S, Model X, and Cybertruck. These icons appear as lifelike 3D renderings, complete with recognizable shapes and proportions that match the actual cars charging at the site:

This refinement improves the user experience during road trips and daily charging stops. As drivers approach a Supercharger, the navigation display now shows not just generic occupied markers but identifiable vehicle types plugged into each stall.

Blue indicators highlight active charging sessions, while other visual cues denote availability or maintenance status. The feature integrates seamlessly with the existing map interface, allowing quick assessment of the best available spot based on vehicle size and positioning.

Tesla continues to expand the availability of these detailed Site Maps across its global network. Initially piloted at a limited number of locations, the rollout has progressed steadily, with more stations gaining support in recent software versions.

Owners benefit from better planning, as the system helps identify compatible stalls and reduces uncertainty upon arrival. The update reflects Tesla’s ongoing commitment to refining its navigation and charging ecosystem through iterative software improvements.

In addition to model-specific icons, the enhanced maps maintain all prior functionalities, such as integration with nearby amenities and energy usage predictions. This ensures a comprehensive tool for efficient Supercharging.

As Tesla’s fleet grows and the network scales, such features play a key role in optimizing the overall ownership experience. Future updates may extend similar visualizations to additional sites and incorporate even more data points for drivers.

With this piggyback enhancement, Tesla demonstrates how small but thoughtful additions can elevate an already useful tool, making Supercharger visits smoother and more informed for its customers. The company is expected to broaden the feature’s reach in upcoming releases, further solidifying its leadership in EV charging infrastructure.

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Tesla Full Self-Driving v14.3.3 driver monitoring: We tested it

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Credit: TESLARATI

Tesla Full Self-Driving v14.3.3 driver monitoring was reportedly scaled back in recent releases, but a new version that was released in the early hours of June 3 aimed to do a better job of keeping those in control of their cars honest, according to release notes.

The release notes for FSD v14.3.3, via Software Version 2026.14.6.7 added:

“Improved driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting conditions.”
However, Tesla said this was already enabled in the first rollout of FSD v14.3.3 in late May. We tested it anyway, especially as the Standard Speed Profile seemed less-than-worried about what you were doing during operation.

I decided to try out the Hurry and Mad Max Speed Profiles for this test, and it gave me results that I would have expected. Tesla has evidently ramped up driver monitoring based on the Speed Profile you are using to travel.

The more aggressive the Speed Profile, the more on the hook you will be for taking your attention away from the road. Our testing showed that Mad Max was less likely to allow you to do normal things like change music or adjust navigation without getting an on-screen warning or nag from the driver monitoring system.

Hurry Mode Results

On Hurry, the driver monitoring system on FSD v14.3.3, via Software Version 2026.14.6.7, was more restrictive than Standard but less restrictive than Mad Max. I found that I could scroll through music options for a considerable amount of time, more than 30 seconds:

Standard gave me about 80 seconds of phone scrolling with absolutely no nags or warnings in a previous test. It is worth noting that this was a previous branch of v14.3.3, but Standard is such a goodie-two-shoes on the road that it is my impression it would not change much.

Mad Max Results

I spent the majority of the drive on Mad Max to see how it truly reacted to the driver having their attention elsewhere. While I did do a short phone test, I am aiming to steer away from those and use the center screen. I think it is a valid criticism that the phone test is dangerous and, not to mention, illegal in Pennsylvania. Changing the navigation and music is a more reasonable, more responsible, and safer test.

With Mad Max being the fastest and most aggressive Speed Profile, I anticipated this being the quickest mode to give me an alert that I needed to look at the road. That was the case with music:

As well as adjusting Navigation, when I received two nags:

These nags were more than reasonable, and I think it’s probably good that Tesla is ramping up the driver monitoring. I do believe that it should be relatively strict across all of the Speed Profiles, especially with phone use. When using the center screen, the nag intervals should be based on the speed profile you are utilizing at the time.

These driver monitoring adjustments are a great thing to have while FSD is still under its “Supervised” moniker, but I expect Tesla to continue pushing the limits on what it will allow, especially considering CEO Elon Musk has hinted that phone use is capable with the more recent versions.

You can watch the full drive on YouTube below:

 

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Tesla responds to Robotaxi skeptics with a massive move in Austin

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Credit: @AdanGuajardo/X

Tesla has responded to the skeptics of its Robotaxi program by launching a massive expansion of the unsupervised program in its initial rollout city of Austin.

The company’s geofence, the enabled area of operation for rides, now covers the entire Austin Metropolitan area, an incredible move just days after media headlines attempted to discredit the ride-hailing service.

Those who have access to the Tesla Robotaxi app on their smartphones can now request a ride in any portion of the Austin Metro area. The company confirmed this on the social media platform X:

This is Tesla’s fifth expansion of the geofence, with the others occurring in July, early August, late August, and late October 2025. It has remained at that size since October 26, but Tesla has now more than doubled that size.

It is now covering the entire area, including suburbs like Pflugerville and Manor, as well as I-35 highways, Gigafactory Texas, and the Austin-Bergstrom Airport.

The move comes just days after various media outlets highlighted the small fleet size of Tesla’s Robotaxi fleet in Austin, something that is a reasonable criticism but an understandable move on the company’s part to prioritize safety.

Tesla expands Robotaxi geofence, but not the garage

Tesla has expanded its Robotaxi geofence many times, but its fleet has remained at a relatively conservative size as the company continues to push safety as its most crucial metric.

The latest expansion is a key indicator of Tesla’s comfort level to expand the ride-hailing service. The move shows Tesla is scaling unsupervised autonomy, as it demonstrates that the company’s Full Self-Driving system has reached sufficient reliability for a broader real-world deployment, which is something the company has worked on extensively.

It also shows Tesla is game for a competition with its rivals in the autonomous ride-hailing sector. Tesla has often matched or exceeded competitors like Waymo in coverage area, despite its smaller fleet. This step highlights Tesla’s iterative, data-driven progress toward a high-margin, app-based Robotaxi network.

It’s not the absolute largest area expansion ever, but achieving full unsupervised operations across a major metro is a key moment in the Robotaxi story. It shifts the program from limited pilot/testing toward a more mature commercial service, while gathering the miles needed for faster growth.

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