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Tesla FSD Beta 10.69.2.2 extending to 160k owners in US and Canada: Elon Musk

Credit: Whole Mars Catalog

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It appears that after several iterations and adjustments, FSD Beta 10.69 is ready to roll out to the greater FSD Beta program. Elon Musk mentioned the update on Twitter, with the CEO stating that v10.69.2.2. should extend to 160,000 owners in the United States and Canada. 

Similar to his other announcements about the FSD Beta program, Musk’s comments were posted on Twitter. “FSD Beta 10.69.2.1 looks good, extending to 160k owners in US & Canada,” Musk wrote before correcting himself and clarifying that he was talking about FSD Beta 10.69.2.2, not v10.69.2.1. 

While Elon Musk has a known tendency to be extremely optimistic about FSD Beta-related statements, his comments about v10.69.2.2 do reflect observations from some of the program’s longtime members. Veteran FSD Beta tester @WholeMarsBlog, who does not shy away from criticizing the system if it does not work well, noted that his takeovers with v10.69.2.2 have been marginal. Fellow FSD Beta tester @GailAlfarATX reported similar observations. 

Tesla definitely seems to be pushing to release FSD to its fleet. Recent comments from Tesla’s Senior Director of Investor Relations Martin Viecha during an invite-only Goldman Sachs tech conference have hinted that the electric vehicle maker is on track to release “supervised” FSD around the end of the year. That’s around the same time as Elon Musk’s estimate for FSD’s wide release. 

It should be noted, of course, that even if Tesla manages to release “supervised” FSD to consumers by the end of the year, the version of the advanced driver-assist system would still require drivers to pay attention to the road and follow proper driving practices. With a feature-complete “supervised” FSD, however, Teslas would be able to navigate on their own regardless of whether they are in the highway or in inner-city streets. And that, ultimately, is a feature that will be extremely hard to beat. 

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Following are the release notes of FSD Beta v10.69.2.2, as retrieved by NotaTeslaApp

– Added a new “deep lane guidance” module to the Vector Lanes neural network which fuses features extracted from the video streams with coarse map data, i.e. lane counts and lane connectivities. This architecture achieves a 44% lower error rate on lane topology compared to the previous model, enabling smoother control before lanes and their connectivities becomes visually apparent. This provides a way to make every Autopilot drive as good as someone driving their own commute, yet in a sufficiently general way that adapts for road changes.

– Improved overall driving smoothness, without sacrificing latency, through better modeling of system and actuation latency in trajectory planning. Trajectory planner now independently accounts for latency from steering commands to actual steering actuation, as well as acceleration and brake commands to actuation. This results in a trajectory that is a more accurate model of how the vehicle would drive. This allows better downstream controller tracking and smoothness while also allowing a more accurate response during harsh maneuvers.

– Improved unprotected left turns with more appropriate speed profile when approaching and exiting median crossover regions, in the presence of high speed cross traffic (“Chuck Cook style” unprotected left turns). This was done by allowing optimisable initial jerk, to mimic the harsh pedal press by a human, when required to go in front of high speed objects. Also improved lateral profile approaching such safety regions to allow for better pose that aligns well for exiting the region. Finally, improved interaction with objects that are entering or waiting inside the median crossover region with better modeling of their future intent.

– Added control for arbitrary low-speed moving volumes from Occupancy Network. This also enables finer control for more precise object shapes that cannot be easily represented by a cuboid primitive. This required predicting velocity at every 3D voxel. We may now control for slow-moving UFOs.

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– Upgraded Occupancy Network to use video instead of images from single time step. This temporal context allows the network to be robust to temporary occlusions and enables prediction of occupancy flow. Also, improved ground truth with semantics-driven outlier rejection, hard example mining, and increasing the dataset size by 2.4x.

– Upgraded to a new two-stage architecture to produce object kinematics (e.g. velocity, acceleration, yaw rate) where network compute is allocated O(objects) instead of O(space). This improved velocity estimates for far away crossing vehicles by 20%, while using one tenth of the compute.

– Increased smoothness for protected right turns by improving the association of traffic lights with slip lanes vs yield signs with slip lanes. This reduces false slowdowns when there are no relevant objects present and also improves yielding position when they are present.

– Reduced false slowdowns near crosswalks. This was done with improved understanding of pedestrian and bicyclist intent based on their motion.

– Improved geometry error of ego-relevant lanes by 34% and crossing lanes by 21% with a full Vector Lanes neural network update. Information bottlenecks in the network architecture were eliminated by increasing the size of the per-camera feature extractors, video modules, internals of the autoregressive decoder, and by adding a hard attention mechanism which greatly improved the fine position of lanes.

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– Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.

– Improved recall of animals by 34% by doubling the size of the auto-labeled training set.

– Enabled creeping for visibility at any intersection where objects might cross ego’s path, regardless of presence of traffic controls.

– Improved accuracy of stopping position in critical scenarios with crossing objects, by allowing dynamic resolution in trajectory optimization to focus more on areas where finer control is essential.

– Increased recall of forking lanes by 36% by having topological tokens participate in the attention operations of the autoregressive decoder and by increasing the loss applied to fork tokens during training.

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– Improved velocity error for pedestrians and bicyclists by 17%, especially when ego is making a turn, by improving the onboard trajectory estimation used as input to the neural network.

– Improved recall of object detection, eliminating 26% of missing detections for far away crossing vehicles by tuning the loss function used during training and improving label quality.

– Improved object future path prediction in scenarios with high yaw rate by incorporating yaw rate and lateral motion into the likelihood estimation. This helps with objects turning into or away from ego’s lane, especially in intersections or cut-in scenarios.

– Improved speed when entering highway by better handling of upcoming map speed changes, which increases the confidence of merging onto the highway.

– Reduced latency when starting from a stop by accounting for lead vehicle jerk.

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– Enabled faster identification of red light runners by evaluating their current kinematic state against their expected braking profile.

Press the “Video Record” button on the top bar UI to share your feedback. When pressed, your vehicle’s external cameras will share a short VIN-associated Autopilot Snapshot with the Tesla engineering team to help make improvements to FSD. You will not be able to view the clip.

Don’t hesitate to contact us with news tips. Just send a message to simon@teslarati.com to give us a heads up.

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla Robotaxi has already surpassed Waymo in this key metric

Tesla Robotaxi has already overtaken Waymo in Austin in one key metric, but there’s still more work to do.

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Credit: @HanChulYong/X

Tesla Robotaxi has already surpassed Waymo in one extremely important key metric: size of service area.

Tesla just expanded its service area in Austin on Monday morning, pushing the boundaries of its Robotaxi fleet in an interesting fashion with new capabilities to the north. Yes, we know what it looks like:

The expansion doubled Tesla Robotaxi’s potential travel locations, which now include the University of Texas at Austin, a school with over 53,000 students.

The doubling of the service area by Tesla has already made its travel area larger than Waymo’s, which launched driverless rides in October 2024. It became available to the public in March 2025.

According to Grok, the AI agent on X, Tesla Robotaxi’s current service area spans 42 square miles, which is five square miles larger than Waymo’s service area of 37 square miles.

The service area is one of the most important metrics in determining how much progress a self-driving ride-hailing service is making. Safety is the priority of any company operating a ride-hailing network, especially ones that are making it a point to use autonomy to deploy it.

However, these companies are essentially racing for a larger piece of the city or cities they are in. Waymo has expanded to several different regions around the United States, including Arizona and Los Angeles.

Tesla is attempting to do the same in the coming months as it has already filed paperwork in both California and Arizona to deploy its Robotaxi fleet in states across the U.S.

As the platform continues to show more prowess and accuracy in its operation, Tesla will begin to expand to new areas, eventually aiming for a global rollout of its self-driving service.

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Tesla Megapacks arrive for massive battery replacing coal plant

Tesla Megapacks have started arriving on-site to the Stanwell Battery Project, just as Queensland prepares to wind down the Stanwell coal plant.

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Credit: Tesla

The first of over 300 Tesla Megapacks have arrived to the site of a massive battery energy storage system (BESS) being built in Australia, dubbed the Stanwell Battery Project after a coal plant it’s set to replace.

In a press release last week, the Stanwell Battery Project announced that the first Tesla Megapack 2XL units had arrived to the site, which is located outside of Rockhampton in Queensland, Australia. The project will eventually feature 324 Megapack units, set to arrive in the coming months, in order to support the 300MW/1,200MWh battery project.

“The Stanwell Battery is part of the diversification of our portfolio, to include cleaner and more flexible energy solutions,” said Angie Zahra, Stanwell Central Generation General Manager. “It is just one part of the 800 MW of battery energy storage capacity we have in our pipeline.

“Capable of discharging 300 MW of energy for up to four hours (1,200 MWh), our mega battery will be one of the largest in Queensland.”

Credit: Stanwell

READ MORE ON TESLA MEGAPACKS: Tesla Lathrop Megafactory celebrates massive Megapack battery milestone

The state is working with government-owned company Yurika to facilitate construction, and the process is expected to create roughly 80 jobs. The project is expected to come fully online in May 2027, with initial commissioning of the Megapacks aiming for November 2025.

The Stanwell Battery is set to replace the nearby Stanwell coal generation plant, which the government is planning to wind down starting in 2026 as part of efforts to reach an 80 percent renewable energy generation ratio by 2035. Meanwhile, the government is also set to begin winding down the Tarong and Callide coal plants, while several other Megapack projects are being built or coming online. o ya

Tesla currently has two Megapack production facilities, located in Lathrop, California, in the U.S. and another that came online earlier this year in Shanghai, China. The Shanghai Megafactory shipped its first units to Australia in March, while both factories are expected to be capable of producing 10,000 Megapack units per year upon reaching volume production.

xAI receives more Tesla Megapacks for Colossus 2

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The Tesla Diner is basically finished—here’s what it looks like

The company first broke ground on the Diner, Drive-in, and Supercharger location in September 2023. Now, it has served one of its first internal customers.

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Tesla has finally completed the construction of its highly anticipated Diner, Drive-in, and Supercharger in Los Angeles, and recent photos of the interior’s “retro-futuristic” style are making their way around the internet.

X user Brad Goldberg shared photos from the Tesla Diner site last Tuesday, depicting some of the Supercharger stalls, indoor and outdoor seating areas, multiple neon lights, and even an Optimus robot. Goldberg also noted that there had been a “flurry of activity on site” while he was snapping the photos last week, suggesting that the restaurant location could be getting close to opening.

The Tesla Diner also served one of its first internal customers in the past few days, as Elon Musk posted on X on early Monday morning that he had just finished up eating a meal at the site:

I just had dinner at the retro-futuristic Tesla diner and Supercharger.

Team did great work making it one of the coolest spots in LA!

The photos also show that the site is pretty much done, with some of them even showing vehicles charging at the charging stalls.

You can see some of the latest photos of the Tesla Diner below.

Credit: BradGoldbergMD | X

Credit: BradGoldbergMD | X

Credit: BradGoldbergMD | X

Credit: BradGoldbergMD | X

Credit: TeslaKing420 | X

Credit: TeslaKing420 | X

Credit: Brad Goldberg (via Sawyer Merritt on X)

Credit: Brad Goldberg (via Sawyer Merritt on X)

Credit: Brad Goldberg (via Sawyer Merritt on X)

Credit: Brad Goldberg (via Sawyer Merritt on X)

Credit: Brad Goldberg (via Sawyer Merritt on X)

READ MORE ON TESLA’S LA DINER: Tesla readies Drive-In Diner Supercharger for launch with app inclusion

When will the Tesla Diner open to external customers?

While it’s still not open to external customers yet, the news again suggests that the company could be close to an official opening date. Tesla first broke ground on the Diner in September 2023, after receiving a wave of building permit approvals throughout that yearTeslarati also covered much of the construction progress throughout last year, including when crews installed the first and second drive-in screens.

Located at 7001 West Santa Monica Boulevard, the idea was first discussed in 2018 by Musk and a few others on Twitter, featuring 1950s rock and roll, waiters on roller skates, and drive-in movie theater screens playing clips from some of history’s best movies. Notably, the photos of the front doors also show that the site will be open 24 hours a day, 7 days a week, whenever it does end up opening.

Tesla’s progress on Supercharger with diner, drive-in seen in aerial footage

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