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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. 

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

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– 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.

– 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.

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– 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.

– 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.

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– 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.

– 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.

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

– 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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Energy

Tesla Model 3 and Model Y can now do what only Cybertruck could

Tesla Model 3 and Model Y can power your home with Powerwall 3 during outages.

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Tesla has turned its two top sellers into backup batteries for the house.

Tesla Energy announced on Tuesday that Powershare Home Backup is now available for new Model 3 and Model Y vehicles paired with a Powerwall 3, saying the car can “extend your home backup by over 2 days.” Minutes later, Tesla’s main account quoted the post with a broader pitch: “With Powerwall 3, every Tesla can now serve as your home’s backup battery.”

Until this week, the Cybertruck was the only Tesla that could send power back into a home, and that capability only began working alongside Powerwall 3 last month, after years of ambitious targets.

Tesla’s updated Powershare page says every Model 3 and Model Y ordered in the U.S. or Puerto Rico on or after October 1, 2026 can use the feature. Some, but not all, earlier cars also qualify. Owners can check on the touchscreen under Software, then Additional Vehicle Information, where a capable car shows “Powershare Support: Enabled.” As Electrek reported, bidirectional power on the two cars runs through an inverter Tesla calls PCS2 Lite, and the company has not said when that part entered production on each trim.

The home side is simpler. A house that already has a Powerwall 3 and either a Wall Connector 3 or Universal Wall Connector needs no additional equipment, and Tesla says compatibility is enabled through a software update. When the grid drops, the Powerwall and the car work together, with up to 11.52 kW of continuous power available. Tesla’s “over two days” estimate assumes a home using 30 kWh per day and a car starting at a 90 percent charge. Standard trims are rated for up to two days, while the Cybertruck adds more than three.

There are limits. Powerwall 2 and Powerwall+ support is listed as “coming soon.” Model S and Model X are not included, and Grid Support, the program that lets Cybertruck owners in Texas send power back to the grid during demand spikes for bill credits, is not available for Model 3 or Model Y.

The rollout also lines up with something Elon Musk said more than three years ago. At Tesla’s March 2023 Investor Day, Musk said, “I don’t think very many people are going to want to use bidirectional charging, unless you have a Powerwall.” Tesla has now shipped the feature for its volume cars with exactly that requirement attached.

The Powerwall pairing was the hard part on Cybertruck. Tesla told owners in December 2025 that Powershare with Powerwall had been pushed to mid 2026, and lead engineer Wes Morrill explained that two devices capable of forming a home’s grid have to negotiate which one leads during an outage, across multiple generations of hardware. With that work done for the truck, Tesla was able to extend it to the Model 3 and Model Y within a month.

Ford and GM have offered home backup from their EVs for several years, but both require a separate inverter and backup hardware. Tesla’s version leans on equipment many Powerwall 3 owners already have on the wall. Powershare for the two cars also ships as part of software update 2026.38.3, the same release that began delivering Halloween Mode on Tuesday.

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News

Tesla ships ‘spooky’ Halloween Mode with creepy and fun features

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Credit: Tesla

Tesla is now starting to ship a “Halloween Mode” that is filled with some creepy and fun features; the company says, “This spooky update turns your Tesla into a haunted house on wheels.”

The update is just the latest in a series of updates that Tesla typically ships out in a seasonal fashion. The Spring and Summer Updates provided some fun novelty items while also packing some cool features that are actually useful for the ownership experience.

This one seems to be more fun-forward, and there are not any updates to the Full Self-Driving suite or overall operation of the vehicle. Instead, these novelty features are geared toward getting you in the mood for the Fall and Halloween.

New Ghost Costume on Car Avatar

Driver Visualization will now show your vehicle as a ghost, as an all-white sheet is draped over the vehicle. Pedestrians are turned into mummies or skeletons, and other vehicles are all a spooky green:

Credit: Tesla

Additionally, the Park Scene with your Tesla now displays that ghost costume draped over your vehicle in the foreground of a scary backdrop with Jack-o-Lanterns and a haunted house:

Credit: Tesla

Trick or Treat Mode

Trick or Treat Mode will enable the vehicle to play spooky sounds and flicker the lights as visitors approach. This might be a nice touch for when you’re handing out candy to kids on Halloween Night.

Other Features

Tesla is also adding a new Light Show, new Wrap Options, and a new Lock Sound with this update.

Credit: Tesla

Additionally, Photobooth has a new Halloween option:

Credit: Tesla

You will also be able to speak remotely through the app and transmit your voice to people outside, which is not a new feature, but the car will say it in a voice of its own, which is a new feature with that bullhorn-like feature.

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Investor's Corner

SpaceX reveals how its 1 Million AI satellite network will work and prevent space collisions

SpaceX reveals plans for one million Starmind AI satellites and calls out operators hiding maneuvers.

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Concept rendering of SpaceX Starmind constellation via Grok
Concept rendering of SpaceX Starmind constellation via Grok

SpaceX has put the largest satellite count it has ever published into writing, and it says that plan only works if every other operator in orbit starts sharing what it knows.

In a new Space Safety page highlighted Tuesday morning by Sawyer Merritt on X, SpaceX said it “plans to operate up to 100,000 Starlink satellites and up to 1 million Starmind AI satellites to meet the growing demand for broadband and supercompute.” Starlink has a little over 11,000 satellites in orbit today, so the target alone implies roughly a ninefold expansion of the broadband network.

Starmind is SpaceX’s orbital AI compute constellation. Elon Musk confirmed the Starmind name in June after an xAI trademark filing surfaced, and in August SpaceX said it was working with Nvidia on the compute payload. The FCC accepted the filing for up to one million satellites back in February.

FCC accepts SpaceX filing for 1 million orbital data center plan

SpaceX also released a new render of what a full Starmind constellation could look like. Alongside it, SpaceX VP Michael Nicolls explained why the satellites will not operate on their own. “We need to operate clusters of satellites in tight formation to get enough coherent compute to run AI models efficiently,” Nicolls said. “A cluster will be 10-ish satellites connected with 10 terabits or so of bandwidth between them, and interconnected to the broader constellation.”

That is the most specific detail SpaceX has given on how Starmind will be built. Instead of a million independent servers, the network would work as tightly packed groups of about 10 satellites acting as one compute unit, with Starlink’s laser links carrying results back to Earth.


Packing satellites that close together, at that scale, makes collision avoidance the central problem, and most of the Space Safety page is aimed at other operators. SpaceX said Starlink encountered collision risks with about 650 unique maneuvering third party satellites in 2026, and only about half of them shared data. Over six months, Starlink recorded roughly 164,000 more collision risks where the closest approach came within four hours of an unannounced maneuver.

Some operators keep maneuver plans private over proprietary concerns, while others cannot get government permission to share them. SpaceX called those policies “counterproductive,” saying they “largely only serve to create preventable collision risk between satellites.” Starlink is also offering a free ephemeris sharing and screening platform that returns risk results within a minute, backed by its Stargaze network of 30,000 optical sensors.

The push comes as the Starmind application draws opposition from astronomers and environmental groups. In a September filing with the FCC, SpaceX said each Starmind satellite could weigh up to 4,000 kg, nearly seven times the mass of a Starlink V2 Mini. Musk has brushed off crowding concerns before, telling viewers in June that “space is enormous” and that SpaceX already knows how to run very large constellations safely.

SpaceX’s Starmind page says its Gigasat factory in Bastrop, Texas, is designed to produce AI satellites at scale, with deployment of thousands of units starting as soon as late 2027.

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