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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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Elon Musk

Tesla gives the Roadster an official “Go for launch” demonstration date

Tesla teased an October 1 Roadster reveal, reviving years of delayed SpaceX thruster hover promises.

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Concept rendering of a Tesla Roadster with SpaceX Package via Grok
Concept rendering of a Tesla Roadster with SpaceX Package via Grok

Tesla teased an October 1 event date for its next generation Roadster, posting an image on X Saturday that shows the car lit up like it is sitting on a launch pad, with the date “10.01” stamped across the bottom and the caption “Go for launch.” A countdown clock on Tesla’s Roadster order page now points to the same date, which falls on a Thursday. The company has not said where the event will happen or whether it will be streamed at the moment. Stay with us @Teslarati for live updates.


Tesla has since sent formal invitations to reservation holders confirming the event will take place in Waco, Texas, about 90 minutes north of its Austin headquarters, based on a digital ticket shared on X by Sawyer Merritt. Tesla did not name the exact venue, though Waco sits close to SpaceX’s McGregor, Texas, rocket test site, previously reported as the planned location for a Roadster thruster demonstration. The invite sets the reveal for 8:30 p.m. Eastern on October 1, requires RSVPs by midnight on September 16, and limits entry to guests 21 and older. Invitations are non-transferable.

The tease follows nine years of a project defined by unimaginable specs along with slipped dates. Musk first showed the second generation Roadster in November 2017 as a surprise reveal at the end of the Tesla Semi event, promising a 0 to 60 mph time under two seconds, a top speed above 250 mph, 620 miles of range from a 200 kWh battery, and production starting in 2020. At last November’s shareholder meeting, Musk set an April 1 demo date and joked the choice gave him “deniability” if it slipped again, which it did, moving first to late April, then to “a month or so,” then to August.

Tesla Roadster SpaceX Package’s 1.1-second 0-60 mph launch visualized in concept video

Whatever Tesla shows on October 1 is expected to center on the SpaceX developed thruster package Musk has described since 2018. Internally code named A71, a nod to the Lockheed SR-71 Blackbird, the system reportedly uses cold gas thrusters fed by a composite overwrapped pressure vessel, the same tank design SpaceX uses on Falcon 9. Musk has said a thruster equipped Roadster could hit 60 mph in about 1.1 seconds under roughly 2.75 g of launch force, well past the 1.9 second figure quoted for the standard car. That version reportedly will not be street legal and has reportedly been discussed as a limited run sold through a track only program.

The standard Roadster is still expected to carry the original $200,000 base price and $250,000 Founders Series tier, both set when Tesla opened $50,000 and $250,000 reservations in 2017. Tesla VP of Vehicle Engineering Lars Moravy has confirmed production will happen at Gigafactory Texas, with Musk targeting 2027 or 2028, 12 to 18 months after whatever the company demonstrates next month.

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Tesla plans big safety improvements for Full Self-Driving v15

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Credit: Tesla

Tesla is planning to roll out some pretty significant safety and accident avoidance features with Full Self-Driving version 15, which will be the next major FSD deployment from the company.

Tesla AI lead Ashok Elluswamy used a near-miss this week to preview what the company says is the next leap in Full Self-Driving.

In response to a driver whose car had swerved away from another vehicle pulling out of a parking lot, Elluswamy wrote that he was glad the owner was safe and that “even earlier prediction of hazards, even faster reaction time and overall significantly better safety and collision avoidance” would arrive with FSD v15.

The comment landed as Tesla continues to treat software as the primary safety upgrade path. v15 is described internally as a larger architectural step, with a much bigger neural network and tighter coupling between prediction and control.

The company has already begun using early v15 software in some robotaxi operations while rolling out safety features such as Automatic Collision Evasion into current customer cars, allowing the driving stack to intervene even when the driver is in manual control.

Tesla is rolling out a new FSD version with a massive safety addition

Tesla’s published telemetry is the backbone of its safety argument. In recent North American Vehicle Safety Report data, vehicles with FSD (Supervised) engaged traveled roughly 5.1 million to 5.7 million miles between major collisions, defined as airbag-deployment events.

Tesla’s estimate of the U.S. average over the same period is about 699,000 miles per comparable crash. That is the comparison Tesla often frames as roughly seven times fewer major collisions.

A tighter comparison uses the same Tesla fleet. Cars driven manually with active safety features such as automatic emergency braking still recorded a major collision about every 2.1 million miles. Against that baseline, FSD’s advantage shrinks to roughly 2.4 to 2.7 times fewer severe crashes, which independent researchers argue is the more apples-to-apples figure.

European data released in 2026 pointed in the same direction: Tesla reported FSD as 3.5 times safer than manual driving in the Netherlands and 4.1 times fewer collisions than manually driven Teslas with active safety across more than 100 million kilometers in five approved countries.

Those numbers do not settle every debate. NHTSA’s Standing General Order still shows Tesla accounting for the large majority of U.S. Level 2 driver-assist crash reports, in part because the fleet logs far more assisted miles than rivals. Critics also note that Tesla’s “U.S. average” mixes crash definitions and driving mix.

Even so, Tesla’s own same-car comparisons, plus lower rates of automatic emergency braking and harsh maneuvers when FSD is engaged, are the evidence Elluswamy is pointing to when he says v15 will push prediction and collision avoidance further. The claim is not that software already eliminates risk. It is that each major version is meant to widen the gap between the system and an unaided human driver.

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Cybertruck

Tesla’s most delayed Cybertruck feature is finally here

Tesla finally links Cybertruck Powershare with Powerwall 3 for extended home backup after years overdue.

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Tesla’s Cybertruck can now pair with a Powerwall 3 to keep a house running longer during an outage, a feature the company first promised when the truck launched in November 2023.

The official Cybertruck account posted the update on X Thursday: “Powerwall 3 & I can now power your house together. This extends your home backup by over 3 days, equivalent to 9 additional Powerwalls,” Cybertruck lead engineer Wes Morrill confirmed the rollout separately, calling it the first time a vehicle and a home battery have worked together this way. Powerwall 2 and Powerwall+ compatibility is still coming later this year, per both the Cybertruck account and Morrill.

Powershare itself is not new. Tesla enabled the version that lets Cybertruck power tools, appliances or another EV through its bed outlets when the truck launched in 2023. Home backup through a Powershare Gateway and Universal Wall Connector arrived in 2024, and Tesla extended that support to homes with solar the following year. What has been missing until now is Powershare working alongside an existing Powerwall, instead of functioning as a separate backup source competing for the same job.

The pairing matters because a single Powerwall home battery typically covers a home for about a day, less if usage is heavy or the outage stretches into a heat wave or freeze. A second Powerwall for more backup storage costs several thousand dollars installed. A Cybertruck instead uses a battery the owner already has, one large enough here to add roughly three more days of backup without mounting another unit or booking an installer visit. For households in wildfire, hurricane or winter storm regions where outages run past a day, that keeps the refrigerator and medical equipment running instead of shutting down.

Tesla provides Cybertruck Powershare release update

The company told owners in October 2024 that Powerwall integration was coming sometime in 2025. That date passed, and in December 2025 Tesla pushed the target to mid-2026, with Morrill explaining at the time that two grid-forming devices need to negotiate which one manages a home during an outage, and that certifying the process across multiple generations of Powerwall took longer than expected.

For owners who bought Powershare hardware expecting it to work with whatever battery setup they already had, Thursday’s update closes a gap that has shown up repeatedly in owner complaints since Cybertruck deliveries began. Tesla has also rolled out a separate Powershare grid support program in Texas, letting Cybertrucks send power back to the grid during high demand events, so the truck’s role in a home’s energy setup keeps expanding even as individual pieces of it arrive later than promised.

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