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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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Tesla wins over Netflix’s Selling Sunset star, who’s now ditching his Bentley

Selling Sunset’s Jason Oppenheim swapped his Bentley for a Tesla and promised ten for employees.

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Jason Oppenheim, the luxury real estate broker best known as the star of Netflix’s Selling Sunset, has parked his Bentley for good and moved into a Tesla Model Y, and he says Full Self-Driving (Supervised) is the reason.

Oppenheim, who founded The Oppenheim Group, the Los Angeles brokerage at the center of the show, posted a video to X on Saturday evening that he called “the most important video I’ve ever posted.” In it, he rides from Newport Beach to his firm’s Los Angeles office, a trip he put at roughly an hour and 15 minutes, while FSD handles the drive and parks the car without him touching the wheel or the accelerator. He said he handed the Bentley to his father because he no longer has any use for it.

Tesla shared the clip from its main account on X about two hours later, pulling out the quote that has since spread well beyond the Tesla community:

“[FSD Supervised] is life-changing. I was on the phone with my brother last night, and I made him buy one. He literally bought one while we were talking. I’m buying 10 of my employees a Tesla with FSD. It’s 8x safer than the average driver. There’s nothing more important than the safety of you and your loved ones.”

Oppenheim was candid about why the safety pitch landed with him. He admitted in the video that he is a distracted driver who answers emails and texts behind the wheel, and framed the employee purchases as a way to keep his team off their phones while driving. Elon Musk posted “Tesla FSD feels like magic” less than half an hour after the video went live.

The endorsement lands at a convenient moment for Tesla. The company delivered 486,532 vehicles in Q3, beating Wall Street’s estimates and marking its best quarter ever without the $7,500 federal EV tax credit.

Tesla FSD has been subscription only in the U.S. since February at $99 per month, and Tesla said in its Q2 update that active subscriptions hit 1.48 million, up 56 percent year over year, with more than 55 percent of new North American deliveries leaving with FSD attached. That attach rate is the figure Ron Baron cited last month when he told CNBC “the time to buy the stock is now.” At current pricing, Oppenheim’s 10 employee cars alone would add $990 a month, or about $11,880 a year, in FSD revenue.

Tesla AI head Ashok Elluswamy said in July that FSD had logged more than 12 billion miles while going roughly twice as far between collisions as manual driving. FSD also remains a supervised system, so Oppenheim and his employees are still required to watch the road, even as Tesla rolls out v14.3.10 with Automatic Collision Evasion, which can steer or brake on its own to avoid a frontal crash.

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Elon Musk

Elon Musk follows Trump’s lead, says a SpaceX name change is coming

Elon Musk says SpaceXAI will become SpaceXSI, marking its second rebrand in under three months.

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Elon Musk wants to rename his artificial intelligence company again, less than three months after its last rebrand.

In a string of posts on X early Sunday morning, Musk wrote “No more AI,” followed by “SI” and “It’s better.” He then added, “SpaceX is a super intelligence company.” When a user asked whether SpaceXAI could become SpaceXSI, Musk replied, “Yes, we will make that change.”

The posts extend a terminology push that began at the White House last week. On September 29, President Donald Trump signed an executive order directing federal agencies to replace “artificial intelligence” and “AI” with “Super Intelligence” and “SI” on government websites, policy documents and press releases. The same day, Musk sat beside Trump as the heads of the largest AI companies signed a voluntary safety accord, as Teslarati reported. Speaking to reporters afterward, Musk caught himself mid sentence: “I think it is worth highlighting the positive benefits of A.I. … S.I., pardon me.”

Elon Musk and Trump are closer than ever, and Tesla could be the big winner

SpaceXSI would be the third name for the business since February. SpaceX acquired xAI on February 2 in a deal that valued the combined company at $1.25 trillion. In May, Musk said xAI would be dissolved as a separate company, and on July 6 the division adopted the SpaceXAI name and a new logo that placed the xAI letters inside the SpaceX identity.

Musk gave no timeline. He did not say whether SpaceXSI would be a legal name change or a branding update, whether the @SpaceXAI handle on X would change, or how the shift would apply to products like Grok. The company had not issued a formal announcement as of Sunday morning.

The change would reach well beyond a chatbot. SpaceXAI now houses Grok, the X platform, the Colossus training clusters in Memphis and the coding tool Cursor, which SpaceX acquired in August. It also runs the orbital compute effort SpaceX is building around Nvidia hardware, which Musk said during the company’s first earnings call would be exclusive to Nvidia.

It’s unclear if rivals like Anthropic, OpenAI, Google, Meta and Nvidia have plans to also rename their companies or products. OpenAI CEO Sam Altman has continued to say “AI” in public, while Nvidia CEO Jensen Huang has gone partway, describing data centers as “super intelligence factories.”

The rename would also line up SpaceX’s AI branding with the federal government’s language as Musk takes on a new advisory role at the Pentagon, where he is helping lead the Project Meridian study on the future of warfare.

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Starlink launches Communities Program for passive income through internet sharing

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(Credit: Starlink | X)

Starlink is launching a new beta path for ordinary property owners and local operators to turn a single Starlink kit into a small shared-access business for passive income.

Under the Starlink for Communities program, a host installs one dish and router setup in a location with nearby demand: an apartment complex, campground, rural crossroads, or event site. Neighbors or local users can buy short-term passes rather than full individual subscriptions, giving the Starlink provider a potential path to passive income.

Hour, day, and week passes cover one device. A month pass covers up to four. Starlink handles account creation, payments, access controls, and the satellite link itself. The host’s role is mainly placement, power, and basic upkeep, with earnings tied to each paid connection.

The model echoes the passive-income vision long attached to Tesla’s Robotaxi plans, and it seems like it’s something Musk has hinted toward in the past as he believes AI will make the need to work relatively optional. In both cases, the platform owns the hard parts of matching, billing, and network management, while an individual supplies a physical asset that sits idle much of the time.

A Starlink host’s dish can serve multiple nearby users without each household buying and installing its own terminal. A Tesla owner, under the stated Robotaxi concept, would leave a vehicle enrolled in the fleet during unused hours so the car generates rides while the owner is at work or asleep.

Both arrangements convert under-utilized hardware into a revenue stream. They also let the company scale coverage or capacity without owning every endpoint.

Differences are practical. A Starlink kit is a fixed, relatively low-cost terminal whose main constraint is local congestion and line-of-sight. A Tesla Robotaxi is a mobile, high-value vehicle whose earnings depend on demand density, utilization rates, insurance, cleaning, and charging.

Starlink’s program is already accepting host applications in multiple countries and describes the revenue split as ongoing. Tesla’s owner-network version remains more aspirational.

The company currently operates a limited company-controlled robotaxi service in select areas and has solicited interest from fleet buyers for Cybercab vehicles, while private Full Self-Driving owners have not yet been able to dispatch their own cars for paid rides at scale.

Tesla primes Cybercabs for 4K streaming and high bandwidth gaming with Starlink integration

Starlink is a satellite broadband service operated by SpaceX that uses a constellation of low-Earth-orbit satellites to deliver internet to locations where terrestrial broadband is slow, expensive, or absent. It has grown to millions of subscribers worldwide by selling direct residential, mobile, and enterprise terminals, and have become widely available at a wide array at retail locations like Target and Best Buy.

The Communities program extends that reach by letting hosts resell short bursts of capacity to people nearby, while also providing high-speed internet access to those who are simply around a Starlink user.

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