News
Tesla FSD Beta 10.69.2.2 extending to 160k owners in US and Canada: Elon Musk
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:
– 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.
– 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.
– 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.
– 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.
Tesla Full Self-Driving is now the centerpiece of the company’s newly revised Referral Program, which launched on October 29.
Instead of referring people to purchase vehicles and the referrer receiving $250 in Tesla Credit, the new program now incentivizes Full Self-Driving subscriptions.
If a Tesla owner is on an FSD trial and uses a referral code to subscribe to Full Self-Driving, the person whose Referral Link was used will receive one month of FSD (Supervised). Their code can be utilized 12 times per year, with January 1 marking the reset date.
Realistically, this means that if your Referral Code is used by 12 Tesla owners on an FSD trial, you will receive a full year of FSD for free.
🚨 Here is Tesla’s new Referral Program for Full Self-Driving (Supervised):
When someone subscribes to FSD using your link, you’ll get a month free. Up to a year of FSD is available to you for free!
If you’d like to use my link: https://t.co/g00IX9OCE3 https://t.co/GFBzEO2jjS
— TESLARATI (@Teslarati) October 30, 2026
The previous program made it pretty difficult to get referrals; buying a vehicle is obviously a much larger financial strain than subscribing to Full Self-Driving for a month.
Of course, the previous Referral Program also offered a tangible benefit: $250 in credits you could use on Service, Supercharging, or anything in the Tesla Shop. It truly could pay for someone’s travel for a year. It recently bought me a new backpack and a T-shirt.
However, this new program is much more attainable for those who do not have a massive online presence of a slew of friends in the Tesla community who will use the code and max out subscriptions for vehicle purchases.
Woke up to maxed out Referrals! Thank you guys, that’s awesome!
Share your referral link below so others can use it! https://t.co/kesbwTcoTV
— TESLARATI (@Teslarati) October 30, 2026
The Full Self-Driving suite will now be the keystone of the Referral Program, which makes it more inclusive and more fun for everyone with an awesome benefit.
It also gives the impression that Tesla is truly focused on FSD subscriptions, something that saw a tremendous increase in volume in Q3, as 75 percent of deliveries for the quarter came with an FSD subscription attached.
Full Self-Driving data is so instrumental to the suite’s improvement that this kind of program benefits Tesla as much as it does the consumer.
Elon Musk
Tesla made napping in a Robotaxi easier with its latest update
Tesla’s quiet mode reaches Model Y Robotaxis, blacking out the screen for riders wanting rest.
Tesla’s quiet mode, the setting that blacks out the screen for riders who want to rest, has moved beyond the Cybercab. A video posted Thursday by Spencer (@scotsrule08) shows the feature running in a Model Y Robotaxi on a night ride that appears to be in Dallas.
New quiet mode now on @Robotaxi https://t.co/2cM2eM9NeN — Spencer (@scotsrule08) October 29, 2026
The rider taps a small crescent moon icon in the bottom right corner of the map screen. The map, media player, app shortcuts and Grok prompt disappear, leaving a dark display with “Arriving soon,” the destination and a line reading “Tap display to exit quiet mode.” Controls a passenger may still need, including Pull Over, cabin temperature, volume and Support, stay visible. One tap anywhere brings the full map back.
Quiet mode first showed up in the Cybercab last week, which Teslarati reported alongside a new rear camera view. Tesla has been trimming cabin noise in other ways too. On October 25, Spencer reported that Robotaxi turn signals now chime for the first four blinks and then go silent. Tesla has not published release notes for either change.
Elon Musk has been pitching this use for more than a decade. In October 2014, he said that “maybe five or six years from now I think we’ll be able to achieve true autonomous driving where you could literally get in the car, go to sleep and wake up at your destination,”
By 2017 he was setting a higher bar. Speaking at TED, Musk said the hard part was not making self-driving work 99.9 percent of the time, “because, like, if a car crashes one in a thousand times, then you’re probably still not going to be comfortable falling asleep. You shouldn’t be, certainly.”
Owners asked for something similar in their own cars. In December 2019, a Tesla owner requested a Nap Mode that would keep the climate running and wake the occupant with an alarm, and Musk answered “Ok,” as Teslarati covered at the time.
The line returned when the Cybercab was unveiled at the We, Robot event in October 2024. “We’ll move from supervised Full Self-Driving to unsupervised Full Self-Driving, where you can fall asleep and wake up at your destination,” Musk said. On Tesla’s first quarter earnings call in April 2025, he called it the deciding measure: “The acid test is, can you go to sleep in your car and wake up in your destination and I’m confident that will be available in many cities in the US by the end of this year,”
Tesla has run driverless Model Y rides in Dallas and Houston since April, so a passenger dozing off on the way home is now a realistic use of the button. Tesla is also offering new riders a free first trip in both cities, according to an in-app screen shared by tracker Ethan McKanna, and said on its third quarter call that Cybercab rides would launch in Dallas next month.
News
FCC green lights SpaceX’s move to a showdown with Verizon and AT&T
The FCC advanced plans opening 482 MHz to satellite phone service, boosting SpaceX’s Starlink Mobile.
The Federal Communications Commission voted Thursday to move forward with a proposal that would open an additional 482 MHz of spectrum to satellite service beamed directly to ordinary phones, a step that could widen the road for SpaceX’s Starlink Mobile to compete with the country’s largest wireless carriers.
The commission adopted the notice of proposed rulemaking at its October open meeting in Washington, Reuters reported. The proposal would raise the number of bands eligible for Supplemental Coverage from Space from five to 13, according to the FCC fact sheet. Commissioners also advanced a companion item proposing an auction of 25 MHz in the 1675 to 1695 MHz and 2020 to 2025 MHz bands, which could be used for terrestrial service, direct to device service or both.
Thursday’s vote does not hand any spectrum to SpaceX. It opens a public comment period, and final rules will come later. Under the draft, comments would be due 60 days after the notice is published in the Federal Register. The FCC had not released the adopted text at the time of writing, so it is not yet clear whether any bands were changed before the vote.
That question is where the fight now moves. AT&T, Verizon and T-Mobile, through industry group CTIA, asked the FCC to drop the 2.5 GHz and 3.45 GHz bands, which make up 290 MHz of the 482 MHz on the table, as Teslarati reported ahead of the vote. T-Mobile argued satellite interference could wipe out up to 96% of a cell site’s uplink coverage area. SpaceX asked the commission to go the other way and add the 902 to 928 MHz band.
The rule change that matters most to SpaceX may be a structural one. Today, a satellite operator must lease spectrum from every carrier holding co-channel licenses across an entire region such as the contiguous United States. The proposal would replace that with a certification that the operator has coexistence agreements covering only the areas it plans to serve, or that it holds the terrestrial licenses itself.
SpaceX has spent this year building that second path. It bought EchoStar’s AWS-4 and H-block licenses in a deal worth roughly $17 billion, and earlier this month agreed to acquire Grain Management’s nationwide 800 MHz portfolio, which the company said would pave the way for Starlink to become a major US mobile carrier. The FCC approved SpaceX’s purchase of three unused AWS-3 licenses from Tristar on October 21, and cleared its plan for 15,000 next generation direct to cell satellites on October 6.
The regulator has not always sided with SpaceX. In April, the FCC dismissed a SpaceX petition seeking access to Mobile Satellite Service spectrum held by incumbents, and it rejected 2.5 GHz for satellite coverage when it first adopted the framework in 2024.
The carriers are also building their own defenses. In May, the three companies agreed in principle to form a joint venture pooling spectrum for satellite service, and T-Mobile remains SpaceX’s US launch partner for Starlink Mobile even as it leads the push to keep satellites out of 2.5 GHz. SpaceX President Gwynne Shotwell has said service on SpaceX’s own airwaves is targeted for early 2028.
Tesla Full Self-Driving becomes main pillar of new Referral Program
Tesla made napping in a Robotaxi easier with its latest update
