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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.
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– 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.
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– 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.
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– 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.
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Elon Musk
Tesla FSD takes owner on a 20,000+ mile joy ride
Tesla owner David Moss just pushed his intervention free FSD streak past 20,000 miles total.
Tesla Model 3 owner David Moss has spent the better part of eight months turning his vehicle into a rolling stress test for Full Self-Driving, and this week he pushed his single, continuous FSD streak past 20,000 miles without a human intervening.
Moss, a Tacoma, Washington resident who sells LiDAR scanning equipment for a living, first drew wide attention in December 2025 when he logged 10,000 consecutive miles on FSD v14.2. Days later he drove from the Tesla Diner in Los Angeles to Myrtle Beach, South Carolina, covering 2,732 miles in two days and 20 hours with zero disengagements, the first verified coast to coast autonomous drive in Tesla’s history. Tesla even featured the trip as an official customer story in March. That original streak eventually reached 12,961 miles across 30 states before ending in rural Wisconsin in January, when snow and single digit temperatures forced Moss to take over.
Tesla FSD successfully completes full coast-to-coast drive with zero interventions
He started over, and this run has gone further. In late May, Moss drove 3,760 miles across Canada with two companions, from Horseshoe Bay in Vancouver to a Tesla showroom in Halifax, again without a single intervention, a trip Tesla AI software VP Ashok Elluswamy publicly congratulated him for on X. In June, he pushed the same unbroken streak south, aiming to link the Canadian border to the Mexican border, and crossed 10,000 miles on Tesla’s newly added in car streak counter along the way, the first driver to do so since Tesla began showing confetti animations for the feature.
20,000 Mile Tesla FSD Screen Streak!
Special thank you to @DevinOlsenn, @scotsrule08, & @OwenSparks for helping co drive during all these fun adventures these last couple of months
Also thank you to @wholemars for always tracking me along the journey verifying it all with his… pic.twitter.com/CZ2yO6Ev0X
— David Moss (@DavidMoss) July 27, 2026
It’s worth noting that every mile is logged through the FSD Database, a community run tracker built by Tesla influencer Omar Qazi, well known as @WholeMars on X, that pulls telemetry straight from the car and records disengagements down to a tenth of a mile. That verification is what separates Moss’s numbers from casual claims on social media.
The streak itself is a fairly recent addition to Tesla’s software. FSD v14.2 introduced a Self Driving Stats panel tracking the ratio of autonomous to manual miles, and v14.3.4 added the live streak counter in June, which resets the moment a driver brakes, wrenches the wheel or cancels navigation. Reaching 20,000 miles on that counter means a single Tesla drove itself through countless highways, city grids, construction zones and Supercharger stalls without a single reset.
Moss has said the goal was never to set a record for its own sake, but to show, mile by verified mile, what the software can already do.
Elon Musk told The Economist that artificial intelligence will likely surpass the combined intelligence of every human on Earth within about five years, and that humans may not remain in charge once that happens. In a wide-ranging interview with editor-in-chief Zanny Minton Beddoes, recorded at Giga Texas for the outlet’s Insider series, Musk compared the widening gap between AI and human intelligence to the gap between humans and chimpanzees.
“It’s hard to imagine that the chimpanzee would be in charge,” he said, addressing what happens to human authority once AI moves far beyond us.
Elon Musk reiterates his most optimistic prediction yet with “UHI” forecast
Musk’s timeline stretches out from there. Five years for AI to out-think humanity combined, ten years before humans lose meaningful control, and by 2036, he says, money itself may stop mattering.
Musk notes that if robots and AI produce more goods and services than people could ever consume, currency loses its purpose. He told Beddoes that governments could respond with direct payments, what he called “universal high income,” a term he first used in an X post last August describing a future where “everyone will have the best medical care, food, home, transport and everything else.”
There will be universal high income (not merely basic income).
Everyone will have the best medical care, food, home, transport and everything else.
Sustainable abundance.
— Elon Musk (@elonmusk) August 24, 2025
He also floated a more surprising prediction that deflation, and not inflation, would become the bigger economic problem, since expanding the supply of goods and services faster than the money supply grows would push prices down rather than up.
None of this is new territory for Musk, who has spent years describing an “age of abundance” built on Optimus and autonomous vehicles. What’s notable is the timing. The interview landed the same week Tesla shares dropped roughly 19 percent following a second quarter earnings report that beat on revenue but missed badly on profit, and as SpaceX stock continues to slide from its post-IPO peak.
Musk’s own net worth has fallen close to $700 billion since mid-June, according to the Bloomberg Billionaires Index, even as he describes a future where personal wealth stops being the point.
Musk did not dodge the risk side of the equation either. He put the odds of AI contributing to human extinction somewhere in the 10 to 20 percent range, then arrived at what he called his “philosophical conclusion” since the technology cannot realistically be stopped and the arguably better response is to keep building it and hope the outcome leans toward abundance rather than catastrophe. “I’ve gone from exhilaration to terror regarding AI,” he told Beddoes, “even intraday.”
Tesla is adding a new “Traction Control Modes” feature to its cars for better handling in any conditions. These features will roll out to the Model 3 and Model Y, the two vehicles in Tesla’s lineup that typically do not have drive modes for various conditions.
Tesla did include this in the Model S and Model X, as well as the Cybertruck.
The new feature will roll out with the 2026 Summer Update, which Tesla announced last week and subsequently started rolling out to some owners today. The Summer Update is the latest iteration of the usual four seasonal releases the company rolls out throughout the year. These releases typically feature some owner-requested features, as well as improvements to things like the Full Self-Driving suite.
Tesla reveals 2026 Summer Update with crazy fixes to Nav and more
This release is no different. Among the changes are improvements to Navigation, new customization options with wraps and how they can be shared and stored, more functionality with the Tesla smartphone app, and new gamification with self-driving.
However, Tesla announced today that it was adding another feature to the Summer Update. Traction Control Modes will now be available with the release
Tesla describes them:
“Choose from three updated Traction Control Modes: Auto for normal driving conditions, Slippery Surface for icy or wet roads, Stuck Assist when stuck in snow, mud, or sand. The mode resets to Auto at the start of each drive. To select, go to Controls > Dynamics > Traction Control Mode.”
Tesla’s 2026 Summer Update also includes new Traction Control Modes
📸: @PatchesHQ https://t.co/N9cD2lGP14 pic.twitter.com/ogLC5ROIgc
— TESLARATI (@Teslarati) July 26, 2026
The use of these modes will help improve a Tesla’s overall performance in less-than-ideal conditions. Typically, these traction control modes monitor wheel speed through sensors and track engine power to adjust responsiveness in various conditions.
These drive modes are not an ultimate solution to all driving conditions; just because there is a “Stuck Assist,” doesn’t mean your Tesla will dig itself out of a foot-and-a-half trench during a blizzard. It is important to remember that some of these scenarios also require some assistance from the driver. For example, driving in sand requires tires to be aired down significantly to increase traction and control.
However, this will be a welcome addition for those who use the Full Self-Driving suite and might not be convinced of its performance in adverse conditions. Some of us prefer to be in control in rain, snow, or ice, which is totally understandable. However, adjusting the Traction Control Mode while utilizing FSD in snow, rain, or ice could increase confidence and overall experience.
Tesla’s Summer Update is already rolling out to some owners, so it should be making its way to most of the fleet over the next several weeks. The Spring Update rolled out at a very conservative pace, so if you don’t have it by the end of August, don’t be too upset. It might just be Tesla’s method.
Tesla FSD takes owner on a 20,000+ mile joy ride
Elon Musk explains what happens when AI outsmarts all of us
