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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.
– 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.
Electric vehicle maker Lucid Group has denied rumors of an imminent bankruptcy after a report from this morning sent the stock on a dramatic drop on Wall Street, seeing losses of more than 40 percent during trading hours.
Lucid’s Director of Communications, Nick Twork, responded to the report from Eletric-Vehicles.com, which stated the company’s restructuring advisor, AlixPartners, was asked to review two decisions: taking Lucid shares private or filing for Chapter 11 bankruptcy protection.
The report also claims AlixPartners told the Lucid board to “concentrate on Gravity production while improving its quality, and to temporarily hold back the Lucid Air, the sedan that has defined the company since its launch.”
Twork said:
$LCID The rumors are completely false. The company has sufficient liquidity to carry its operations well into next year, as recently published in its last quarterly filings, and it has not formed any special Board committee to explore the scenarios reported today. Our focus is…
— Nick Twork (@ntwork) July 14, 2026
Shares rebounded after the response to the report, halving its losses as the trading day neared 3 p.m. Eastern.
Lucid has struggled to get its sales off the ground and into more respectable numbers, but the company is in its early years, when things are hard to begin with. It is also backed by several notable investors, including the Saudi Public Investment Fund (PIF), which has nearly limitless money and likely would not ditch an investment of this size so soon.
Lucid shares were down just 14 percent at the time of publication, a far cry from the 55 percent its losses topped out at during the day.
A Tesla owner who purchased a Model S Signature Edition, one of the final 250 units of the all-electric flagship vehicle that the company discontinued earlier this year, is attempting to sell the car despite a no-resale clause that prohibits reselling for the first year.
The car is being sold by J&S Autohaus in Ewing, New Jersey, and is priced at $260,490, well above the $159,420 that Tesla sold it for earlier this year.
🚨 The first Tesla Model S Signature Edition is up for sale for $260,490
Tesla placed a no-resale clause on the Model S and X Signature, so it will be interesting to see if the company takes any action. https://t.co/N9rKGHnbD6 pic.twitter.com/6FZhDL1KNR
— TESLARATI (@Teslarati) July 14, 2026
To those who do not know, the Model S Signature was a highly exclusive, limited-run farewell variant of the Model S Plaid that was produced this year to mark the end of production of both the Model S and Model X, Tesla’s two flagship vehicles.
Limited to just 250 units with invite-only sales, it serves as a collector’s item celebrating the legacy of the Model S, which helped pioneer Tesla’s electric vehicle success since its 2012 launch.
It bundles top-tier performance with bespoke cosmetic and luxury upgrades, plus Tesla’s Luxe Package. Here’s what the Model S Signature has over the typical Model S Plaid:
- Exclusive Exterior – Unique Garnet Red Paint, matching door handles, gold Tesla “T” badges upfront, gold Plaid and Signature badging at the rear.
- Premium Interior – White Alcantara upholstery with gold piping/accents, gold Plaid seat badges, Signature-marked door sills, individually numbered dashboard plaque, gold puddle lights, special interior lighting sequence, and a custom Signature key fob.
- Performance Upgrades – Carbon-ceramic brakes with gold calipers
- Bundled Luxe Package – Full Self-Driving (Supervised), four years of Premium Connectivity, free lifetime Supercharging
- Performance Metrics – ~1,020 horsepower, sub-2-second 0-60 MPH, ~390-mile range
Tesla quickly introduced a No Resale Agreement for the Signature Editions of the Model S and Model X, which would penalize the seller for “the amount of $50,000 or the value received as consideration for the sale or transfer, whichever is greater.”
The company continues:
“If you sell or otherwise transfer the ownership of your Model S or Model X, the remainder of the Recommended Maintenance, Wheel and Tire Protection Plan, and Windshield Protection Plan will transfer automatically to the buyer. The Full Self-Driving (Supervised), Free Supercharging and Premium Connectivity will not transfer with the vehicle and will terminate once the ownership of the Model S or Model X is transferred.”
Tesla will likely come after the seller, especially as it has been about two months since Tesla launched deliveries.
Tesla rolled out Full Self-Driving (Supervised) v14.3.5 yesterday, and about fifty miles of driving on the new version has given me enough time to highlight what seems to be strong about the release and what is not.
Additionally, Tesla has added a few new features with this specific update, which we’ll highlight as well.
Tesla Full Self-Driving v14.3.5 Performance
The new update is business as usual. Things seem to be running completely normal and necessary, but there are a few things that we’ve seemed to pick up on based on our own experience with v14.3.5, as well as what other users are seeing.
Initially, it seems to be more aware of its surroundings, making moves that are incredibly courteous to other drives and operating just a tad more reserved than what the suite might have done previously.
We had two instances where it showed this, the first being FSD needing to pass a Flagger Force vehicle that was placing down signage for the day. Their work truck was right at the front corner of a right-hand turn; typically where most cars travel when they take that turn.
FSD v14.3.5 recognized this, slowed down, and took the turn wide with no issues:
🚨 Tesla Full Self-Driving v14.3.5 takes a wide turn as flagger crews set up signage for the day https://t.co/3v0PL9qhlI pic.twitter.com/i4CKqxE16c
— TESLARATI (@Teslarati) July 13, 2026
Additionally, v14.3.5 backed up for a semi truck that was making a wide turn onto a road my car was on. This is not new, but it seemed to be backing up for courtesy; it didn’t seem completely necessary, but it might have put some peace of mind in the truck driver’s head:
🚨 Tesla Full Self-Driving v14.3.5 backs up for an oncoming tractor trailer taking a wide turn https://t.co/0WuAqNMpRR pic.twitter.com/s6yZGVm5Te
— TESLARATI (@Teslarati) July 13, 2026
X user Mike P, also a Pennsylvania native like myself, shared three clips of his Tesla running v14.3.5 performing similar maneuvers. He said:
“FSD turns right into a small alley that only fits one car at a time, sees oncoming car, reverses out of alley to make space, realizes oncoming car is actually parking, re-enters alley.”
Check it out here:
Rapidfire epic moments on FSD V14.3.5
1) FSD turns right into a small alley that only fits one car at a time, sees oncoming car, reverses out of alley to make space, realizes oncoming car is actually parking, re-enters alley.2) Insane speed to vehicle cues. As FSD approaches… pic.twitter.com/bSnySSlFHR
— Mike P (@mikepat711) July 13, 2026
It seems like Speed Profiles are still in need of some tweaking; I am adjusting what Speed Profile I’m in frequently, constantly changing it to get it to travel at the correct speed. This was an issue for me on v14.3.4. It seems like they’re just a little inconsistent.
Terrible Parking
Parking attempts on v14.3.5 were not good. There are quite a few people who have said this:
Yeah it seems like FSD v14.3.5 is having some issues with parking early on https://t.co/Bw5ULfVmDq pic.twitter.com/RHdpjOEpIo
— TESLARATI (@Teslarati) July 13, 2026
David Moss, the Tesla owner who has taken multiple coast-to-coast drives without any interventions, also has had some issues with parking early on with v14.3.5:
Horrible first impression v14.3.5 on my 2025 Tesla Model 3 LR RWD Premium 😭
3 terrible parking jobs in 23 min including parking on a ramp in a business park & parking perpendicular out in the road on street only parking situation.Wish I had a better drive but I still believe… pic.twitter.com/TtyhRHAFG7
— David Moss (@DavidMoss) July 13, 2026
New Features
Tesla has added the ability to open Camera Preview at any time. Previously, it was only available in Park. Here’s what that feature looks like in action:
🚨 Here’s the new Camera Preview feature on FSD v14.3.5 pic.twitter.com/OodfZgDppy
— TESLARATI (@Teslarati) July 13, 2026
Check back later this week for a longer review of what we’ve noticed on Full Self-Driving v14.3.5.
Lucid denies rumors of bankruptcy after over 40% stock drop
Tesla owner attempts resale of Model S Signature Edition for over $260k
