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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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Tesla’s AI lead Ashok Elluswamy doubled down on the company’s strategy regarding Full Self-Driving’s speed settings, and owners are definitely confused.
Earlier versions of Full Self-Driving allowed owners to set a max speed that the vehicle could travel while operating under the semi-autonomous driver assistance platform. This allowed more customization for the driver, giving them the ability to experience FSD’s robust performance with their own personal preferences.
Speed is massively important for obvious reasons — it’s not only a question of keeping the vehicle occupants comfortable by traveling at a safe speed, but it’s also something that could contribute to a ticket or infraction from law enforcement.
With the release of FSD v14 last year, Tesla removed the ability to set a max speed and instead opted for five Speed Profiles, ranging from “Sloth,” the most conservative, to “Mad Max,” the most aggressive and spirited. These profiles not only control speed, but also how frequently the vehicle will execute passes, perform lane changes, and other contributing factors.
The removal of the Max Speed setting was a major complaint amongst the Tesla community because it left owners scrambling for a way to experience suitable behaviors while traveling at an appropriate speed. Most felt the driving profiles would be a good indicator of the behaviors, while speed would still be left up to the discretion of the driver.
Instead, Tesla’s Speed Profiles determine both, and the constant tinkering of how they behave has been a major bottleneck and point of confusion for both owners and the company. From update to update, the Speed Profiles will change, sometimes more drastically than others. Some owners have complained that the “Standard” profile is too fast, while others have experienced “Mad Max” traveling below the speed limit:
What has happened to Mad Max?
At one point it was going 32 in a 35. Traffic ahead had pulled away considerably https://t.co/bjKvaMVTNX pic.twitter.com/aaZSWmLu5v
— TESLARATI (@Teslarati) January 24, 2026
These things change with each update, but the big complaint is that owners are on the hook for any tickets that come from FSD’s infractions; that’s the caveat of the suite being named FSD (Supervised). It ultimately means the driver is responsible, and the automaker has no liability when it comes to speeding tickets or general traffic infractions.
It is the driver’s responsibility to take over or adjust based on this.
Elluswamy essentially confirmed that there are no plans to bring back Max Speed control, because it is what he referred to as “an anti pattern.” He then echoed something that CEO Elon Musk has started to really push with FSD, and that’s the idea that Tesla is really honing in on the preferences of the driver.
Max speed control is an anti pattern.
We are working on better learning of user’s implied preferences.
— Ashok Elluswamy (@aelluswamy) August 3, 2026
Owners were confused by Tesla’s decision, stating that there must be a better way, especially considering disengagements for incorrect speeds are common:
This…. is not the way
— Kyle Conner (@itskyleconner) August 4, 2026
😭 I appreciate this mentality ! But currently the no.1 reason I disengage in Australia is incorrect speed zones.
— Ryan’s Model Y (@ryanjaycowan) August 3, 2026
This is fine but you need to start accepting liability for speeding tickets then. https://t.co/lyCgdA83gQ
— Jeremy Judkins (@jeremyjudkins_) August 4, 2026
Okay https://t.co/nOvoXQkNg1 pic.twitter.com/jGRtF2xtox
— Chad Moran (@ChadMoran) August 3, 2026
From personal experience and using FSD for over 72 percent of my driving miles since v14 was released late last year, I make Speed Profile adjustments constantly. If FSD is traveling a tad too quickly, I will scale it back, and if it’s too conservative, I’ll make it more aggressive.
I don’t complain about making the Speed Profile changes too frequently, but it would certainly be nice to have it happen less frequently. There are far too many times I am concerned about getting a ticket, even in Standard mode.
The biggest issue for me, personally, which seems to be echoed throughout the community, is the fact that Tesla’s goal is to minimize disengagements. Many drivers are stating that speed is a major reason for disengagements.
However, Tesla is not willing to bring back this one level of input because it would technically be a regression.
Whether it’s right or wrong in your opinion, it is what Tesla is going with, and it seems like it has pivoted quite a bit from its other strategies for minimizing interventions by pushing its AI to behave in a way that would fit the occupant’s personal preferences.
Tesla is one of several automakers whose vehicles qualify for an awesome new first-time EV buyer incentive program in California.
The Golden State launched the MyFirstEV incentive program, which helps those buying an electric vehicle for the first time with a $3,500 incentive on new-inventory purchases of a Model 3 or Model Y.
First-time electric vehicle buyers in California can now get $3,500 off eligible Model 3 and Model Y new inventory vehicle purchases.
To be eligible, you must place your order on or after August 3, 2026 and take delivery while funds are still available. The incentive applies to… pic.twitter.com/yuXF00XA50
— Sawyer Merritt (@SawyerMerritt) August 4, 2026
The incentive requires an order on or after August 3, and delivery must be taken while the program is still being funded. California has set aside $135.5 million to help strengthen its SEV market and support automotive innovation.
Incentives are offered at the point of sale, and used EVs are also available for a partial incentive of $1,750. Half of the $3,500 and $1,750 incentive amounts are covered by California, with the other half being covered by participating OEMs.
Additionally, rules apply for MSRP and how the vehicle will qualify for the incentive. Any vehicle from a non-California headquartered OEM must have an MSRP of $50,000 or less. Used vehicles must be priced at $25,000 or less and must be at least two model years older than the year of purchase.
The cars must also be purchased from manufacturers as certified pre-owned vehicles. Private dealerships are not eligible.
In total, California expects to incentivize over 73,000 ZEVs.
Participating Manufacturers
Fourteen total automakers are participating in California’s MyFirstEV program:
- Chevrolet – Launching August 2026
- Ford – Launching August 2026
- Honda – Launching September 2026
- Hyundai – Launching August 2026
- Kia – Launching August 2026
- Lexus – Launching September 2026
- Lucid – Launching August 2026
- Mitsubishi – Launching November 2026
- Nissan – Coming Soon
- Rivian – Coming Soon
- Subaru – Launching September 2026
- Tesla – Launching August 2026
- Toyota – Launching September 2026
- Volvo – Coming Soon
Elon Musk’s space exploration company, SpaceX (NASDAQ: SPCX), is set to report its earnings for the second quarter today in what will be its first-ever earnings call since going public in July.
SpaceX is trading down roughly 25 percent from its IPO. These early stock signals are usually a bit tumultuous, and considering this is the first company actively launching rockets that is available on the stock exchange, investors might have a tendency to be a bit skittish.
However, there are going to be some details that investors will hear for the first time today on the earnings call. Here’s what to look for:
Wall Street Expectations
Revenue is expected to fall somewhere around $6.8 billion, and will be heavily driven by Starlink, which is SpaceX’s widely popular satellite internet platform that has been adopted by numerous airlines, cruise ships, and other maritime operations. It is also available for consumers at home or in their cars.
Earnings Per Share (EPS) expectations fall at a net loss of $0.23 per share. Wall Street sees this as a total net loss of roughly $1.9 billion.
EBITDA is expected to come in between $2 billion and $2.1 billion.
What Investors Want to Know
Tesla uses the Say platform to help work with both retail and institutional investors to answer relevant and quality questions that address concerns or questions that they might have.
However, SpaceX is doing things differently, as the company launched its own Investor Relations website where these questions are being fielded. Just like the Tesla questions, they seem to be less focused on the operational tasks and overall progress of the company, and more novelty.
Here are the top five:
- Has the team thought about what possibilities there are with your mascot Asteroid? Whether it’s starting additional foundations for kids in its name, helping kids learn about space, etc. Kids are our future, and Asteroid would be a fun and easy way to help.
- Baby Asteroid is already making a difference through charity around the world. Could SpaceX take it even further with programs that inspire kids to explore space?
- SpaceX has some legendary vehicle names. Would you ever allow the public to name a Starship, even knowing there is a 99% chance it becomes Shipy McShipface?
- When can we expect to see more footage of the Human Landing System?
- Will Asteroid (your mascot) go to Mars?
SpaceX will report its earnings today, August 4, at 4:30 P.M. EDT.
Tesla’s AI lead doubles down on FSD’s speed strategy, and owners are confused
Tesla qualifies for awesome new first-time EV buyer incentive in California
