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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.
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Elon Musk
Elon Musk just upped his Tesla stake further fueling SpaceX merger conversation
Elon Musk just collected a $116 billion Tesla payday and the timing is eye-opening
Elon Musk quietly collected one of the largest single-transaction paydays in corporate history on Monday. A Form 4 filed with the SEC on June 17, 2026 disclosed that Musk exercised 303,960,630 Tesla stock options from his 2018 compensation package, with the transaction dated June 16. No shares were sold on the open market.
The numbers are straightforward but striking. Musk exercised the options at a split-adjusted strike price of $23.34, with Tesla closing at $404.66 that day, putting the spread at $381.32 per share and generating roughly $115.9 billion in paper gains in a single transaction. To cover the exercise cost, Tesla withheld 17,531,857 shares through a net share settlement, meaning Musk paid nothing out of pocket.
For perspective, in 2018, Elon Musk’s award was originally approved by Tesla shareholders on March 21, 2018, and structured entirely around performance milestones that many analysts at the time called unreachable. Every tranche eventually vested. The original grant covered 20,264,042 shares at $350.02, which after Tesla’s 5-for-1 split in 2020 and 3-for-1 split in 2022 adjusted to 303,960,630 shares at $23.34. A Delaware court rescinded the award in January 2024, ruling the board was conflicted. As Teslarati reported, Tesla shareholders voted to ratify the package anyway in June 2024 by a wide margin. The Delaware Supreme Court reversed the decision in December 2025, finding full cancellation too extreme, and Tesla’s board signed an Implementation Agreement on April 21, 2026 to formally deliver the shares.
The Tesla and SpaceX merger everyone is talking about is quietly building
The timing and structure of the Form 4 filing carries more weight than a routine stock option exercise typically would. Musk exercised his 2018 Tesla award on June 16, a week into SpaceX completing its IPO and trading publicly, and giving SpaceX a public market valuation and share currency for the first time in the company’s history. A stock-for-stock merger between two companies requires the acquiring entity to have tradeable shares it can offer to the target’s shareholders, and SpaceX now has exactly that. At the same time, Musk just increased his direct Tesla voting power to approximately 20%, giving him greater influence over any shareholder vote that a merger would require. The restricted shares he received cannot be sold until 2033, which removes any near-term incentive to cash out and instead positions this stake as long-term structural collateral in a deal. Additionally, Musk’s two companies are already deeply intertwined through shared semiconductor fabrication at their joint TERAFAB facility in Austin, cross-company supply chain transactions, and Tesla’s $2 billion investment in xAI prior to the SpaceX-xAI merger.
Wedbush analyst Dan Ives has publicly placed the odds of a Tesla and SpaceX combination at 80% to 90% by early 2027. The Implementation Agreement that made Monday’s exercise possible was signed on April 21, 2026, roughly two months before the SpaceX IPO closed. That sequencing, building Musk’s Tesla ownership to its highest point ever immediately before SpaceX gains the public currency needed to acquire it, is either an extraordinary coincidence or a carefully staged foundation for the largest corporate merger in history.
Tesla Full Self-Driving is going to be getting a major parking upgrade. That’s according to CEO Elon Musk, who detailed a crafty new feature that will improve parking preferences, removing a layer of human input.
Musk said that upcoming releases of Full Self-Driving will “remember your parking preferences.” It will go to the location you prefer, based on where you’ve parked in the past, instead of taking the first spot available, which is where the suite is currently.
The CEO went on to explain that destination parking is “by far” the biggest reason for intervention during FSD operation. We’d have to believe this is true; many takeovers in my Model Y, which runs the latest version of FSD as it is in the Early Access Program, are due to parking because it chooses a spot I do not want to be in.
Many times, as soon as I enter a parking lot, I take over and park manually. I prefer to park away from the entrance of wherever I am, away from cars. Too many lessons learned over the years from people with free-swinging doors.
Upcoming releases of FSD will remember your parking preferences, so that the car goes to the right location at your home, office, school drop off, etc.
Destination parking is by far the biggest reason people now intervene with FSD. Critical safety interventions are extremely…
— Elon Musk (@elonmusk) June 17, 2026
We’d imagine these new updates will also solve things like parking orientation. Let’s say when you arrive at work, you always park in the third spot in the third row, and you prefer to back in. It seems as if Musk is implying that your car will now do this, learning from takeovers and aiming to eliminate the need to manually park whenever possible.
This is a major upgrade because parking is a major shortcoming of FSD currently. We’ve requested things like manual input of parking preferences, choosing to park far away, first available, or away from cars, for example.
This is a big reason Parking Preferences with Supervised FSD will be so valuable.
If possible, parking a little further away and being distant from people like this is worth it. https://t.co/1YqQLgnfTz pic.twitter.com/3Ac71KQiQ3
— TESLARATI (@Teslarati) June 7, 2026
However, some have used the option of dropping a pin at the location you’d like to park at your destination. This has worked some of the time, but FSD will still choose to park in whatever it sees first.
Musk did not give a timetable for when the improvements would be released, but it is likely to come soon. Tesla has been releasing a new FSD version every few weeks, so we may not have to wait long to test it.
In a remarkable demonstration of how advanced vehicle technology can intersect with family care and rapid response, a Tesla Model Y equipped with Full Self-Driving (FSD) Supervised helped save a driver’s life during a severe heart attack. The incident, which occurred on November 15, 2025, highlights the life-saving potential of Tesla’s connected ecosystem.
John Brandt, 55, was driving his new 2026 Model Y Launch Edition on Interstate 20 from Atlanta toward Birmingham early that morning. He had recently received the FSD v14.1.3 update. Around 3:50 a.m., he began experiencing severe chest pain. Barely conscious and unable to safely control the vehicle, John managed to call his son, Jack Brandt.
FSD Supervised remained engaged, keeping the car steadily on course while John reached out for help.
As an authorized driver on his father’s Tesla account, Jack quickly sprang into action from his own phone. He located Tanner Medical Center in Carrollton, Georgia—a facility equipped for cardiac emergencies—via Google Maps and shared the destination directly through the Tesla app.
A Model Y driver started experiencing a medical emergency with chest pain mid-drive & called his son.
His son then remotely rerouted the car – which had FSD Supervised enabled – to the nearest hospital & let them know the vehicle was en route. ER staff were standing by on… pic.twitter.com/yi1tHISK9y
— Tesla North America (@tesla_na) June 16, 2026
The Model Y responded immediately, rerouting: it took the next exit, turned around on I-20, navigated local roads, and pulled directly up to the emergency room entrance. Jack also alerted hospital staff that a heart attack patient was en route in a Tesla.
Doctors diagnosed John with a massive STEMI heart attack, requiring immediate intervention on three blocked arteries. They later confirmed that without the swift reroute, John likely would not have survived—whether he had pulled over to wait for an ambulance or attempted to continue driving. He received life-saving treatment and is now recovering fully.
Tesla shared the story on X, including an interview video featuring John and Jack reflecting on the event. John described the terrifying onset of symptoms, while Jack detailed the ease of remote intervention thanks to the app’s features. Only authorized users with vehicle access can change navigation destinations, adding a layer of security and family coordination.
This case underscores Tesla’s emphasis on connectivity and supervised autonomy. Features like remote navigation allow loved ones to assist in real-time emergencies, while FSD handles complex driving tasks reliably. Tesla notes that FSD Supervised requires active driver supervision and is not fully autonomous; this was a specific incident, not a general emergency protocol.
The story has resonated widely, with many praising Tesla’s technology for bridging gaps in critical moments. Jack previously shared details on social media in February 2026, and Tesla’s recent post has amplified its reach. As vehicles become smarter and more connected, such integrations could redefine personal safety on the road—turning cars into proactive partners in health crises.
For Tesla owners, the incident serves as a powerful reminder to add trusted family members as authorized drivers and explore FSD capabilities. While no technology replaces professional medical care, this blend of AI-assisted driving and seamless app control proved invaluable. John’s survival stands as a testament to innovation that prioritizes human life.
Elon Musk just upped his Tesla stake further fueling SpaceX merger conversation
Tesla Full Self-Driving is getting a major parking upgrade, Elon Musk says
