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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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Tesla has scaled back driver monitoring to be less naggy with the latest version of the Full Self-Driving (Supervised) suite, which is version 14.3.3.
The latest version is already earning praise from owners, who are reporting that the suite is far less invasive when it comes to keeping drivers from taking their eyes off the road. The first to mention it was notable Tesla community member on X known as Zack, or BLKMDL3.
14.3.3 nags less too https://t.co/IuiWzuYO6O
— Elon Musk (@elonmusk) May 18, 2026
Musk confirmed that v14.3.3 was made to nag drivers significantly less, something that Tesla has worked toward in the past and has said with previous versions that it is less likely to push drivers to look ahead, at least after looking away for a few seconds.
This refinement aligns with Tesla’s ongoing push toward unsupervised FSD. The update also brings faster Actual Smart Summon (now up to 8 mph), reliable “Hey Grok” voice commands, richer visualizations, smoother Mad Max acceleration, and an intervention streak counter that rewards consistent use. Reviewers describe the drive as more human-like and confident, with fewer twitches or unnecessary maneuvers.
Musk has repeatedly signaled this direction. In late 2025, he stated that FSD would allow phone use “depending on context of surrounding traffic,” noting safety data would justify relaxing rules so drivers could text in low-risk scenarios like stop-and-go traffic.
We tested this, and even still, the cell phone monitoring really seems to be less active in terms of alerting drivers:
Tesla Full Self-Driving v14.2.1 texting and driving: we tested it
Earlier, ahead of v14, Musk promised the system would “nag the driver much less” once safety metrics improved.
In 2023, he confirmed the steering wheel torque nag would be “gradually reduced, proportionate to improved safety,” shifting reliance to the cabin camera. Subsequent updates like v13.2.9 and v12.4 further loosened monitoring, cracking down on workarounds while easing legitimate distractions.
These steps reflect Tesla’s data-driven approach: FSD’s safety record—reportedly averaging millions of miles per crash—now outpaces human drivers in many scenarios, giving the company confidence to dial back interventions. Reduced nags improve usability and trust, encouraging more drivers to rely on the system rather than disengaging out of frustration.
However, there are certainly still some concerns. In many states, it is illegal to handle a cell phone in any way, requiring the use of hands-free devices. In Pennsylvania, it is illegal to use your cell phone at stop lights, which is definitely a step further than using it while the car is actively in motion.
v14.3.3 represents tangible progress. Making FSD less adversarial and more seamless is definitely a step forward, but drivers need to be aware of the dangers of distracted driving. FSD is extremely capable, but it is in no way fully autonomous, nor does its performance warrant owners to take their attention off the road.
Tesla has officially expanded its Full Self-Driving (FSD) suite in Europe once again, as it will now be offered to customer vehicles in Lithuania, marking a significant milestone as the second European Union country to offer the system.
Tesla confirmed FSD’s rollout in Lithuania this morning:
FSD Supervised now rolling out to Teslas in Lithuania 🇱🇹!
Making European roads safer, one by one pic.twitter.com/Uuj0bNG7pP
— Tesla Europe, Middle East & Africa (@teslaeurope) May 20, 2026
Tesla showed several clips of Full Self-Driving navigation in Lithuania to mark the announcement, while Lithuanian Transport Minister Juras Taminskas highlighted the system’s potential to assist with lane-keeping, speed adjustment, and traffic tasks on longer drives, while emphasizing that drivers must stay alert and ready to intervene.
Just a few weeks ago, Tesla officially entered Europe with Full Self-Driving in the Netherlands. The expansion of FSD on the continent is now officially underway.
Full Self-Driving’s European Journey
Europe has long posed one of the toughest regulatory challenges for Tesla’s autonomy ambitions due to stringent safety standards under the United Nations Economic Commission for Europe (UNECE) framework, particularly UN Regulation 171 for Driver Control Assistance Systems.
The Netherlands’ RDW authority granted the pioneering approval after over 18 months of rigorous testing, including 1.6 million kilometers on European roads and extensive data submissions.
This approval enables mutual recognition across the EU, allowing other member states to adopt it nationally without full re-testing. Lithuania quickly leveraged this mechanism, becoming the second adopter. Tesla positions FSD Supervised as a tool to incrementally improve road safety, with the company claiming it reduces incidents when used properly.
Bottlenecks slowing broader European deployment include fragmented national regulations, varying levels of regulatory skepticism, and requirements for robust driver monitoring. Some EU officials have raised concerns about performance in adverse conditions like icy roads or speeding scenarios, alongside frustrations over Tesla’s public advocacy approach.
Additional hurdles involve data privacy, liability frameworks, and the need for EU-wide harmonization. While countries like Belgium appear to be fast-tracking adoption, larger markets such as Germany, France, and Italy are expected to follow in the coming months, with potential EU-wide progress targeted for later in 2026.
Tesla Full Self-Driving Across the World
As of May, Full Self-Driving (Supervised) is available in approximately ten countries.
In North America, it has been live for years in the United States, Canada, Mexico, and Puerto Rico. Asia-Pacific additions include Australia, New Zealand, and South Korea, while China utilizes what Tesla calls “City Autopilot.” In Europe, the Netherlands and now Lithuania join the list, with more countries mulling the possibility of also approving FSD.
Tesla offers FSD via monthly subscriptions (around €99 in Europe) or one-time purchases (with deadlines approaching in many markets), shifting toward recurring revenue models. Today is the final day Europeans will be able to purchase the suite outright.
This expansion underscores Tesla’s push for global autonomy, starting with supervised and building toward greater capabilities. With Lithuania now online, momentum is building across Europe, though regulatory caution will continue shaping the pace. Owners in approved regions report smoother highway and urban driving, but the system remains Level 2, which requires human oversight.
Elon Musk
Tesla ditches India after years of broken promises
Tesla has ditched its plans to build a factory in India after years of failed negotiations.
Tesla’s long-running effort to establish a manufacturing presence in India is officially over. India’s Minister of Heavy Industries H.D. Kumaraswamy confirmed on May 19, 2026 that Tesla has informed authorities it will not proceed with a manufacturing facility in the country.
Tesla first signaled serious interest in India around 2021, when it began hiring local staff and lobbying the Indian government for lower import tariffs. The ask was straightforward: reduce duties enough for Tesla to test the market with imported vehicles before committing capital to a local factory. India’s position was equally firm, with an ask of Tesla to commit to manufacturing first, then receive tariff relief. Neither side moved, and the talks quietly collapsed.
Tesla to open first India experience center in Mumbai on July 15
India had offered a policy that would reduce import duties from 110% down to 15% on EVs priced above $35,000, provided companies committed at least $500 million toward local manufacturing investment within three years. Tesla declined to participate. The tariff standoff was only part of the problem. Analysts pointed to significant gaps in India’s local supply chain, inadequate industrial infrastructure, and a mismatch between Tesla’s premium pricing and the purchasing power of India’s automotive market as additional factors that made the investment difficult to justify.
First signs of an unraveling relationship came in April 2024, when Musk abruptly cancelled a planned trip to India where he was set to meet Prime Minister Modi and announce Tesla’s market entry. By July 2024, Fortune reported that Tesla executives had stopped contacting Indian government officials entirely. The government at that point understood Tesla had capital constraints and no plans to invest.
The more fundamental issue is that Tesla’s existing factories are currently operating at approximately 60% capacity, making a commitment to building new manufacturing capacity in a new market difficult to defend to investors. Tesla will continue selling imported Model Y vehicles through its existing showrooms in Mumbai, Delhi, Gurugram, and Bengaluru, but local production is no longer part of the plan.
Tesla scales back driver monitoring with latest Full Self-Driving release
Tesla Full Self-Driving expands in Europe, entering its second country
