News
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.
Tesla is going to fix the nearly 219,000 vehicles that it recalled due to an issue with the rearview camera with a simple software update, giving owners no need to travel to a service center to resolve the problem.
Tesla is formally recalling 218,868 U.S. vehicles after regulators discovered a software glitch that can delay the rearview camera image by up to 11 seconds when drivers shift into reverse.
The affected models include certain 2024-2025 Model 3 and Model Y, as well as 2023-2025 Model S and Model X vehicles running software version 2026.8.6 and equipped with Hardware 3 computers. The National Highway Traffic Safety Administration (NHTSA) determined the lag violates Federal Motor Vehicle Safety Standard 111 on rear visibility and could increase crash risk.
Yet this is no ordinary recall. Owners do not need to schedule a service-center visit, hand over keys, or wait for parts.
Tesla fans call for recall terminology update, but the NHTSA isn’t convinced it’s needed
Tesla identified the issue on April 10, halted further deployment of the faulty firmware the same day, and began pushing a corrective over-the-air (OTA) software update on April 11.
By the time the NHTSA posted the recall notice on May 6, more than 99.92 percent of the affected fleet had already received the fix. Tesla reports no crashes, injuries, or fatalities linked to the glitch.
The episode underscores a deeper problem with regulatory language. For decades, “recall” meant hauling a vehicle to a dealership for hardware repairs or replacements. That definition no longer fits software-defined cars. When a fix arrives wirelessly in minutes — identical to an iPhone update — the term evokes unnecessary alarm and misleads the public about the actual risk and remedy.
Elon Musk has repeatedly called for exactly this change. After earlier NHTSA actions, he stated plainly: “The terminology is outdated & inaccurate. This is a tiny over-the-air software update.” On another occasion, he added that labeling OTA fixes as recalls is “anachronistic and just flat wrong.”
The terminology is outdated & inaccurate. This is a tiny over-the-air software update. To the best of our knowledge, there have been no injuries.
— Elon Musk (@elonmusk) September 22, 2022
Musk’s point is simple: regulators must evolve their vocabulary to match the technology. Traditional recalls involve physical intervention and downtime; OTA updates do not. Retaining the old label distorts consumer perception, inflates perceived defect rates, and slows the industry’s shift to faster, safer software iteration.
Tesla’s rapid, remote remedy demonstrates the safety advantage of over-the-air capability. Problems that once required weeks of dealer appointments are now resolved in hours, often before most owners notice. As more automakers adopt software-first designs, the entire regulatory framework needs to catch up.
Updating “recall” terminology would align language with reality, reduce public confusion, and recognize that modern vehicles are no longer static hardware — they are continuously improving computers on wheels.
For the 219,000 Tesla owners involved, the process is already complete. The camera works, the car is safe, and no one left their driveway. That is the new standard — and the vocabulary should reflect it.
News
Tesla is seeing record sales rebounds in key markets globally
Tesla reported robust sales momentum in April 2026, extending a multi-month recovery in its two largest markets amid intensifying global EV competition.
Tesla is seeing record sales rebounds in key markets across the world, and as skeptics and bears of the company that builds electric powertrains rejoice on the weak registration figures that have been reported in the past, the Musk-fronted company is keen on making a comeback.
Tesla reported robust sales momentum in April 2026, extending a multi-month recovery in its two largest markets amid intensifying global EV competition.
While the company does not release official monthly global delivery figures—reserving those for quarterly reports—data from local registration and wholesale sources show significant year-over-year gains in China and several European countries, building on a turnaround from 2025’s declines.
In China, Tesla’s Shanghai Gigafactory shipped 79,478 Model 3 and Model Y vehicles in April, a 36% increase from the same month last year. The figure marks the sixth consecutive month of year-on-year growth for China-made EVs, which include both domestic sales and exports to Europe and other regions.
Although down slightly from March’s 85,670 units, the April performance underscores Tesla’s resilience against domestic rivals like BYD. Wholesale volumes from the plant have helped Tesla regain ground after softer retail figures earlier in the year, with analysts noting improved demand fueled by competitive pricing and new configurations
Europe also delivered encouraging results. Registrations—a close proxy for sales—surged in multiple countries. France posted a 112 percent jump, Sweden 111%, Denmark 102%, and Ireland 100%. The Netherlands rose 23%, while Belgium and Romania recorded gains of 47% and 53%, respectively.
These double- and triple-digit increases reflect a broader EV market recovery across the continent, where battery-electric vehicle market share climbed to 20.5% in Q1 2026 from 13.2% a year earlier. Chinese brands continue to challenge Tesla’s position in some markets, but the U.S. automaker’s rebound has been widespread in Northern and Western Europe.
Germany, Europe’s largest auto market, contributed to the positive momentum. Although full April registration data had not yet been released as of early May, March’s figures were record-setting: 9,252 Tesla vehicles registered, a staggering 315% increase year-over-year and the company’s strongest March performance in years.
Germany reported 3,149 Tesla sales and 1.3% market share in April. BEV penetration is 25.8% and Tesla has 4.9% of this segment. 🇩🇪
• +256% vs. April last year and +142% compared to January the first month of the previous quarter
• Best April ever
• Highest first month of the… pic.twitter.com/n4MIJv4w6t— Roland Pircher (@piloly) May 7, 2026
That month alone accounted for 72% of Tesla’s Q1 total in Germany (12,829 units, up 160%). Industry observers expect April to follow suit, supported by new EV subsidies and rising fuel prices.
The April figures come after Tesla’s Q1 2026 global deliveries of 358,023 vehicles, which showed modest growth but trailed some analyst expectations. The European and Chinese rebounds suggest accelerating demand heading into Q2, driven by refreshed lineups, competitive pricing, and expanding charging infrastructure.
However, Tesla faces ongoing pressure from lower-cost Chinese competitors and softening demand in select markets like Norway and Portugal, where April registrations fell sharply.
Overall, April’s data paints an optimistic picture for Tesla. The company’s ability to post consistent growth in China while reclaiming share in Europe signals renewed strength after 2025’s challenges.
Investors and analysts will watch closely for May and June numbers as Tesla prepares its Q2 report, which could confirm whether this rebound translates into sustained record-setting momentum. With approximately 450 words, this snapshot highlights how targeted execution is paying dividends in Tesla’s most critical regions
Lifestyle
Tesla Semi hauls fresh Cybercab batch as Robotaxi era takes hold
A Tesla Semi was filmed hauling Cybercab units out of Giga Texas for the first time.
A Tesla Semi loaded with Cybercab units was recently filmed leaving Gigafactory Texas, marking what appears to be the first documented delivery run of Tesla’s autonomous two-seater. The footage shows multiple Cybercabs secured on a flatbed trailer being hauled by a production Tesla Semi, a truck rated for a gross combination weight of 82,000 lbs. The location is consistent with Giga Texas in Austin, where Cybercab production has been ramping since February 2026.
The sighting follows a wave of Cybercab activity at the Austin facility. In late April, drone operator Joe Tegtmeyer spotted approximately 60 Cybercabs parked in two organized groups in the factory’s outbound lot, the largest concentration observed to date. Units being staged in an outbound lot is a standard pre-delivery step, and the Semi footage is the logical next frame in that sequence.
En route with @tesla_semi pic.twitter.com/ZfuOjaeLH1
— Tesla Robotaxi (@robotaxi) May 7, 2026
This is not the first time Tesla has used its own Semi to move Tesla products. When the Semi was unveiled in 2017, Musk noted it would be used for Tesla’s own operations, and over the years Semi prototypes were spotted carrying cargo ranging from concrete weights to Tesla vehicles being delivered to consumers. In 2023, a Semi was photographed transporting a Cybertruck on a trailer ahead of that vehicle’s delivery launch.
The Cybercab itself was first revealed publicly at Tesla’s “We, Robot” event on October 10, 2024, at Warner Bros. Studios in Burbank, where 20 pre-production units gave attendees rides around the studio lot. Musk stated at the event that Tesla intends to produce the Cybercab before 2027. The first production unit rolled off the Giga Texas line on February 17, 2026, with Musk posting on X: “Congratulations to the Tesla team on making the first production Cybercab.”
Tesla’s annual production goal is 2 million Cybercabs per year once multiple factories reach full design capacity, with the company targeting a price under $30,000 per unit. Tesla has confirmed plans to expand its robotaxi service to seven cities in the first half of 2026, including Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas, building on the unsupervised service already running in Austin. Musk has said he expects robotaxis to cover between a quarter and half of the United States by end of year.
Tesla to fix 219k vehicles in recall with simple software update
Tesla is seeing record sales rebounds in key markets globally
