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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.
News
Tesla Cabin Camera gets an incredible new feature for added driver safety
The company quietly expanded the capabilities of its in-cabin camera with the rollout of Software Update 2026.8.6. Tesla hacker greentheonly revealed that coding for the software version provides details on now tracking the age of the driver.
Tesla’s interior Cabin-facing Camera just got a brand new feature that is an incredible addition, as it provides yet another layer of added safety.
The company quietly expanded the capabilities of its in-cabin camera with the rollout of Software Update 2026.8.6. Tesla hacker greentheonly revealed that coding for the software version provides details on now tracking the age of the driver.
The camera, which is positioned just above the rearview mirror, is now performing facial analysis to estimate the driver’s age. While not yet user-facing, the feature is the latest example of Tesla’s ongoing push to refine its driver monitoring system for both everyday safety and future Robotaxi operations.
Ha, interesting, cabin camera / driver monitor is now (2026.8.6) doing “driver age” checking.
I wonder if it’s going to filter out children or elderly too?
— green (@greentheonly) April 10, 2026
The cabin camera already processes images entirely onboard the vehicle for privacy, sharing data with Tesla only if owners enable it during safety-critical events.
Age estimation likely uses computer vision to classify facial features, similar to existing attention-tracking algorithms. Potential applications include preventing underage drivers from engaging Full Self-Driving (FSD) or shifting into drive, acting as a secondary safety lock.
It could also be linked to Robotaxi readiness: the upcoming Cybercab will need robust occupant verification to ensure children cannot hail or ride unsupervised.
In consumer vehicles, it could enable tailored FSD behaviors—more conservative acceleration and braking for elderly drivers, for instance—or simply block unauthorized use by minors.
Beyond age checks, the cabin camera powers Tesla’s comprehensive driver monitoring system, introduced years earlier and continuously improved. It first gained prominence for detecting inattentiveness. When Autopilot or FSD is active, the camera tracks eye gaze, head position, and steering inputs in real time.
If the driver looks away too long or fails to keep their hands ready, the system issues escalating visual and audible alerts before disengaging assistance. This has dramatically reduced misuse cases and helped Tesla meet stricter regulatory demands for hands-on supervision.
The camera also monitors for drowsiness. Activated above roughly 40 mph (65 km/h) after at least 10 minutes of manual driving, the Driver Drowsiness Warning analyzes facial cues—frequency of yawns and blinks—alongside driving patterns like lane drifting or erratic steering.
When fatigue is detected, a clear on-screen message and chime prompt the driver to pull over and rest, or even to activate Full Self-Driving. Tesla explicitly states this feature enhances active safety without relying on facial recognition for identity.
These layered capabilities create a robust safety net. Inattentiveness detection alone has curbed distracted driving during assisted operation. Drowsiness alerts address a leading cause of highway crashes by intervening before impairment escalates.
Adding age verification extends this protection: it could flag inexperienced young drivers for extra caution or restrict high-autonomy features, while preparing vehicles for a future where robotaxis must safely manage passengers of all ages.
With privacy safeguards intact and processing done locally, Tesla’s cabin camera continues evolving from a simple attention monitor into a sophisticated guardian—advancing safer roads today and autonomous mobility tomorrow.
Elon Musk
Tesla’s Semi truck factory is open with a detail that changes everything
Tesla’s dedicated Nevada Semi factory has opened, targeting 50,000 trucks per year as fleet adoptions accelerate nationwide.
Nearly nine years after Elon Musk unveiled the Tesla Semi in November 2017, the company is now opening a dedicated factory just outside of Reno, Nevada, and ramping toward mass production of 50,000 trucks per year.
Volume production began in March 2026 at the new Tesla Semi factory, with the competitive advantage not being the factory itself. Rather, it’s where Tesla built it. By constructing the 1.7 million square foot facility directly adjacent to Gigafactory Nevada in Sparks, Tesla closed the one supply chain loop that had delayed the Semi program for years. The 4680 battery cells that power the Semi are manufactured in the same complex, which significantly streamlines supply logistics. That single decision eliminates the bottleneck that forced Tesla to prioritize battery supply for passenger cars over the Semi throughout 2020, 2021, and 2022, which is precisely why the first deliveries slipped three years past the original target. Every other electric truck manufacturer sources its battery cells from a separate supplier, ships them to a separate factory, and absorbs the cost and delay that comes with that. Tesla built its Semi factory around its battery factory, and that vertical integration is what makes 50,000 trucks per year a realistic number rather than an aspirational one.
At the 2025 Annual Shareholder Meeting, Musk was direct about where things stood, stating “Starting next year, we will manufacture the Tesla Semi. We already have a lot of prototype Semis in operation – PepsiCo and other companies have been using them for some time. But in 2026, we’ll begin volume production at our Northern Nevada factory.” Full ramp to volume output is targeted before June 30, 2026.
🚨 Awesome new video showing the new Tesla Semi factory in Sparks, Nevada
The future of sustainable logistics is being built here: pic.twitter.com/dbiGV8FYn3
— TESLARATI (@Teslarati) April 10, 2026
The first limited deliveries happened in December 2022 to PepsiCo, which eventually doubled its fleet to 50 trucks out of its California distribution facility. Since then the Semi has been showing up in more corporate fleets. As Teslarati noted in March, a Ralph’s Supermarkets branded Semi was spotted on a Los Angeles highway, confirming Kroger’s partnership with Tesla to deploy up to 500 electric Semis. Walmart, Costco, Sysco, US Foods, DHL, Hight Logistics and WattEV are among the companies actively running or receiving units. DHL logged real-world efficiency of 1.72 kWh per mile under a full 75,000 pound load over 388 miles, matching Tesla’s targets closely.
The 2026 production model arrives with meaningful upgrades over the original, with a 1,000 pound weight reduction, updated aerodynamics, and support for 1.2 MW Megacharger speeds that can restore 60% of range in around 30 minutes during a mandatory driver rest break. Tesla opened its first public Megacharger in Ontario, California in March, positioned near the I-10 and I-15 interchange serving the Ports of Los Angeles and Long Beach. The company plans 37 Megacharger sites by end of 2026 and 66 total across 15 states by early 2027, with construction beginning at the nation’s largest truck stop operator in the first half of this year.
Tesla reveals various improvements to the Semi in new piece with Jay Leno
Musk has described the Semi’s economics as a straightforward case. “The Semi is a TCO no-brainer,” he said, noting the total cost of ownership is “much, much cheaper than any other transportation you could have.” At under $300,000, the truck costs roughly double a comparable diesel, but California’s $200,000 per vehicle subsidy has driven over 1,000 state orders alone. As Teslarati has tracked, the prototype fleet accumulated over 13.5 million miles with 95% fleet uptime before production ever scaled. The factory opening now turns that proof of concept into a production program.
News
Tesla Full Self-Driving gets first-ever European approval
Tesla owners in the Netherlands with a Full Self-Driving subscription will receive a software update “shortly,” the company said, activating the operation of the company’s semi-autonomous driving tech for the first time in Europe.
Tesla Full Self-Driving (Supervised) got its first-ever European approval, as the Netherlands gave the suite the green light to begin operation.
Tesla owners in the Netherlands with a Full Self-Driving subscription will receive a software update “shortly,” the company said, activating the operation of the company’s semi-autonomous driving tech for the first time in Europe.
The Dutch vehicle authority RDW granted the type approval after more than 18 months of rigorous testing on both closed tracks and public roads. FSD Supervised complies with UN R-171 standards and benefits from Article 39 exemptions under EU Regulation 2018/858. Importantly, it is not a fully autonomous vehicle.
The RDW stressed that the driver remains fully responsible and must maintain attention at all times. “Safety is paramount for the RDW,” the authority stated. “Proper use of this driver assistance system contributes positively to road safety.” Sensors monitor driver alertness, issuing warnings if eyes leave the road or hands are unavailable to take control immediately.
CEO Elon Musk also commented on the approval in a post on X, saying:
“First (supervised) FSD approval in Europe! Congratulations to the Tesla team and thank you to the regulatory authorities in the Netherlands for all of the hard work required to make this happen.”
First (supervised) FSD approval in Europe!
Congratulations to the Tesla team and thank you to the regulatory authorities in the Netherlands for all the hard work required to make this happen. https://t.co/8hidEOPSxm
— Elon Musk (@elonmusk) April 10, 2026
Trained on billions of kilometers of real-world driving data, FSD Supervised allows the vehicle to handle residential streets, dense city traffic, and highways under constant supervision. Tesla’s post declared:
“It can drive you almost anywhere under your supervision – from residential roads to city streets & highways. No other vehicle can do this.”
The company added that it is “excited to bring FSD Supervised to more European countries soon.”
This national approval paves the way for broader EU adoption. Other member states can recognize the Dutch certification individually, with a potential bloc-wide rollout via European Commission committee vote anticipated by this Summer. The decision underscores Europe’s stricter safety and documentation requirements compared to U.S. self-certification.
Tesla Europe shares FSD test video weeks ahead of launch target
The Netherlands’ approval represents a pivotal step for Tesla in Europe, where complex regulations and mixed traffic have delayed rollout. Musk added that the RDW was “rigorous” in its assessment of FSD.
By proving the system’s safety in one of the continent’s most bicycle- and tram-heavy nations, Tesla positions itself to transform mobility across the EU—delivering greater convenience while keeping drivers firmly in control.
As the first domino falls, anticipation builds for FSD Supervised to reach additional countries soon.
Tesla Cabin Camera gets an incredible new feature for added driver safety
Tesla’s Semi truck factory is open with a detail that changes everything
