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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving
Tesla released FSD Beta 10.69 to the first round of testers over the weekend. Read v.10.69’s release notes below to check out the latest improvements.
Stay in your Lanes
- 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 connectivites. 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.
Nothing Like Smooth Driving
- 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 manevuers.
- 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.
- 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.
- Reduced latency when starting from a stop by accounting for lead vehicle jerk.
Chuck’s Left Turn
- 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 optimizable 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.
Safety is Number 1
- 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.
- Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
- Improved speed when entering highway by better handling of upcoming map speed changes, which increases the confidence of merging onto the highway.
- Enabled faster identification of red light runners by evaluating their current kinematic state against their expected braking profile.
Tesla FSD “Brain” Improvements
- 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.
- 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.
- Improved recall of animals by 34% by doubling the size of the auto-labeled training set.
- 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.
Tesla is rolling out FSD Beta v.10.69 in phases, starting with ~1,000 testers over the weekend. Once the update is rolled out for wide release, the price of FSD Beta will increase.
The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.
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Elon Musk’s Grokipedia surges to 5.6M articles, almost 79% of English Wikipedia
The explosive growth marks a major milestone for the AI-powered online encyclopedia, which was launched by Elon Musk’s xAI just months ago.
Elon Musk’s Grokipedia has grown to an impressive 5,615,201 articles as of today, closing in on 79% of the English Wikipedia’s current total of 7,119,376 articles.
The explosive growth marks a major milestone for the AI-powered online encyclopedia, which was launched by Elon Musk’s xAI just months ago. Needless to say, it would only be a matter of time before Grokipedia exceeds English Wikipedia in sheer volume.
Grokipedia’s rapid growth
xAI’s vision for Grokipedia emphasizes neutrality, while Grok’s reasoning capabilities allow for fast drafting and fact-checking. When Elon Musk announced the initiative in late September 2025, he noted that Grokipedia would be an improvement to Wikipedia because it would be designed to avoid bias.
At the time, Musk noted that Grokipedia “is a necessary step towards the xAI goal of understanding the Universe.”
Grokipedia was launched in late October, and while xAI was careful to list it only as Version 0.1 at the time, the online encyclopedia immediately earned praise. Wikipedia co-founder Larry Sanger highlighted the project’s innovative approach, noting how it leverages AI to fill knowledge gaps and enable rapid updates. Netizens also observed how Grokipedia tends to present articles in a more objective manner compared to Wikipedia, which is edited by humans.
Elon Musk’s ambitious plans
With 5,615,201 total articles, Grokipedia has now grown to almost 79% of English Wikipedia’s article base. This is incredibly quick, though Grokipedia remains text-only for now. xAI, for its part, has now updated the online encyclopedia’s iteration to v0.2.
Elon Musk has shared bold ideas for Grokipedia, including sending a record of the entire knowledge base to space as part of xAI’s mission to preserve and expand human understanding. At some point, Musk stated that Grokipedia will be renamed to Encyclopedia Galactica, and it will be sent to the cosmos.
“When Grokipedia is good enough (long way to go), we will change the name to Encyclopedia Galactica. It will be an open source distillation of all knowledge, including audio, images and video. Join xAI to help build the sci-fi version of the Library of Alexandria!” Musk wrote, adding in a later post that “Copies will be etched in stone and sent to the Moon, Mars and beyond. This time, it will not be lost.”
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Tesla Model 3 becomes Netherlands’ best-selling used EV in 2025
More than one in ten second-hand electric cars sold in the country last year was a Tesla Model 3.
The Tesla Model 3 became the most popular used electric car in the Netherlands in 2025, cementing its dominance well beyond the country’s new-car market.
After years at the top of Dutch EV sales charts, the Model 3 now leads the country’s second-hand EV market by a wide margin, as record used-car purchases pushed electric vehicles further into the mainstream.
Model 3 takes a commanding lead
The Netherlands recorded more than 2.1 million used car sales last year, the highest level on record. Of those, roughly 4.8%, or about 102,000 vehicles, were electric. Within that growing segment, the Tesla Model 3 stood far ahead of its competitors.
In 2025 alone, 11,338 used Model 3s changed hands, giving the car an 11.1% share of the country’s entire used EV market. That means more than one in ten second-hand electric cars sold in the country last year was a Tesla Model 3, Auto Week Netherlands reported. The scale of its lead is striking: the gap between the Model 3 and the second-place finisher, the Volkswagen ID3, is more than 6,700 vehicles.
Rivals trail as residual values shape rankings
The Volkswagen ID.3 ranked a distant second, with 4,595 used units sold and a 4.5% market share. Close behind was the Audi e-tron, which placed third with 4,236 registrations. As noted by Auto Week Netherlands, relatively low residual values likely boosted the e-tron’s appeal in the used market, despite its higher original price.
Other strong performers included the Kia Niro, the Tesla Model Y, and the Hyundai Kona, highlighting continued demand for compact and midsize electric vehicles with proven range and reliability. No other model, however, came close to matching the Model 3’s scale or market presence.
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Tesla Model Y Standard Long Range RWD launches in Europe
The update was announced by Tesla Europe & Middle East in a post on its official social media account on X.
Tesla has expanded the Model Y lineup in Europe with the introduction of the Standard Long Range RWD variant, which offers an impressive 657 km of WLTP range.
The update was announced by Tesla Europe & Middle East in a post on its official social media account on X.
Model Y Standard Long Range RWD Details
Tesla Europe & Middle East highlighted some of the Model Y Standard Long Range RWD’s most notable specs, from its 657 km of WLTP range to its 2,118 liters of cargo volume. More importantly, Tesla also noted that the newly released variant only consumes 12.7 kWh per 100 km, making it the most efficient Model Y to date.
The Model Y Standard provides a lower entry point for consumers who wish to enter the Tesla ecosystem at the lowest possible price. While the Model 3 Standard is still more affordable, some consumers might prefer the Model Y Standard due to its larger size and crossover form factor. The fact that the Model Y Standard is equipped with Tesla’s AI4 computer also makes it ready for FSD’s eventual rollout to the region.
Top Gear’s Model Y Standard review
Top Gear‘s recent review of the Tesla Model Y Standard highlighted some of the vehicle’s most notable features, such as its impressive real-world range, stellar infotainment system, and spacious interior. As per the publication, the Model Y Standard still retains a lot of what makes Tesla’s vehicles well-rounded, even if it’s been equipped with a simplified interior.
Top Gear compared the Model Y Standard to its rivals in the same segment. “The introduction of the Standard trim brings the Model Y in line with the entry price of most of its closest competition. In fact, it’s actually cheaper than a Peugeot e-3008 and costs £5k less than an entry-level Audi Q4 e-tron. It also makes the Ford Mustang Mach-E look a little short with its higher entry price and worse range,” the publication wrote.
Elon Musk’s Grokipedia surges to 5.6M articles, almost 79% of English Wikipedia
Tesla Model 3 becomes Netherlands’ best-selling used EV in 2025
