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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.
Elon Musk
Tesla’s $2.9 billion bet: Why Elon Musk is turning to China to build America’s solar future
Tesla looks to bring solar manufacturing to the US, with latest $2.9 billion bet to acquire Chinese solar equipment.
Tesla is reportedly in talks to purchase $2.9 billion worth of solar manufacturing equipment from a group of Chinese suppliers, including Suzhou Maxwell Technologies, which is the world’s largest producer of screen-printing equipment used in solar cell production. According to Reuters sources, the equipment is expected to be delivered before autumn and shipped to Texas, where Tesla plans to anchor its next phase of domestic solar production.
The move is a direct extension of a vision Elon Musk has been building for months. At the World Economic Forum in Davos this past January, Musk announced that both Tesla and SpaceX were independently working to establish 100 gigawatts of annual solar manufacturing capacity inside the United States. Days later, on Tesla’s Q4 2025 earnings call, he made the ambition concrete: “We’re going to work toward getting 100 GW a year of solar cell production, integrating across the entire supply chain from raw materials all the way to finished solar panels.”
Job postings on Tesla’s website reflect that same target, with language explicitly calling for 100 GW of “solar manufacturing from raw materials on American soil before the end of 2028.”
Tesla job listing for Staff Manufacturing Development Engineer, Solar Manufacturing
The urgency behind the latest solar manufacturing target is rooted in a set of rapidly emerging pressures related to AI and Tesla’s own energy business. U.S. power consumption hit its second consecutive record high in 2025 and is projected to climb further through 2026 and 2027, driven largely by the explosion in AI data centers and the broader electrification of transportation. Tesla’s own energy division, which produces the Megapack utility-scale battery storage system, has been growing rapidly, and solar supply is a critical companion component for the business to scale. Musk has argued that solar is not just a clean energy option but the only one that makes economic sense at the scale AI infrastructure demands.
Tesla lands in Texas for latest Megapack production facility
Ironically, the path to domestic solar independence currently runs through China. Sort of.
Despite Tesla’s stated push to localize its supply chain, mirrored recently by the company’s plan for a $4.3 billion LFP battery manufacturing partnership with LG Energy Solution in Michigan, Tesla still relies on China-based suppliers to keep its cost structure intact.
The $2.9 billion equipment deal underscores a tension Musk himself acknowledged at Davos: “Unfortunately, in the U.S. the tariff barriers for solar are extremely high and that makes the economics of deploying solar artificially high, because China makes almost all the solar.” Building the factory in America requires buying the machinery from the country Tesla is trying to reduce its dependence on.
Tesla named by U.S. Gov. in $4.3B battery deal for American-made cells
The regulatory pathway adds another layer of complexity. Suzhou Maxwell has been seeking export approval from China’s commerce ministry, and it remains unclear how quickly that clearance will come. Still, the market has already reacted, with shares in the Chinese firms reportedly involved in the talks surged more than 7% following the Reuters report that broke the story.
Whether Tesla can hit its 2028 target of 100GW of solar manufacturing remains an open question. Though that scale may seem staggering, especially in such a short timeframe, we know that Musk has a documented history of “always pulling it off” in the face of ambitious deadlines that may slip. But, rest assured – it’ll get done.
Elon Musk
Elon Musk reveals date of Tesla Full Self-Driving’s next massive release
Initially planned for a January or February release, v14.3 aims to add some reasoning and logic to the decisions that Full Self-Driving makes, which could improve a lot of things, including Navigation, which is a major complaint of many owners currently.
Tesla CEO Elon Musk revealed the date of Full Self-Driving’s next massive release: v14.3.
For months, Tesla owners with Hardware 4 have been utilizing Full Self-Driving v14.2 and subsequent releases. Currently, the most up-to-date FSD version is v14.2.2.5, which has definitely brought out mixed reviews. With releases, some things get better, and other things might regress slightly.
For the most part, things are better in terms of overall behavior.
However, many owners have been looking forward to the next release, which is v14.3, about which Musk has said many great things. Back in November, Musk said that v14.3 “is where the last big piece of the puzzle lands.”
He added:
“We’re gonna add a lot of reasoning and RL (reinforcement learning). To get to serious scale, Tesla will probably need to build a giant chip fab. To have a few hundred gigawatts of AI chips per year, I don’t see that capability coming online fast enough, so we will probably have to build a fab.”
Initially planned for a January or February release, v14.3 aims to add some reasoning and logic to the decisions that Full Self-Driving makes, which could improve a lot of things, including Navigation, which is a major complaint of many owners currently.
Tesla Full Self-Driving v14.2 is a considerable improvement from early versions of the suite, but we have written about the somewhat confusing updates that have come with recent versions.
Tesla Full Self-Driving v14.2.2.5 might be the most confusing release ever
They’ve been incredibly difficult to gauge in terms of progress because some things have gotten better, but there seems to be some real regression on a handful of things, especially with confidence and assertiveness.
Musk confirmed today on X that Tesla is already testing v14.3 internally right now. It will hit a wide release “in a few weeks,” so we should probably expect it by late April.
It’s in testing right now. Wide release in a few weeks.
— Elon Musk (@elonmusk) March 19, 2026
Overall, there are high hopes that v14.3 could be a true game changer for Tesla Full Self-Driving, as many believe it could be the version that Robotaxis in Austin, Texas, some of which are driverless and unsupervised, are running.
It could also include some major additions, including “Banish,” also referred to as “Reverse Summon,” which would go find a parking spot after dropping occupants off at their destination.
What Tesla will roll out, and when exactly it arrives, all remain to be seen, but fans have been ready for a new version as v14.2.2.5 has definitely run its course. We have had a lot of readers tell us their biggest request is to fix Navigation errors, which seem to be one of the most universal complaints among daily FSD users.
Cybertruck
Chattanooga Charge: Tesla and EV fans ready for the Southeast’s wildest Tesla party
From Cybertruck Convoys to Kid-Friendly Fun Zones: The Chattanooga Charge Has Something for Everyone
Hundreds of like-minded Tesla and EV enthusiasts are descending on Chattanooga Charge this weekend for the largest Tesla meet in the Southeast. Taking place on March 20–22, 2026 at the stunning Tennessee Riverpark.
If you were there last year, you’ll know that it’s the ultimate experience to see the wildest Teslas in action, see the best in EV tech, and arguably the most fun – finally put a name to the face and connect with those social media buddies IRL! Oh, and that epic night time Tesla light show is a once-in-a-lifetime experience that will transform the Riverpark into something out of a sci-fi film that’s remarkably unforgettable and must be seen in person.
This year’s event takes everything up a notch, with over 100 Cybertrucks expected to be on display, many sporting jaw-dropping modifications and custom wraps that push the boundaries of what these stainless steel beasts can look like.
Whether you’re a diehard Tesla fan, EV supporter, or just EV-mod-curious, the sheer spectacle is worth the drive.
The Chattanooga Charge doesn’t wait until Saturday morning to get started. The weekend technically kicks off Friday, March 20th, and the venue sets the tone immediately. Come share roadtrip stories over drinks at the W-XYZ Rooftop Bar on the top floor of the Aloft Chattanooga Hamilton Place Hotel, with sunset views over the city.
Come morning, nurse your hangover with a some good coffee, and convoy with hundreds of other Tesla and EV drivers through Chattanooga to the event for some morning meet and greets before the speaker panel starts and the food trucks fire up.
Tesla owner clubs travel from across the country to be here, not just to show off their vehicles,, but to connect, share, and celebrate a shared passion for the future of driving.
Sounds like a plan to me. See you there, guys. Don’t miss it. Get your tickets at ChattanoogaCharge.com and join the charge. 🔋⚡
Chattanooga Charge is a premier Tesla and EV gathering inspired by the X Takeover, known as one of the largest Tesla event gatherings. What began as a bold idea from the team at DIY Wraps/TESBROS, hosted in their hometown of Chattanooga, Tennessee, the event quickly became a movement across social media. The first annual Chattanooga Charge united over 16 Tesla clubs from 16 states, proof that the EV community was hungry for something big in the South. Year after year, the event has grown in scale, ambition, and heart.
Tesla’s $2.9 billion bet: Why Elon Musk is turning to China to build America’s solar future
Elon Musk reveals date of Tesla Full Self-Driving’s next massive release
