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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.
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– 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.
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– 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.
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– 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.
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Cybertruck
Tesla Cybertruck production snaps back after ugly supplier fight
Cybertrucks are piling up again at Giga Texas after Tesla’s court win against a parts supplier.
Cybertruck production at Giga Texas is showing its first visible recovery since Tesla sued a supplier last month over withheld manufacturing tooling.
Aerial observer Joe Tegtmeyer flew over the Austin factory Wednesday morning and counted roughly 100 or more Cybertrucks filling the outbound lot, a sharp jump from the thin numbers seen in recent weeks. The flyover came a day after a judge granted Tesla a temporary restraining order against Angstrom Automotive Group, the parts supplier at the center of the dispute.
Tesla filed an emergency lawsuit in late July after Angstrom told the automaker it planned to close the Troy, Texas facility where Tesla’s die-cast tools, trim dies and other Cybertruck stamping equipment were housed. According to Tesla’s complaint, a shipment of 700 finished parts never left the building, and when Tesla sent representatives to retrieve its equipment, accompanied by law enforcement, they were turned away. Angstrom allegedly then asked for an extra $250,000 a week to keep operating, which Tesla’s filing described as holding its own property for ransom.
TESLA: U.S. District Judge Christopher R. Wolfe of the U.S. District Court for the Western District of Texas, Waco Division granted Tesla a Temporary Restraining Order and Writ of Replevin in its dispute with Angstrom Automotive (Case No. 6:26-cv-00477).
The order authorizes… https://t.co/E1DKcQSxMn pic.twitter.com/LR8aAiV2Og
— S.E. Robinson, Jr. (@SERobinsonJr) August 5, 2026
The restraining order gives Tesla immediate right of entry to Angstrom’s facility to recover the tooling. It is temporary, with a fuller hearing still to come, but the speed of Wednesday’s rebound suggests the Angstrom shortage was indeed the main bottleneck limiting Cybertruck output. Outbound lot counts are an imperfect measure of actual production, since finished trucks can sit for days before shipping, but a lot that full after a lean stretch is a meaningful signal.
Cybertruck output at Giga Texas has fluctuated all year as Tesla worked through supply issues and introduced new trims, including a cheaper Dual Motor AWD version that drew strong early demand.
Elon Musk
Space finally faced the people living next to its next Terafab mega-project
SpaceX confirmed Terafab’s Grimes County site is locked in, with construction starting within months.
SpaceX and Terafab representatives sat across from Grimes County residents for the first time on Wednesday, telling a packed Commissioners Court room that the $55 billion chip manufacturing project is now a done deal at the Gibbons Creek Reservoir site.
The meeting followed a $10 million check SpaceX sent the county earlier this week, satisfying a payment deadline built into the tax abatement agreement both sides signed in June. Elon Musk shared a post on X confirming the payment, and County Judge Joe Fauth told the San Antonio Express-News his office deposited the check after it beat its deadline.
Wednesday’s session, first reported by KBTX, moved the project from paperwork to construction. Terafab representative Riley Trennell told residents the JETI tax break agreements with Iola ISD and Anderson-Shiro CISD are signed and active, and that civil work and foundation prep are starting almost immediately. Renderings of the facility could be released within days, he said, with construction beginning within months.
The foundations for an exciting future are being built in Texas. Next up: Terafab → https://t.co/jGg52Zhn5I pic.twitter.com/SNfSXNr2tb
— SpaceX (@SpaceX) August 6, 2026
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
Musk first announced Terafab in March as a joint venture between Tesla, SpaceX and xAI aimed at producing over a terawatt of AI compute annually, an amount that dwarfs the roughly 20 gigawatts the entire global chip industry produces today. Intel joined as a manufacturing partner in April. Musk has said the project needed its own day in the spotlight rather than being squeezed into an earnings call, and for months the Grimes County site remained unconfirmed even as reporting pointed there.
SpaceX attorney Buck Brannon used Wednesday’s meeting to note that the company’s abatement is roughly 78 percent, not the 100 percent some earlier reports suggested. In exchange, SpaceX will pay Grimes County a fixed $20 million a year for 35 years, a total of $710 million, which Brannon said exceeds the $14 million Tesla paid Travis County in 2025.
SpaceX also addressed environmental concerns that have followed the project since Musk’s Terafab partnership with Intel was announced. Representatives said Terafab will not raise electric bills for other ratepayers, will not deplete local water supplies and will not draw down the Navasota River. SpaceX confirmed it owns the Navasota River pumping station, which it plans to use to divert stormwater into the Gibbons Creek Reservoir, and said it will build its own natural gas plants to power the facility rather than pulling from the ERCOT grid.
Grimes County commissioners also approved an addendum letting county employees use ten approved AI chatbots for work, including Grok.
Elon Musk has declared that SpaceX has effectively solved one of Starship’s most persistent engineering challenges: the reliability of its heat shield tiles.
During the company’s first-ever Earnings Call, the SpaceX CEO stated:
“I don’t want to jinx it or anything, but I think I would call the heat shield problem solved at this point. All indications from data and visual inspection is we have solved it. That doesn’t mean we won’t make improvements, but we do not see any technical obstacles to achieving rapid reusability at this point.”
Starship’s heat shield consists of roughly 18,000 hexagonal ceramic tiles covering the windward side of the upper stage. These tiles form the thermal protection system that shields the vehicle’s stainless-steel structure from the extreme heat of atmospheric reentry.
Elon says he believes the heat shield problem with Starship is currently solved.
He called it “arguably the single biggest problem” pic.twitter.com/eEE9vM5zlz
— TESLARATI (@Teslarati) August 4, 2026
During descent, atmospheric friction generates temperatures exceeding several thousand degrees Celsius and creates plasma flows capable of melting unprotected metal. The tiles absorb, radiate, and insulate against this energy, allowing the vehicle to survive and potentially fly again. Without a durable heat shield, full and rapid reusability, the cornerstone of Starship’s design for frequent launches, satellite deployments, and deep-space missions, would remain impossible.
The tiles have long been a source of difficulty. On earlier test flights, a significant number of tiles detached during ascent due to vibration, aerodynamic loads, and imperfect attachment methods using pins and adhesives. Gaps between tiles allowed hot plasma to infiltrate, causing secondary damage and hot spots on the underlying structure.
These issues echoed challenges faced by NASA’s Space Shuttle, whose ceramic tiles required extensive, labor-intensive inspections and replacements between missions, preventing rapid turnaround. SpaceX has iteratively improved materials, standardized tile shapes, refined attachment techniques, added secondary ablative layers, and tested sealing methods such as “crunch wrap” felt to close gaps.
Progress was visible across Flights 10–12, with steadily better tile retention, yet questions remained about whether the system could support the minimal-refurbishment goal of rapid reuse.
Flight 13 on July 24 provided the decisive evidence. Ship 40 flew a deliberately more demanding profile with higher dynamic pressure to stress the heat shield beyond typical operational loads. It successfully deployed 20 operational Starlink V3 satellites, the first such payload on a Starship mission, performed an in-space Raptor engine relight, and executed a controlled reentry.
Elon Musk sheds two new bits of detail on Starship after 13th test launch
Cameras on six of the satellites and onboard sensors captured extensive imagery and data of the shield throughout the flight. The ship then achieved its softest splashdown to date in the Indian Ocean, remaining intact and floating rather than breaking apart or exploding as on prior missions. This allowed drone inspections and continuous telemetry of the heat shield in near-real time.
Post-flight analysis showed the majority of tiles remaining attached with only minor damage and limited plasma streaking at seams. Musk noted that the mission delivered “all the heat shield data we needed and then some.” Combined with visual inspections, these results underpinned his subsequent assessment that the core technical barriers to rapid reusability have been cleared. While refinements will continue, Flight 13 marked a pivotal step toward Starship’s operational future.
Tesla Cybertruck production snaps back after ugly supplier fight
Space finally faced the people living next to its next Terafab mega-project
