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.
Investor's Corner
Tesla and SpaceX take “Terafab” Trademark fight to Federal Court
Tesla and SpaceX sue a small Illinois firm after cease and desist letters over Terafab.
Tesla and SpaceX are asking a federal judge to rule that their planned Terafab chip factory does not infringe a small Illinois company’s trademark, a request that arrives only after months of quiet negotiation broke down this summer.
The dispute traces to May 18, when Tesla filed three U.S. trademark applications for “Terafab” and “Tesla Terafab,” covering semiconductor chips and related chip making services. TERA-print LLC, a nanotechnology company that has held a federal trademark for “Tera-Fab” since 2021, responded five days later with a cease and desist letter. According to the lawsuit, first reported by Reuters, TERA-print argued that Tesla and SpaceX’s use of “Terafab” would confuse consumers familiar with its own trademark, which covers a desktop photolithography printer sold to researchers for sensor and bioengineering work.
What stands out in the filing is the timing of TERA-print’s own paperwork. One day before sending that cease and desist letter, on May 22, TERA-print applied to expand its existing registration to cover semiconductor materials, silicon chips, nanoelectronic devices and AI design services, categories it had not previously claimed. Tesla and SpaceX call that filing opportunistic in their complaint, noting it arrived two months after Tesla’s public Terafab announcement and just days after Tesla’s own trademark applications went in.
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
By June 10, TERA-print was threatening to sue for federal trademark infringement, false designation of origin and unfair competition, the complaint states. Rather than wait to be sued, Tesla, SpaceX and SpaceXAI met with TERA-print six separate times between June and August trying to resolve the dispute directly. Those talks collapsed, and the companies filed for declaratory judgment this week in the U.S. District Court for the Western District of Texas, asking a judge to find that “Terafab” does not infringe TERA-print’s mark before TERA-print can file a claim of its own.
TERA-print isn’t backing down. The company told PCMag it discussed a settlement with Tesla as recently as September 2 and feels misled by what it called Tesla’s professed interest in settling. Its CTO, Andrey Ivankin, said TERA-print holds a Defense Department contract to fabricate semiconductors and partially owns Mattiq Inc., an AI company built on TERA-print’s products, and that the company will vigorously defend its rights.
Tesla and SpaceX argue the overlap is superficial. Terafab is planned as a $16.8 billion complex spanning roughly 100 million square feet at the Grimes County site SpaceX confirmed last month, built to produce chips for Optimus robots, Tesla’s AI computing needs and SpaceX’s orbital data center ambitions, a scale and purpose the companies say no reasonable consumer would confuse with a tabletop lab printer. TERA-print’s product line has stayed focused on lithography tools for biological and sensor research since it registered its mark in 2021.
The trademark fight is the second legal dispute tied to the Terafab project in the past week, following a separate SpaceX suit aimed at keeping company records about the facility out of public view, as KBTX reported. Whether construction proceeds under the Terafab name now depends on a federal judge in Austin.
News
NHTSA just escalated its Tesla Cybercab investigation in a big way
NHTSA escalated its Cybercab audit into a sworn Special Order with a September 30 deadline.
Federal regulators have moved from asking Tesla questions about its Cybercab to demanding sworn answers. The National Highway Traffic Safety Administration issued a Special Order that requires a Tesla officer to sign an affidavit attesting to the completeness of the company’s responses, with a deadline of September 30.
The order builds on Audit Query AQ26002, which NHTSA opened on September 3, the same day Tesla began commercial Cybercab service in Austin. Teslarati covered that initial inquiry when it surfaced, noting the agency wanted to understand how Tesla certified a vehicle with no permanently attached steering wheel, pedals, or mirrors as compliant with Federal Motor Vehicle Safety Standards. A Special Order is a different tool and converts a fact finding review into a legally enforceable demand, the same mechanism NHTSA used against Tesla in 2023 during its Autopilot investigation.
Several of the 21 requests target a specific gap in Cybercab’s design. One asks whether Tesla used temporarily attached human controls at any point to help certify the vehicle, and if so, which standards depended on that equipment being present. Another quotes an existing rule directly: “The service brakes shall be activated by means of a foot control.” Cybercab has no foot pedal. NHTSA wants a detailed explanation of how the vehicle satisfies that requirement, and how it complies without the kind of exemption granted to Zoox in July under Part 555, the regulatory pathway built for steering wheel free vehicles.
The order does not claim Cybercab is unsafe or that Tesla broke a rule. It requires Tesla to explain, under oath, the reasoning behind decisions the company already made when it self-certified the vehicle. That distinction matters, but so does the exposure. Motor1’s reporting, summarized here, put potential civil penalty exposure as high as $139 million if NHTSA later finds the certification was flawed, on top of whatever criminal risk comes with a false sworn statement.
Tesla has not said publicly how it plans to respond. Cybercab is still carrying passengers in Austin through the Robotaxi app while the September 30 deadline approaches, and the company has continued expanding the vehicle’s footprint even as the regulatory question remains open. The Special Order does not pause any of that and just sets a date by which Tesla has to put its certification logic on the record, with a company officer’s name attached to it.
In a new interview on Wednesday, Tesla uber bull Ron Baron said that anyone looking to buy the company’s stock should do so as soon as they can.
Baron, founder and CEO of Baron Capital and one of Tesla’s most persistent institutional bulls, used a CNBC Squawk Box appearance on Wednesday to deliver a familiar message with fresh urgency: In his opinion, Tesla stock is a buy:
“The time to buy the stock is now. FSD is catching on, and it’s going to be bigger and bigger. 55% of new buyers are buying it (Teslas) with FSD. It’s going to be everywhere. It’s safer.”
The Baron Capital frontman’s case is built around Full Self-Driving. Tesla reported 1.48 million active FSD subscriptions in the second quarter, up 56 percent year over year, and company officials have said roughly 55 percent of new North American deliveries left with a subscription enabled.
Baron framed that attach rate as proof the product is moving from enthusiast extra to default expectation, and as a reason software, not just vehicle volume, should drive the next phase of value.
His conviction on Tesla shares is not theoretical, as Baron Capital made its first Tesla investment in 2014, after years of meetings that began around the 2010 IPO roadshow. The firm later built a large SpaceX position starting in 2017.
Ron Baron today in new interview on Tesla:
“The time to buy the stock is now. FSD is catching on, and it’s going to be bigger and bigger. 55% of new buyers are buying it (Teslas) with FSD. It’s going to be everywhere. It’s safer.” pic.twitter.com/Rv5PB0bVZ2
— Sawyer Merritt (@SawyerMerritt) September 16, 2026
Baron said those Musk-led bets have generated about $30 billion of the $71 billion in profits Baron Capital has produced for clients. He put the firm’s current exposure at roughly $25 billion in SpaceX and $5 billion in Tesla. Personally, he described SpaceX as his largest holding, at about $5 billion, with about $1.5 billion in Tesla and additional Tesla exposure through the firm’s funds.
That concentration is also a statement of loyalty. Asked about talk of a SpaceX-Tesla combination, Baron said he had already walked Elon Musk through arguments for and against a deal, then declined to repeat them on air. His public position was simpler: “Whatever you decide is better is what I’m going to support,” he said to Musk.
Baron also said that he picked up the farewell edition of the Model S after Tesla decided to sunset the vehicle earlier this year, calling it his favorite car he’s ever driven.
Tesla and SpaceX take “Terafab” Trademark fight to Federal Court
NHTSA just escalated its Tesla Cybercab investigation in a big way
