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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.
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With the news of a merger between SpaceX and xAI being confirmed earlier this week by CEO Elon Musk directly, the first moves of an umbrella company that combines all of the serial tech entrepreneur’s companies have been established.
The move aims to combine SpaceX’s prowess in launches with xAI’s expanding vision in artificial intelligence, as Musk has detailed the need for space-based data centers that will require massive amounts of energy to operate.
It has always been in the plans to bring Musk’s companies together under one umbrella.
“My companies are, surprisingly in some ways, trending toward convergence,” Musk said in November. With SpaceX and xAI moving together, many are questioning when Tesla will be next. Analysts believe it is a no-brainer.
SpaceX officially acquires xAI, merging rockets with AI expertise
Dan Ives of Wedbush wrote in a note earlier this week that there is a “growing chance” Tesla could be merged in some form with the new conglomeration over the next 12 to 18 months.
“In our view, there is a growing chance that Tesla will eventually be merged in some form into SpaceX/xAI over time. The viewis this growing AI ecosystem will focus on Space and Earth together… and Musk will look to combine forces,” Ives said.
Let’s take a look at the potential.
The Case for Synergies – Building the Ultimate AI Ecosystem
A triple merger would create a unified “Musk Trinity,” blending Tesla’s physical AI with Robotaxi, Optimus, and Full Self-Driving, SpaceX’s orbital infrastructure through Starlink and potential space-based computer, and xAI’s advanced models, including Grok.
This could accelerate real-world AI applications, more specifically, ones like using satellite networks for global autonomy, or even powering massive training through solar-optimized orbital data centers.
The FCC welcomes and now seeks comment on the SpaceX application for Orbital Data Centers.
The proposed system would serve as a first step towards becoming a Kardashev II-level civilization and serve other purposes, according to the applicant. pic.twitter.com/TDnUPuz9w7
— Brendan Carr (@BrendanCarrFCC) February 4, 2026
This would position the entity, which could ultimately be labeled “X,” as a leader in multiplanetary AI-native tech.
It would impact every level of Musk’s AI-based vision for the future, from passenger use to complex AI training models.
Financial and Structural Incentives — and Risks
xAI’s high cash burn rate is now backed by SpaceX’s massive valuation boost, and Tesla joining the merger would help the company gain access to private funding channels, avoiding dilution in a public-heavy structure.
The deal makes sense from a capital standpoint, as it is an advantage for each company in its own specific way, addressing specific needs.
Because xAI is spending money at an accelerating rate due to its massive compute needs, SpaceX provides a bit of a “lifeline” by redirecting its growing cash flows toward AI ambitions without the need for constant external fundraising.
Additionally, Tesla’s recent $2 billion investment in xAI also ties in, as its own heavy CapEx for Dojo supercomputers, Robotaxis, and Optimus could potentially be streamlined.
Musk’s stake in Tesla and SpaceX, after the xAI merger, is also uneven. His ownership in Tesla equates to about 13 percent, only increasing as he achieves each tranche of his most recent compensation package. Meanwhile, he owns about 43 percent of the private SpaceX.
A triple merger between the three companies could boost his ownership in the combined entity to around 26 percent. This would give Musk what he wants: stronger voting power and alignment across his ventures.
It could also be a potential facilitator in private-to-public transitions, as a reverse merger structure to take SpaceX public indirectly via Tesla could be used. This avoids any IPO scrutiny while accessing the public markets’ liquidity.
Timeline and Triggers for a Public Announcement
As previously mentioned, Ives believes a 12-18 month timeline is realistic, fueled by Musk’s repeated hints at convergence between his three companies. Additionally, the recent xAI investment by Tesla only points toward the increased potential for a conglomeration.
Of course, there is speculation that the merger could happen in the shorter term, before June 30 of this year, which is a legitimate possibility. While this possibility exists but remains at low probability, especially when driven by rapid AI/space momentum, longer horizons, like 2027 or later, allow for key milestones like Tesla’s Robotaxi rollout and Cybercab ramp-up, Optimus scaling, or regulatory clarity under a favorable administration.
Credit: Grok Imagine
The sequencing matters: SpaceX-xAI merger as “step one” toward a unified stack, with a potential SpaceX IPO setting a valuation benchmark before any Tesla tie-up.
Full triple convergence could follow if synergies prove out.
Prediction markets are also a reasonable thing to look at, just to get an idea of where people are putting their money. Polymarket, for example, sits at between a 12 and 24 percent chance that a Tesla-SpaceX merger is officially announced before June 30, 2026.
Looking Ahead
The SpaceX-xAI merger is not your typical corporate shuffle. Instead, it’s the clearest signal yet that Musk is architecting a unified “Muskonomy” where AI, space infrastructure, and real-world robotics converge to solve humanity’s biggest challenges.
Yet the path is fraught with execution risks that could turn this visionary upside into a major value trap. Valuation mismatches remain at the forefront of this skepticism: Tesla’s public multiples are unlike any company ever, with many believing they are “stretched.” On the other hand, SpaceX-xAI’s private “marked-to-muth” pricing hinges on unproven synergies and lofty projects, especially orbital data centers and all of the things Musk and Co. will have to figure out along the way.
Ultimately, the entire thing relies on a high-conviction bet on Musk’s ability to execute at scale. The bullish case is transformative: a vertically integrated AI-space-robotics giant accelerates humanity toward abundance and multi-planetary civilization faster than any siloed company could.
News
IM Motors co-CEO apologizes to Tesla China over FUD comments
Liu said later investigations showed the accident was not caused by a brake failure on the Tesla’s part, contrary to his initial comments.
Liu Tao, co-CEO of IM Motors, has publicly apologized to Tesla China for comments he made in 2022 suggesting a Tesla vehicle was defective following a fatal traffic accident in Chaozhou, China.
Liu said later investigations showed the accident was not caused by a brake failure on the Tesla’s part, contrary to his initial comments.
IM Motors co-CEO issues apology
Liu Tao posted a statement addressing remarks he made following a serious traffic accident in Chaozhou, Guangdong province, in November 2022, as noted in a Sina News report. Liu stated that based on limited public information at the time, he published a Weibo post suggesting a safety issue with the Tesla involved in the crash. The executive clarified that his initial comments were incorrect.
“On November 17, 2022, based on limited publicly available information, I posted a Weibo post regarding a major traffic accident that occurred in Chaozhou, suggesting that the Tesla product involved in the accident posed a safety hazard. Four hours later, I deleted the post. In May 2023, according to the traffic police’s accident liability determination and relevant forensic opinions, the Chaozhou accident was not caused by Tesla brake failure.
“The aforementioned findings and opinions regarding the investigation conclusions of the Chaozhou accident corrected the erroneous statements I made in my previous Weibo post, and I hereby clarify and correct them. I apologize for the negative impact my inappropriate remarks made before the facts were ascertained, which caused Tesla,” Liu said.
Investigation and court findings
The Chaozhou accident occurred in Raoping County in November 2022 and resulted in two deaths and three injuries. Video footage circulated online at the time showed a Tesla vehicle accelerating at high speed and colliding with multiple motorcycles and bicycles. Reports indicated the vehicle reached a speed of 198 kilometers per hour.
The incident drew widespread attention as the parties involved provided conflicting accounts and investigation details were released gradually. Media reports in early 2023 said investigation results had been completed, though the vehicle owner requested a re-investigation, delaying the issuance of a final liability determination.
The case resurfaced later in 2023 following a defamation lawsuit filed by Tesla China against a media outlet. According to a court judgment cited by Shanghai Securities News, forensic analysis determined that the fatal accident was unrelated to any malfunction on the Tesla’s braking or steering systems. The court also ruled that the media outlet must publish an apology, address the negative impact on Tesla China’s reputation, and pay a penalty of 30,000 yuan.
Elon Musk
SpaceX is exploring a “Starlink Phone” for direct-to-device internet services: report
The update was reportedly shared to Reuters by people familiar with the matter.
SpaceX is reportedly exploring new products tied to Starlink, including a potential Starlink-branded phone.
The update was reportedly shared to Reuters by people familiar with the matter.
A possible Starlink Phone
As per Reuters’ sources, SpaceX has reportedly discussed building a mobile device designed to connect directly to the Starlink satellite constellation. Details about the potential device and its possible release are still unclear, however.
SpaceX has dabbled with mobile solutions in the past. The company has partnered with T-Mobile to provide Starlink connectivity to existing smartphones. And last year, SpaceX initiated a $19.6 billion purchase of satellite spectrum from EchoStar.
Elon Musk did acknowledge the idea of a potential mobile device recently on X, writing that a Starlink phone is “not out of the question at some point.” Unlike conventional smartphones, however, Musk described a device that is “optimized purely for running max performance/watt neural nets.”
Starlink and SpaceX’s revenue
Starlink has become SpaceX’s dominant commercial business. Reuters’ sources claimed that the private space company generated roughly $15–$16 billion in revenue last year, with about $8 billion in profit. Starlink is estimated to have accounted for 50% to 80% of SpaceX’s total revenue last year.
SpaceX now operates more than 9,500 Starlink satellites and serves over 9 million users worldwide. About 650 satellites are already dedicated to SpaceX’s direct-to-device initiative, which aims to eventually provide full cellular coverage globally.
Future expansion of Starlink’s mobile capabilities depends heavily on Starship, which is designed to launch larger batches of upgraded Starlink satellites. Musk has stated that each Starship launch carrying Starlink satellites could increase network capacity by “more than 20 times.”
Will Tesla join the fold? Predicting a triple merger with SpaceX and xAI
IM Motors co-CEO apologizes to Tesla China over FUD comments
