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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.
Lifestyle
Tesla Semi hauls fresh Cybercab batch as Robotaxi era takes hold
A Tesla Semi was filmed hauling Cybercab units out of Giga Texas for the first time.
A Tesla Semi loaded with Cybercab units was recently filmed leaving Gigafactory Texas, marking what appears to be the first documented delivery run of Tesla’s autonomous two-seater. The footage shows multiple Cybercabs secured on a flatbed trailer being hauled by a production Tesla Semi, a truck rated for a gross combination weight of 82,000 lbs. The location is consistent with Giga Texas in Austin, where Cybercab production has been ramping since February 2026.
The sighting follows a wave of Cybercab activity at the Austin facility. In late April, drone operator Joe Tegtmeyer spotted approximately 60 Cybercabs parked in two organized groups in the factory’s outbound lot, the largest concentration observed to date. Units being staged in an outbound lot is a standard pre-delivery step, and the Semi footage is the logical next frame in that sequence.
En route with @tesla_semi pic.twitter.com/ZfuOjaeLH1
— Tesla Robotaxi (@robotaxi) May 7, 2026
This is not the first time Tesla has used its own Semi to move Tesla products. When the Semi was unveiled in 2017, Musk noted it would be used for Tesla’s own operations, and over the years Semi prototypes were spotted carrying cargo ranging from concrete weights to Tesla vehicles being delivered to consumers. In 2023, a Semi was photographed transporting a Cybertruck on a trailer ahead of that vehicle’s delivery launch.
The Cybercab itself was first revealed publicly at Tesla’s “We, Robot” event on October 10, 2024, at Warner Bros. Studios in Burbank, where 20 pre-production units gave attendees rides around the studio lot. Musk stated at the event that Tesla intends to produce the Cybercab before 2027. The first production unit rolled off the Giga Texas line on February 17, 2026, with Musk posting on X: “Congratulations to the Tesla team on making the first production Cybercab.”
Tesla’s annual production goal is 2 million Cybercabs per year once multiple factories reach full design capacity, with the company targeting a price under $30,000 per unit. Tesla has confirmed plans to expand its robotaxi service to seven cities in the first half of 2026, including Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas, building on the unsupervised service already running in Austin. Musk has said he expects robotaxis to cover between a quarter and half of the United States by end of year.
Cybertruck
Tesla Cybertruck too safe for even Musk’s biggest critics to ignore
Krassenstein’s decision reveals that superior safety isn’t a partisan issue. For parents prioritizing family protection over personal or political grudges, the Cybertruck has become too safe to ignore.
The Tesla Cybertruck is an extremely polarizing vehicle because of its potential symbolism as a political stance instead of just a pickup truck — or at least that is what many would want you to believe.
Of course, the Cybertruck is an icon of Tesla culture, and it is one of those things that never has a middle ground: you love it, or you don’t.
But maybe there is an establishment of that “grey area” happening.
In a striking illustration of engineering triumph over political tribalism, prominent Elon Musk critic Brian Krassenstein has purchased a Tesla Cybertruck, openly citing its exceptional safety as the deciding factor for his family.
The announcement on X triggered predictable backlash, yet it underscores a growing reality: the Cybertruck’s safety credentials are proving impossible for even Musk’s fiercest detractors to dismiss.
I might get hate for this too but I bought a Cybertruck.
With a young family, safety was important and so is not polluting the atmosphere with $5 a gallon gasoline. pic.twitter.com/XJqFqR6O9r
— Brian Krassenstein (@krassenstein) May 6, 2026
Krassenstein, who has repeatedly clashed with Musk over issues ranging from content moderation and “wokeness” to public health figures, made no attempt to hide his reservations. In his May 6 post, he acknowledged the coming criticism: “I might get hate for this too but I bought a Cybertruck.”
He stressed that the decision had “nothing to do with Elon or politics,” pointing instead to practical advantages—his existing Tesla charger, eligibility for Full Self-Driving upgrades, a returning-owner discount, and crucially, the vehicle’s strong safety profile.
With gasoline prices hovering near $5 a gallon in some areas, he also highlighted the environmental benefit of switching from a polluting combustion engine.
The numbers, data, and awards validate Krassenstein’s choice.
The 2025 Cybertruck earned the Insurance Institute for Highway Safety’s (IIHS) elite Top Safety Pick+ award—the only pickup truck to achieve this highest rating. It delivered “Good” scores across every crashworthiness category, including the challenging updated moderate overlap front crash test, while excelling in crash avoidance and mitigation systems.
The National Highway Traffic Safety Administration (NHTSA) awarded it a perfect 5-star overall rating, with top marks in frontal, side, and rollover categories. No other pickup truck holds both distinctions simultaneously.
Tesla Cybertruck crash test rating situation revealed by NHTSA, IIHS
Beyond lab results, the Cybertruck’s stainless-steel exoskeleton and ultra-rigid structure have demonstrated remarkable real-world resilience. Owners have reported surviving high-speed collisions with minimal cabin intrusion.
In one widely discussed incident, a Cybertruck endured a 70 mph sideswipe on the interstate; the driver reported barely feeling the impact while the other vehicle was heavily damaged.
Tesla’s crash demonstrations and independent analyses consistently show how the vehicle’s design prioritizes occupant protection through a fortified passenger cell rather than traditional crumple zones, giving families superior safeguarding in many common crash scenarios.
The online pile-on following Krassenstein’s post focused on aesthetics, politics, and perceived hypocrisy rather than the data. Critics called the angular truck “ugly” or accused him of selling out.
Yet his purchase highlights an inconvenient truth for polarized discourse: when objective safety metrics—IIHS awards, NHTSA ratings, and documented crash performance—point decisively toward one vehicle, even Musk’s biggest critics are forced to confront its merits.
Krassenstein’s decision reveals that superior safety isn’t a partisan issue. For parents prioritizing family protection over personal or political grudges, the Cybertruck has become too safe to ignore.
SpaceXAI announced today that it had signed an agreement with Anthropic to give the company access to its Colossus 1 data center in Memphis, Tennessee.
It is a monumental deal as Anthropic will gain access to all of the compute at the plant, delivering more than 300 megawatts of power and over 220,000 NVIDIA GPUs within the month.
Anthropic’s Claude AI account on X announced the partnership:
“We’ve agreed to a partnership with SpaceX that will substantially increase our compute capacity. This, along with our other recent compute deals, means that we’ve been able to increase our usage limits for Claude Code and the Claude API.”
The company is also:
- Doubling Claude Code’s 5-hour rate limits for Pro, Max, and Team plans;
- Removing the peak hours limit reduction on Claude Code for Pro and Max plans; and
- Substantially raising its API rate limits for Opus models.
We’ve agreed to a partnership with @SpaceX that will substantially increase our compute capacity.
This, along with our other recent compute deals, means that we’ve been able to increase our usage limits for Claude Code and the Claude API.
— Claude (@claudeai) May 6, 2026
SpaceX also published its own release on the new agreement, noting that it is “the only organization with the launch cadence, mass-to-orbit economics, and constellation operations experience to make orbital compute a near-term engineering program rather than a research concept.”
CEO Elon Musk also commented on the partnership and shed light on intense meetings he had with senior members of Anthropic last week, stating, “nobody set on my evil detector.”
Same here.
By way of background for those who care, I spent a lot of time last week with senior members of the Anthropic team to understand what they do to ensure Claude is good for humanity and was impressed.
Everyone I met was highly competent and cared a great deal about…
— Elon Musk (@elonmusk) May 6, 2026
This has turned the argument that SpaceX is as much an AI company as a space exploration company into a very valid argument:
SpaceX is following in Tesla’s footsteps in a way nobody expected
Nevertheless, this is an incredibly valuable and important move in the grand scheme of things. AI scaling is fundamentally bottlenecked by compute, and demand for Claude has surged, bringing terrestrial power grids, land, and cooling operations hitting limits everywhere.
Anthropic has been aggressively signing multiple large-scale deals to be competitive in the space, including:
- Up to 5GW with Amazon
- 5GW with Google and Broadcom
- Strategic $30b Azure deal with Microsoft/NVIDIA
- $50b U.S. infrastructure investment with Fluidstack
Access to Colossus 1 gives Anthropic immediate relief on NVIDIA GPU capacity. For SpaceXAI, it turns its rapid buildout into revenue. It also showcases its ability to deliver at world-leading speed and scale.
Most importantly, it plants the seed that its much larger vision, orbital AI compute, is totally viable.
Starlink V3 satellites could enable SpaceX’s orbital computing plans: Musk
Within the month, Anthropic will begin using 100 percent of Colossus 1’s compute, directly expanding capacity for Claude Pro and Max subscribers and the API. This means fewer limits, faster responses, and support for heavier workloads.
In the long term, meaning 2026 and beyond, there will be a continued rollout of other multi-GW deals Anthropic has signed, and an early exploration of orbital compute with SpaceXAI.
Tesla Semi hauls fresh Cybercab batch as Robotaxi era takes hold
Tesla Cybertruck too safe for even Musk’s biggest critics to ignore
