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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 Optimus Gen 3 is coming to the Tesla Diner with new ambitions
Tesla’s Optimus robot left the Hollywood Diner within months of opening. Now Musk is planning its return with a bigger role and a major Gen 3 upgrade underway.
![Tesla Optimus Gen 3 [Credit: Tesla]](https://www.teslarati.com/wp-content/uploads/2026/03/tesla-optimus-gen3-diner.jpg)
Tesla’s Optimus robot was one of the most talked-about features when the Tesla Diner opened on Santa Monica Boulevard in Hollywood on July 21, 2025. Dubbed “Poptimus” by Tesla fans, the Gen 2 robot stood upstairs at the retro-futuristic, drive-in theater and Tesla Supercharging station, scooping popcorn into bags and handing them to guests with a wave.
The diner itself had been years in the making. Elon Musk first floated the idea in 2018 with a tweet about building an “old-school drive-in, roller skates & rock restaurant” at a Hollywood Supercharger. What eventually opened was a unique two-story neon-lit space, with 80 EV charging stalls, and Optimus serving as a live demonstration of where Tesla’s ambitions were headed.
If our retro-futuristic diner turns out well, which I think it will, @Tesla will establish these in major cities around the world, as well as at Supercharger sites on long distance routes.
An island of good food, good vibes & entertainment, all while Supercharging! https://t.co/zmbv6GfqKf
— Elon Musk (@elonmusk) July 21, 2025
But Optimus did not stay long, and was gone by December 2025.
Now, the robot is set to return with a more demanding job. Musk has ambitions for Optimus to take on a food runner role in 2026, delivering meals directly to cars at the Supercharger stalls. While the latest Gen 3 Optimus is likely to initially take on its previous popcorn-serving role, it wouldn’t be out of the question for Optimus to see a quick promotion. With improved hand dexterity that features 50 total actuators and 22 degrees of freedom per hand, and significantly more powerful processing through Tesla’s latest AI5 chip that includes Grok-powered voice interaction, Musk described Optimus at the Abundance Summit on March 12, 2026, as “by far the most advanced robot in the world, Nothing’s even close.”
Back to work
See you at Tesla Diner tomorrow pic.twitter.com/H3tTajrUbu
— Tesla Optimus (@Tesla_Optimus) March 30, 2026
That confidence is backed by a major manufacturing shift. At the Q4 2025 earnings call in January, Musk announced Tesla would discontinue the Model S and Model X and convert those Fremont production lines to build Optimus. “It’s time to basically bring the Model S and X programs to an end,” he said, calling for a pivot that reflects where the Tesla’s future lies.
Elon Musk
Musk forces Judge’s exit from shareholder battles over viral social media slip-up
McCormick insisted in a court filing that she harbors no actual bias against Musk or the defendants. She claimed she either never clicked the “support” button, LinkedIn’s version of a “like,” or did so accidentally.
Many Tesla fans are familiar with the name Kathaleen McCormick, especially if they are investors in the company.
McCormick is a Delaware Chancery Court Judge who presided over Tesla CEO Elon Musk’s pay package lawsuit over the past few years, as well as his purchase of Twitter. However, she will no longer be sitting in on any issues related to Musk.
Elon Musk demands Delaware Judge recuse herself after ‘support’ post celebrating $2B court loss
In a rare admission of potential optics issues in one of America’s most powerful corporate courts, Delaware Chancery Court Chancellor Kathaleen McCormick stepped aside Monday from a cluster of shareholder lawsuits targeting Elon Musk and Tesla’s board.
The move came just days after Musk’s legal team highlighted her apparent “support” on LinkedIn for a post that mocked the billionaire over his 2022 tweets about the $44 billion Twitter acquisition.
McCormick insisted in a court filing that she harbors no actual bias against Musk or the defendants. She claimed she either never clicked the “support” button, LinkedIn’s version of a “like,” or did so accidentally.
She wrote in a newly published memo from the Delaware Chancery Court:
“The motion for recusal rests on a false premise — that I support a LinkedIn post about Mr. Musk, which I do not in fact support. I am not biased against the defendants in these actions.”
Yet she granted the reassignment anyway, acknowledging that the intense media scrutiny surrounding her involvement had become “detrimental to the administration of justice.”
The consolidated cases will now be handled by three of her colleagues on the Delaware Court of Chancery, the nation’s go-to venue for high-stakes corporate disputes. The lawsuits accuse Musk and Tesla directors of breaching fiduciary duties through lavish executive compensation and lax governance oversight.
One prominent claim, filed by a Detroit pension fund, challenges massive stock awards granted to board members, alleging the payouts harmed the company. The litigation also overlaps with issues stemming from Musk’s turbulent 2022 Twitter purchase.
McCormick’s history with Musk made her a lightning rod. In 2022, she presided over the fast-tracked lawsuit that ultimately forced Musk to complete the Twitter deal after he tried to back out.
Then in 2024, she struck down his record $56 billion Tesla compensation package, ruling the approval process was flawed and overly CEO-friendly. The Delaware Supreme Court later reinstated the pay on technical grounds, but the ruling fueled Musk’s long-standing criticism of the state’s judiciary.
Musk has repeatedly urged companies to reincorporate elsewhere, arguing Delaware courts have grown hostile to visionary leaders. Monday’s recusal hands him a symbolic victory and underscores how personal social-media activity can collide with judicial impartiality standards.
Delaware law requires judges to step aside if there’s even a “reasonable basis” to question their neutrality.
Court watchers say the episode highlights growing tensions in corporate America’s legal epicenter. While McCormick maintained her impartiality, the appearance of bias proved too costly to ignore. The cases will proceed without her, but the broader debate over Delaware’s dominance in business litigation is far from over.
Elon Musk
Elon Musk has generous TSA offer denied by the White House: here’s why
Musk stepped in on March 21 via a post on X, writing: “I would like to offer to pay the salaries of TSA personnel during this funding impasse that is negatively affecting the lives of so many Americans at airports throughout the country.”
Tesla and SpaceX CEO Elon Musk made a generous offer to pay the salaries of Transportation Security Administration (TSA) employees last week, but the offer was denied by the White House.
In a striking display of private-sector initiative clashing with federal bureaucracy, the White House has turned down an offer from Elon Musk to personally cover the salaries of TSA officers amid an ongoing partial government shutdown. The rejection, reported last Wednesday by multiple outlets, highlights the legal and political hurdles facing unconventional solutions to Washington’s funding gridlock.
The impasse began weeks ago when Congress failed to pass funding for the Department of Homeland Security (DHS), leaving TSA employees, essential workers who screen millions of travelers daily, without paychecks while still required to report for duty.
Frustrated travelers have endured record-long security lines at major airports, with reports of chaos and delays rippling across the country.
Musk stepped in on March 21 via a post on X, writing: “I would like to offer to pay the salaries of TSA personnel during this funding impasse that is negatively affecting the lives of so many Americans at airports throughout the country.”
I would like to offer to pay the salaries of TSA personnel during this funding impasse that is negatively affecting the lives of so many Americans at airports throughout the country
— Elon Musk (@elonmusk) March 21, 2026
But it was not for no reason.
White House spokesperson Abigail Jackson responded on behalf of the Trump administration, expressing appreciation for Musk’s gesture.
However, the legal obstacles, which would be insurmountable, would inhibit Musk from doing so. Jackson said:
“We greatly appreciate Elon’s generous offer. This would pose great legal challenges due to his involvement with federal government contracts.”
Musk’s companies hold significant federal contracts, including NASA launches through SpaceX and potential Defense Department work, raising concerns about conflicts of interest, ethics rules, and anti-bribery statutes that prohibit private payments to government employees. Administration officials also indicated they expect the shutdown to end soon, making external funding unnecessary.
The episode underscores deeper tensions in Washington. Musk, who has advised on government efficiency efforts and maintains a close relationship with President Trump, has frequently criticized wasteful spending and bureaucratic delays.
His offer came as airport security lines ballooned, drawing public frustration toward both parties. TSA officers, many of whom rely on paychecks to cover mortgages and family expenses, have continued working without compensation, a situation that has drawn bipartisan concern but little immediate resolution.
Critics of the rejection argue it prioritizes red tape over practical relief for frontline workers and travelers. Supporters of the White House position counter that allowing private funding sets a dangerous precedent and could undermine congressional authority over the budget.
The White House eventually came to terms with the TSA on Friday and started paying them once again, and lines at airports instantly shrank. The Department of Homeland Security (DHS) said that TSA staf would begin receiving paychecks “as early as” today.
![Tesla Optimus Gen 3 [Credit: Tesla]](https://www.teslarati.com/wp-content/uploads/2026/03/tesla-optimus-gen3-diner-80x80.jpg)
Tesla Optimus Gen 3 is coming to the Tesla Diner with new ambitions
Musk forces Judge’s exit from shareholder battles over viral social media slip-up
Elon Musk has generous TSA offer denied by the White House: here’s why
Elon Musk says Tesla is developing a new vehicle: ‘Way cooler than a minivan’
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
