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.
Tesla just raised Model Y prices for the first time in two years, with the largest increase being $1,000.
The move signals shifting dynamics in the competitive electric vehicle market as the company continues to work on balancing demand, profitability, and accessibility.
The new pricing affects premium trims while leaving entry-level options unchanged. The Model Y Premium Rear-Wheel Drive (RWD) now starts at $45,990, a $1,000 increase.
The Model Y Premium All-Wheel Drive (AWD)—previously referred to in the post as simply “Model Y AWD”—rises to $49,990, also up $1,000. The top-tier Model Y Performance sees a more modest $500 bump, bringing its starting price to $57,990.
Tesla Model Y prices just went up:
New prices:
🚗 Model Y Premium RWD: $45,990 – up $1,000
🚗 Model Y AWD: $49,990 – up $1,000
🚗 Model Y Performance: $57,990 – up $500 https://t.co/e4GhQ0tj4H pic.twitter.com/TCWqr3oqiV— TESLARATI (@Teslarati) May 16, 2026
Base models remain untouched to preserve affordability. The entry-level Model Y RWD holds steady at $39,990, and the base Model Y AWD stays at $41,990. This selective approach keeps the crossover accessible for budget-conscious buyers while extracting more revenue from higher-margin configurations.
After years of aggressive price cuts to stimulate volume amid slowing EV adoption and rising competition from rivals like BYD, Ford, and GM, Tesla appears confident in underlying demand. Recent lineup refreshes for the 2026 Model Y, including refreshed styling and efficiency gains, have helped maintain its status as America’s best-selling EV.
By protecting base prices, Tesla avoids alienating price-sensitive customers while improving margins on the more popular variants.
Tesla Model Y ownership review after six months: What I love and what I don’t
For consumers, the changes are relatively modest—under 3% on affected trims—and still position the Model Y competitively against gas-powered SUVs in the same class. Federal tax credits and potential state incentives may further offset costs for eligible buyers.
This marks a subtle but notable shift from the deep discounting era that defined much of 2024 and 2025. As the EV market matures into 2026, Tesla’s pricing strategy will be closely watched for clues about production ramps, new variants like the rumored longer-wheelbase Model Y, and broader profitability goals.
In short, today’s adjustment reflects a company that remains dominant yet pragmatic—willing to test higher pricing where demand supports it. It is unlikely to deter consumers from choosing other options.
Elon Musk cannot be fired from SpaceX, and there’s a reason for that.
In a blunt post on X on Friday, Elon Musk confirmed plans to structurally shield his leadership at SpaceX, ensuring he cannot be fired while tying a potential trillion-dollar compensation package to the company’s long-term goal of establishing a self-sustaining colony on Mars.
Yes, I need to make sure SpaceX stays focused on making life multiplanetary and extending consciousness to the stars, not pandering to someone’s bullshit quarterly earnings bonus!
Obviously, IF SpaceX succeeds in this absurdly difficult goal, it will be worth many orders of…
— Elon Musk (@elonmusk) May 15, 2026
The revelation stems from a Financial Times report detailing SpaceX’s intention to restructure its governance and compensation framework. The moves are designed to protect Musk’s control and align his incentives with the company’s founding mission rather than short-term financial pressures. Musk’s reply left no ambiguity:
“Yes, I need to make sure SpaceX stays focused on making life multiplanetary and extending consciousness to the stars, not pandering to someone’s bullshit quarterly earnings bonus!”
He added that success in this “absurdly difficult goal” would generate value “many orders of magnitude more than the economy of Earth,” though he cautioned that the journey will not be smooth. “Don’t expect entirely smooth sailing along the way,” Musk wrote.
The strategy reflects Musk’s deep concerns about how public-market expectations could derail SpaceX’s core objective. Founded in 2002, SpaceX has repeatedly stated its purpose is to reduce the cost of space travel and ultimately make humanity a multiplanetary species.
Unlike Tesla, which went public in 2010 and has faced repeated battles over Musk’s compensation and board influence, SpaceX remains privately held. Musk has long resisted taking the rocket company public precisely to avoid the quarterly earnings treadmill that forces most CEOs to prioritize short-term stock performance over ambitious, high-risk projects.
By embedding protections against his removal and linking any outsized pay package to verifiable milestones—such as a functioning Mars colony—SpaceX aims to insulate its leadership from activist investors or board members who might demand faster profits or safer bets.
Musk has referenced past experiences, including his ouster from OpenAI and shareholder lawsuits at Tesla, as cautionary tales. In those cases, he argued, external pressures risked diluting the original vision.
Critics may view the arrangement as excessive, especially given Musk’s already substantial voting power and wealth. Supporters, however, argue it is a necessary safeguard for a company pursuing goals measured in decades rather than quarters. Achieving a Mars colony would require sustained investment in Starship development, orbital refueling, life-support systems, and in-situ resource utilization—technologies that may deliver no immediate financial return.
Musk’s post underscores a broader philosophical point: true breakthrough innovation often demands tolerance for volatility and a willingness to ignore conventional business wisdom. As SpaceX prepares for increasingly ambitious Starship test flights and eventual crewed missions, the new governance structure signals that the company’s North Star remains unchanged—humanity’s expansion beyond Earth.
Whether the trillion-dollar package materializes depends on execution, but Musk’s message is clear: SpaceX exists to reach the stars, not to chase the next earnings beat. For investors or employees who share that vision, the protections are not a perk—they are a prerequisite for success.
News
Tesla discloses two Robotaxi crashes to NHTSA
Newly unredacted data filed with the National Highway Traffic Safety Administration (NHTSA) reveals the two incidents.
Tesla has disclosed information on two low-speed crashes that occurred in Austin with its Robotaxi platform. These incidents occurred with teleoperators steering the vehicle, and there were no passengers in the car at the time they happened.
Newly unredacted data filed with the National Highway Traffic Safety Administration (NHTSA) reveals the two incidents.
The first crash took place in July 2025, shortly after Tesla launched its nascent Robotaxi network in Austin. The ADS reportedly struggled to move forward while stopped on a street. A teleoperator assumed control, gradually accelerating and turning left toward the roadside. The vehicle then mounted the curb and struck a metal fence.
In the second incident, in January 2026, the ADS was traveling straight when the safety monitor requested navigation support. The teleoperator took over from a stop, continued forward, and collided with a temporary construction barricade at approximately 9 mph, scraping the front-left fender and tire.
Tesla Robotaxi service in Austin achieves monumental new accomplishment
Tesla has previously told lawmakers that teleoperators are authorized to pilot vehicles remotely—but only at speeds below 10 mph, as the only maneuvers they were approved to perform were repositioning in awkward areas.
“This capability enables Tesla to promptly move a vehicle that may be in a compromising position, thereby mitigating the need to wait for a first responder or Tesla field representative to manually recover the vehicle,” the company stated in filings earlier this year.
Before this week, Tesla redacted the NHTSA reports, but they decided to reveal all 17 Robotaxi incidents recorded since the launch in Austin last Summer. Most of the other crashes involved the Tesla being struck by other road users and were not caused by the self-driving suite itself.
There were other incidents, including two additional self-caused accidents involving the ADS clipping side mirrors on parked cars. In September 2025, one Robotaxi struck a dog that darted into the roadway (the dog escaped unharmed), while another made an unprotected left turn into a parking lot and hit a metal chain.
Although Waymo and Zoox have reported more total crashes, Tesla operates at a far smaller scale. The cautious pace reflects the company’s broader safety concerns; it has been very slow with the Robotaxi rollout to ensure the suite is ready for operation.
Last month, CEO Elon Musk acknowledged that “making sure things are completely safe” remains the primary bottleneck to expanding the network, describing the company’s approach as “very cautious.”
The unredacted filings arrive amid heightened regulatory scrutiny of autonomous vehicles. NHTSA recently closed a separate probe into Tesla’s Full Self-Driving software repeatedly striking parking-lot obstacles such as bollards and chains—a problem that also prompted a recall at Waymo last year.
Tesla Robotaxi has been a widely successful program in its early days of operation, and the transparency Tesla brings here is greatly appreciated. Incidents will happen, of course, but the honesty gives customers and regulators a sense of where Tesla is in terms of developing its self-driving and fully autonomous ride-hailing suite.
Tesla Model Y prices just went up for the first time in two years
Elon Musk explains why he cannot be fired from SpaceX
