Tesla appears to have started slowly rolling out v11 of the Full Self-Driving Beta program this morning, just a few days after CEO Elon Musk stated the company would begin releasing it to more vehicles.
Tesla’s FSD Beta v11.3.1 started to roll out to employees late last year and a select few of the automaker’s long-standing testers a few weeks ago.
The controlled rollout allows Tesla to monitor its behaviors and tendencies in a highly safe way, as it can determine issues or bugs in a small sample size and fix them before a wider release begins.
On March 14, Musk stated that “ V11 starts going wide this weekend,” and we’ve heard it before. However, it appears the automaker is happy with the early reviews and is starting to release it to more vehicles.
V11 starts going wide this weekend
— Elon Musk (@elonmusk) March 15, 2023
v11.3.2 is the newest version of the Beta and is being rolled out with Tesla Software Update 2022.45.11. According to statistics from TeslaScope, more vehicles are being updated with the new FSD Beta v11, and more drivers on the r/TeslaMotors subreddit are beginning to report that they have received the update.
Drivers who have experienced the early editions of this rollout have reported that there have been several improvements to highway driving, and inner-city street navigation has also been refined and feels more accurate than ever before, which is undoubtedly a step in the right direction.
The full release notes for the FSD Beta are available below via TeslaScope:
- Enabled FSD Beta on highway. This unifies the vision and planning stack on and off-highway and replaces the legacy highway stack, which is over four years old. The legacy highway stack still relies on several single-camera and single-frame networks, and was setup to handle simple lane-specific maneuvers. FSD Beta’s multi-camera video networks and next-gen planner, that allows for more complex agent interactions with less reliance on lanes, make way for adding more intelligent behaviors, smoother control and better decision making.
- Improved recall for close-by cut-in cases by 15%, particularly for large trucks and high-yaw rate scenarios, through an additional 30k auto-labeled clips mined from the fleet. Additionally, expanded and tuned dedicated speed control for cut-in objects.
- Improved the position of ego in wide lanes, by biasing in the direction of the upcoming turn to allow other cars to maneuver around ego.
- Improved handling during scenarios with high curvature or large trucks by offsetting in lane to maintain safe distances to other vehicles on the road and increase comfort.
- Improved behavior for path blockage lane changes in dense traffic. Ego will now maintain more headway in blocked lanes to hedge for possible gaps in dense traffic.
- Improved lane changes in dense traffic scenarios by allowing higher acceleration during the alignment phase. This results in more natural gap selection to overtake adjacent lane vehicles very close to ego.
- Made turns smoother by improving the detection consistency between lanes, lines and road edge predictions. This was accomplished by integrating the latest version of the lane-guidance module into the road edge and lines network.
- Improved accuracy for detecting other vehicles’ moving semantics. Improved precision by 23% for cases where other vehicles transition to driving and reduced error by 12% for cases where Autopilot incorrectly detects its lead vehicle as parked. These were achieved by increasing video context in the network, adding more data of these scenarios, and increasing the loss penalty for control- relevant vehicles.
- Extended maximum trajectory optimization horizon, resulting in smoother control for high curvature roads and far away vehicles when driving at highway speeds.
- Improved driving behavior next to row of parked cars in narrow lanes, preferring to offset and staying within lane instead of unnecessarily lane changing away or slowing down.
- Improved back-to-back lane change maneuvers through better fusion between vision-based localization and coarse map lane counts.
- Added text blurbs in the user interface to communicate upcoming maneuvers that FSD Beta plans to make. Also improved the visualization of upcoming slowdowns along the vehicle’s path. Chevrons render at varying opacity and speed to indicate the slowdown intensity, and a solid line appears at locations where the car will come to a stop.
- Improved the recall and precision of object detection, notably reducing the position error of semi-trucks by 10%, increasing the recall and precision of crossing vehicles over 100m away by 3% and 7%, respectively, and increasing the recall of motorbikes by 5%. This was accomplished by implementing additional quality checks in our two million video clip autolabeled dataset.
- Reduced false offsetting around objects in wide lanes and near intersections by improving object kinematics modeling in low speed scenarios.
I’d love to hear from you! If you have any comments, concerns, or questions, please email me at joey@teslarati.com. You can also reach me on Twitter @KlenderJoey, or if you have news tips, you can email us at tips@teslarati.com.
Tesla is being sued by the family of the woman who was killed in a Texas crash involving a Model 3. The driver, who is also being sued, claimed the vehicle was operating on Autopilot mode, but Tesla executives have come out challenging that claim, stating that the driver of the vehicle overrode the system.
The lawsuit was filed by 76-year-old Martha Avila’s daughter and her husband, who allege a “design defect” involving a Tesla and a failure to warn. The suit alleges negligence against Tesla and the driver, Michael Butler.
Butler “stated he was operating with an automated driving assistance system engaged at the time of the crash,” the Harris County Sheriff’s Office said in a statement. He showed no signs of intoxication and was cooperative, the Sheriff’s Office said, according to NBC News.
Just after reports of the crash and numerous headlines that immediately blamed Tesla’s Autopilot suite, both Tesla CEO Elon Musk and Head of AI Ashok Elluswamy challenged that. Musk said the crash made “no sense” given that Tesla Autopilot and Full Self-Driving do not travel at the speeds the door cameras captured the car traveling at, which Tesla says was 73 MPH.
Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration
Elluswamy also revealed that Tesla data showed Butler overrode the system by pressing the accelerator to 100%, and that the pedal was compressed fully even after the car had crashed. Tesla has not released this data to the public, likely because it is communicating with agencies like the NHTSA on an investigation.
The suit uses a Washington Post analysis of government data that “identified at least 17 fatal incidents linked to Tesla Autopilot.”
This is far from the first time an accident has been blamed on Autopilot. A fatal crash in Texas was blamed on Autopilot several years ago, but when Tesla released data to the NTSB, which was investigating the crash, Autopilot was not available where the crash occurred, and Autosteer was never enabled, meaning the car was manually controlled at the time of the accident.
“Application of the accelerator pedal was found to be as high as 98.8 percent,” the NTSB said in their findings. The highest recorded speed in the five seconds leading up to the impact was 67 miles per hour. The area where the crash occurred is residential, and Texas State laws… pic.twitter.com/XGD97NHVZ2
— TESLARATI (@Teslarati) March 18, 2026
More information on the accident will be released as Tesla works with agencies to find the cause of the crash. From personal experience, it is hard to imagine Tesla Autopilot or FSD operating in this manner. It drives sometimes too cautiously in residential areas in parking lots, at least in my experience. Speeding happens, but at this rate in this type of area, it is hard to believe.
We look forward to more details being released with time.
The Insurance Institute for Highway Safety (IIHS) has awarded the 2025-2026 Tesla Cybertruck crew cab pickup its highest honor: Top Safety Pick+. This marks the Cybertruck as the only full-size pickup to achieve this distinction in recent evaluations.
The award applies specifically to vehicles built after April 2025, following structural upgrades including front underbody reinforcements and footwell modifications.
These changes enabled strong performance in updated crash tests. The Cybertruck earned “Good” ratings in the small overlap front (driver and passenger sides), updated moderate overlap front, and updated side tests—core requirements for the Top Safety Pick+ designation.
It also secured acceptable or good headlights across trims and a “Good” rating for its standard front crash prevention system in pedestrian scenarios, along with acceptable or good performance in vehicle-to-vehicle testing.
The Cybertruck avoided every single pedestrian collision, including:
- Daytime child crossing
- Nightitime adult crossing
- Night parallel adult
In IIHS pedestrian front crash prevention tests, @Cybertruck avoided every single collision – daytime, nighttime & different angles
It was also the only pickup to earn Top Safety Pick+ (highest award) in 2026https://t.co/BNPqT9TbsW pic.twitter.com/M6nwDisBFK
— Tesla (@Tesla) June 24, 2026
In the large pickup category, competitors such as the Toyota Tundra received only a standard Top Safety Pick, while the Ford F-150 and Ram 1500 did not qualify for either award. This positions the Cybertruck as a standout in occupant protection and crash avoidance among its peers.
Credit: IIHS
Ironically, the same vehicle celebrated for superior U.S. safety performance remains banned from public roads in the United Kingdom and much of Europe. Regulators there cite the Cybertruck’s sharp external edges and highly rigid stainless-steel construction as failing pedestrian-protection standards. European and UK rules require rounded surfaces on protruding parts to minimize injury risk in collisions with vulnerable road users.
Critics also point to the truck’s substantial weight and unyielding body structure, which some argue could transfer more force to other vehicles or pedestrians rather than absorbing it.
Tesla’s engineering philosophy underpins the Cybertruck’s strong IIHS results. The vehicle features a distinctive stainless-steel exoskeleton made from ultra-hard 30X cold-rolled stainless steel. This provides exceptional structural rigidity and a robust safety cage that resists deformation in side impacts and rollovers.
Engineers designed integrated load paths to channel crash forces away from the occupant compartment while allowing controlled energy absorption in key zones. Post-April 2025 refinements to the front underbody further optimized performance in overlap crashes.
Complementing the passive structure is Tesla’s advanced active safety suite, including the standard Collision Avoidance Assist system with automatic emergency braking. This contributed directly to the vehicle’s strong front crash prevention scores. The skateboard platform and low center of gravity also enhance stability and handling, reducing the likelihood of certain crashes.
The IIHS recognition highlights how Tesla’s combination of high-strength materials, structural innovation, and software-driven safety systems can deliver top-tier protection in rigorous testing. While global regulatory differences on design and pedestrian interaction continue to limit the Cybertruck’s availability outside North America, its U.S. safety credentials set a new benchmark for full-size pickups.
Elon Musk
SpaceX’s newest Starmind will make earth data centers obsolete
Elon Musk confirmed Starmind as SpaceX’s AI satellite constellation name, targeting one million orbital compute nodes.
Elon Musk confirmed that Starmind will be the official name of SpaceX’s planned AI satellite constellation, following a trademark filing by xAI that surfaced earlier this week. Starmind is what’s being described to the FCC as a constellation of up to one million AI satellites
It’s worth noting that SpaceX’s Starlink communication satellite and Starmind are built on the same orbital infrastructure concept but serve entirely different purposes. Starlink is a connectivity network, with satellites receiving and relaying data between points on Earth, and functioning as a high-speed internet backbone in space. The satellites themselves do not process or think, and move information from one place to another, the same function a fiber cable performs underground.
SpaceX just forced Verizon, AT&T and T-Mobile to team up for the first time in history
Starmind, on the other hand, is something completely different, and tather than moving data, its satellites would compute data through artificial intelligence and directly in orbit using onboard processors powered by large solar arrays. Where a Starlink satellite is essentially a very fast pipe, a Starmind satellite is a server. The practical implication is that Starmind would allow AI models to run inference, process queries, and generate outputs from space, then beam results down to users anywhere on Earth within milliseconds, and without the data ever needing to travel to a terrestrial data center.
Starship will be able to carry 30 to 50 AI1 satellites per launch, delivering the equivalent of dozens of server racks per flight, with no land acquisition, no power grid approval, and no cooling infrastructure required on the ground.
SpaceX is pursuing this new technology as terrestrial data centers are running into hard limits such as lack of physical space, community opposition, and power and water consumption at a scale that is increasingly difficult to permit. Space has unlimited solar power, natural vacuum cooling, and no zoning boards. Musk said in a June 8 video presentation that he expects space to become the lowest-cost location to deploy AI compute within two to three years. Two AI1 prototypes are scheduled to launch in early 2027, with volume production targeted for the end of that year at a new facility called Gigasat.
The real world applications Starmind enables extend well beyond powering Grok. A constellation of orbiting AI processors could run inference workloads for any paying customer, anywhere on Earth, with latency measured in milliseconds rather than the seconds associated with ground-based cloud routing across continents. Starmind, if it scales as described, would make SpaceX the landlord of AI compute the same way Starlink made it the landlord of satellite internet.
Tesla and driver sued by family of woman killed in Texas crash: what we know
Tesla Cybertruck is officially the safest pickup, IIHS says
