The release notes for Tesla FSD Beta V11.3 have been shared online. Observers from the electric vehicle community suggest that Tesla Full Self-Driving Beta 11.3 is rolling out to the company’s employee FSD Beta testers, at least for now.
The following are Tesla’s FSD Beta V11.3 release notes:
- 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.
- Added voice drive-notes. After an intervention, you can now send Tesla an anonymous voice message describing your experience to help improve Autopilot.
- Expanded Automatic Emergency Braking (AEB) to handle vehicles that cross ego’s path. This includes cases where other vehicles run their red light or turn across ego’s path, stealing the right-of-way.
- Replay of previous collisions of this type suggests that 49% of the events would be mitigated by the new behavior. This improvement is now active in both manual driving and autopilot operation.
- Improved autopilot reaction time to red light runners and stop sign runners by 500ms, by increased reliance on object’s instantaneous kinematics along with trajectory estimates.
- Added a long-range highway lanes network to enable earlier response to blocked lanes and high curvature.
- Reduced goal pose prediction error for candidate trajectory neural network by 40% and reduced runtime by 3X. This was achieved by improving the dataset using heavier and more robust offline optimization, increasing the size of this improved dataset by 4X, and implementing a better architecture and feature space.
- Improved occupancy network detections by oversampling on 180K challenging videos including rain reflections, road debris, and high curvature.
- Improved recall for close-by cut-in cases by 20% by adding 40k autolabeled fleet clips of this scenario to the dataset. Also improved handling of cut-in cases by improved modeling of their motion into ego’s lane, leveraging the same for smoother lateral and longitudinal control for cut-in objects.
- Added “lane guidance module and perceptual loss to the Road Edges and Lines network, improving the absolute recall of lines by 6% and the absolute recall of road edges by 7%.
- Improved overall geometry and stability of lane predictions by updating the “lane guidance” module representation with information relevant to predicting crossing and oncoming lanes.
- Improved handling through high speed and high curvature scenarios by offsetting towards inner lane lines.
- Improved lane changes, including: earlier detection and handling for simultaneous lane changes, better gap selection when approaching deadlines, better integration between speed-based and nav-based lane change decisions and more differentiation between the FSD driving profiles with respect to speed lane changes.
- Improved longitudinal control response smoothness when following lead vehicles by better modeling the possible effect of lead vehicles’ brake lights on their future speed profiles.
- Improved detection of rare objects by 18% and reduced the depth error to large trucks by 9%, primarily from migrating to more densely supervised autolabeled datasets.
- Improved semantic detections for school busses by 12% and vehicles transitioning from stationary-to-driving by 15%. This was achieved by improving dataset label accuracy and increasing dataset size by 5%.
- Improved decision making at crosswalks by leveraging neural network based ego trajectory estimation in place of approximated kinematic models.
- Improved reliability and smoothness of merge control, by deprecating legacy merge region tasks in favor of merge topologies derived from vector lanes.
- Unlocked longer fleet telemetry clips (by up to 26%) by balancing compressed IPC buffers and optimized write scheduling across twin SOCs.
Here are the V11.3 release notes again if you haven't seen them. Very happy to see improvements in rain reflections as that was rare, but could give some insane errors #FSDBeta @elonmusk pic.twitter.com/ZIOcIhmUMd
— Dirty Tesla (@DirtyTesLa) February 20, 2023
Several longtime FSD Beta testers have pointed out some key improvements that would likely be very appreciated by users in V11.3. These include the systems’ improved handling through high speed and high curvature scenarios, as well as improvements to Automatic Emergency Braking (AEB). With the improvements in place, FSD Beta V11.3 would behave closer to a proper human driver.
Comments from longtime Tesla FSD Beta testers also suggest that V11.3 is still only being released for company employees for now. Considering Tesla’s past updates, it would not be surprising if the greater FSD Beta fleet gets the V11.3 update in the coming week or so. This is, of course, unless V11.3 ends up going the way of FSD Beta V11, which was released to employees in November but not to the greater fleet of FSD Beta testers.
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Tesla welcomed JPMorgan analysts to one of its factories earlier this month, with the Wall Street firm highlighting its findings in a new note to investors. One of the more pertinent pieces of information is that Tesla admitted to slowly integrating Model Y vehicles into its Robotaxi fleet, but it has a good reason.
JPMorgan analysts recently toured Tesla’s Fremont Factory and met with the company’s investor relations team, emerging with a clearer picture of the automaker’s Robotaxi strategy. According to the bank’s note, Tesla is intentionally limiting the addition of Model Y vehicles to its existing Robotaxi fleet.
The firm’s analysts said:
“Tesla indicated it is intentionally holding back on adding Model Y units to the robotaxi fleet, expressing confidence in its ability to scale Cybercab in the near-term. On FSD V15, Tesla views this release as a step-change in performance, comparable to the leap from V13 to V14. The V15 upgrade encompasses seven core technologies, with ~40% of those currently being tested in the robotaxi fleet, where initial feedback has been encouraging.”
JPMorgan after meeting with Tesla recently in Fremont:
“Tesla indicated it is intentionally holding back on adding Model Y units to the robotaxi fleet, expressing confidence in its ability to scale Cybercab in the near-term. On FSD V15, Tesla views this release as a step-change… pic.twitter.com/W9yGCWRT3C
— Sawyer Merritt (@SawyerMerritt) August 20, 2026
Far from signaling delays or doubts about autonomy, the move reflects strong management confidence in the near-term scalability of the purpose-built Cybercab.
Tesla has operated its Robotaxi service primarily with modified Model Ys since launching in Austin and expanding to other markets. Yet the company is now deliberately holding back further Model Y conversions. The rationale is straightforward: leadership believes the Cybercab, a two-seat, steering-wheel- and pedal-free vehicle optimized for high utilization, can ramp production and deployment more efficiently in the coming months.
This dedicated form factor promises better unit economics for the majority of rides, which typically involve one or two passengers, while freeing consumer Model Y inventory for retail sales.
Supporting this pivot is Full Self-Driving (FSD) software version 15, which Tesla describes as a genuine step-change in performance, comparable to the leap from V13 to V14. The update incorporates seven core technologies; roughly 40 percent are already undergoing real-world testing in the current Robotaxi fleet, with early feedback described as encouraging.
Tesla is carefully managing software development to minimize regressions in core driving functions as new capabilities are added. Management positions V15 as the primary gateway to scaling unsupervised FSD. Importantly, the existing AI and Hardware 4 stack is already capable of running V15 and supporting unsupervised operation.
Cybercab itself is only the first vehicle on the platform. Tesla reiterated that additional form factors will follow, pointing to concepts such as the earlier “Robovan” demonstration as examples of how the architecture can evolve.
Tesla’s mysterious Robovan makes a sneak peek with Optimus in Terafab video
Parallel progress continues on the Optimus humanoid robot, which remains on track for start of production in the coming months, with commercial sales possible as early as the second half of 2027. Generation 3 details will be revealed closer to production to preserve competitive advantages, while Generation 4 scope will draw on real-world Gen 3 experience.
JPMorgan left the meeting with a deeper appreciation for Tesla’s manufacturing automation and maintained its $475 price target. The decision to slow Model Y Robotaxi integration is therefore not a setback but a calculated prioritization of a more efficient, purpose-built solution that management believes is ready to scale.
SpaceX CEO Elon Musk announced today that the company will likely attempt to catch the Starship upper stage with its launch tower arms “in a few months.”
In a post on X, Musk wrote, “Looks like we will probably catch the ship with the tower in a few months. If there had been a tower out to sea where we practiced landing the ship, it would have been caught.” He added that the first reflight of a Starship vehicle is expected by the end of 2026 or early 2027, describing it as “a fork in the road of history for consciousness reaching the stars.”
Looks like we will probably catch the ship with the tower in a few months. If there had been a tower out to sea where we practiced landing the ship, it would have been caught.
First reflight of the ship will be either end of this year or early next. That will be a fork in the… https://t.co/O5g9pqrzyo
— Elon Musk (@elonmusk) August 20, 2026
Musk’s prediction comes amid ongoing progress toward full reusability of the Starship system, a two-stage rocket designed for rapid turnaround and dramatically lower launch costs. Catching the upper stage, known simply as “ship,” with the Mechazilla tower’s mechanical arms would mark a major milestone. It would allow both stages to return directly to the launch site for quick refurbishment and reuse, eliminating the need for ocean recovery.
Musk has previously signaled plans for a ship catch. In July, shortly after SpaceX’s wildly successful Starship 13 mission, he stated that the company would attempt to catch the ship with the tower on the next flight unless problems emerged in the mission data review. Earlier comments also outline conditions such as successful soft ocean landings before attempting a land recovery to minimize risk.
SpaceX has solved Starship’s biggest challenge, Elon Musk says
The latest update from Musk adjusts this timeline to a few months, reflecting the iterative nature of the test campaign.
SpaceX has already demonstrated the tower catch technique successfully with the Super Heavy booster on a couple of occasions. The first successful booster catch occurred during Flight 5 in October 2024, when the massive first stage returned to the Starbase pad in Texas and was plucked from the air by the tower arms.
Additional catches followed on later flights, including Flight 7, proving the concept for the booster and building confidence in the system as a whole.
Achieving a similar catch for the upper stage would represent a significant step forward. The ship returns from much higher speeds and greater heat loads after orbital or near-orbital flight. Success would advance SpaceX’s goal of full and rapid reusability, potentially reducing the cost of access to orbit by a factor of 100 or more and supporting ambitions for frequent satellite deployments, lunar missions, and eventual Mars flights.
Musk has long emphasized that true reusability, refueling rather than discarding hardware, is essential for making humanity a multi-planetary species.
As SpaceX continues refining Starship through successive test flights, the coming months will test whether the ambitious catch timeline can be met. The combination of prior booster successes and improving ship landing precision suggests the company is steadily closing in on this historic capability.
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SpaceX has achieved an incredible milestone by launching its 11,000th Starlink satellite into orbit.
This accomplishment occurred during the Starlink Group 17-50 mission, which lifted off on August 19 at 04:01 UTC from Space Launch Complex 4 East at Vandenberg Space Force Base in California.
Falcon 9 launches 24 @Starlink satellites from California pic.twitter.com/UscpmAxDls
— SpaceX (@SpaceX) August 19, 2026
A Falcon 9 rocket carried 24 Starlink V2 Mini satellites on this flight, successfully deploying them into low Earth orbit approximately one hour after liftoff. The first stage booster, identified as B1097 on its twelfth flight, landed successfully on the droneship Of Course I Still Love You in the Pacific Ocean.
According to tracking data compiled around that date, this deployment brought the total number of Starlink satellites in orbit to just over 11,000.
The Starlink program began with test satellites known as Tintin A and B, launched on February 22, 2018. The first operational batch of 60 Starlink satellites followed on May 24, 2019, when a Falcon 9 rocket lifted off from Cape Canaveral. Those initial satellites marked the start of a rapid expansion that has continued for more than seven years.
SpaceX has conducted hundreds of dedicated Starlink missions since then, routinely launching batches of 20 to 30 satellites at a time using reusable Falcon 9 rockets. By mid-2026, the company had already surpassed 12,000 total satellites launched across all versions, with continuous replacements for units that deorbit as designed to manage space debris.
Looking ahead, SpaceX continues to expand the Starlink constellation to enhance global broadband coverage, capacity, and speed. The network already serves millions of users across more than 160 countries and supports applications ranging from residential internet to maritime, aviation, and emergency services.
Future plans center on next-generation hardware, including larger V3 satellites capable of delivering substantially higher throughput, which require the increased payload capacity of the Starship vehicle currently under development and testing.
In July, SpaceX submitted an application to the Federal Communications Commission seeking authority for a Gen3 constellation of up to 100,000 satellites. These spacecraft would operate in very low Earth orbit shells at altitudes near 325 kilometers and 475 kilometers. The filing requests use of existing Ku, Ka, V, and E band spectrum along with new greenfield W and D band frequencies between 92 and 275 GHz.
SpaceX states that the expanded system aims to deliver multi-gigabit symmetrical broadband to consumers, enterprises, governments, and billions of AI-powered devices worldwide while handling a majority of global internet traffic. Approval and subsequent deployment would depend on regulatory review and the operational readiness of Starship for high-volume launches.
This ambitious scale reflects SpaceX’s ongoing commitment to providing ubiquitous high-speed connectivity from space.
Tesla admits to slow Model Y Robotaxi integration, but for a good reason
Elon Musk gives a timeline for SpaceX’s first Starship catch attempt
