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.
The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.
Elon Musk
California snubs Tesla in its newly passed EV incentive that favors Rivian and Lucid
California passed a $135 million EV incentive that rewards Rivian and Lucid while sidelining Tesla
California just drew a line in the EV incentive sand to put Tesla on the wrong side of it. The state recently passed a $135 million program offering first-time electric vehicle buyers a direct incentive with no application required, but the rules were written in a way that leaves Tesla at a structural disadvantage compared to Rivian and Lucid.
The program caps eligible vehicles at $50,000 for new EVs and $25,000 for used ones. That pricing threshold rules out a significant portion of Tesla’s lineup, though some lower-priced Model 3 and Model Y configurations would still qualify. California-based automakers are exempt from the price cap entirely, regardless of what their vehicles cost. Rivian, headquartered in Irvine, and Lucid, based in the San Francisco Bay Area, both benefit from that exemption. Rivian’s R2 starts at roughly $45,000 but has versions above the cap. Lucid’s Air and Gravity start at $70,990 and $79,990 respectively, well above any threshold a non-California company would face.
California hits Tesla Cybercab and Robotaxi driverless cars with new law
Tesla built its reputation and a significant portion of its early market share in California, where EV adoption has consistently led the nation. The company operates its original factory in Fremont, California, and the state was home to Tesla’s headquarters for most of its existence. That changed in 2021 when Tesla moved its corporate headquarters to Austin, Texas. Since then, the relationship between the company and California Governor Gavin Newsom has been openly adversarial, with Musk and Newsom trading public criticism on multiple occasions.
California’s EV incentive landscape has shifted repeatedly in recent years, and Tesla has previously lost eligibility for state-level programs as its vehicles exceeded income-adjusted price thresholds. The federal $7,500 EV tax credit, which Tesla models have qualified for and lost depending on policy cycles, is no longer available after it expired without renewal, making state-level programs more meaningful to buyers than they have been in years.
The practical impact for buyers is more nuanced than the headline suggests. California residents purchasing a Tesla under $50,000 for the first time can still access the incentive. But the exemption written for California-based manufacturers is a structural advantage that rewards where a company plants its headquarters flag rather than where it builds its products, and Tesla moved that flag to Texas.
Elon Musk
SpaceX’s newest logo confirms everything about what it’s become
SpaceX officially absorbed xAI under the SpaceXAI brand, completing the largest private merger in history.
SpaceX made its corporate transformation official in May 2026 when Elon Musk posted on X that xAI would cease to exist as a standalone company. “xAI will be dissolved as a separate company, so it will just be SpaceXAI, the AI products from SpaceX,” he wrote.
A new SpaceXAI logo was announced today, visually embedding the xAI letters inside the SpaceX identity, which can be seen as a deliberate design choice that signals the merger is not a partnership but a full absorption and XAi a core function of the same company. The same way Starlink is not a separate brand but a SpaceX product. The announcement closed the loop on a process that began February 2, 2026, when SpaceX acquired xAI in the largest private merger in history, valued at $1.25 trillion. SpaceX at $1 trillion and xAI at $250 billion.
We are now @SpaceXAI. pic.twitter.com/ema66xDWC9
— SpaceXAI (@SpaceXAI) July 6, 2026
The reason SpaceX bought xAI was stated plainly by Musk at the time of the deal: to build orbital data centers. SpaceX had simultaneously filed with the FCC to launch up to one million satellites designed to function as AI compute nodes in low Earth orbit, escaping what Musk described as the energy constraints limiting AI development on Earth.
xAI provided the AI software stack, with Grok, the X platform, and the Colossus supercomputer infrastructure in Memphis with over 220,000 NVIDIA GPUs, while SpaceX provided the rockets, Starlink, and the capital base to fund it. The two companies needed each other. xAI was burning $2.5 billion in losses on $250 million in revenue. SpaceX was generating an estimated $8 billion in profit on $15 billion in revenue and needed an AI narrative to command the valuation it was targeting for its IPO.
What SpaceX has done, regardless of how the orbital AI vision ultimately plays out, is walk into a public market as something no company has been before: a rocket manufacturer, satellite internet provider, AI software company, social media platform, and supercomputer operator under one ticker. Whether that combination is worth $2 trillion depends entirely on which of those businesses you believe in most.
Tesla brought its innovative Cybercab robotaxi to the National Federation of the Blind (NFB) Annual Convention in Austin, Texas, on July 3 at the JW Marriott Austin.
The hands-on demonstration highlighted the vehicle’s thoughtful design for blind and visually impaired users, underscoring Tesla’s commitment to inclusive autonomous mobility. Attendees, many using white canes or accompanied by service dogs, experienced the steering-wheel-free Cybercab firsthand.
Cybercab at the National Federation of the Blind’s Annual Convention in Austin for a hands-on experience of its accessibility features for blind or visually impaired customers⁰⁰For example:⁰– Braille lettering on physical controls
– Space for service animals & assistive… pic.twitter.com/8wrJcDHkw7— Tesla Robotaxi (@robotaxi) July 6, 2026
The showcase emphasized practical features tailored to the needs of the blind community. Braille lettering appears on physical controls, including door releases and emergency buttons, allowing users to navigate interfaces independently through touch. Generous interior space accommodates service animals and assistive devices such as canes, guide dogs, or mobility aids without compromising comfort.
Wheelchair-height seating facilitates easier transfers for users with additional mobility challenges. Photos from the event captured blind attendees approaching the vehicle confidently, service dogs relaxing inside, and hands exploring Braille-equipped handles.
Tesla Robotaxi’s official account detailed these elements, noting the Cybercab’s focus on accessibility, especially noting the Braille lettering and additional space for service animals.
How Tesla Will Transform Mobility for the Blind
Autonomous vehicles like the Cybercab promise revolutionary independence for the roughly 2.2 million visually impaired Americans. Traditional barriers—reliance on sighted drivers, costly paratransit, or limited public transit—often restrict spontaneous travel. Tesla Full Self-Driving aims to eliminate the need for a human operator, enabling on-demand, door-to-door rides via simple app hailing with voice guidance.
Users gain freedom to work, socialize, shop, or attend events anytime without scheduling hassles or safety concerns. This reduces isolation, boosts employment opportunities, and enhances quality of life, turning mobility from a dependency into true personal autonomy.
The NFB demonstration not only gathered valuable feedback but also generated excitement about a future where technology levels the playing field. By prioritizing inclusive design, Tesla advances a vision of transportation that serves everyone, potentially reshaping daily life for blind individuals and setting a standard for the autonomous industry.
As Cybercab deployment scales, these accessibility innovations could mark a significant step toward equitable mobility.
California snubs Tesla in its newly passed EV incentive that favors Rivian and Lucid
SpaceX’s newest logo confirms everything about what it’s become
