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Tesla FSD Beta V11.3 starts shipping to employees (Release Notes)

Credit: Drive in EV/Twitter

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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.

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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.

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Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Tesla Australia confirms six-seat Model Y L launch in 2026

Compared with the standard five-seat Model Y, the Model Y L features a longer body and extended wheelbase to accommodate an additional row of seating.

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Credit: Tesla China

Tesla has confirmed that the larger six-seat Model Y L will launch in Australia and New Zealand in 2026. 

The confirmation was shared by techAU through a media release from Tesla Australia and New Zealand.

The Model Y L expands the Model Y lineup by offering additional seating capacity for customers seeking a larger electric SUV. Compared with the standard five-seat Model Y, the Model Y L features a longer body and extended wheelbase to accommodate an additional row of seating.

The Model Y L is already being produced at Tesla’s Gigafactory Shanghai for the Chinese market, though the vehicle will be manufactured in right-hand-drive configuration for markets such as Australia and New Zealand.

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Tesla Australia and New Zealand confirmed the vehicle will feature seating for six passengers.

“As shown in pictures from its launch in China, Model Y L will have a new seating configuration providing room for 6 occupants,” Tesla Australia and New Zealand said in comments shared with techAU.

Instead of a traditional seven-seat arrangement, the Model Y L uses a 2-2-2 layout. The middle row features two individual seats, allowing easier access to the third row while providing additional space for passengers.

Tesla Australia and New Zealand also confirmed that the Model Y L will be covered by the company’s updated warranty structure beginning in 2026.

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“As with all new Tesla Vehicles from the start of 2026, the Model Y L will come with a 5-year unlimited km vehicle warranty and 8 years for the battery,” the company said.

The updated policy increases Tesla’s vehicle warranty from the previous four-year or 80,000-kilometer coverage.

Battery and drive unit warranties remain unchanged depending on the variant. Rear-wheel-drive models carry an eight-year or 160,000-kilometer warranty, while Long Range and Performance variants are covered for eight years or 192,000 kilometers.

Tesla has not yet announced official pricing or range figures for the Model Y L in Australia.

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Tesla Roadster patent hints at radical seat redesign ahead of reveal

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A newly published Tesla patent could offer one of the clearest signals yet that the long-awaited next-generation Roadster is nearly ready for its public debut.

Patent No. US 20260061898 A1, published on March 5, 2026, describes a “vehicle seat system” built around a single continuous composite frame – a dramatic departure from the dozens of metal brackets, recliner mechanisms, and rivets that make up a traditional car seat. Tesla is calling it a monolithic structure, with the seat portion, backrest, headrest, and bolsters all thermoformed as one unified piece.

The approach mirrors Tesla’s broader manufacturing philosophy. The same company that pioneered massive aluminum castings to eliminate hundreds of body components is now applying that logic to the cabin. Fewer parts means fewer potential failure points, less weight, and a cleaner assembly process overall.

Tesla Roadster Seat Concept Image by TESLARATI

Tesla ramps hiring for Roadster as latest unveiling approaches

The timing of the filing is difficult to ignore. Elon Musk has publicly targeted April 1, 2026 as the date for an “unforgettable” Roadster design reveal, and two new Roadster trademarks were filed just last month. A patent describing a seat architecture suited for a hypercar, and one that Tesla has promised will hit 60 mph in under two seconds.

The Roadster, originally unveiled in 2017, has been one of Tesla’s most anticipated yet most delayed products. With a target price around $200,000 and engineering ambitions to match, it is being positioned as the ultimate showcase for what Tesla’s technology can do.

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The patent was first flagged by @seti_park on X.

Tesla Roadster Monolithic Seat: Feature Highlights via US Patent 20260061898 A1

  1. Single Continuous Frame (Monolithic Construction). The core invention is a seat assembly built from one continuous frame that integrates the seat portion, backrest portion, and hinge into a single component — eliminating the need for separate structural parts and mechanical joints typical in conventional seats.
  2. Integrated Flexible Hinge. Rather than a traditional mechanical recliner, the hinge is built directly into the continuous frame and is designed to flex, and allowing the backrest to move relative to the seat portion. The hinge can be implemented as a fiber composite leaf spring or an assembly of rigid linkages.
  3. Thermoformed Anisotropic Composite Material. The continuous frame is manufactured via thermoforming from anisotropic composite materials, including fiberglass-nylon, fiberglass-polymer, nylon carbon composite, Kevlar-nylon, or Kevlar-polymer composites, enabling a molded-to-shape monolithic structure.
  4. Regionally Tuned Stiffness Zones. The frame is engineered with up to six distinct stiffness regions (R1–R6) across the seat, backrest, hinge, headrest, and bolsters. Each zone can have a different stiffness, allowing precise ergonomic and structural tuning without adding separate components.
  5. Linkage Assembly Hinge Mechanism. The hinge incorporates one or more linkage assemblies consisting of multiple interlocking links with gears, connected by rods. When driven by motors or actuators, these linkages act as a flexible member to control backrest movement along a precise, ergonomically optimized trajectory.
  6. Multi-Actuator Six-Degree-of-Freedom Positioning System. The seat uses four distinct actuator pairs, all controlled by a central controller. These actuators work in coordinated combinations to achieve fore/aft, height, cushion tilt, and backrest rotation adjustments simultaneously.
  7. ECU-Based Controller Architecture. An Electronic Control Unit (ECU) and programmable controller manage all seat actuators, receive user input via a user interface (touchscreen, buttons, or switches), and incorporate sensor feedback to confirm and maintain desired seat positions, essentially making this a software-driven seat system.
  8. Airbag-Integrated Bolster Deployment System. The backrest bolsters (216) are geometrically shaped and sized to guide airbag deployment along a specific, pre-configured trajectory. Left and right bolsters can have different shapes so that each guides its respective airbag along a distinct trajectory, improving occupant protection.
  9. Ventilation Holes Formed into the Backrest. The continuous frame includes one or more ventilation holes formed directly into the backrest portion, configured to either receive airflow into or deliver airflow from the seat frame — enabling passive or active thermal comfort without requiring separate ventilation components.
  10. Soft Trim Recess for Tool-Free Integration. The headrest and backrest portions together define a molded recess, specifically designed to receive and secure a soft trim component (foam, fabric, or cushioning) directly into the continuous frame, eliminating the need for separate attachment hardware and simplifying final assembly.

 

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Elon Musk’s xAI plans $659M expansion at Memphis supercomputer site

The new building is planned for a 79-acre parcel located at 5414 Tulane Road, next to xAI’s Colossus 2 data center site.

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Credit: xAI

Elon Musk’s artificial intelligence company xAI has filed a permit to construct a new building at its growing data center complex outside Memphis, Tennessee. 

As per a report from Data Center Dynamics, xAI plans to spend about $659 million on a new facility adjacent to its Colossus 2 data center. Permit documents submitted to the Memphis and Shelby County Division of Planning and Development show the proposed structure would be a four-story building totaling about 312,000 square feet.

The new building is planned for a 79-acre parcel located at 5414 Tulane Road, next to xAI’s Colossus 2 data center site. Permit filings indicate the structure would reach roughly 75 feet high, though the specific function of the building has not been disclosed.

The filing was first reported by the Memphis Business Journal.

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xAI uses its Memphis data centers to power Grok, the company’s flagship large language model. The company entered the Memphis area in 2024, launching its Colossus supercomputer in a repurposed Electrolux factory located in the Boxtown district.

The company later acquired land for the Colossus 2 data center in March last year. That facility came online in January.

A third data center is also planned for the cluster across the Tennessee–Mississippi border. Musk has stated that the broader campus could eventually provide access to about 2 gigawatts of compute power.

The Memphis cluster is also tied to new power infrastructure commitments announced by SpaceX President Gwynne Shotwell. During a White House event with United States President Donald Trump, Shotwell stated that xAI would develop 1.2 gigawatts of power for its supercomputer facility as part of the administration’s “Ratepayer Protection Pledge.”

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“As you know, xAI builds huge supercomputers and data centers and we build them fast. Currently, we’re building one on the Tennessee-Mississippi state line… xAI will therefore commit to develop 1.2 GW of power as our supercomputer’s primary power source. That will be for every additional data center as well… 

“The installation will provide enough backup power to power the city of Memphis, and more than sufficient energy to power the town of Southaven, Mississippi where the data center resides. We will build new substations and invest in electrical infrastructure to provide stability to the area’s grid,” Shotwell said.

Shotwell also stated that xAI plans to support the region’s water supply through new infrastructure tied to the project. “We will build state-of-the-art water recycling plants that will protect approximately 4.7 billion gallons of water from the Memphis aquifer each year. And we will employ thousands of American workers from around the city of Memphis on both sides of the TN-MS border,” she said.

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