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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.

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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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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Investor's Corner

New drone video shows Tesla’s Optimus Factory reaching a turning point

New drone footage shows Tesla’s dedicated Optimus factory steel frame nearing completion at Giga Texas.

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Tesla’s dedicated Optimus factory at Gigafactory Texas is closing in on a finished steel frame, according to drone footage posted Thursday afternoon by longtime site observer Joe Tegtmeyer. In the video, Tegtmeyer said structural steel assembly is now about five column grids away from reaching the building’s north perimeter beam, putting the primary skeleton in its final stretch roughly six months after Tesla broke ground on the North Campus site in late March.

Tegtmeyer’s footage shows concrete already going in on three upper floors while crews continue laying rebar and pouring grade beam footings at ground level. That kind of parallel work, steel rising at one end of the site while concrete sets at the other, is a scheduling approach Tesla used at the original Giga Texas building and appears to be repeating here to save time before the plant’s targeted 2027 production start.

Teslarati has tracked the building’s progress since Tesla confirmed construction was officially underway in May, when the first steel structure went up on what was then bare, reclaimed land. The facility is part of a more than 5.2 million square foot expansion of Giga Texas’s North Campus that Tesla has said will eventually run nearly the length of the existing vehicle factory, over 4,000 feet, while sitting somewhat narrower. Musk has pegged the long term output target at 10 million Optimus units a year once the line is running at full capacity, a volume that would dwarf the one million unit pilot line Tesla is standing up separately at its Fremont, California factory.

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Tesla Giga Texas to feature massive Optimus V4 production line

The Texas facility sits alongside another major buildout on the same campus. Terafab, the joint Tesla and SpaceX chip fabrication plant that will eventually supply the silicon running Optimus units in the field. Housing robot assembly and chip production on the same grounds is a deliberate supply chain decision, cutting down on the shipping and lead time that would otherwise sit between the two.

Tesla has not given an updated timeline beyond its previously stated goal of bringing high volume Optimus production online at the site in the summer of 2027. Fremont’s smaller pilot line began mass producing the current Gen 3 robot in January, with that plant expected to build tens of thousands of units this year primarily to generate the real world data Tesla needs to refine the robot’s software before Giga Texas ramps up. Six months of visible construction progress, tracked almost entirely through Tegtmeyer’s recurring drone flights, gives the clearest outside look yet at how seriously Tesla is treating that 2027 deadline.

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Investor's Corner

Tesla and SpaceX take “Terafab” Trademark fight to Federal Court

Tesla and SpaceX sue a small Illinois firm after cease and desist letters over Terafab.

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SpaceX Terafab rendering

Tesla and SpaceX are asking a federal judge to rule that their planned Terafab chip factory does not infringe a small Illinois company’s trademark, a request that arrives only after months of quiet negotiation broke down this summer.

The dispute traces to May 18, when Tesla filed three U.S. trademark applications for “Terafab” and “Tesla Terafab,” covering semiconductor chips and related chip making services. TERA-print LLC, a nanotechnology company that has held a federal trademark for “Tera-Fab” since 2021, responded five days later with a cease and desist letter. According to the lawsuit, first reported by Reuters, TERA-print argued that Tesla and SpaceX’s use of “Terafab” would confuse consumers familiar with its own trademark, which covers a desktop photolithography printer sold to researchers for sensor and bioengineering work.

What stands out in the filing is the timing of TERA-print’s own paperwork. One day before sending that cease and desist letter, on May 22, TERA-print applied to expand its existing registration to cover semiconductor materials, silicon chips, nanoelectronic devices and AI design services, categories it had not previously claimed. Tesla and SpaceX call that filing opportunistic in their complaint, noting it arrived two months after Tesla’s public Terafab announcement and just days after Tesla’s own trademark applications went in.

Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry

By June 10, TERA-print was threatening to sue for federal trademark infringement, false designation of origin and unfair competition, the complaint states. Rather than wait to be sued, Tesla, SpaceX and SpaceXAI met with TERA-print six separate times between June and August trying to resolve the dispute directly. Those talks collapsed, and the companies filed for declaratory judgment this week in the U.S. District Court for the Western District of Texas, asking a judge to find that “Terafab” does not infringe TERA-print’s mark before TERA-print can file a claim of its own.

TERA-print isn’t backing down. The company told PCMag it discussed a settlement with Tesla as recently as September 2 and feels misled by what it called Tesla’s professed interest in settling. Its CTO, Andrey Ivankin, said TERA-print holds a Defense Department contract to fabricate semiconductors and partially owns Mattiq Inc., an AI company built on TERA-print’s products, and that the company will vigorously defend its rights.

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Tesla and SpaceX argue the overlap is superficial. Terafab is planned as a $16.8 billion complex spanning roughly 100 million square feet at the Grimes County site SpaceX confirmed last month, built to produce chips for Optimus robots, Tesla’s AI computing needs and SpaceX’s orbital data center ambitions, a scale and purpose the companies say no reasonable consumer would confuse with a tabletop lab printer. TERA-print’s product line has stayed focused on lithography tools for biological and sensor research since it registered its mark in 2021.

The trademark fight is the second legal dispute tied to the Terafab project in the past week, following a separate SpaceX suit aimed at keeping company records about the facility out of public view, as KBTX reported. Whether construction proceeds under the Terafab name now depends on a federal judge in Austin.

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NHTSA just escalated its Tesla Cybercab investigation in a big way

NHTSA escalated its Cybercab audit into a sworn Special Order with a September 30 deadline.

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Federal regulators have moved from asking Tesla questions about its Cybercab to demanding sworn answers. The National Highway Traffic Safety Administration issued a Special Order that requires a Tesla officer to sign an affidavit attesting to the completeness of the company’s responses, with a deadline of September 30.

The order builds on Audit Query AQ26002, which NHTSA opened on September 3, the same day Tesla began commercial Cybercab service in Austin. Teslarati covered that initial inquiry when it surfaced, noting the agency wanted to understand how Tesla certified a vehicle with no permanently attached steering wheel, pedals, or mirrors as compliant with Federal Motor Vehicle Safety Standards. A Special Order is a different tool and converts a fact finding review into a legally enforceable demand, the same mechanism NHTSA used against Tesla in 2023 during its Autopilot investigation.

Several of the 21 requests target a specific gap in Cybercab’s design. One asks whether Tesla used temporarily attached human controls at any point to help certify the vehicle, and if so, which standards depended on that equipment being present. Another quotes an existing rule directly: “The service brakes shall be activated by means of a foot control.” Cybercab has no foot pedal. NHTSA wants a detailed explanation of how the vehicle satisfies that requirement, and how it complies without the kind of exemption granted to Zoox in July under Part 555, the regulatory pathway built for steering wheel free vehicles.

The order does not claim Cybercab is unsafe or that Tesla broke a rule. It requires Tesla to explain, under oath, the reasoning behind decisions the company already made when it self-certified the vehicle. That distinction matters, but so does the exposure. Motor1’s reporting, summarized here, put potential civil penalty exposure as high as $139 million if NHTSA later finds the certification was flawed, on top of whatever criminal risk comes with a false sworn statement.

Tesla has not said publicly how it plans to respond. Cybercab is still carrying passengers in Austin through the Robotaxi app while the September 30 deadline approaches, and the company has continued expanding the vehicle’s footprint even as the regulatory question remains open. The Special Order does not pause any of that and just sets a date by which Tesla has to put its certification logic on the record, with a company officer’s name attached to it.

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