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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. 

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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.

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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Elon Musk

SpaceX Starship just nailed something it’s never done before

SpaceX’s Starship flew successfully Friday, landing both stages and deploying its first Starlink V3 satellites.

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Starship’s thirteenth test flight delivered exactly what SpaceX needed with a clean liftoff, two successful stage recoveries, and the first real payload the vehicle has ever carried to space. Booster 20 and Ship 40 lifted off at 5:51 p.m. CT from Starbase, and by the time the mission wrapped roughly an hour later, both halves of the rocket had done exactly what they were supposed to do.

Booster 20 separated from Ship 40 a few minutes into the flight and stuck a controlled splashdown in the Gulf of Mexico about six minutes after liftoff. That is a meaningful turnaround from Flight 12 in May, when the booster lost several engines during its boostback burn before a hard water landing attempt.


Starship 40’s performance was arguably the bigger win. The vehicle deployed the first 20 operational Starlink V3 satellites Starship has ever carried, then flew a suborbital arc to a landing in the Indian Ocean that SpaceX commentator Dan Huot called the company’s softest splashdown yet. “This is a dream scenario for this team that’s trying to get this heat shield data,” Huot said on the live broadcast, according to Space.com’s live coverage. “I’m a little over the moon right now. Wow. Lucky number 13.”

Unlike the mass simulators SpaceX flew on Flight 12, these were production Starlink V3 satellites, meant to extend solar arrays and antennas and attempt to link with the broader constellation before reentering minutes later. Getting real hardware through a full deploy sequence on only the second flight of the V3 generation keeps Starship on schedule for the payload work NASA is counting on for future Artemis lunar landings.

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— TESLARATI (@Teslarati) July 25, 2026

The flight also arrives at a moment when SpaceX needed a win. SPCX has traded below its $135 IPO price since mid-July, as Teslarati reported when the mission slipped to Friday, and short interest has climbed to roughly a third of the tradable float. A clean flight will not fix a balance sheet, but it does answer the one question SpaceX absolutely needed answered this week: whether the fixes made after the July 16 abort would hold up under real flight conditions. They did, on both stages, on the first try after the redesign.

SpaceX has not set a target date for Flight 14, though the company has said it wants to push toward an orbital attempt on the next mission. After Friday, that goal looks a lot more within reach.

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Tesla’s Supercharger Diner probably just secured more locations

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tesla diner
Credit: Tesla

Tesla’s Supercharger Diner in Los Angeles dominated the company’s global usage rankings after just one year, proving the concept is more than just a one-off novelty location that will fade away.

The performance could incite the company to build more locations, something that CEO Elon Musk has hinted at for some time.

Tesla’s Supercharger Diner delivered 21.2 GWh of energy in its first year of operation, the company’s head of Charging, Max de Zegher, revealed on X. Of the top 10 most utilized Supercharger locations in Tesla’s global infrastructure, the Diner in Los Angeles was the most used by drivers, and it wasn’t particularly close:

On its launch day one year ago, nobody was too sure what the Tesla Diner would be about. It seemed like an interesting concept, and considering it had been in the works for years, it was a highly anticipated launch that many were looking forward to.

Based on its success, we could see additional Diners with Superchargers built throughout the United States, and potentially beyond. Musk has said on several occasions that the company would be willing to bring the Diner idea to more markets.

Tesla makes major change at Supercharger Diner amid epic demand

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Of the markets that Musk has mentioned, both Palo Alto and Austin have come to be perceived as ideal selections. However, there are no concrete plans as of now to build new Supercharger Diners anywhere; the location on Santa Monica Boulevard will remain the exclusive spot to pick up Tesla-inspired eats, at least for the time being.

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Investor's Corner

Tesla short sellers win big after shares fall after earnings

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A red Tesla Roadster driving around a turn
(Credit: Tesla)

Tesla short sellers won big following the company’s massive fall on Wall Street after it reported subpar Earnings on Wednesday.

Tesla short sellers collected about $4.12 billion in single-day profits on Thursday, according to BloombergShares fell as much as 15 percent during Thursday’s session. It closed as one of the worst days for Tesla on Wall Street in the past three years.

Investors sold off the stock after Tesla said it would aggressively direct its spending toward AI and its Optimus robot project. The company had record revenues, which were driven by one of the strongest quarters in terms of vehicle deliveries in company history.

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However, it missed EPS estimates by reporting just $0.33, a far cry from the $0.53 analysts expected.

S3 Partners reported that about 3 percent of Tesla’s outstanding stock is sold short. Managing Director at S3, Ihor Dusaniwsky, provided the short seller’s potential profit, as well as another figure: shorts have likely had paper gains of $8.92 billion this year, as Tesla shares are down 30 percent in 2026.

Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue

Tesla has burned short sellers many times in the past, but the company’s latest Earnings Call was a chance for those skeptics to taste some payback. Although the company gave some very transparent information regarding future projects, the rollout of Robotaxi, Optimus, and Semi, many investors took their profits on Thursday.

Notable short sellers like Michael Burry have been transparent about their skepticism around Tesla shares. Burry just revealed three weeks ago that he had opened up a new short on the stock, stating he shorted Tesla shares at $416.22. “Happy it jumped back to this level,” he said in a blog post.

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At the time of publication, Tesla shares were down about 3 percent and the stock was trading at $309.92.

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