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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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Tesla Semi lands the biggest electric truck deal in U.S. history

Tesla leads a record 2,500 truck order, but not every truck will be a Semi.

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Tesla has landed the largest electric truck order in U.S. history. ZET SCALE, a new alliance of shippers and carriers, named Tesla its primary manufacturer on Tuesday for an initial order of 2,500 electric Class 8 trucks. The deal alone would nearly double the number of electric heavy trucks operating in the country.

According to the press release from Catalyst Mobility, the nonprofit formerly known as CALSTART, Kenworth, RIDE and Volvo were also selected as secondary manufacturers that carriers can pick if their operations call for it. No split between the four brands has been published, so the exact number of Semis in the order is not yet known.

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Tesla won the top slot through a competitive request for proposals. The alliance, which Catalyst Mobility runs with the Smart Freight Centre, scored bidders on price, range, charging capability and production capacity. Pooling freight demand from founding shippers, including Microsoft and PepsiCo, let every truck maker bid lower than it would for a single fleet. “The Tesla Semi is designed for lower cost per mile operations than diesel,” said Dan Priestley, director of the Tesla Semi program, as noted in the press release.

The financing is built to pull in carriers who have avoided electric trucks. ZET Financial is issuing the purchase order for all 2,500 units and will place them with fleets through a fair market value lease. The trucks will be deployed over the next few years across 10 freight hubs in Los Angeles, Stockton, Bakersfield, Seattle and Tacoma, Houston, Dallas, San Antonio, Chicago, Atlanta, and the Newark and New York area. ZET SCALE says the first order is only the opening round, with a longer term goal of 10,000 trucks or more.

Even if Tesla ends up with only a majority share, it would still be the biggest Semi deal to date. Einride’s 500 unit order in August was the previous record, and WattEV’s 370 truck order in May was the largest California deal at the time. Einride’s CEO has since said he expects all 500 trucks delivered by the end of 2027.

The announcement lands two days before Tesla formally inaugurates its Semi factory in Nevada on September 24. The 1.7 million square foot plant sits next to Gigafactory Nevada’s 4680 cell lines and is designed for 50,000 trucks a year.

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Tesla integrates Grok Bot into its vehicles for the ultimate personal assistant

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Credit: Grok

Tesla has expanded Grok from an in-car chatbot into a hands-free work assistant. On September 22, Tesla officially launched Grok Bot capability, confirming that drivers can now manage email, calendars, files, chats, and tasks by voice and then hand more ambitious errands to the AI-fueled productivity cheat code.

Grok itself is built by xAI. The new car features split into two layers: Connectors link Grok to outside accounts. Grok Bot, currently limited to SuperGrok Heavy subscribers, can complete multi-step tasks such as placing a usual coffee order, booking a reservation, or scheduling an appointment. It truly puts the driver in a nearly complete hands-free driving and productivity setting, with ironically the only task truly requiring your hands being to touch the “Start Self-Driving” button.

We were granted access to Grok Bot’s Tesla integration a few weeks back, and we’ve been able to do a handful of things with it. On a handful of occasions, we’ve used it to order food and have it ready for pickup slightly later into the evening; we’ve managed to pick up groceries after a day of errands with Grok Bot, and outside of the car, it’s helped with budgeting and even my fantasy football draft.

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Tesla shows another way to utilize it: in their demo, a driver says “Hey Grok,” asks the assistant to check an inbox, and hears that a message concerns a weekend reservation. Grok then scans the calendar, reports no conflicts, and confirms the Tahoe trip is clear. It can also add check-in details to a road-trip itinerary. The point is not novelty chat. It is keeping eyes on the road, or on Full Self-Driving, while the car handles the paperwork of a trip:

This Grok rollout is not a gadget add-on as much as it is Tesla’s thesis in software form: the car should stop being a machine you operate and start being a room you occupy.

Connectors and Grok Bot treat the cabin as an office that happens to move, and that has truly been Tesla’s intention for years now. The car has slowly become an extension of a home more than a vehicle. Inbox, calendar, groceries, takeout, and reservations become voice work, not dashboard chores that you need to do before you get in your car.

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Responsibility shifts from the driver to the stack, and as many Tesla owners rely on FSD for travel, Grok Bot now handles the monotony of dinner reservations or appointments.

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Elon Musk

X changed how everyone gets paid, and this lawsuit shows why

X sued a Bitcoin account network over fake payouts as its creator pay model shifts

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Elon Musk’s X has taken a Bitcoin-focused engagement ring to court, and the case doubles as a receipt for how differently the platform pays creators today. The company filed suit in the High Court of England and Wales against Vivek Kumar Sen and Zamyang Sherpa, alleging the pair ran six accounts, including @Vivek4real_, @Bitcoin_Teddy and @TrendingBitcoin, as one coordinated operation to fake the kind of engagement that used to translate directly into money.

According to the filing, first reported by Gizmodo, the accounts posted near identical “BREAKING” crypto headlines seconds apart, in one case 11 seconds, then had three more handles like, reply to and repost the material to manufacture what X called “a false appearance of genuine, human communication and interaction.” X says the scheme pulled in at least £207,384, about $278,000, and pegs its own investigation and remediation costs at another £75,000. The accounts were suspended August 18. X general counsel James Burnham announced the case on X last weekend, writing that the company “will act forcefully to protect our platform and the earnings of genuine creators.” Musk’s own reaction, posted shortly after, was three words: “Don’t mess with 𝕏.”

The timing lines up with a a recent update to how X pays its creators. The program these accounts allegedly gamed, Creator Revenue Sharing, launched in mid 2023 and paid out based on how much a post got engaged with. Originality was never part of the formula, which is exactly how the platform ended up flooded with recycled clips, copy pasted “BREAKING” posts and replies engineered purely to farm reactions from paying subscribers.

X tried patching the model more than once, including an April cut to aggregator payouts and a March regional weighting change that Musk personally paused hours after it was announced. X retired Creator Revenue Sharing for good on September 7 and opened its replacement, Original Content Rewards, the next day.

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The new math is stricter. Payouts now come only from qualified impressions, meaning unique Home Timeline views from Premium subscribers where at least half the post is visible, and replies no longer count toward eligibility at all. Copied posts, reuploaded media and reposts without meaningful changes are explicitly excluded. Allegra Jacchia, senior product manager for Creators at SpaceXAI, which now runs X’s product and AI work following xAI’s acquisition of the platform, put it bluntly, saying the goal is to reward creators who bring original ideas and perspective, “not those who have become best at gaming the system.”

Read that way, the lawsuit isn’t really about six crypto accounts. It’s X putting a dollar figure on what the old incentive structure cost, then suing to collect it right as the new one goes live. For live updates on how the case and the new rewards program shake out, follow @Teslarati on X.

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