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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 Optimus Gen 3 shows off a cleaner, factory-ready design in new app discovery

Renders hidden inside Tesla’s Android app show Optimus Gen 3’s design before any official reveal.

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Tesla Optimus Gen 3 [Credit: Tesla]

Tesla may have accidentally given a first look at its newest Optimus Gen 3 humanoid robot when photos were found in the Tesla smartphone app.

Design files tucked inside a recent Android version of the Tesla app appear to show the third generation humanoid robot next to the older Gen 2.5 prototype. The assets were extracted from the app package by Tesla community member @wholemars, who posted the renders on X late Tuesday night before deleting them. The Tesla Newswire reshared the side by side comparison on Wednesday, and the images have circulated widely since.

Tesla Optimus Gen 2.5 vs Gen 3 comparison via @WholeMars on X

Tesla Optimus Gen 2.5 vs Gen 3 comparison via @WholeMars on X

The files are labeled “gen3” and were built as models for Tesla app’s own interface, as validated directly by Grok to be official.

The comparison shows a robot that looks built for a factory line rather than a lab bench. Gen 2.5’s exposed mechanical linkages and gold plating on the knees and shins are gone. In their place, Gen 3 uses matte black fairings on the lower legs, paired with a more contoured champagne gold body. Flexible covers now seal the joint where the torso meets the upper thighs, keeping bearings and moving parts sealed from debris and unnecessary contact.

The body panels fit more tightly, and the hands, which Tesla has said carry 22 degrees of freedom, look far more refined than those on earlier units.

This most recent leak fills a gap Tesla has left open for most of the year. Elon Musk said on March 31 that Optimus 3 was walking around but needed “some finishing touches” before it could be shown, a delay Teslarati covered when Tesla missed its first quarter reveal target. Musk later said Tesla would hold the design back until closer to production, partly to keep competitors from copying it. No reveal date has been announced.

The app itself has been preparing for Optimus for months. In July, code in the Tesla app pointed to a dedicated robot phone key, a consent screen for collecting video and spatial data while Optimus works inside a home, and an alert system for low battery and mechanical faults. Finished 3D models of Gen 3 suggest the interface owners will eventually use is moving past placeholder code toward something Tesla intends to ship.

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Manufacturing is moving in parallel. Tesla tore out the original Model S and Model X lines at Fremont this summer to make room for Optimus production, with a planned capacity of one million robots a year. At Giga Texas, the steel frame of a dedicated Optimus factory is nearing completion ahead of a targeted 2027 start, with Musk pointing to an eventual output of 10 million units annually.

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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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