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.
Here are the V11.3 release notes again if you haven't seen them. Very happy to see improvements in rain reflections as that was rare, but could give some insane errors #FSDBeta @elonmusk pic.twitter.com/ZIOcIhmUMd
— Dirty Tesla (@DirtyTesLa) February 20, 2023
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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News
The secret behind Tesla’s Cybercab Gold goes well beyond just the color
Tesla has spent years trying to engineer its way out of the automotive paint shop, one of the most expensive, space-consuming, and environmentally costly steps in vehicle manufacturing. With the Cybercab, Tesla confirmed on X this week that a new reaction injection molding process will embed color directly into the panel itself during production.
“Our new reaction injection molding (RIM) process shrinks Cybercab paint cycles from hours to minutes. This cuts those parts’ manufacturing and supply chain emissions by 35% and eliminating 100% of paint volatile organic compounds (VOCs) emitted in traditional paint methods.” noted Tesla.
While the RIM process isn’t necessarily new and has existed since the 1960s, what makes Tesla’s application notable is how it is being used specifically for exterior body panels that traditionally required a separate paint process after forming.
Tesla’s RIM approach integrates the color directly into the panel material during the molding process itself. The pigment is part of the polymer mix injected into the mold, meaning the panel comes out of the mold already colored, with no separate paint application required. The clear coat or protective layer can be applied at the mold stage or through a much faster post-process than traditional multi-stage painting. Tesla claims this compresses what was a multi-hour paint cycle into minutes per panel.
Tesla’s obsession with killing the paint shop is one of the most consistent threads running through the company’s manufacturing philosophy going back years. As far back as 2018, Musk was trimming paint color options to simplify production, tweeting at the time: “Moving 2 of 7 Tesla colors off menu on Wednesday to simplify manufacturing.” Two years later, in a 2020 Automotive News interview, Musk laid out his broader vision, saying he believed Tesla factories could one day be 1,000 times more efficient than conventional plants, and pointing to the paint shop as one of the biggest sources of waste, cost, and complexity. The Cybertruck was the most extreme expression of that thinking. Tesla chose an unpainted stainless steel exterior partly because it would eliminate the need for a $200 million paint facility at Gigafactory Texas. The stainless approach proved harder and more expensive than anticipated, but the underlying ambition never changed. The Cybercab is what happens when that same ambition meets a manufacturing process that delivers on it.
Lifestyle
Tesla app update makes Robotaxi ownership make a lot more sense
Tesla’s app now shows a live indicator when your car is actively driving itself.
A recent Tesla app update, released last week (4.58.5), gives visibility on whether a vehicle is navigating in its semi-autonomous mode or being drive by a human driver. The updated app now displays a live “Self-Driving” indicator in bright blue text directly beneath the vehicle’s speed readout whenever Full Self-Driving is actively engaged, along with the signature glowing blue navigation path that FSD users see on the main touchscreen. It is a small visual update with meaningful implications for how Tesla owners monitor their vehicles remotely.
The feature was first spotted in the wild by X user Jordan Camina, who shared video of a Hardware 3 Model S displaying the new animation through the app while driving. That detail is significant because it confirms the update is not limited to newer HW4 vehicles. It works across hardware generations, and Tesla confirmed it will eventually support all vehicles regardless of chip platform once both the app and vehicle software are updated. The vehicle side requires software version 2026.20.6.1, which has reached nearly 40% of the fleet so far, as monitored by NotaTeslaApp.
The feature makes the most practical sense when viewed through the lens of Tesla’s expanding robotaxi operation. In a robotaxi context, the owner of a vehicle generating ride revenue has a direct financial and safety interest in knowing whether their car is operating under autonomous control at any given moment. The app’s new FSD indicator gives fleet owners exactly that visibility, the same way a logistics company monitors whether a delivery driver is following the planned route. It also carries implications for Tesla’s insurance model. Tesla’s own insurance product prices premiums in part based on FSD engagement rates, and real-time visibility into when FSD is active creates a feedback loop that could eventually tie directly into policy pricing. For individual owners who have opted their personal vehicles into the robotaxi network, the update effectively turns the Tesla app into a fleet management dashboard, one that tells you whether your car is earning money, whether it is driving itself to do it, and whether everything is operating the way it should from wherever you happen to be.
Tesla expands Robotaxi to Florida, marking its third state for autonomy
As Teslarati has reported, Tesla launched unsupervised robotaxi rides in Miami this summer, a milestone that makes a remote FSD status indicator significantly more practical than a cosmetic feature. When a vehicle is operating as a robotaxi without a driver present, the owner or fleet operator needs a reliable way to confirm autonomy is engaged. The app now provides exactly that.
As noted by NotATeslaApp, The update also arrived alongside a hint buried in the same app version that Tesla plans to use the cabin camera to verify driver identity before FSD can be activated. Pairing identity verification with a live autonomy status indicator points toward the infrastructure Tesla is building for a fleet of driverless vehicles that owners can monitor the way you would track a package delivery.
Elon Musk
California snubs Tesla in its newly passed EV incentive that favors Rivian and Lucid
California passed a $135 million EV incentive that rewards Rivian and Lucid while sidelining Tesla
California just drew a line in the EV incentive sand to put Tesla on the wrong side of it. The state recently passed a $135 million program offering first-time electric vehicle buyers a direct incentive with no application required, but the rules were written in a way that leaves Tesla at a structural disadvantage compared to Rivian and Lucid.
The program caps eligible vehicles at $50,000 for new EVs and $25,000 for used ones. That pricing threshold rules out a significant portion of Tesla’s lineup, though some lower-priced Model 3 and Model Y configurations would still qualify. California-based automakers are exempt from the price cap entirely, regardless of what their vehicles cost. Rivian, headquartered in Irvine, and Lucid, based in the San Francisco Bay Area, both benefit from that exemption. Rivian’s R2 starts at roughly $45,000 but has versions above the cap. Lucid’s Air and Gravity start at $70,990 and $79,990 respectively, well above any threshold a non-California company would face.
California hits Tesla Cybercab and Robotaxi driverless cars with new law
Tesla built its reputation and a significant portion of its early market share in California, where EV adoption has consistently led the nation. The company operates its original factory in Fremont, California, and the state was home to Tesla’s headquarters for most of its existence. That changed in 2021 when Tesla moved its corporate headquarters to Austin, Texas. Since then, the relationship between the company and California Governor Gavin Newsom has been openly adversarial, with Musk and Newsom trading public criticism on multiple occasions.
California’s EV incentive landscape has shifted repeatedly in recent years, and Tesla has previously lost eligibility for state-level programs as its vehicles exceeded income-adjusted price thresholds. The federal $7,500 EV tax credit, which Tesla models have qualified for and lost depending on policy cycles, is no longer available after it expired without renewal, making state-level programs more meaningful to buyers than they have been in years.
The practical impact for buyers is more nuanced than the headline suggests. California residents purchasing a Tesla under $50,000 for the first time can still access the incentive. But the exemption written for California-based manufacturers is a structural advantage that rewards where a company plants its headquarters flag rather than where it builds its products, and Tesla moved that flag to Texas.