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.
The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.
Elon Musk
Elon Musk has generous TSA offer denied by the White House: here’s why
Musk stepped in on March 21 via a post on X, writing: “I would like to offer to pay the salaries of TSA personnel during this funding impasse that is negatively affecting the lives of so many Americans at airports throughout the country.”
Tesla and SpaceX CEO Elon Musk made a generous offer to pay the salaries of Transportation Security Administration (TSA) employees last week, but the offer was denied by the White House.
In a striking display of private-sector initiative clashing with federal bureaucracy, the White House has turned down an offer from Elon Musk to personally cover the salaries of TSA officers amid an ongoing partial government shutdown. The rejection, reported last Wednesday by multiple outlets, highlights the legal and political hurdles facing unconventional solutions to Washington’s funding gridlock.
The impasse began weeks ago when Congress failed to pass funding for the Department of Homeland Security (DHS), leaving TSA employees, essential workers who screen millions of travelers daily, without paychecks while still required to report for duty.
Frustrated travelers have endured record-long security lines at major airports, with reports of chaos and delays rippling across the country.
Musk stepped in on March 21 via a post on X, writing: “I would like to offer to pay the salaries of TSA personnel during this funding impasse that is negatively affecting the lives of so many Americans at airports throughout the country.”
I would like to offer to pay the salaries of TSA personnel during this funding impasse that is negatively affecting the lives of so many Americans at airports throughout the country
— Elon Musk (@elonmusk) March 21, 2026
But it was not for no reason.
White House spokesperson Abigail Jackson responded on behalf of the Trump administration, expressing appreciation for Musk’s gesture.
However, the legal obstacles, which would be insurmountable, would inhibit Musk from doing so. Jackson said:
“We greatly appreciate Elon’s generous offer. This would pose great legal challenges due to his involvement with federal government contracts.”
Musk’s companies hold significant federal contracts, including NASA launches through SpaceX and potential Defense Department work, raising concerns about conflicts of interest, ethics rules, and anti-bribery statutes that prohibit private payments to government employees. Administration officials also indicated they expect the shutdown to end soon, making external funding unnecessary.
The episode underscores deeper tensions in Washington. Musk, who has advised on government efficiency efforts and maintains a close relationship with President Trump, has frequently criticized wasteful spending and bureaucratic delays.
His offer came as airport security lines ballooned, drawing public frustration toward both parties. TSA officers, many of whom rely on paychecks to cover mortgages and family expenses, have continued working without compensation, a situation that has drawn bipartisan concern but little immediate resolution.
Critics of the rejection argue it prioritizes red tape over practical relief for frontline workers and travelers. Supporters of the White House position counter that allowing private funding sets a dangerous precedent and could undermine congressional authority over the budget.
The White House eventually came to terms with the TSA on Friday and started paying them once again, and lines at airports instantly shrank. The Department of Homeland Security (DHS) said that TSA staf would begin receiving paychecks “as early as” today.
Elon Musk
Tesla FSD mocks BMW human driver: Saves pedestrian from near miss
Tesla FSD anticipated a BMW driver’s lane drift before the human behind the wheel could react.
A video posted to r/TeslaFSD this week put a sharp spotlight on Tesla’s Full Self-Driving (FSD) software being able to react to pedestrian intent than an actual human driver behind the wheel. In the Reddit clip, a BMW driver can be seen rolling through a neighborhood street completely unaware of a pedestrian stepping in to cross. At the same time, a Tesla driving on FSD had already begun slowing down before the pedestrian even began their attempt to cross the street The BMW kept moving, prompting the pedestrian to hop back, while the Tesla came to a stop and provide right-of-way for the human to safely cross.
That gap between what the BMW driver saw and what FSD had already processed is the story. Tesla FSD wasn’t reacting to a person in the street, rather it was reading the signals that a person was about to enter it based on the pedestrian’s movement, trajectory, and their trajectory to telegraph intent.
Tesla’s FSD is now built on an end-to-end neural network trained on billions of real-world miles, learning to interpret subtle human behavioral cues the same way an experienced human driver does instinctively. The difference is consistency. A human driver distracted for two seconds misses what FSD does not.
Tesla sues California DMV over Autopilot and FSD advertising ruling
Reddit commenters in the thread were blunt about the BMW driver’s failure, with several pointing out that the pedestrian was visible well before the crossing. One response put it plainly that the car on FSD saw the situation developing before the human in the other car had registered there was a situation at all.
Tesla has published data showing FSD (Supervised) is 54% safer than a human driver, accumulated across billions of miles driven on the system. Elon Musk has said FSD v14 will outperform human drivers by a factor of two to three, and that v15 has “a shot” at a 10x improvement. Pedestrian safety is where the stakes are highest, and where intent prediction closes the gap fastest. At 30 mph, a car covers roughly 44 feet per second. An extra second of awareness from reading a person’s body language rather than waiting for them to step out is often the difference between a near miss and a fatality.
Video and community discussion: r/TeslaFSD on Reddit
FSD saves man from becoming a pancake. BMW driver nearly flattens him.
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u/Qwertygolol in
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Tesla Robotaxi gets a small but significant change
In the world of Tesla, where billion-dollar battery breakthroughs and autonomy milestones dominate headlines, a quiet design update can still pack a punch.
In the world of Tesla, where billion-dollar battery breakthroughs and autonomy milestones dominate headlines, a quiet design update can still pack a punch.
Last week in downtown Austin, sharp-eyed observers spotted a subtle but telling evolution on the Cybercab: a new “ROBOTAXI” logo graphic now graces the vehicle’s doors at Tesla’s Autonomy Popup.
What looks at first glance like a minor stylistic choice is, in fact, a deliberate rebranding move that hints at how the company envisions its robotaxi fleet fitting into everyday life.
The updated lettering is bold, graffiti-inspired, and unapologetically street-smart. Rendered in black with dripping white accents and a glowing yellow outline, the font evokes urban energy and playful irreverence.
Live From Downtown Austin:
Tesla Cybercab with new logo Graphic at their Autonomy Popup pic.twitter.com/MTTb9KDr3b
— David Moss (@DavidMoss) March 13, 2026
Gone is the sleek, minimalist typography that defined earlier Cybercab prototypes. In its place is something more human, almost rebellious.
The new logo pops against the Cybercab’s smooth, metallic body, turning the autonomous pod into a rolling piece of public art rather than just another futuristic taxi.
Designers know that fonts are silent brand ambassadors. They shape perception before a single ride is taken. Tesla’s classic sans-serif aesthetic screams precision engineering and Silicon Valley cool.
The new Robotaxi script leans into accessibility and fun, suggesting the vehicle is approachable, not intimidating. For a product meant to ferry strangers through city streets 24/7, that matters. It signals that the robotaxi isn’t reserved for tech elites; it’s for everyone.
Tesla Cybercab spotted next to Model Y shows size comparison
The timing is no accident. With regulatory approvals for unsupervised autonomy advancing and Tesla preparing to scale Cybercab production, the company is shifting from prototype showcase to fleet deployment.
A fresh logo helps differentiate the vehicles visually in dense urban environments—crucial for rider recognition and brand recall. It also aligns with Elon Musk’s long-standing ethos: make the future feel exciting, not sterile.
Small changes like this often foreshadow a larger strategy. Tesla has always obsessed over details—door handles, screen interfaces, even the curvature of a steering wheel.
Updating the Robotaxi font reflects the same meticulous care now applied to consumer-facing autonomy. It’s not just paint on metal; it’s a statement that the ride of the future should feel personal, memorable, and undeniably cool.
In an industry racing toward self-driving fleets, Tesla’s willingness to evolve even the smallest visual cues shows confidence. A font won’t launch the robotaxi network, but it might just help millions climb aboard with a smile.