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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Tesla has expanded its branded ‘For Business’ Supercharger program that it launched last year, as yet another company is using the platform to attract EV owners to its business and utilize a unique advertising opportunity.
Francis Energy of Oklahoma is launching four Superchargers in Norman, where the University of Oklahoma is located. The Superchargers, which are fitted with branding for Francis Energy, will officially open tomorrow.
It will not be the final Supercharger location that Francis Energy plans to open, the company confirmed to EVWire.
Back in early September, Tesla launched the new “Supercharger for Business” program in an effort to give businesses the ability to offer EV charging at custom rates. It would give their businesses visibility and would also cater to employees or customers.
“Purchase and install Superchargers at your business,” Tesla wrote on a page on its website for the new program. “Superchargers are compatible with all electric vehicles, bringing EV drivers to your business by offering convenient, reliable charging.”
The first site opened in Land O’ Lakes, Florida, which is Northeast of Tampa, as a company called Suncoast launched the Superchargers for local EV owners.
Tesla launches its new branded Supercharger for Business with first active station
The program also does a great job at expanding infrastructure for EV owners, which is something that needs to be done to encourage more people to purchase Teslas and other electric cars.
Francis Energy operates at least 14 EV charging locations in Oklahoma, spanning from Durant to Oklahoma City and nearly everywhere in between. Filings from the company, listed by Supercharge.info, show the company’s plans to convert some of them to Tesla Superchargers, potentially utilizing the new Supercharger for Business program to advertise.
Moving forward, more companies will likely utilize Tesla’s Supercharger for Business program as it presents major advantages in a variety of ways, especially with advertising and creating a place for EV drivers to gain range in their cars.
Tesla Cybercab is perhaps the most highly-anticipated project that the company plans to roll out this year, and as it is undergoing its testing phase in pre-production currently, there are some things to work through with it.
Over the weekend, an image of the Cybercab being loaded onto a tow truck started circulating on the internet, and people began to speculate as to what the issue could be.
Hmmmmmm… https://t.co/L5hWcOXQkb pic.twitter.com/OJBDyHNTMj
— TESLARATI (@Teslarati) January 11, 2026
The Cybercab can clearly be seen with a Police Officer and perhaps the tow truck driver by its side, being loaded onto, or even potentially unloaded from, the truck.
However, it seems unlikely it was being offloaded, as its operation would get it to this point for testing to begin with.
It appears, at first glance, that it needs assistance getting back to wherever it came from; likely Gigafactory Texas or potentially a Bay Area facility.
The Cybercab was also spotted in Buffalo, New York, last week, potentially undergoing cold-weather testing, but it doesn’t appear that’s where this incident took place.
It is important to remember that the Cybercab is currently undergoing some rigorous testing scenarios, which include range tests and routine public road operation. These things help Tesla assess any potential issue the vehicle could run into after it starts routine production and heads to customers, or for the Robotaxi platform operation.
This is not a one-off issue, either. Tesla had some instances with the Semi where it was seen broken down on the side of a highway three years ago. The all-electric Semi has gone on to be successful in its early pilot program, as companies like Frito-Lay and PepsiCo. have had very positive remarks.
The Cybercab’s future is bright, and it is important to note that no vehicle model has ever gone its full life without a breakdown. It happens, it’s a car.
Nevertheless, it is important to note that there has been no official word on what happened with this particular Cybercab unit, but it is crucial to remember that this is the pre-production testing phase, and these things are more constructive than anything.
Tesla analyst Andrew Percoco of Morgan Stanley teased the company’s dominance in its self-driving initiative, stating that its lead over competitors is “not even close.”
Percoco recently overtook coverage of Tesla stock from Adam Jonas, who had covered the company at Morgan Stanley for years. Percoco is handling Tesla now that Jonas is covering embodied AI stocks and no longer automotive.
His first move after grabbing coverage was to adjust the price target from $410 to $425, as well as the rating from ‘Overweight’ to ‘Equal Weight.’
Percoco’s new note regarding Tesla highlights the company’s extensive lead in self-driving and autonomy projects, something that it has plenty of competition in, but has established its prowess over the past few years.
He writes:
“It’s not even close. Tesla continues to lead in autonomous driving, even as Nvidia rolls out new technology aimed at helping other automakers build driverless systems.”
Percoco’s main point regarding Tesla’s advantage is the company’s ability to collect large amounts of training data through its massive fleet, as millions of cars are driving throughout the world and gathering millions of miles of vehicle behavior on the road.
This is the main point that Percoco makes regarding Tesla’s lead in the entire autonomy sector: data is King, and Tesla has the most of it.
One big story that has hit the news over the past week is that of NVIDIA and its own self-driving suite, called Alpamayo. NVIDIA launched this open-source AI program last week, but it differs from Tesla’s in a significant fashion, especially from a hardware perspective, as it plans to use a combination of LiDAR, Radar, and Vision (Cameras) to operate.
Percoco said that NVIDIA’s announcement does not impact Morgan Stanley’s long-term opinions on Tesla and its strength or prowess in self-driving.
NVIDIA CEO Jensen Huang commends Tesla’s Elon Musk for early belief
And, for what it’s worth, NVIDIA CEO Jensen Huang even said some remarkable things about Tesla following the launch of Alpamayo:
“I think the Tesla stack is the most advanced autonomous vehicle stack in the world. I’m fairly certain they were already using end-to-end AI. Whether their AI did reasoning or not is somewhat secondary to that first part.”
Percoco reiterated both the $425 price target and the ‘Equal Weight’ rating on Tesla shares.
Tesla expands its branded ‘For Business’ Superchargers
Tesla Cybercab ‘breakdown’ image likely is not what it seems
