Tesla appears to have started slowly rolling out v11 of the Full Self-Driving Beta program this morning, just a few days after CEO Elon Musk stated the company would begin releasing it to more vehicles.
Tesla’s FSD Beta v11.3.1 started to roll out to employees late last year and a select few of the automaker’s long-standing testers a few weeks ago.
The controlled rollout allows Tesla to monitor its behaviors and tendencies in a highly safe way, as it can determine issues or bugs in a small sample size and fix them before a wider release begins.
On March 14, Musk stated that “ V11 starts going wide this weekend,” and we’ve heard it before. However, it appears the automaker is happy with the early reviews and is starting to release it to more vehicles.
V11 starts going wide this weekend
— Elon Musk (@elonmusk) March 15, 2023
v11.3.2 is the newest version of the Beta and is being rolled out with Tesla Software Update 2022.45.11. According to statistics from TeslaScope, more vehicles are being updated with the new FSD Beta v11, and more drivers on the r/TeslaMotors subreddit are beginning to report that they have received the update.
Drivers who have experienced the early editions of this rollout have reported that there have been several improvements to highway driving, and inner-city street navigation has also been refined and feels more accurate than ever before, which is undoubtedly a step in the right direction.
The full release notes for the FSD Beta are available below via TeslaScope:
- 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.
- Improved recall for close-by cut-in cases by 15%, particularly for large trucks and high-yaw rate scenarios, through an additional 30k auto-labeled clips mined from the fleet. Additionally, expanded and tuned dedicated speed control for cut-in objects.
- Improved the position of ego in wide lanes, by biasing in the direction of the upcoming turn to allow other cars to maneuver around ego.
- Improved handling during scenarios with high curvature or large trucks by offsetting in lane to maintain safe distances to other vehicles on the road and increase comfort.
- Improved behavior for path blockage lane changes in dense traffic. Ego will now maintain more headway in blocked lanes to hedge for possible gaps in dense traffic.
- Improved lane changes in dense traffic scenarios by allowing higher acceleration during the alignment phase. This results in more natural gap selection to overtake adjacent lane vehicles very close to ego.
- Made turns smoother by improving the detection consistency between lanes, lines and road edge predictions. This was accomplished by integrating the latest version of the lane-guidance module into the road edge and lines network.
- Improved accuracy for detecting other vehicles’ moving semantics. Improved precision by 23% for cases where other vehicles transition to driving and reduced error by 12% for cases where Autopilot incorrectly detects its lead vehicle as parked. These were achieved by increasing video context in the network, adding more data of these scenarios, and increasing the loss penalty for control- relevant vehicles.
- Extended maximum trajectory optimization horizon, resulting in smoother control for high curvature roads and far away vehicles when driving at highway speeds.
- Improved driving behavior next to row of parked cars in narrow lanes, preferring to offset and staying within lane instead of unnecessarily lane changing away or slowing down.
- Improved back-to-back lane change maneuvers through better fusion between vision-based localization and coarse map lane counts.
- Added text blurbs in the user interface to communicate upcoming maneuvers that FSD Beta plans to make. Also improved the visualization of upcoming slowdowns along the vehicle’s path. Chevrons render at varying opacity and speed to indicate the slowdown intensity, and a solid line appears at locations where the car will come to a stop.
- Improved the recall and precision of object detection, notably reducing the position error of semi-trucks by 10%, increasing the recall and precision of crossing vehicles over 100m away by 3% and 7%, respectively, and increasing the recall of motorbikes by 5%. This was accomplished by implementing additional quality checks in our two million video clip autolabeled dataset.
- Reduced false offsetting around objects in wide lanes and near intersections by improving object kinematics modeling in low speed scenarios.
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Tesla has opened its northernmost Supercharger in Fairbanks, Alaska, with eight V4 stalls located in one of the most frigid cities in the U.S.
Located just 196 miles from the Arctic Circle, Fairbanks’s average temperature for the week was around -12 degrees Fahrenheit. However, there are plenty of Tesla owners in Alaska who have been waiting for more charging options out in public.
There are only 36 total Supercharger stalls in Alaska, despite being the largest state in the U.S.
Eight Superchargers were added to Fairbanks, which will eventually be a 48-stall station. Tesla announced its activation today:
North America’s northernmost Supercharger Fairbanks, AK (8 stalls) opened to public. https://t.co/M4l04DZ6B5 pic.twitter.com/zyL6bDuA93
— Tesla Charging (@TeslaCharging) December 12, 2025
The base price per kWh is $0.43 at the Fairbanks Supercharger. Thanks to its V4 capabilities, it can charge at speeds up to 325 kW.
Despite being the northernmost Supercharger in North America, it is not even in the Top 5 northernmost Superchargers globally, because Alaska is south of Norway. The northernmost Supercharger is in Honningsvåg, Norway. All of the Top 5 are in the Scandanavian country.
Tesla’s Supercharger expansion in 2025 has been impressive, and although it experienced some early-quarter slowdowns due to V3-to-V4 hardware transitions, it has been the company’s strongest year for deployments.
🚨🚨 Tesla Supercharging had a HUGE year, and they deserve to be recognized.
🍔 Opened Tesla Diner, a drive-in movie theater with awesome, Chef-curated cuisine
🔌 Gave access to Superchargers to several EV makers, including Hyundai, Genesis, Mercedes-Benz, Kia, Lucid, Toyota,… pic.twitter.com/yYT2QEbqoW
— TESLARATI (@Teslarati) December 10, 2025
Through the three quarters of 2025, the company has added 7,753 stations and 73,817 stalls across the world, a 16 percent increase in stations and an 18 percent increase in stalls compared to last year.
Tesla is on track to add over 12,000 stalls for the full year, achieving an average of one new stall every hour, an impressive statistic.
Recently, the company wrapped up construction at its Supercharger Oasis in Lost Hills, California, a 168-stall Supercharger that Tesla Solar Panels completely power. It is the largest Supercharger in the world.
News
Tesla shocks with latest Robotaxi testing move
Why Tesla has chosen to use a couple of Model S units must have a reason; the company is calculated in its engineering and data collection efforts, so this is definitely more than “we just felt like giving our drivers a change of scenery.”
Tesla Model S vehicles were spotted performing validation testing with LiDAR rigs in California today, a pretty big switch-up compared to what we are used to seeing on the roads.
Tesla utilizes the Model Y crossover for its Robotaxi fleet. It is adequately sized, the most popular vehicle in its lineup, and is suitable for a wide variety of applications. It provides enough luxury for a single rider, but enough room for several passengers, if needed.
However, the testing has seemingly expanded to one of Tesla’s premium flagship offerings, as the Model S was spotted with the validation equipment that is seen entirely with Model Y vehicles. We have written several articles on Robotaxi testing mules being spotted across the United States, but this is a first:
🚨 Tesla is using Model S vehicles fitted with LiDAR rigs to validate FSD and Robotaxi, differing from the Model Ys that it uses typically
Those Model Y vehicles have been on the East Coast for some time. These Model S cars were spotted in California https://t.co/CN9Bw5Wma8 pic.twitter.com/UE55hx5mdd
— TESLARATI (@Teslarati) December 11, 2025
Why Tesla has chosen to use a couple of Model S units must have a reason; the company is calculated in its engineering and data collection efforts, so this is definitely more than “we just felt like giving our drivers a change of scenery.”
It seems to hint that Tesla could add a premium, more luxury offering to its Robotaxi platform eventually. Think about it: Uber has Uber Black, Lyft has Lyft Black. These vehicles and services are associated with a more premium cost as they combine luxury models with more catered transportation options.
Tesla could be testing the waters here, and it could be thinking of adding the Model S to its fleet of ride-hailing vehicles.
Reluctant to remove the Model S from its production plans completely despite its low volume contributions to the overall mission of transitioning the world to sustainable energy, the flagship sedan has always meant something. CEO Elon Musk referred to it, along with its sibling Model X, as continuing on production lines due to “sentimental reasons.”
However, its purpose might have been expanded to justify keeping it around, and why not? It is a cozy, premium offering, and it would be great for those who want a little more luxury and are willing to pay a few extra dollars.
Of course, none of this is even close to confirmed. However, it is reasonable to speculate that the Model S could be a potential addition to the Robotaxi fleet. It’s capable of all the same things the Model Y is, but with more luxuriousness, and it could be the perfect addition to the futuristic fleet.
News
Rivian unveils self-driving chip and autonomy plans to compete with Tesla
Rivian, a mainstay in the world of electric vehicle startups, said it plans to roll out an Autonomy+ subscription and one-time purchase program, priced at $49.99 per month and $2,500 up front, respectively, for access to its self-driving suite.
Rivian unveiled its self-driving chip and autonomy plans to compete with Tesla and others at its AI and Autonomy Day on Thursday in Palo Alto, California.
Rivian, a mainstay in the world of electric vehicle startups, said it plans to roll out an Autonomy+ subscription and one-time purchase program, priced at $49.99 per month and $2,500 up front, respectively, for access to its self-driving suite.
CEO RJ Scaringe said it will learn and become more confident and robust as more miles are driven and it gathers more data. This is what Tesla uses through a neural network, as it uses deep learning to improve with every mile traveled.
He said:
“I couldn’t be more excited for the work our teams are driving in autonomy and AI. Our updated hardware platform, which includes our in-house 1600 sparse TOPS inference chip, will enable us to achieve dramatic progress in self-driving to ultimately deliver on our goal of delivering L4. This represents an inflection point for the ownership experience – ultimately being able to give customers their time back when in the car.”
At first, Rivian plans to offer the service to personally-owned vehicles, and not operate as a ride-hailing service. However, ride-sharing is in the plans for the future, he said:
“While our initial focus will be on personally owned vehicles, which today represent a vast majority of the miles to the United States, this also enables us to pursue opportunities in the rideshare space.”
The Hardware
Rivian is not using a vision-only approach as Tesla does, and instead will rely on 11 cameras, five radar sensors, and a single LiDAR that will face forward.
It is also developing a chip in-house, which will be manufactured by TSMC, a supplier of Tesla’s as well. The chip will be known as RAP1 and will be about 50 times as powerful as the chip that is currently in Rivian vehicles. It will also do more than 800 trillion calculations every second.
Meet the Rivian Autonomy Processor.
Fast, smart, scalable and purpose-built for autonomous driving and the world of physical AI. Hitting the open road in 2026. pic.twitter.com/0wYXi5WKy7
— Rivian (@Rivian) December 11, 2025
RAP1 powers the Autonomy Compute Module 3, known as ACM3, which is Rivian’s third-generation autonomy computer.
ACM3 specs include:
- 1600 sparse INT8 TOPS (Trillion Operations Per Second).
- The processing power of 5 billion pixels per second.
- RAP1 features RivLink, a low-latency interconnect technology allowing chips to be connected to multiply processing power, making it inherently extensible.
- RAP1 is enabled by an in-house developed AI compiler and platform software
As far as LiDAR, Rivian plans to use it in forthcoming R2 cars to enable SAE Level 4 automated driving, which would allow people to sit in the back and, according to the agency’s ratings, “will not require you to take over driving.”
More Details
Rivian said it will also roll out advancements to the second-generation R1 vehicles in the near term with the addition of UHF, or Universal Hands-Free, which will be available on over 3.5 million miles of roadway in the U.S. and Canada.
More than any other feature, our owners have asked for more hands-free miles.
With Universal Hands-Free, you can now enjoy hands-free assisted driving on any road with clearly defined lanes. That’s roughly 3.5 million miles in the U.S. and Canada.
Look for it in our next… pic.twitter.com/ZFhwVzvt6b
— Rivian (@Rivian) December 11, 2025
Rivian will now join the competitive ranks with Tesla, Waymo, Zoox, and others, who are all in the race for autonomy.
Tesla’s northernmost Supercharger in North America opens
Tesla shocks with latest Robotaxi testing move
