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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving

(Credit: Tesla)

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4 years ago

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Tesla released FSD Beta 10.69 to the first round of testers over the weekend. Read v.10.69’s release notes below to check out the latest improvements. 

Stay in your Lanes

  • Added a new “deep lane guidance” module to the Vector Lanes neural network which fuses features extracted from the video streams with coarse map data, i.e. lane counts and lane connectivites. This architecture achieves a 44% lower error rate on lane topology compared to the previous model, enabling smoother control before lanes and their connectivities becomes visually apparent. This provides a way to make every Autopilot drive as good as someone driving their own commute, yet in a sufficiently general way that adapts for road changes.

 Nothing Like Smooth Driving

  • Improved overall driving smoothness, without sacrificing latency, through better modeling of system and actuation latency in trajectory planning. Trajectory planner now independently accounts for latency from steering commands to actual steering actuation, as well as acceleration and brake commands to actuation. This results in a trajectory that is a more accurate model of how the vehicle would drive. This allows better downstream controller tracking and smoothness while also allowing a more accurate response during harsh manevuers.
  • Increased smoothness for protected right turns by improving the association of traffic lights with slip lanes vs yield signs with slip lanes. This reduces false slowdowns when there are no relevant objects present and also improves yielding position when they are present.
  • Reduced false slowdowns near crosswalks. This was done with improved understanding of pedestrian and bicyclist intent based on their motion.
  • Enabled creeping for visibility at any intersection where objects might cross ego’s path, regardless of presence of traffic controls.
  • Improved accuracy of stopping position in critical scenarios with crossing objects, by allowing dynamic resolution in trajectory optimization to focus more on areas where finer control is essential.
  • Reduced latency when starting from a stop by accounting for lead vehicle jerk.

Chuck’s Left Turn

  • Improved unprotected left turns with more appropriate speed profile when approaching and exiting median crossover regions, in the presence of high speed cross traffic (“Chuck Cook style” unprotected left turns). This was done by allowing optimizable initial jerk, to mimic the harsh pedal press by a human, when required to go in front of high speed objects. Also improved lateral profile approaching such safety regions to allow for better pose that aligns well for exiting the region. Finally, improved interaction with objects that are entering or waiting inside the median crossover region with better modeling of their future intent.

Safety is Number 1

  • Added control for arbitrary low-speed moving volumes from Occupancy Network. This also enables finer control for more precise object shapes that cannot be easily represented by a cuboid primitive. This required predicting velocity at every 3D voxel. We may now control for slow-moving UFOs.
  • Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
  • Improved speed when entering highway by better handling of upcoming map speed changes, which increases the confidence of merging onto the highway.
  • Enabled faster identification of red light runners by evaluating their current kinematic state against their expected braking profile.

Tesla FSD “Brain” Improvements

  • Upgraded Occupancy Network to use video instead of images from single time step. This temporal context allows the network to be robust to temporary occlusions and enables prediction of occupancy flow. Also, improved ground truth with semantics-driven outlier rejection, hard example mining, and increasing the dataset size by 2.4x.
  • Upgraded to a new two-stage architecture to produce object kinematics (e.g. velocity, acceleration, yaw rate) where network compute is allocated O(objects) instead of O(space). This improved velocity estimates for far away crossing vehicles by 20%, while using one tenth of the compute.
  • Improved geometry error of ego-relevant lanes by 34% and crossing lanes by 21% with a full Vector Lanes neural network update. Information bottlenecks in the network architecture were eliminated by increasing the size of the per-camera feature extractors, video modules, internals of the autoregressive decoder, and by adding a hard attention mechanism which greatly improved the fine position of lanes.
  • Improved recall of animals by 34% by doubling the size of the auto-labeled training set.
  • Increased recall of forking lanes by 36% by having topological tokens participate in the attention operations of the autoregressive decoder and by increasing the loss applied to fork tokens during training.
  • Improved velocity error for pedestrians and bicyclists by 17%, especially when ego is making a turn, by improving the onboard trajectory estimation used as input to the neural network.
  • Improved recall of object detection, eliminating 26% of missing detections for far away crossing vehicles by tuning the loss function used during training and improving label quality.
  • Improved object future path prediction in scenarios with high yaw rate by incorporating yaw rate and lateral motion into the likelihood estimation. This helps with objects turning into or away from ego’s lane, especially in intersections or cut-in scenarios.

Tesla is rolling out FSD Beta v.10.69 in phases, starting with ~1,000 testers over the weekend. Once the update is rolled out for wide release, the price of FSD Beta will increase.

The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.

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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 Full Self-Driving insurance program with heavy discount expands

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7 hours ago

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August 3, 2026

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Lemonade has expanded its innovative Autonomous Car insurance program to Tennessee, giving Tesla owners in the state a substantial discount on Full Self-Driving (FSD) miles. Announced on August 3, the product offers 50 percent off every mile driven with FSD activated, positioning the digital insurer as a leader in pricing insurance around autonomous technology.

The program, marketed as Lemonade Autonomous Car insurance, uses a direct connection via Tesla’s Fleet API (with customer permission) to automatically distinguish FSD-engaged miles from manual driving. Policyholders pay a low base rate when the vehicle is stationary and a few cents per mile when moving, with the 50 percent reduction applied specifically to FSD miles.

Coverage includes standard protections such as liability, collision, comprehensive, roadside assistance, and Tesla-specific benefits like access to certified repair shops and emergency crash services. Eligible vehicles require Hardware 4, as well as recent firmware.

Lemonade first unveiled the product on January 21 of this year, describing it as a first-of-its-kind offering designed for self-driving cars, starting with Tesla FSD. It began rolling out in Arizona on January 26, followed by Oregon about a month later. Subsequent expansions brought it to Indiana in early June 2026 and Colorado later that month.

Tennessee marks the fifth state.

Tesla Full Self-Driving gets outrageous insurance offer with insanely cheap rates

The discount rests on Lemonade’s strong belief in the safety of Tesla’s FSD system. The company cites Tesla’s data showing that FSD-driven miles are twice as safe as those driven manually, or associated with roughly a 50 percent crash reduction.

Lemonade Co-founder and President Shai Wininger has emphasized this distinction: “Traditional insurers treat a Tesla like any other car, and AI like any other driver. But a car that sees 360 degrees, never gets drowsy, and reacts in milliseconds can’t be compared to a human.”

He added that “Teslas driven with FSD are involved in far fewer accidents” and committed that as FSD software improves and becomes safer, Lemonade’s prices will drop further.

Tesla Full Self-Driving gets an offer to be insured for ‘almost free’

This approach leverages Lemonade’s existing pay-per-mile technology and AI-driven risk models, which analyze nuanced vehicle data including software version and sensor performance. The company expects the model to reward higher FSD usage with greater savings while supporting mixed households that include both Tesla and non-Tesla vehicles under one policy. Bundling with home, renters, or pet insurance can yield additional discounts.

As autonomous driving technology advances, Lemonade’s state-by-state expansion of usage-based pricing that directly reflects real-world safety data represents a notable shift in how insurers evaluate risk.

Tesla owners in the five available states – Arizona, Oregon, Indiana, Colorado, and now Tennessee – can obtain quotes quickly through the Lemonade app or website, potentially lowering the overall cost of ownership for vehicles equipped with advanced driver-assistance systems. Further states are expected as regulatory approvals progress.

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Cybertruck

Tesla quietly made the Cybertruck even stronger

Published

12 hours ago

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August 3, 2026

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Credit: Tesla

Tesla has continued to flex the strength, rigidity, and robustness of its all-electric pickup, the Cybertruck. In fact, since 2019, Cybertruck’s ability to avoid dents, dings, and even gunfire has been one of the main selling points Tesla has used to attract buyers who are looking for a vehicle that can handle the most intense challenges.

But that does not mean Tesla is not still actively trying to make it even better.

In a new hardware update, Tesla has decided to change the material of the Cybertruck’s underbody panels from aluminum to carbon fiber, a move that aims to not only increase pricing efficiency but also improve strength.

RELATED:

Tesla Cybertruck is officially the safest pickup, IIHS says

Cybertruck Lead Engineer Wes Morrill confirmed the change was made to the Cybertruck recently after it was spotted by Coleton Guerin of Out of Spec. This particular trim level was a Cyberbeast, but it is being applied to all trims to keep supply chain efficiency high and have less variance across trim levels.

Morrill said that Tesla tested different materials for the underbody panel protection, and carbon fiber performed better than aluminum, which is what the company was using since its first deliveries in 2023.

Additionally, there are some efficiency improvements because Tesla can better form the areas around the bolts to keep underbody airflow cleaner than previously.

Carbon fiber is traditionally lighter and more durable than aluminum, which is why it is such a popular material among luxury automakers, and EV makers will utilize some of the materials around battery packs to save weight.

This is the first instance of Tesla utilizing carbon fiber on the Cybertruck’s exterior to help with overall performance and strength. As previously mentioned, Tesla used aluminum to protect the underside of the body, but it is pretty typical for the company to continue making engineering changes that will improve the car in the future.

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Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident

Published

1 day ago

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August 2, 2026

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Credit: Teslarati

Tesla released Full Self-Driving version 14.3.7 yesterday, and after about 90 miles of testing today, it is evident there are some definite fixes from version 14.3.6, which I wrote about last week and called a regression.

Within the first 40 minutes of my drive on v14.3.7, it saved me from getting into an accident with an unaware Dodge Charger driver, and some of the things Tesla seemed to miss in v14.3.6 were definitely improved. All in all, the release so far has some really great performance, and I’m looking forward to testing it further.

For now, here’s everything I noticed with v14.3.7:

Overall Improvement

Just generally speaking from a ride perspective, this was a really great experience. A lot of the hesitancy I experienced on v14.3.6 was gone. There were no instances of brake-stabbing, wheel-jerking, or any uncertain or unconfident movements. It was void of anything that I felt made it timid with v14.3.6.

The one thing I do hope to see down the road is a smaller need to adjust Speed Profiles so often. Because Tesla calls FSD “Supervised,” I’m okay with needing to hit the scroll wheel a few times a drive.

However, I hope that things can be incrementally improved upon with speed. Sometimes it’s too fast; other times it’s too slow. It’s a difficult thing to hone in and refine, but I hope it eventually gets there.

I didn’t notice any significant left lane camping or any behaviors that were completely out of line. I am hopeful that this opinion does not change, but after driving a few days with this version and putting it in a variety of different situations, you are exposed to more behaviors, some of which are not necessarily what I’d prefer.

The big things to notice, at least in my experience thus far, are that the major issues with previous versions — meaning the braking stabbing and wheel jerking — simply weren’t there. That’s enough to already consider this progress compared to .6.

Manual Signal Override is More Responsive

On .6, I had quite a few issues with FSD ignoring my manually input turn signals. If Tesla wants to call it “Supervised,” then the car should not ignore any input the driver gives. If I touch the accelerator on FSD, the car speeds up.

The car did a great job of obeying my turn signals when I wanted it to change lanes, which is welcome.

Parking Lot Performance

Before .6, I traditionally took over in nearly every parking lot my car entered, because I knew it would not park somewhere that I wanted, and usually, it was just a tad too timid in this setting.

The one bright spot of .6 was how well it handled parking lots. This continued with v14.3.7:

 

I’m always really happy to see progress at all, but once parking preferences come to FSD, as long as this performance is still around, that could potentially be the biggest improvement I’ve seen in FSD in the year I’ve been using it personally on a daily basis.

Full Self-Driving Averts Disaster

A Dodge Charger changed into my lane without checking if I was there, running me off the road. FSD made the initial avoidance maneuver; I grabbed the wheel out of instinct, looked in my side mirror to ensure I had nobody following closely behind, hit the brake, and straightened the car back up to avoid a curb:

There have been quite a few responses to this video stating that I should never have grabbed the wheel. To be honest, I really wish I had not done so, because I do believe FSD would have avoided any sort of collision with anything, including the car or the curb.

However, this was the first time I had ever been this close to being hit while using FSD. My natural reaction was to take over. I think if I had had something like this happen before, my reaction might have been different.

Hitting the brake avoided hitting the curb, while FSD swerved to avoid the car. My concern after the car was clear of my front end was the curb. All in all, I’m really happy with how things turned out, and I think anyone could be a critic of how I handled it. I only had a split second to really make a decision, and thankfully, any damage was avoided.

It is clear FSD managed to avoid the car coming down before I was able to. I truly credit FSD for avoiding the collision.

What Needs to Improve

Better Recognition of Potholes, Uneven Roads, Sharp Changes in Roadway/Bumps

On Friday, my Fianceè and I were in the car, and FSD was driving us. We crossed over a roadway that has a traffic light, and FSD was traveling at 40 MPH on Standard, 5 MPH over the speed limit. Everything was more than reasonable.

However, the road we were crossing at the light has a major bump both as you start and finish crossing it. Without a speed reduction, your car can go airborne. The Tesla did just this on Friday on v14.3.6; it was an uncomfortable bounce that pretty much confirmed I would not ever let FSD go over again unless we were sitting at that intersection when there is a red light.

I even tried scrolling down into Sloth quickly, but I ended up just taking over:

A few people have said it remains related to the vision-based approach and its difficulty comprehending 3D. This is a huge issue because this can cause serious damage at certain speeds.

Navigation

Nothing new here. I still turn off “Online Routing” quite frequently to get the car to take logical routes from time to time.

Auto Wipers

Auto Wipers are just plain bad. I really hope Tesla just uses a rain sensor. I thought they had improved at one point, but I still get dry wipes, Speed 4 on a drizzle, and Speed 2 on a steady rain. In reality, these should be switched.

You can watch our full review of Tesla Full Self-Driving v14.3.7 below:

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