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Tesla FSD Beta 10.13’s improvements to be (especially) evident for non-CA users

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Elon Musk recently provided some updates on the wide rollout of FSD Beta 10.13. The latest iteration of the company’s advanced driver-assist system began its initial release earlier this month, but its wide release has not been initiated yet.

In a recent post on Twitter, Elon Musk admitted that while Tesla is working extremely hard on FSD Beta 10.13, the system itself is not ready for wide release just yet. He estimated that FSD Beta 10.13’s wide release would likely be a week or so away, but when it does, drivers outside California will experience some very notable improvements. 

As noted by the Tesla CEO, users “outside of California will notice improvements the most.” This is an interesting comment, especially considering that Musk has admitted in the past that FSD Beta “seems to work better in California” than in other areas such as Rhode Island. Musk admitted to this last year, noting that FSD Beta has been overfitted to the Bay Area

As noted in a Benzinga report, overfitting in statistics suggests that a model relates to a specific set of data points far too closely, which may not translate well with different data points. In the case of FSD Beta, this could result in the advanced driver assist system working very well in areas like San Francisco but not as well in other areas of the United States. 

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Release notes of FSD Beta 10.13 leaked earlier this month have revealed that the update includes a number of key performance improvements. 

Following are the partial release notes of FSD Beta 10.13 that have been shared thus far: 

  • Improved decision making for unprotected left turns using better estimation of ego’s interaction with other objects through the maneuver. 
  • Improved stopping pose while yielding for crossing objects at “Chuck Cook style” unprotected left turns by utilizing the median safety regions. 
  • Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects. 
  • Enabled creeping for visibility at any intersection where objects might cross ego’s path, regardless of presence of traffic controls. 
  • Improved lane position error by 5% and lane recall by 12%…
  • Improved lane position error of crossing and merging lanes by 22% by adding long-range skip connections and a more powerful trunk to the network architecture. 
  • Improved pedestrian and bicyclist velocity error by 17%, especially when ego is making a turn, by improving the onboard trajectory estimation used as input to the neural network. 
  • Improved animal detection recall by 34% and decreased false positives by 8% by doubling the size of the auto-labeled training set. 
  • Improved detection recall of far away crossing vehicles by 4% by tuning the loss function used during training and improving label quality.
  • Improved the “is parked” attribute for vehicles by 5% by adding 20% more examples to the training set. 
  • Upgraded the occupancy network to detect dynamic objects and improved performance by adding a video module, tuning the loss function, and adding 37k new clips to the training set. 
  • Reduced false slowdowns around crosswalks by better classification of pedestrians and bicyclists as not intending to interact with ego. 
  • Reduced false lane changes for cones or blockages by preferring gentle offsetting in-lane where appropriate. 
  • Improved in-lane positioning on wide residential roads. 
  • Improved object future path prediction in scenarios with high yaw rate. 
  • Improved speed limit sign accuracy on digital speed limits by 29%, on signs with difficult relevance by 23%, on 3-digit speeds by 39%, and on speed limit end signs by 62%. Neural network was trained with 84% more examples in the training set and with architectural changes which allocated more compute in the network head. 

Don’t hesitate to contact us with news tips. Just send a message to simon@teslarati.com to give us a heads up.

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla faces Full Self-Driving pushback in EU over ‘speeding’

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Credit: Tesla

A new report from Reuters claims that a transport authority in Sweden is pushing back against the approval of Tesla’s Full Self-Driving suite because it will travel over speed limits.

The report says the Swedish Transport Administration (TRV) recommends the European Union votes against FSD’s approval. TRV believes it should not be approved until Tesla disables FSD’s ability to speed.

TRV sent a letter to the European Union’s Technical Committee on Motor Vehicles (TCMV), which is set to meet on June 30 to discuss the potential approval of the Tesla FSD suite in the country. Tesla, which has received various approvals in Europe over the past two months, has not provided a comment.

Tesla Full Self-Driving gets first-ever European approval

Teslas operating on FSD do travel over the speed limit, depending on the Speed Profile that is chosen. Drivers have the ability to disengage FSD at any point; Tesla specifically states that those supervising the suite are responsible for its actions.

Let’s cut to the chase: humans operating any vehicle speed almost daily in the United States. Realistically, speed limits in the U.S. are more frequently treated as speed minimums. However, other countries are different, and driving behaviors are less aggressive.

TRV believes that “allowing automated systems to systematically exceed legal speed limits…risks undermining both the legal framework and the expected safety benefits of ​vehicle automation,” the report stated. It’s surprising that Tesla has not received this claim from other countries previously.

This could be a good argument to bring Max Speed back, the setting that previously allowed the driver to choose the absolute fastest the car would travel.

This would still put the responsibility of supervision in the hands of the driver. It would allow the driver to choose whether the car would travel over the speed limit or not, acknowledging that they set the speed, and if they get pulled over, there would be no ability to argue it.

However, it does not seem as if this is something Tesla will do, especially considering many U.S. drivers have requested the feature in an effort to eliminate speeding or at least tone it down. The company has not shown any interest in bringing it back.

Tesla has approvals for FSD in Europe in Estonia, Lithuania, Denmark, the Netherlands, and Belgium.

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Tesla teases greater Grok FSD integration and ‘Banish’ feature ‘in about 3 months’

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Credit: Tesla

Tesla is going to let you guide Full Self-Driving with Grok in 3 months, CEO Elon Musk confirmed on X.

The response from Musk, which revealed Tesla plans to allow drivers to effectively control the car and its navigation more explicitly using Grok, puts the feature for about September.

A Tesla owner said that Full Self-Driving is great, but owners should be able to “converse with Grok like we can with an Uber driver.” She then used examples like, “Grok, turn right here,” and “Drop us off right here, we’ll walk due to traffic,” and finally,” Drop at entrance first, then park far away.”

Coincidentally, the final piece of dialogue would also mean features like Banish are potentially on the way soon.

Banish is also referred to as “Reverse Summon,” and would enable the car to self-park while dropping occupants off at their destination.

This would be a great way to improve the overall experience while supervising FSD. Navigation is already a major painpoint that many owners complain about. Manual overrides when a maneuver is requested or canceled (like using the turn signal stalk to override a navigation route), do not always work.

The feature could be especially useful in street parking scenarios in a city, where spots are sometimes tough to come by. Many of us who grab dinner in a more populated area will park a street or two over from wherever we’re going, because sometimes you know that’s the best you will get. If a driver using FSD could say, “Hey Grok, turn right here on Queen St. and park in that open spot on the right,” it could save a lot of confusion FSD might have on its own.

Musk teased that a similar feature was “coming” back in February:

Tesla Full Self-Driving set to get an awesome new feature, Elon Musk says

It is certainly surprising that Tesla is doing it at this point. The company’s more recent moves have been more evident of taking control and inputs away from humans and putting them in the AI’s hands more frequently. The biggest example of this was taking away Max Speed in AI4 cars, giving us Speed Profiles, and not having any input on the fastest speed the car will travel.

Of course, giving navigation preferences to Grok is availble already in Teslas, but not at the drop of a hat. Instead, you can suggest a certain route at the beginning of your drive.

Here’s an example of that from December:

Finally, the original post that Musk responded to mentioned a parking preference after dropping off the occupants, which describes the Banish feature that Tesla has teased for years.

We’re not sure if Musk was responding more to the ability to guide the car with Grok, or whether he also was including Banish in the three-month prediction timeframe.

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Tesla Cybercab has one important piece that AI4 cars might need for FSD

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Credit: @tpgoebel | X

A close-up image of a Cybercab engineering vehicle in Peabody, Massachusetts, reveals a compact triangular side repeater camera housing equipped with an integrated washer mechanism.

This seemingly small hardware addition could prove to be one of the most critical components for achieving reliable, unsupervised Full Self-Driving (FSD) — not just for the dedicated Robotaxi but potentially for existing AI4-equipped vehicles as well.

The washer system’s importance cannot be overstated in Tesla’s vision-only autonomy approach. Cameras are the sole sensory input for the neural networks powering FSD, constantly interpreting the environment for safe navigation. In real-world conditions, however, lenses quickly accumulate rain, snow, mud, dust, or road spray.

Many of us Tesla owners, especially those who deal with any sort of winter weather at all, know the all-too-common alert that pops up when cameras are obstructed:

Even brief obstructions can drop perception confidence, trigger safety disengagements, or force the vehicle to pull over, although these are relatively rare. Instead, most of the time, the camera will need a wipe from the owner next time they stop the car.

But unlike human drivers who can manually clear their view, a Robotaxi operating 24/7 without a steering wheel or mirrors must maintain pristine vision autonomously. The Cybercab’s side repeater washer delivers targeted cleaning bursts precisely where needed for merging, lane changes, and blind-spot monitoring — functions that demand uninterrupted visibility from the external cameras:

This hardware directly tackles a known pain point in current FSD deployments. Owners frequently report camera-related alerts during inclement weather, which is understandable, but needs to be solved for a true autonomous experience.

For a production Robotaxi fleet aiming for high utilization and minimal downtime, robust washer systems represent a foundational reliability upgrade; essentially, they’re a must-have. Early sightings suggest the design may extend to rear cameras as well, creating a comprehensive cleaning architecture that keeps the entire vision suite operational in harsh environments.

Without it, even the most advanced neural nets struggle when their “eyes” are compromised.

What Does This Mean for AI4 Cars?

This Cybercab detail raises timely questions for AI4 cars already on the road. While Hardware 4 delivers superior compute and camera resolution compared to earlier versions, production models typically lack dedicated side and rear washers. Tesla has included them on Model Y robotaxis that it is using in the fleet:

Tesla Robotaxi has a highly-requested hardware feature not available on typical Model Ys

As Tesla refines unsupervised FSD for broader release, the gap in environmental resilience becomes evident. Software improvements can help mitigate issues, but they cannot fully replace physical cleaning in heavy rain or muddy conditions. Analysts and owners increasingly speculate that AI4 vehicles may eventually require similar washer retrofits — or a future AI4.5 variant — to match the Cybercab’s all-weather readiness and support the same level of autonomy.

As testing progresses, the Cybercab’s washer mechanism highlights Tesla’s pragmatic focus on real-world robustness. It may well become the hardware piece that determines how quickly and reliably FSD scales from prototypes to everyday vehicles.

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