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Tesla FSD Beta 10.13’s improvements to be (especially) evident for non-CA users
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.
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.
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News
Tesla Robotaxi will be a 24/7 service: here’s when
Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.
The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.
next month or so. the next tech to merge on the v15 plan will enable it.
— Ashok Elluswamy (@aelluswamy) September 4, 2026
That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.
Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.
Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.
By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.
Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.
Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.
If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.
That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.
News
Tesla Full Self-Driving will now overtake manual driving to avoid disaster
Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.
Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.
FSD Supervised v14.3.9 starting to roll out shortly
This release includes a new active safety feature set: FSD Supervised can now activate on your behalf when an imminent collision is detected and Automatic Emergency Braking (AEB) may not be enough.
It may also engage if we…
— Tesla AI (@Tesla_AI) September 4, 2026
The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.
The intervention is meant as a last-resort safety net, not a replacement for attentive driving.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.
After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.
The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.
Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.
The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.
If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.
News
Tesla Cybercab launch catches NHTSA’s attention who wants to know more
Tesla launched the all-electric, steering wheel-less, and pedal-less Cybercab last night at a quiet and small event in downtown Austin, Texas.
The launch, which marked the beginning of unsupervised ride-hailing for Tesla’s Robotaxi platform with Cybercab, has already caught the attention of the National Highway Traffic Safety Administration (NHTSA) who has more questions.
NHTSA opened an Audit Query (AQ) into the Cybercab’s Federal Motor Vehicle Safety Standards (FMVSS) certification that Tesla gave the vehicle. Manufacturers self-certify vehicles much of the time to avoid excessive regulatory delays.

Tesla Cybercab interior, note the lack of steering wheel and pedals. (Credit: @niccruzpatane/X< /a>)
However, the agency needs more information; it said in a summary:
“On September 3, 2026, Tesla began commercial deployment with a small number of its Cybercab vehicles in Austin, Texas. Tesla notified the Agency that it certified those Cybercab vehicles as compliant with all applicable Federal Motor Vehicle Safety Standards (FMVSS). Tesla also notified the Agency that it plans to gradually expand commercial deployment of the Cybercab to include additional vehicles and locations.”
It also went on to state that the Cybercab lacks traditional automotive controls, which is a groundbreaking move. The process is entirely new to the NHTSA, which gives the agency some leverage to put Tesla’s launch under a microscope:
“The vehicles lack permanently attached, conventional manual controls, such as a brake pedal, gas pedal, steering wheel, and mirrors. NHTSA is opening this AQ to examine the process and technical data on which Tesla relied when certifying the Cybercab and related issues. Among other things, NHTSA will consider the extent to which Tesla’s certification depended on determinations that certain FMVSS are inapplicable to the Cybercab.”
Tesla has added 45 Cybercab units to its fleet of Robotaxi-enabled cars in Austin, according to public documents the company submitted to the State of Texas over the past week. Enabling this level of self-driving is something Tesla has worked toward for many years, and now that it is finally here, it seems more than reasonable that regulatory agencies will have some questions.
Many outlets might try to frame this as a negative, but it is truly an agency looking to gain more information about groundbreaking tech that Tesla has been developing for years.
In an effort to keep riders, pedestrians, and property safe, any and all data accumulated from these first days, weeks, and months of rides will likely be shared with the NHTSA to enable broader rollout strategies across the United States and more in the future.