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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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Elon Musk dismissed reports claiming SpaceX had placed a massive order for NVIDIA GPUs worth $52 billion. The denial came hours after Taiwanese media, citing unnamed industry sources, reported that SpaceX planned to acquire approximately 13,000 AI server racks, equating to roughly 1 million GB300 GPUs, from Foxconn.
Each rack was estimated at around $4 million, with deliveries potentially starting in late 2025.
The story suggested this would mark SpaceX’s first major foray into Foxconn-manufactured NVIDIA hardware, breaking from suppliers like Supermicro and Dell. Musk responded bluntly on X:
This is fake news
— Elon Musk (@elonmusk) July 20, 2026
Despite the denial, the rumored scale aligns with SpaceX’s explosive growth in AI infrastructure. NVIDIA’s GB300 (successor to the GB200 NVL) racks deliver unprecedented performance for large-scale training and inference. A $52 billion commitment would dwarf most corporate AI budgets and provide the compute muscle needed for frontier models.
SpaceX already operates gigawatt-scale terrestrial clusters like Colossus in Memphis, Tennessee, and has monetized them aggressively through leasing deals.
SpaceX’s newest Starmind will make earth data centers obsolete
Major customers include Anthropic (paying ~$1.25 billion monthly for 220,000+ GPUs), Google (~$920 million monthly for 110,000 GPUs), and Reflection AI. These arrangements are projected to generate tens of billions in annual revenue, far outpacing traditional SpaceX businesses.
Such an investment would fuel internal AI efforts, particularly Grok models under the integrated SpaceXAI division, while supporting ambitious orbital data center plans. SpaceX envisions launching thousands of AI-optimized satellites powered by solar energy and cooled in space, bypassing terrestrial power and land constraints.
This “Starmind” constellation could position the company as a leader in space-based computing.
SpaceX as an Emerging AI Powerhouse
Once primarily known for reusable rockets and Starlink satellite internet, SpaceX has transformed into a multifaceted AI player.
The 2026 acquisition of xAI integrated Grok development directly into the company. Starlink’s low-latency global network complements massive compute clusters, enabling efficient data flow for training and serving AI models.
Musk has long argued that AI scaling demands solutions beyond Earth, citing things like real estate and electricity limits on the ground.
While the Foxconn deal may not be in the cards, SpaceX’s trajectory is continuing on the path of blending aerospace engineering with hyperscale AI to dominate both launches and intelligence infrastructure.
Elon Musk shed more details on the upcoming improvements to Tesla’s Full Self-Driving suite, specifically one that the CEO mentioned last week, which should help owners see fewer interventions.
Last week, Musk hinted that one major improvement that Tesla planned to roll out to Full Self-Driving users was the car’s ability “to remember your specific interventions and match each person’s individual preferences.”
Elon Musk says your Tesla will start to learn your individual preferences
This small bit of detail was linked to a post from Tesla community member Whole Mars, who said that FSD’s tendency to exit the carpool lane, a feature that owners can turn on but at times the car will disregard.
It sounds like, based on Musk’s two responses since that original post, it is safe to say the things FSD will start to remember are wide-ranging. However, it seems the biggest differences will be noticed with parking performance, which Musk continues to mention.
Highway Lane Preferences
The initial post Musk mentioned, with these new remembered preferences soon to arrive for Tesla owners everywhere, was the Carpool/Express Lane.
Tesla has a setting in the FSD menu that lets drivers enable HOV Lane travel. However, the car won’t always stay in that suggested or preferred lane.
The car will start to remember your specific interventions and match each person’s individual preferences
— Elon Musk (@elonmusk) July 18, 2026
Some owners have also complained of left lane camping, an illegal maneuver in at least some states. Cruising in the passing lane has resulted in tickets for some, as it is illegal in over 30 states in the U.S.
Tesla did not confirm if these preferences would also be included in new FSD behaviors, but it would certainly help move the company toward fewer interventions.
Parking Preferences
This seems to be the real focus of the entire operation, as Musk stated several weeks ago that parking was overwhelmingly the most frequent reason for interventions.
The major issue with parking is not necessarily the parking “performance,” as FSD is generally good at parking. It definitely has its issues; we’ve recorded plenty of them, including this one as recent as last week:
Yeah it seems like FSD v14.3.5 is having some issues with parking early on https://t.co/Bw5ULfVmDq pic.twitter.com/RHdpjOEpIo
— TESLARATI (@Teslarati) July 13, 2026
However, the changes coming are more about preferences, meaning where you park and how your car enters the spot, either pulling in or backing in. Owners have also reported that pulling into the correct driveway is a relatively rare thing for FSD, something else that needs to be confronted.
Musk basically confirmed that all of these things would be part of Tesla’s plan to address driver preferences with FSD:
Yes
— Elon Musk (@elonmusk) July 20, 2026
It’s obvious there is something big coming with FSD, and the company’s focus seems to be eliminating any intervention that would be related to preferences. This is probably the biggest bottleneck between Tesla and being fully autonomous. Critical interventions do occur, but they are much less frequent.
The only time a driver should be taking over is because of a critical intervention; this seems to be the goal of Tesla right now.
This all seems to be a priority as Tesla continues to move closer to the prospect of unsupervised driving.
Elon Musk said today on X that Teslas will start to learn your individual preferences. This is something that he seemed to hint toward earlier this month when he said parking was by far the biggest reason drivers intervene with Full Self-Driving.
Musk made the comment in response to notable Tesla influencer Whole Mars, who said that his vehicle will sometimes disobey the settings he has enabled for his car. He responded to the post, stating that “The car will start to remember your specific interventions and match each person’s individual preferences.”
The car will start to remember your specific interventions and match each person’s individual preferences
— Elon Musk (@elonmusk) July 18, 2026
This is something that could be perhaps one of the biggest ways Tesla could minimize or even work closer toward eliminating interventions altogether. While FSD does a lot of things really well, many people intervene a vast majority of the time not due to major or critical safety errors.
Instead, many take over because the car is doing something that they do not like as a preference; it might park in a parking spot that is not preferred by the driver, it might linger too long in the left lane on the highway (a personal favorite), or it could even take a route that the driver does not like.
These all lead to interventions, but they are not triggered by a major safety issue. Instead, it’s just preference.
READ OUR REVIEW OF TESLA’S LATEST FSD VERSION:
Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance
If Teslas could start to learn the personal preferences of the person who owns them, interventions will truly begin to be less frequent. Some of this is already pretty evident, in my opinion. Teslas use a neural network to learn behaviors and accumulate data to improve performance.
For months now, we’ve tracked FSD’s performance at “Except Right Turn” stop signs, something that is very common in Pennsylvania, but many of our readers located in other parts of the U.S. have never heard of. FSD handles one Except Right Turn stop sign very well, one that I travel past frequently. Others that I do not navigate through as often do not have as confident a performance. It seems like the cars might already be doing this to an extent.
🚨 Tesla Full Self-Driving v14.3 proceeds through an Except Right Turn Stop Sign pic.twitter.com/YemRSlens7
— TESLARATI (@Teslarati) April 8, 2026
That example is also for something that is a street sign and not necessarily a driver preference; however, I still feel it is worth mentioning because it only handles that commonly passed Except Right Turn stop sign with true confidence. Others it still seems to struggle with.
This could be one of Tesla’s big moves toward full autonomy, and it could be a pathway to truly unsupervised driving. Every day, millions of cars on the road travel at a human driver’s personal preferences with no incident. Why can’t autonomous vehicles still cater to a passenger’s preferences while being autonomous? Tesla seems to have the idea that it would be possible.
Elon Musk dispels $52 billion SpaceX-NVIDIA GPU deal: ‘Fake news’
Elon Musk sheds details on Tesla FSD’s upcoming improvements
