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Tesla FSD Beta 10.11 release notes tease critical improvements

Credit: @evamcmillan333/Twitter)

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The release notes for Tesla’s Full Self-Driving Beta v10.11 hint at a number of critical improvements for the advanced driver-assist software. Tesla FSD Beta 10.11 is rolling out to Tesla employees for the time being. However, if the system performs well, external users should receive the update within the coming days. 

There are several notable improvements outlined in FSD Beta v10.11’s release notes. Tesla stated that V10.11 utilizes more accurate predictions of where other vehicles are turning or merging, reducing unnecessary slowdowns. The company also stated that V10.11 should improve vehicles’ right-of-way understanding, which should be invaluable in scenarios when maps turn out to be inaccurate.

More importantly, FSD Beta V10.11 featured specific improvements for vulnerable road users (VRU). Tesla notes that the most recent version of FSD Beta should improve VRU detection by 44.9%, allowing the system to dramatically reduce “spurious false positive pedestrians and bicycles.” The company was able to accomplish these VRU improvements by increasing the size of its next-generation labelers. 

Following are FSD Beta v10.11’s release notes

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Early Access Program | FSD Beta 10.11 

– Upgraded modeling of lane geometry from dense rasters (“bag of points”) to an autoregressive decoder that directly predicts and connects “vector space” lanes point by point using a transformer neural network. This enables us to predict crossing lanes, allows computationally cheaper and less error-prone post-processing, and paves the way for predicting many other signals and their relationships jointly and end-to-end. 

– Use more accurate predictions of where vehicles are turning or merging to reduce unnecessary slowdowns for vehicles that will not cross our path. 

– Improved right-of-way understanding if the map is inaccurate or the car cannot follow the navigation. In particular, modeling intersection extents is now entirely based on network predictions and no longer uses map-based heuristics. 

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– Improved the precision of VRU detections by 44.9%, dramatically reducing spurious false positive pedestrians and bicycles (especially around tar seams, skid marks, and rain drops). This was accomplished by increasing the data size of the next-gen auto-labeler, training network parameters that were previously frozen, and modifying the network loss functions. We find that this decreases the incidence of VRU-related false slowdowns. 

– Reduced the predicted velocity error of very close-by motorcycles, scooters, wheelchairs, and pedestrians by 63.6%. To do this, we introduced a new dataset of simulated adversarial high-speed VRU interactions. This update improves autopilot control around fast-moving and cutting-in VRUs. 

– Improved creeping profile with higher jerk when creeping starts. 

– Improved control for nearby obstacles by predicting continuous distance to static geometry with the general static obstacle network. 

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– Reduced vehicle “parked” attribute error rate by 17%, achieved by increasing the dataset size by 14%. 

– Improved clear-to-go scenario velocity error by 5% and highway scenario velocity error by 10%, achieved by tuning loss function targeted at improving performance in difficult scenarios. 

– Improved detection and control for open car doors. 

– Improved smoothness through turns by using an optimization-based approach to decide which road lines are irrelevant for control given lateral and longitudinal acceleration and jerk limits as well as vehicle kinematics. 

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– Improved stability of the FSD Ul visualizations by optimizing the ethernet data transfer pipeline by 15%.

Tesla FSD Beta v10.11 will likely be released as software version number 2022.4.5.15, as per reports from the online electric vehicle community. Tests of v10.11’s performance in real-world roads are typically shared by members of the company’s FSD Beta program within hours of the system’s wide release. 

The Teslarati team would appreciate hearing from you. If you have any tips, reach out to 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 announces crazy new Full Self-Driving milestone

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

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Credit: Tesla

Tesla has announced a crazy new Full Self-Driving milestone, as it has officially confirmed drivers have surpassed over 8 billion miles traveled using the Full Self-Driving (Supervised) suite for semi-autonomous travel.

The FSD (Supervised) suite is one of the most robust on the market, and is among the safest from a data perspective available to the public.

On Wednesday, Tesla confirmed in a post on X that it has officially surpassed the 8 billion-mile mark, just a few months after reaching 7 billion cumulative miles, which was announced on December 27, 2025.

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

The milestone itself is significant, especially considering Tesla has continued to gain valuable data from every mile traveled. However, the pace at which it is gathering these miles is getting faster.

Secondly, in January, Musk said the company would need “roughly 10 billion miles of training data” to achieve safe and unsupervised self-driving. “Reality has a super long tail of complexity,” Musk said.

Training data primarily means the fleet’s accumulated real-world miles that Tesla uses to train and improve its end-to-end AI models. This data captures the “long tail” — extremely rare, complex, or unpredictable situations that simulations alone cannot fully replicate at scale.

This is not the same as the total miles driven on Full Self-Driving, which is the 8 billion miles milestone that is being celebrated here.

The FSD-supervised miles contribute heavily to the training data, but the 10 billion figure is an estimate of the cumulative real-world exposure needed overall to push the system to human-level reliability.

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Tesla Cybercab production begins: The end of car ownership as we know it?

While this could unlock unprecedented mobility abundance — cheaper rides, reduced congestion, freed-up urban space, and massive environmental gains — it risks massive job displacement in ride-hailing, taxi services, and related sectors, forcing society to confront whether the benefits of AI-driven autonomy will outweigh the human costs.

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Credit: Tesla | X

The first Tesla Cybercab rolled off of production lines at Gigafactory Texas yesterday, and it is more than just a simple manufacturing milestone for the company — it’s the opening salvo in a profound economic transformation.

Priced at under $30,000 with volume production slated for April, the steering-wheel-free, pedal-less Robotaxi-geared vehicle promises to make personal car ownership optional for many, slashing transportation costs to as little as $0.20 per mile through shared fleets and high utilization.

While this could unlock unprecedented mobility abundance — cheaper rides, reduced congestion, freed-up urban space, and massive environmental gains — it risks massive job displacement in ride-hailing, taxi services, and related sectors, forcing society to confront whether the benefits of AI-driven autonomy will outweigh the human costs.

Let’s examine the positives and negatives of what the Cybercab could mean for passenger transportation and vehicle ownership as we know it.

The Promise – A Radical Shift in Transportation Economics

Tesla has geared every portion of the Cybercab to be cheaper and more efficient. Even its design — a compact, two-seater, optimized for fleets and ride-sharing, the development of inductive charging, around 300 miles of range on a small battery, half the parts of the Model 3, and revolutionary “unboxed” manufacturing — is all geared toward rapid production.

Operating at a fraction of what today’s rideshare prices are, the Cybercab enables on-demand autonomy for a variety of people in a variety of situations.

Tesla ups Robotaxi fare price to another comical figure with service area expansion

It could also be the way people escape expensive and risky car ownership. Buying a vehicle requires expensive monthly commitments, including insurance and a payment if financed. It also immediately depreciates.

However, Cybercab could unlock potential profitability for owning a car by adding it to the Robotaxi network, enabling passive income. Cities could have parking lots repurposed into parks or housing, and emissions would drop as shared electric vehicles would outnumber gas cars (in time).

The first step of Tesla’s massive production efforts for the Cybercab could lead to millions of units annually, turning transportation into a utility like electricity — always available, cheap, and safe.

The Dark Side – Job Losses and Industry Upheaval

With Robotaxi and Cybercab, they present the same negatives as broadening AI — there’s a direct threat to the economy.

Uber, Lyft, and traditional taxis will rely on human drivers. Robotaxi will eliminate that labor cost, potentially displacing millions of jobs globally. In the U.S. alone, ride-hailing accounts for billions of miles of travel each year.

There are also potential ripple effects, as suppliers, mechanics, insurance adjusters, and even public transit could see reduced demand as shared autonomy grows. Past automation waves show job creation lags behind destruction, especially for lower-skilled workers.

Gig workers, like those who are seeking flexible income, face the brunt of this. Displaced drivers may struggle to retrain amid broader AI job shifts, as 2025 estimates bring between 50,000 and 300,000 layoffs tied to artificial intelligence.

It could also bring major changes to the overall competitive landscape. While Waymo and Uber have partnered, Tesla’s scale and lower costs could trigger a price war, squeezing incumbents and accelerating consolidation.

Balancing Act – Who Wins and Who Loses

There are two sides to this story, as there are with every other one.

The winners are consumers, Tesla investors, cities, and the environment. Consumers will see lower costs and safer mobility, while potentially alleviating themselves of awkward small talk in ride-sharing applications, a bigger complaint than one might think.

Elon Musk confirms Tesla Cybercab pricing and consumer release date

Tesla investors will be obvious winners, as the launch of self-driving rideshare programs on the company’s behalf will likely swell the company’s valuation and increase its share price.

Cities will have less traffic and parking needs, giving more room for housing or retail needs. Meanwhile, the environment will benefit from fewer tailpipes and more efficient fleets.

A Call for Thoughtful Transition

The Cybercab’s production debut forces us to weigh innovation against equity.

If Tesla delivers on its timeline and autonomy proves reliable, it could herald an era of abundant, affordable mobility that redefines urban life. But without proactive policies — retraining, safety nets, phased deployment — this revolution risks widening inequality and leaving millions behind.

The real question isn’t whether the Cybercab will disrupt — it’s already starting — it’s whether society is prepared for the economic earthquake it unleashes.

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Tesla Model 3 wins Edmunds’ Best EV of 2026 award

The publication rated the Model 3 at an 8.1 out of 10, and with its most recent upgrades and changes, Edmunds says, “This is the best Model 3 yet.”

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Credit: Tesla

The Tesla Model 3 has won Edmunds‘ Top Rated Electric Car of 2026 award, beating out several other highly-rated and exceptional EV offerings from various manufacturers.

This is the second consecutive year the Model 3 beat out other cars like the Model Y, Audi A6 Sportback E-tron, and the BMW i5.

The car, which is Tesla’s second-best-selling vehicle behind the popular Model Y crossover, has been in the company’s lineup for nearly a decade. It offers essentially everything consumers could want from an EV, including range, a quality interior, performance, and Tesla’s Full Self-Driving suite, which is one of the best in the world.

The publication rated the Model 3 at an 8.1 out of 10, and with its most recent upgrades and changes, Edmunds says, “This is the best Model 3 yet.”

In its Top Rated EVs piece on its website, it said about the Model 3:

“The Tesla Model 3 might be the best value electric car you can buy, combining an Edmunds Rating of 8.1 out of 10, a starting price of $43,880, and an Edmunds-tested range of 338 miles. This is the best Model 3 yet. It is impressively well-rounded thanks to improved build quality, ride comfort, and a compelling combination of efficiency, performance, and value.”

Additionally, Jonathan Elfalan, Edmunds’ Director of Vehicle Testing, said:

“The Model 3 offers just about the perfect combination of everything — speed, range, comfort, space, tech, accessibility, and convenience. It’s a no-brainer if you want a sensible EV.”

The Model 3 is the perfect balance of performance and practicality. With the numerous advantages that an EV offers, the Model 3 also comes in at an affordable $36,990 for its Rear-Wheel Drive trim level.

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