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Elon Musk says next FSD version to let drivers wear sunglasses

Image Credit: Dirty Tesla/YouTube

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Tesla’s next version of Full Self-Driving (FSD) has been widely discussed in recent weeks, and a new update from CEO Elon Musk over the weekend highlights the fact that it won’t prevent drivers from wearing sunglasses anymore.

The FSD Supervised system uses a driver monitoring feature that makes sure drivers remain attentive and awake, though the system won’t allow the driver to wear sunglasses with the system engaged without nags. In response to one X user complaining about not being able to wear sunglasses while using FSD on Saturday, Musk wrote that the issue would be fixed in v12.5, to which many users in the thread expressed appreciation.

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Tesla FSD v12.4.1 with no nag starts rolling out to select customers

It’s still not clear exactly when Tesla plans to start deploying FSD Supervised v12.5.

Musk originally said that FSD v12.5 would be out in late June, and many are especially waiting for the update as it’s expected to finally bring FSD Supervised to the Cybertruck. Despite missing the late June target for the release, Musk has highlighted a handful of the other improvements in the version, as well as noting on Thursday that the release was in fact ready to hit the Cybertruck upon its deployment.

He also said this month that FSD Supervised v12.5 will finally merge the city and highway software stacks, as was previously done with v11, though it was apparently rolled back at some point with the arrival of v12.

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Tesla started rolling out FSD Supervised v12.4.3 to some customers earlier this month, after previous versions had been delayed due to an extremely low level of interventions—and after the company essentially halted the rollout of v12.4.2.

Musk highlighted the issue of low interventions earlier this month.

He also detailed the problem during Tesla’s Annual Shareholder Meeting last month, explaining that the fewer interventions there are, the more difficult it becomes to test versions and point versions against each other to see which ones are performing best.

“And then, like I was saying earlier, it actually gets, as the system gets better, it gets harder to figure out which AI model is better, because now you know, like, ‘Okay, it’s thousands of miles between interventions.’

“How do we, as quickly as possible, figure out which AI model is better. And when you make these different AI models, they’re obviously not like super deterministic, so we have a new model that eliminates one problem but creates another problem. So we’re trying to solve this by a combination of simulation, uploading models, having them run in Shadow Mode.

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“It’s actually kind of helpful that not everyone has Full Self-Driving, because we can see, we can run it in Shadow Mode and see, ‘What would this new model have done compared to what the user did?’

“So since we’ve got, you know, millions of cars that we can do this with, that gives us a delta between what the AI model predicted would do and the user would do. And if you kind of sum up the errors between them, you can see ‘Oh, there was a bigger error stack from this model versus that model,’ when you uploaded them into, each uploaded them into 100,000 cars.

“But that’s the biggest limiter right now. It’s not training, it’s not data, it’s actually testing the AI models. And then figuring out clever ways to figure out if a new model is better or not. Like there were sort of particular intersections that are difficult.”

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What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

Zach is a renewable energy reporter who has been covering electric vehicles since 2020. He grew up in Fremont, California, and he currently lives in Colorado. His work has appeared in the Chicago Tribune, KRON4 San Francisco, FOX31 Denver, InsideEVs, CleanTechnica, and many other publications. When he isn't covering Tesla or other EV companies, you can find him writing and performing music, drinking a good cup of coffee, or hanging out with his cats, Banks and Freddie. Reach out at zach@teslarati.com, find him on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

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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.

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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.

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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).

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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.

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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.

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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.

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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:

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“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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