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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.

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

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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.

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.

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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.’

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“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.

“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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Tesla offers owners $1,000 off to upgrade from EAP to FSD in new car

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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SpaceX wants to catch Starship for launch 14, Elon Musk says

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Credit: SpaceX

Just hours after Starship Flight 13 achieved a successful soft splashdown of its upper stage in the Indian Ocean on July 24, Elon Musk announced an ambitious next step for the company’s next launch of the rocket.

“Unless we discover problems after mission data review, SpaceX will attempt to catch the ship with the tower on [the] next flight,” the SpaceX CEO posted on X on Friday.

That “next flight” is expected to be Flight 14. The plan involves returning the Starship upper stage, commonly called the “ship,” to the Starbase launch tower in Texas and catching it mid-air using the same mechanical “chopsticks” arms that have already proven themselves with the Super Heavy booster.

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A successful catch would mark the first time an orbital-class upper stage has been recovered this way, advancing SpaceX’s goal of full and rapid reusability for the entire vehicle.

SpaceX has already demonstrated the tower-catch technique multiple times with Super Heavy. The first successful catch came on Flight 5 in October 2024, when Booster 12 was plucked from the sky by the Mechazilla arms. Subsequent flights, including those involving Boosters 14 and 15, repeated the feat. Several of those recovered boosters were later inspected, refurbished, and flown again, proving the system’s viability for quick turnaround.

Traditional reusable rockets, such as SpaceX’s own Falcon 9 or Blue Origin’s New Shepard, land on legs either on land or droneships. Rocket Lab has recovered its small Electron first stages by helicopter, but those are far lighter vehicles.

SpaceX Starship just nailed something it’s never done before

The China Academy of Launch Vehicle Technology (CALT), a subsidiary of the China Aerospace Science and Technology Corp. (CASC), completed a catch of its booster on July 10. They are the only entity besides SpaceX to attempt and complete the feat.

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Flight 13 provided encouraging data. The ship executed a controlled reentry, flipped, and soft-landed intact in the ocean after deploying Starlink satellites, offering the first clear post-splashdown views of an undamaged heat shield. The Super Heavy booster, meanwhile, experienced a harder splashdown in the Gulf of Mexico.

Musk has previously stressed that ship catches would only follow multiple successful soft ocean landings to minimize risk of debris over land.

If Flight 14 succeeds, SpaceX would take a major stride toward routine, rapid reuse of both stages—critical for lowering launch costs and supporting ambitious plans for lunar and Mars missions. For now, teams are reviewing the Flight 13 data. Should everything check out, the next Starship flight could deliver one of the most spectacular recoveries in aerospace history.

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Tesla to open source Model S and Model X designs and software

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Credit: Tesla

In a move echoing its earlier commitment to open innovation, Tesla CEO Elon Musk announced recently that the company plans to make the design and software of its Model S and Model X fully open source.

This follows the same approach Tesla took with its original Roadster, releasing all available design, engineering, and diagnostic materials in November 2023 so that “whatever we have, you now have.”

The Model S, introduced in 2012, was Tesla’s first mass-produced vehicle and a groundbreaking luxury electric sedan. It offered impressive range, rapid acceleration, and over-the-air software updates that redefined expectations for electric cars.

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The Model X, launched in 2015, built on that foundation as a high-performance electric SUV notable for its distinctive falcon-wing doors, spacious interior, and advanced safety features. Both models served as flagships that helped establish Tesla as a leader in the EV industry and popularized long-range battery-electric vehicles.

Production of the Model S and Model X was wound down earlier in 2026, with manufacturing ending in the second quarter. Tesla redirected the Fremont factory space previously used for these vehicles toward higher-priority projects, including Optimus humanoid robots and the Cybercab autonomous vehicle.

By the time of Musk’s open-source announcement, custom orders had closed and only remaining inventory was available.

Open-sourcing the designs and software offers several clear advantages. Owners of these aging but still capable vehicles gain better access to technical documentation, diagnostic tools, and software resources, making independent repairs and modifications easier and more affordable.

Independent repair shops and third-party specialists can support the large existing fleet without relying solely on Tesla’s service network. Enthusiasts and engineers can study real-world implementations of Tesla’s battery, powertrain, and software systems, potentially accelerating broader industry progress in electric mobility.

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The step aligns with Tesla’s 2014 patent pledge and its overall mission to advance sustainable transport by sharing hard-won knowledge rather than locking it behind proprietary walls.

By releasing these materials now that the models have left production, Tesla ensures continued support for its early adopters while freeing internal resources for future technologies. The open-source release of the original Roadster already enabled simulations, community projects, and deeper technical understanding.

Extending that practice to the Model S and Model X should deliver similar benefits on a larger scale, helping keep these influential vehicles relevant and repairable for years to come

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Tesla flexes incredible Robotaxi metric that skeptics will hate

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Credit: Tesla

Tesla flexed one incredible Robotaxi metric during the Q2 Earnings Call that skeptics have to hate to hear. The company’s platform has already driven more than 380,000 miles of unsupervised ride-hailing across several states with no notable incidents.

During the company’s Q2 Earnings Call on Wednesday, Vice President of AI, Ashok Elluswamy, said:

“First of all, I’d like to state that the Robotaxi program has been operating extremely well. Especially in terms of safety, the program has had an impeccable safety record. We have driven more than 380,000 miles of unsupervised Robotaxi, now across six cities in two different states. We have had zero notable incidents. Any reports have been of other actors impacting us when we were stationary. I like to emphasize how safe the operation has been so far. Zero notable incidents over 380,000 miles.”

Elluswamy’s claim over Robotaxi miles is a significant milestone for Tesla in the grand scheme, especially considering this is a sizeable number of miles without any incident.

Tesla’s self-driving approach is much different than that of other companies. Tesla has maintained that vision is the only thing needed to have a solid and effective self-driving suite. Many self-driving companies utilize things like LiDAR, sensors, and other elements to improve performance, but Elluswamy sent a jab at those who believe it’s needed.

“Historically, the so-called experts have always claimed that you need LiDARs, radars, HD maps, and the entire kitchen sink to drive safely. Here we show that such is not true. You can have safe, comfortable, and affordable autonomy with just cameras. This record should be a huge validation of Tesla’s entire AI approach.”

The feat of accumulating this many miles without any driver behind the wheel is impressive. The thing is, Tesla is also doing this across several different locations, with varying traffic rules, pedestrian levels, weather patterns, and other important factors.

While Tesla is not ready to roll out an unsupervised platform completely, it is a slow but steady indication that the company is well on its way to figuring things out.

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The company’s attitude toward expansion is slow, safe, and controlled, and despite this huge milestone, it will still be some time until we see Tesla truly unleash unsupervised rides more aggressively.

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