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Tesla Full Self-Driving changes your perception of travel — long or short

Tesla Full Self-Driving will ruin controlling your vehicle manually.

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Credit: Tesla

Tesla does not tell you what Full Self-Driving will do to your perception of travel. Whether your next trip is a two-minute ride up the street to the grocery store or a 1,500-mile trip across multiple states, you’ll never look at driving the same way.

This past weekend, I was lucky enough to have a new Tesla Model Y for the weekend. Equipped with the company’s Hardware 4 computer, the latest software version, and all of the new Model Y’s improvements from the legacy iteration, I knew much of my weekend would be spent testing FSD, as I have never had an extended experience with it.

By the time the weekend was over and it was time to pick up my non-Tesla car, I realized I was not ready to let go. Having the car drive me around from location to location all weekend was something I truly enjoyed, but it was more than just a convenience thing. I felt impressed, relaxed, and even, in some instances, safer.

What Tesla Full Self-Driving Did Well

Now, before I truly begin, I do want to say that I don’t think I’ll ever feel safer than when I’m in ultimate control of the vehicle. However, a lot of things that give me stress during a drive were handled with relative ease by the car — and I was happy I didn’t have to deal with it.

One instance was merging onto a busy highway with a very short merge lane. Full Self-Driving took a no-holds-barred approach, taking the space it was given and grabbing a spot in the right lane quickly.

It was not willing to be passive, but it was also not willing to sacrifice safety. It will not wait for others to pull the trigger and go at intersections or four-way stops. If there are a few seconds of stagnation from the car and another driver in that instance, it will go, of course, proceeding safely.

It even did a handful of things I didn’t expect it to do. It would stay in the right lane if multiple on-ramps were approaching. I took it on a stretch of highway where three on-ramps are all within a mile of one another.

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It passed a tractor-trailer just before we made it to the first of those three on-ramps. It stayed in that left lane after overtaking the 18-wheeler, as Driver Visualization showed more cars approaching to merge. It was one of those moments that, even though I have written about this topic for several years, was unbelievably impressive.

It not only drives people safely, but it is also considerate of other drivers, which is very impressive.

I was incredibly surprised to see my Fiancè have so much ease when it was operating.

I figured, just because she is not as familiar with what Tesla does to make FSD better and how it works, that she would be very on edge during our rides. This was the opposite. She felt comfortable enough to look away from the road while in the passenger seat. Scrolling her phone or looking out at the blooming flowers was what she did in the car. It was no different from when I’m driving, and I think that was what was most impressive to me.

Driving after FSD

I found that picking up my car and driving manually back home truly brought me back to real life. Everyone with a Tesla and Full Self-Driving says that when you go back to another car, you feel like you’re stuck in the past.

I really did feel that way. Not only because of the aesthetic of the interior, but just because I was doing something that I just realized could be done for me with the right vehicle.

While I love the car I own now, I’m still deciding whether I love it enough to keep it. To be completely honest, I have hopped around with the idea of trading in my car for the new Model Y. Whether I will or not truly depends on the next few weeks and how I feel, but I know that I will be considering it for the next few months easily.

Joey has been a journalist covering electric mobility at TESLARATI since August 2019. In his spare time, Joey is playing golf, watching MMA, or cheering on any of his favorite sports teams, including the Baltimore Ravens and Orioles, Miami Heat, Washington Capitals, and Penn State Nittany Lions. You can get in touch with joey at joey@teslarati.com. He is also on X @KlenderJoey. If you're looking for great Tesla accessories, check out shop.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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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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