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Tesla Autopilot impresses in 79-minute ‘Torture Test’ through long winding roads
A Tesla Model 3 owner recently tested Autopilot’s abilities on the long and winding roads of the Blue Ridge Parkway in North Carolina. The 45.9-mile trip lasted 79 minutes, giving the driver a fair amount of insight regarding Autopilot’s performance with update 2020.16.2.1.
In a later comment on Reddit, the host of Youtube’s The Tech of Tech channel stated that he decided to test Autopilot’s capabilities on rainy, foggy roads stretching across the historic Blue Ridge Parkway in North Carolina.
“I did adjust the maximum speed to accommodate visibility due to fog as Autopilot doesn’t know to just slow down- it will shut off if it can’t see far enough for the speed. However, by lowering the maximum speed to what I’d want to drive anyway, Autopilot remains engaged. Other than that, all steering, braking, acceleration, etc. is done by the car and not me,” the driver wrote.
One notable feature of the update focused on Autopilot’s capability to slow down for sharp curves, which results in safer navigation through abrupt turns. For example, on a right turn, the car will drive closer to the right edge of the pavement, which provides a safer environment if two vehicles are driving through the same curve in opposite directions.
Tech of Tech indicates that the addition of the “Slowing for Sharp Curves” feature was the only reason the car could navigate the tricky roads of the Blue Ridge Parkway, which it did in impressive fashion.
Tesla rolled out a similar feature last year, but there were some issues with its performance that made some drivers feel uncomfortable. The company continually improved the capability, which was then released with 2020.16.2.1 to owners around May 16 this year, according to TeslaFi.com.
“This update introduced new slowing behavior. Autopilot slows much more for tight curves than before, and it does so much more smoothly than the aborted slowing behavior introduced when V10 first released,” the host said.
As could be seen in the video of the torture test, Autopilot managed to navigate through the various challenging sections of the Blue Ridge Parkway for 79 straight minutes before the car took a turn a bit too sharply, which required the driver to intervene. This instance was the only mistake that the car’s software made in almost 46 miles of driving, and that’s in questionable weather conditions and on a stretch of road that challenges even human drivers.
Tesla’s Autopilot software continues to improve through the millions of miles of driving data that owners contribute to the company’s Neural Network. Tesla CEO Elon Musk indicated during the company’s Q1 2020 Earnings Call that the Neural Net’s training was coming along nicely and that contributions were being assessed to improve the safety and performance of the company’s driver-assist features.
“We are collecting data from over 1 million intersections every month at this point. This number will grow exponentially as more people get the update, and as more people start driving again. Soon, we will be collecting data from over 1 billion intersections per month. All of those confirmations are training on neural net, essentially, the driver when driving and taking action is effectively labeling — the labeling reality as they drive, and making the neural net better and better,” Musk said.
Watch The Tech of Tech‘s Tesla Model 3 navigate the Blue Ridge Parkway below.
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Tesla to open source Model S and Model X designs and software
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.”
Just as Tesla made the original Roadster design & software open source, we plan to do the same with Model S & X
— Elon Musk (@elonmusk) July 24, 2026
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.
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.
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
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.
0 notable incidents across over 380,000 miles traveled by Robotaxi
— Tesla (@Tesla) July 22, 2026
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.
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.
Elon Musk
SpaceX Starship just nailed something it’s never done before
SpaceX’s Starship flew successfully Friday, landing both stages and deploying its first Starlink V3 satellites.
Starship’s thirteenth test flight delivered exactly what SpaceX needed with a clean liftoff, two successful stage recoveries, and the first real payload the vehicle has ever carried to space. Booster 20 and Ship 40 lifted off at 5:51 p.m. CT from Starbase, and by the time the mission wrapped roughly an hour later, both halves of the rocket had done exactly what they were supposed to do.
Booster 20 separated from Ship 40 a few minutes into the flight and stuck a controlled splashdown in the Gulf of Mexico about six minutes after liftoff. That is a meaningful turnaround from Flight 12 in May, when the booster lost several engines during its boostback burn before a hard water landing attempt.
Starship as seen from Starlink satellites pic.twitter.com/e2hvfmnewh
— Elon Musk (@elonmusk) July 25, 2026
Starship 40’s performance was arguably the bigger win. The vehicle deployed the first 20 operational Starlink V3 satellites Starship has ever carried, then flew a suborbital arc to a landing in the Indian Ocean that SpaceX commentator Dan Huot called the company’s softest splashdown yet. “This is a dream scenario for this team that’s trying to get this heat shield data,” Huot said on the live broadcast, according to Space.com’s live coverage. “I’m a little over the moon right now. Wow. Lucky number 13.”
Unlike the mass simulators SpaceX flew on Flight 12, these were production Starlink V3 satellites, meant to extend solar arrays and antennas and attempt to link with the broader constellation before reentering minutes later. Getting real hardware through a full deploy sequence on only the second flight of the V3 generation keeps Starship on schedule for the payload work NASA is counting on for future Artemis lunar landings.
What an awesome launch, really seems like everything went super well and it was all incredibly smooth.
SpaceX is awesome. Very interested to see how the market will respond on Monday pic.twitter.com/KSHmyBfV55
— TESLARATI (@Teslarati) July 25, 2026
— TESLARATI (@Teslarati) July 25, 2026
The flight also arrives at a moment when SpaceX needed a win. SPCX has traded below its $135 IPO price since mid-July, as Teslarati reported when the mission slipped to Friday, and short interest has climbed to roughly a third of the tradable float. A clean flight will not fix a balance sheet, but it does answer the one question SpaceX absolutely needed answered this week: whether the fixes made after the July 16 abort would hold up under real flight conditions. They did, on both stages, on the first try after the redesign.
SpaceX has not set a target date for Flight 14, though the company has said it wants to push toward an orbital attempt on the next mission. After Friday, that goal looks a lot more within reach.