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Tesla’s race to full self-driving under pressure as GM Cruise gets $2.25B investment

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In a press release on Thursday, General Motors announced that SoftBank would be investing $2.25 billion in the automaker’s self-driving unit, GM Cruise Holdings LLC. The Detroit-based auto giant would also be investing an additional $1.1 billion into its self-driving division. These investments are aimed at boosting the unit’s capability to reach commercialization at scale by next year.

GM Chairman and CEO Mary Barra lauded the additional investments into the company’s self-driving unit. Barra noted in the press release that the support from SoftBank adds an “additional strong partner” as the automaker pursues its “vision of zero crashes, zero emissions, and zero congestion.”

GM Cruise currently operates a fleet of autonomous Chevy Bolt EVs in San Francisco that provide autonomous ride-hailing services to its employees. Plans are also underway to develop a Chevy Bolt EV variant that is specifically designed to be fully autonomous, with the vehicle not having pedals or a steering wheel.

SoftBank’s $2.25 billion investment into GM Cruise will be made in two tranches. SoftBank Vision Fund will first invest $900 million at the closing of the transaction. Once GM Cruise’s autonomous vehicles are ready to hit the market, Vision Fund will release the second tranche of $1.35 billion. This will ultimately result in SoftBank Vision Fund commanding a 19.6% stake in GM Cruise.

The new investment brings GM Cruise’s valuation close to $11.5 billion. The investment also brings to light the arguable undervaluation of Tesla’s Autopilot system, which has been on the consumer market for several years and has more than 150,000 vehicles from around the world that’s collecting data.

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Still, GM Cruise’s new financial backing puts tremendous pressure on Tesla, which has seen its fair share of scrutiny as it steadily improves its Autopilot software in the public eye. Despite having collected reservation deposits for its Full Self-Driving capability that is yet to be released, Autopilot continues to improve and pacing toward full autonomy, according to CEO Elon Musk.

During the Q4 2017 earnings call, Musk addressed the delays in the company’s planned coast-to-coast autonomous drive. The exhibition, which was set for December 2017, did not pan out, although Tesla could have accomplished the coast-to-coast trip, according to Musk. However, doing so would have required far too much “specialized code” that would only be fully effective on a particular route. During the earnings call, Musk stated that Tesla would likely conduct the autonomous coast-to-coast drive sometime this year. 

A Tesla Model 3 on Autopilot. [Credit: LivingTesla/YouTube]

One notable difference between Tesla and GM Cruise, and Google’s Waymo is the Tesla’s opposition to the utilization of LiDAR technology – a common fixture on self-driving cars. Instead of LiDAR, Tesla’s electric cars rely on a series of cameras, radar, and ultrasonic sensors to collect data on a vehicle’s surroundings. LiDAR, which is used in GM Cruise’s Chevy Bolt EVs and Waymo’s autonomous vehicles, boasts high spatial precision. Inasmuch as LiDAR can measure distances well, however, it performs poorly in bad weather.

Ultimately, Tesla’s ace-in-the-hole in the increasingly competitive self-driving car market could be its neural net and sharing of fleet data. There are roughly 150,000 AP2.0 vehicles on the road today, with each one providing valuable data to Tesla’s deep neural networks. Akin to the human brain, the more data that is available to train the neural network, the better its performance would be. 

Ultimately, Tesla’s neural net could be the difference-maker when the company goes all-in and competes in the self-driving race. Until then, however, the electric car maker could soon be taking a backseat to companies like GM Cruise and Waymo, both of which are accelerating their efforts at rolling out consumer-ready autonomous vehicles in the near future.

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Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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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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