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Tesla’s in-house Full Self-Driving chip puts TSLA 4 years ahead of competition: analyst

Elon Musk at Tesla's Autonomy Day FSD presentation. | Image: Tesla

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Tesla’s decision to develop its Full Self-Driving (FSD) computer chip in-house has put it four years ahead of the competition, according to ARK Invest analyst James Wang.

Wang laid out the case for the all-electric car maker’s custom automotive-grade computer against the next-best options in the market, all Nvidia products, in an article on ARK Invest’s website. His stated goal in the piece was to clarify Tesla’s position and achievement with full self-driving in simple terms as well as explain why an off-the-shelf chip would not have accomplished the same feat.

Admittedly, Tesla’s Autonomy Day livestream debuting the arrival of its Full Self-Driving computer was chock full of very technical details that many outside the computer science world indicated were difficult to follow. Thus, Wang’s FSD simplification is helpful for gaining insight into Tesla’s autonomous driving progress in terms of the bigger industry picture.

In summary, by focusing only on what its particular needs were for its particular software demands, Tesla was was able to improve its chip’s performance efficiency to a level that has allowed it to “leapfrog” over competitors. Wang predicts that by 2021, Tesla will be ready to release its next generation FSD computer while its closest competitor in terms of optimal peak utilization is just coming to market.

Nvidia is a prominent and highly successful leader in computer chip design, and Tesla already uses its products for Hardware 2.5, the computer currently running the electric car maker’s Autopilot features. That said, the industry giant has three self-driving-focused chips in its lineup: Xavier (in production), Pegasus (readying for production) and Orin (still pending an official announcement).

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Pegasus is a Level 5 self-driving computer, as is Tesla’s FSD; however, it has twice as many chips as FSD, consumes seven times more power than FSD, and is too big and expensive for the Model 3. Since Nvidia designs chips for a wide range of hardware manufacturers, much like the Windows and Android operating systems are designed to be flexible enough for different computer and smartphone hardware suites, their functionality cannot be overly streamlined for one system over another. In contrast, Tesla (like Apple hardware/software) can focus all of its autonomy efforts on its specific hardware and software needs, thus achieving a greater output than Nvidia’s product.

Tesla’s Full Self-Driving computer. | Image: Tesla

In a follow up to Tesla’s Autonomy Day presentation wherein FSD was compared to Nvidia’s Xavier computer, a chip designed for semi-autonomous driving only, the chip manufacturer published a company blog piece drawing attention to Pegasus’ capabilities as a better measure for analysis. As pointed out in Wang’s analysis, the FSD and Pegasus still do not achieve the same metrics, leaving Tesla well positioned amongst its self-driving computer peers. Despite the issue, though, Nvidia’s conclusion was a positive response to the car maker’s achievement: Tesla has raised the bar on self-driving and other car manufacturers need to get on board before falling too far behind.

During the Autonomy Day presentation, Tesla CEO Elon Musk crowned FSD as “objectively best in the world”, and James Wang’s analysis is yet another outline of why that is arguably the case. Tesla’s Full Self-Driving Computer (formerly known as Hardware 3) is currently being installed in all new production vehicles, and owners who purchased Full Self-Driving for a car produced in 2016 or later will receive a free upgrade to the FSD computer in the near future. Musk has further predicted that Tesla’s full self-driving software will be complete by the end of this year and fully operational by the second quarter of next year.

Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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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.

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.

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.

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

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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.

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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