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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.

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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).

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.

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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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Ford is charging for a basic EV feature on the Mustang Mach-E

When ordering a new Ford Mustang Mach-E, you’ll now be hit with an additional fee for one basic EV feature: the frunk.

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Credit: Ford Motor Company

Ford is charging an additional fee for a basic EV feature on its Mustang Mach-E, its most popular electric vehicle offering.

Ford has shuttered its initial Model e program, but is venturing into a more controlled and refined effort, and it is abandoning the F-150 Lightning in favor of a new pickup that is currently under design, but appears to have some favorable features.

However, ordering a new Mustang Mach-E now comes with an additional fee for one basic EV feature: the frunk.

The frunk is the front trunk, and due to the lack of a large engine in the front of an electric vehicle, OEMs are able to offer additional storage space under the hood. There’s one problem, though, and that is that companies appear to be recognizing that they can remove it for free while offering the function for a fee.

Ford is charging $495 for the frunk.

Interestingly, the frunk size varies by vehicle, but the Mustang Mach-E features a 4.7 to 4.8 cubic-foot-sized frunk, which measures approximately 9 inches deep, 26 inches wide, and 14 inches high.

When the vehicle was first released, Ford marketed the frunk as the ultimate tailgating feature, showing it off as a perfect place to store and serve cold shrimp cocktail.

Ford Mach-E frunk is perfect for chowders and chicken wings, and we’re not even joking

It appears the decision to charge for what is a simple advantage of an EV is not going over well, as even Ford loyal customers say the frunk is a “basic expectation” of an EV. Without it, it seems as if fans feel the company is nickel-and-diming its customers.

It will be pretty interesting to see the Mach-E without a frunk, and while it should not be enough to turn people away from potentially buying the vehicle, it seems the decision to add an additional charge to include one will definitely annoy some customers.

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Tesla to improve one of its best features, coding shows

According to the update, Tesla will work on improving the headlights when coming into contact with highly reflective objects, including road signs, traffic signs, and street lights. Additionally, pixel-level dimming will happen in two stages, whereas it currently performs with just one, meaning on or off.

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Credit: @jojje167 on X

Tesla is looking to upgrade its Matrix Headlights, a unique and high-tech feature that is available on several of its vehicles. The headlights aim to maximize visibility for Tesla drivers while being considerate of oncoming traffic.

The Matrix Headlights Tesla offers utilize dimming of individual light pixels to ensure that visibility stays high for those behind the wheel, while also being considerate of other cars by decreasing the brightness in areas where other cars are traveling.

Here’s what they look like in action:

As you can see, the Matrix headlight system intentionally dims the area where oncoming cars would be impacted by high beams. This keeps visibility at a maximum for everyone on the road, including those who could be hit with bright lights in their eyes.

There are still a handful of complaints from owners, however, but Tesla appears to be looking to resolve these with the coming updates in a Software Version that is currently labeled 2026.2.xxx. The coding was spotted by X user BERKANT:

According to the update, Tesla will work on improving the headlights when coming into contact with highly reflective objects, including road signs, traffic signs, and street lights. Additionally, pixel-level dimming will happen in two stages, whereas it currently performs with just one, meaning on or off.

Finally, the new system will prevent the high beams from glaring back at the driver. The system is made to dim when it recognizes oncoming cars, but not necessarily objects that could produce glaring issues back at the driver.

Tesla’s revolutionary Matrix headlights are coming to the U.S.

This upgrade is software-focused, so there will not need to be any physical changes or upgrades made to Tesla vehicles that utilize the Matrix headlights currently.

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xAI’s Grok approved for Pentagon classified systems: report

Under the agreement, Grok can be deployed in systems handling classified intelligence analysis, weapons development, and battlefield operations. 

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Credit: xAI

Elon Musk’s xAI has signed an agreement with the United States Department of Defense (DoD) to allow Grok to be used in classified military systems.

Previously, Anthropic’s Claude had been the only AI system approved for the most sensitive military work, but a dispute over usage safeguards has reportedly prompted the Pentagon to broaden its options, as noted in a report from Axios.

Under the agreement, Grok can be deployed in systems handling classified intelligence analysis, weapons development, and battlefield operations. 

The publication reported that xAI agreed to the Pentagon’s requirement that its technology be usable for “all lawful purposes,” a standard Anthropic has reportedly resisted due to alleged ethical restrictions tied to mass surveillance and autonomous weapons use.

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Defense Secretary Pete Hegseth is scheduled to meet with Anthropic CEO Dario Amodei in what sources expect to be a tense meeting, with the publication hinting that the Pentagon could designate Anthropic a “supply chain risk” if the company does not lift its safeguards. 

Axios stated that replacing Claude fully might be technically challenging even if xAI or other alternative AI systems take its place. That being said, other AI systems are already in use by the DoD. 

Grok already operates in the Pentagon’s unclassified systems alongside Google’s Gemini and OpenAI’s ChatGPT. Google is reportedly close to an agreement that will result in Gemini being used for classified use, while OpenAI’s progress toward classified deployment is described as slower but still feasible. 

The publication noted that the Pentagon continues talks with several AI companies as it prepares for potential changes in classified AI sourcing.

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