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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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Elon Musk

Tesla confirms that work on Dojo 3 has officially resumed

“Now that the AI5 chip design is in good shape, Tesla will restart work on Dojo 3,” Elon Musk wrote in a post on X.

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(Credit: Tesla)

Tesla has restarted work on its Dojo 3 initiative, its in-house AI training supercomputer, now that its AI5 chip design has reached a stable stage. 

Tesla CEO Elon Musk confirmed the update in a recent post on X.

Tesla’s Dojo 3 initiative restarted

In a post on X, Musk said that with the AI5 chip design now “in good shape,” Tesla will resume work on Dojo 3. He added that Tesla is hiring engineers interested in working on what he expects will become the highest-volume AI chips in the world.

“Now that the AI5 chip design is in good shape, Tesla will restart work on Dojo3. If you’re interested in working on what will be the highest volume chips in the world, send a note to AI_Chips@Tesla.com with 3 bullet points on the toughest technical problems you’ve solved,” Musk wrote in his post on X. 

Musk’s comment followed a series of recent posts outlining Tesla’s broader AI chip roadmap. In another update, he stated that Tesla’s AI4 chip alone would achieve self-driving safety levels well above human drivers, AI5 would make vehicles “almost perfect” while significantly enhancing Optimus, and AI6 would be focused on Optimus and data center applications. 

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Musk then highlighted that AI7/Dojo 3 will be designed to support space-based AI compute.

Tesla’s AI roadmap

Musk’s latest comments helped resolve some confusion that emerged last year about Project Dojo’s future. At the time, Musk stated on X that Tesla was stepping back from Dojo because it did not make sense to split resources across multiple AI chip architectures. 

He suggested that clustering large numbers of Tesla AI5 and AI6 chips for training could effectively serve the same purpose as a dedicated Dojo successor. “In a supercomputer cluster, it would make sense to put many AI5/AI6 chips on a board, whether for inference or training, simply to reduce network cabling complexity & cost by a few orders of magnitude,” Musk wrote at the time.

Musk later reinforced that idea by responding positively to an X post stating that Tesla’s AI6 chip would effectively be the new Dojo. Considering his recent updates on X, however, it appears that Tesla will be using AI7, not AI6, as its dedicated Dojo successor. The CEO did state that Tesla’s AI7, AI8, and AI9 chips will be developed in short, nine-month cycles, so Dojo’s deployment might actually be sooner than expected. 

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Elon Musk

Elon Musk’s xAI brings 1GW Colossus 2 AI training cluster online

Elon Musk shared his update in a recent post on social media platform X.

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Credit: xAI

xAI has brought its Colossus 2 supercomputer online, making it the first gigawatt-scale AI training cluster in the world, and it’s about to get even bigger in a few months.

Elon Musk shared his update in a recent post on social media platform X.

Colossus 2 goes live

The Colossus 2 supercomputer, together with its predecessor, Colossus 1, are used by xAI to primarily train and refine the company’s Grok large language model. In a post on X, Musk stated that Colossus 2 is already operational, making it the first gigawatt training cluster in the world. 

But what’s even more remarkable is that it would be upgraded to 1.5 GW of power in April. Even in its current iteration, however, the Colossus 2 supercomputer already exceeds the peak demand of San Francisco.  

Commentary from users of the social media platform highlighted the speed of execution behind the project. Colossus 1 went from site preparation to full operation in 122 days, while Colossus 2 went live by crossing the 1-GW barrier and is targeting a total capacity of roughly 2 GW. This far exceeds the speed of xAI’s primary rivals.

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Funding fuels rapid expansion

xAI’s Colossus 2 launch follows xAI’s recently closed, upsized $20 billion Series E funding round, which exceeded its initial $15 billion target. The company said the capital will be used to accelerate infrastructure scaling and AI product development.

The round attracted a broad group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group. Strategic partners NVIDIA and Cisco also continued their support, helping xAI build what it describes as the world’s largest GPU clusters.

xAI said the funding will accelerate its infrastructure buildout, enable rapid deployment of AI products to billions of users, and support research tied to its mission of understanding the universe. The company noted that its Colossus 1 and 2 systems now represent more than one million H100 GPU equivalents, alongside recent releases including the Grok 4 series, Grok Voice, and Grok Imagine. Training is also already underway for its next flagship model, Grok 5.

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Elon Musk

Tesla AI5 chip nears completion, Elon Musk teases 9-month development cadence

The Tesla CEO shared his recent insights in a post on social media platform X.

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Credit: Tesla

Tesla’s next-generation AI5 chip is nearly complete, and work on its successor is already underway, as per a recent update from Elon Musk. 

The Tesla CEO shared his recent insights in a post on social media platform X.

Musk details AI chip roadmap

In his post, Elon Musk stated that Tesla’s AI5 chip design is “almost done,” while AI6 has already entered early development. Musk added that Tesla plans to continue iterating rapidly, with AI7, AI8, AI9, and future generations targeting a nine-month design cycle. 

He also noted that Tesla’s in-house chips could become the highest-volume AI processors in the world. Musk framed his update as a recruiting message, encouraging engineers to join Tesla’s AI and chip development teams.

Tesla community member Herbert Ong highlighted the strategic importance of the timeline, noting that faster chip cycles enable quicker learning, faster iteration, and a compounding advantage in AI and autonomy that becomes increasingly difficult for competitors to close.

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AI5 manufacturing takes shape

Musk’s comments align with earlier reporting on AI5’s production plans. In December, it was reported that Samsung is preparing to manufacture Tesla’s AI5 chip, accelerating hiring for experienced engineers to support U.S. production and address complex foundry challenges.

Samsung is one of two suppliers selected for AI5, alongside TSMC. The companies are expected to produce different versions of the AI5 chip, with TSMC reportedly using a 3nm process and Samsung using a 2nm process.

Musk has previously stated that while different foundries translate chip designs into physical silicon in different ways, the goal is for both versions of the Tesla AI5 chip to operate identically. AI5 will succeed Tesla’s current AI4 hardware, formerly known as Hardware 4, and is expected to support the company’s Full Self-Driving system as well as other AI-driven efforts, including Optimus.

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