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NVIDIA Debuts ‘Superchip’ Aimed at Self-Driving Cars

NVIDIA unveiled its Drive PX2 supercomputer at the 2016 Consumer Electronics Show in Las Vegas. It has the computing power of 150 MacBook Pros and is the size of a lunchbox.

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NVIDIA Drive PX2

Self driving cars are going to need a lot of computing power and NVIDIA will be there to fill the need. On Tuesday, it unveiled its newest supercomputer dubbed the Drive PX2, at CES 2016 in Las Vegas. NVIDIA chief Jen-Hsun Huang wowed the crowd during his keynote address by reeling off the specifications for his company’s latest amazing product.

The Drive PX2 has the processing power of 150 MacBook Pros, he says. It is packaged into a space about the size of a lunchbox. The Verge reports it has 12 CPU cores that enable a combined eight teraflops and 24 deep learning tera operations per second. The Drive PX2 is liquid cooled to keep its internals from overheating.

What can it do? According to Huang, the Drive PX2 can “process the inputs of 12 video cameras, plus lidar, radar and ultrasonic sensors.” Huang believes a true self driving car will need to have enough processing power on board to handle all the input it gets from the many built in sensors without having to rely on the cloud for assistance.

At last year’s GPU Conference, Elon Musk said, “What NVIDIA is doing with Tegra is really interesting and really important for self-driving in the future.” He told the audience that autonomous driving at speeds up to 10 mph is quite easy. Driving on the highway is also fairly easy to do. It is in urban settings at speeds between 10 and 50 mph with traffic lights and pedestrians added into the mix where autonomous driving becomes really hard.

NVIDIA says its new computer is able to detect other cars even in snowy conditions and is can translate road signs in German “better than a human can.” Ford, Mercedes and BMW are using NVIDIA computers to power their autonomous driving systems. Volvo is the first car maker to say it will incorporate the Drive PX2 into its self driving cars.

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Elon thinks the time will come when autonomous cars will be safer than cars with human drivers. He’s even gone as far as saying there may come a day when humans are banned from driving because they are too dangerous. When that day comes, NVIDIA autonomous driving supercomputers will be operating behind the scenes, whether in Teslas or other makes of cars, making it all possible. You can watch Jen-Hsun Huang’s presentation at CES in the video below.

 

 

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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’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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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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