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  4. Nvidia RTX Spark laptops arrive from six makers
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Hardware & Compute

Nvidia RTX Spark laptops arrive from six makers

The Verge: A week with RTX Spark: everything we’ve learned using Nvidia’s new laptops

Nvidia’s new SoC is available in Windows laptops from six different manufacturers. We’ve collectively tested four of them so far. | Photo: Antonio G. Di Benedetto / The Verge Nvidia's RTX Spark N1X processor is finally here, and we've been collectively testing a small fortune's worth of powerful laptops sporting this new "superchip." RTX Spark is designed to be a high-performing Arm-based SoC for laptops and small desktop computers, rivaling the best from Apple, Intel, AMD, and

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Nvidia has released a new Arm-based processor called RTX Spark designed for high-end laptops and small desktop computers. The chip features multiple CPU cores, graphics capabilities, and unified memory to run local AI models and is being positioned to compete with processors from Apple, Intel, AMD, and Qualcomm. Multiple laptop manufacturers are offering RTX Spark in their products at prices ranging from around $2,600 to $7,000, and the laptops are primarily targeted at developers, coders, and content creators. Early testing shows that Windows on Arm has become a functional experience for most applications, though gaming and AI performance vary depending on specific software and settings.

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Nvidia's Jensen Huang pledges $2 billion for Europe, $250 million in compute for UK safety labs

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Microsoft Pushes Custom AI Chips with Azure Maia 300

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AI Data Center Land Buying Hits $6B as Power Premiums Rise

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ScaleFlux bets smarter SSD controllers can break the AI memory bottleneck

AI factories run on graphics processing units that cost a fortune and work at blistering speed, yet those chips increasingly sit idle waiting for data. As the bottleneck moves from compute to memory and storage, NAND flash is being asked to do far more than hold files. That shift is putting data movement constraints at […] The post ScaleFlux bets smarter SSD controllers can break the AI memory bottleneck appeared first on SiliconANGLE.