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Wall Street futures climb, chip stocks rebound ahead of Nvidia results

Wall Street futures have climbed, with chip stocks rebounding ahead of results from Nvidia, the world’s most valuable company at the centre of the global AI boom.

Brent crude has fallen more than 2% to below $110 a barrel on hopes for the latest negotiations between the US and Iran, while investors remain cautious.

“All eyes on Nvidia,” said Ipek Ozkardeskaya, senior analyst at Swissquote.

double quotation markExpectations are, of course, sky high. The company is expected to report around $79bn in revenue – roughly 15% higher than last quarter and nearly 80% above the same quarter last year.

Margins are also expected to remain exceptionally strong, around 75%, confirming that Nvidia still enjoys enormous pricing power despite the massive Blackwell ramp and rising competition.

But Nvidia’s earnings no longer carry the same existential weight they did at the very beginning of the AI craze. Back then, markets were obsessed with training AI models. GPUs became essential because they are incredibly efficient at handling thousands of calculations simultaneously — exactly what AI training requires. Imagine trying to get from point A to B by simultaneously testing millions of possible paths through C, D, F, X, Y or Z. GPUs are built for that kind of parallel processing power. CPUs, on the other hand, are designed for sequential computations.

People walk past the corporation’s headquarters in Taipei, Taiwan, 20 May. Photograph: Ritchie B Tongo/EPA

double quotation markAs such, once the models are trained with GPUs, the focus increasingly shifts toward inference — running the trained model — where TPUs and CPUs can also play a major role, while memory chips are needed to store and process information efficiently.

That’s why GPUs say more about the raw power and evolution of AI models, while CPUs and memory chips increasingly say more about real-world AI adoption and scaling. This growing importance of CPUs and memory infrastructure is also why traditional CPU and memory chip makers have taken over part of the AI narrative — and why Nvidia is developing its own CPU technologies within its next-generation Vera Rubin platform.

Investors will therefore closely watch whether the company can maintain strong margins while scaling production and preparing the transition toward the next-generation Vera Rubin platform — designed for the next phase of AI focused on massive-scale inference, reasoning and AI “factories.”

And the competition for running models efficiently at lower cost is fierce. Besides traditional chipmakers like AMD and Intel, Nvidia’s biggest clients — Big Tech companies like Amazon, Google and Meta — are all working on their own in-house chips to build the most energy- and cost-efficient alternatives to Nvidia’s ultra-powerful premium products.

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