Oracle to Purchase $40 Billion Worth of Nvidia Chips for OpenAI’s US Data Center

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Oracle is set to invest approximately $40 billion in purchasing Nvidia’s high-performance chips to support OpenAI’s new data center in the United States, according to a report by the Financial Times. This significant investment highlights the growing collaboration between cloud service providers and AI companies as they race to build advanced infrastructure to power next-generation artificial intelligence applications.

The new data center will be located in Abilene, Texas, and forms a critical part of the U.S. Stargate Project, a government-backed initiative involving leading AI companies aimed at strengthening America’s position in the global AI race. This project reflects the increasing emphasis on domestic AI capabilities amid intensifying competition with other countries developing their own AI technologies.

Oracle plans to acquire roughly 400,000 of Nvidia’s most advanced GB200 chips, which will be leased to OpenAI to provide the massive computing power required for AI workloads. While Oracle and OpenAI have not publicly commented on the deal, sources familiar with the arrangement confirmed the details to the Financial Times. Nvidia also declined to comment on the specifics.

The data center is expected to become fully operational by mid-2026, with Oracle securing a 15-year lease on the site. Financing for the project is backed primarily by JPMorgan, which has extended two loans totaling $9.6 billion, while the facility’s owners, Crusoe and Blue Owl Capital, have contributed approximately $5 billion in cash. This large-scale investment underscores the commitment of both private and public sectors to accelerate AI development on U.S. soil.

Trump Warns of 25% Tariffs on Apple if iPhones Are Not Manufactured in the US

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President Donald Trump has issued a stern warning to Apple, threatening to impose a tariff of at least 25% on its products if the company does not manufacture iPhones within the United States. This move intensifies the pressure on the tech giant to increase its domestic production capabilities. Trump’s statement was posted on his social media platform, Truth Social, where he emphasized his expectation that iPhones sold in the U.S. should be made on American soil rather than overseas in countries like India or elsewhere.

The announcement caused immediate ripples in the financial markets, with U.S. equity futures falling to session lows. Particularly affected were Nasdaq 100 contracts, and Apple shares saw a drop of up to four percent in pre-market trading. Trump’s broader trade threats also include a plan to implement a 50% tariff on imports from the European Union starting June 1. These aggressive demands highlight a significant challenge for Apple, which has long relied on a complex supply chain centered in China. The U.S. currently lacks the extensive manufacturing ecosystem and supplier network that Asia offers, making a rapid shift to domestic production difficult.

Apple, a frequent target of Trump’s trade policies, did not immediately respond to requests for comment regarding the tariff threat. The company has already warned investors of nearly $900 million in increased costs due to existing tariffs in the current quarter. These rising expenses further complicate Apple’s global manufacturing strategy, which balances cost efficiency with geopolitical and trade considerations.

Adding to the pressure, Trump reiterated his call during a recent trip to the Middle East, urging Apple CEO Tim Cook to halt plans for building factories in India aimed at supplying the U.S. market. This underscores the administration’s push for reshoring production as part of a broader strategy to reduce dependency on China and bolster American manufacturing. How Apple will respond remains to be seen, but the stakes for the tech giant are high as it navigates these geopolitical trade tensions.

Anthropic CEO Dario Amodei Claims AI Models Experience Fewer Hallucinations Than Humans: Report

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Anthropic CEO Dario Amodei recently stated that artificial intelligence (AI) models tend to hallucinate less frequently than humans do. This remark was made during the company’s first-ever Code With Claude event, held on Thursday. At this event, the San Francisco-based AI firm unveiled two new versions of its Claude 4 models, alongside several upgraded features such as enhanced memory and better tool integration. Amodei also commented on the skepticism surrounding AI development, suggesting that despite critics searching for obstacles, no significant barriers to AI progress have emerged so far.

During a press briefing reported by TechCrunch, Amodei elaborated on the nature of hallucinations in AI systems, explaining that these errors do not prevent AI from achieving artificial general intelligence (AGI). When asked about hallucinations, he said, “It really depends how you measure it, but I suspect that AI models probably hallucinate less than humans, but they hallucinate in more surprising ways.” This perspective highlights that while AI does make mistakes, the frequency might be lower than commonly assumed, though the mistakes can sometimes be unexpected.

Amodei also pointed out that errors are a common part of human activity, with TV presenters, politicians, and professionals making mistakes regularly. Therefore, the presence of errors in AI responses does not necessarily undermine its overall intelligence. Nonetheless, he acknowledged the issue of AI confidently presenting false information remains a challenge. A recent incident highlighted this when Anthropic’s lawyer had to apologize in court after the company’s Claude chatbot generated an incorrect citation in a legal filing. This mishap took place during Anthropic’s ongoing lawsuit against music publishers over alleged copyright violations related to hundreds of song lyrics.

Looking ahead, Amodei remains optimistic about the future of AI. In a paper published in October 2024, he claimed that Anthropic could achieve artificial general intelligence as soon as next year. AGI represents a breakthrough form of AI capable of understanding, learning, and performing a broad spectrum of tasks autonomously, without human assistance. If realized, this development would mark a significant milestone in AI research and its practical applications.