Oracle Pauses After AI-Fueled Surge Toward $1 Trillion Valuation

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Oracle shares fell 4% on Thursday, cooling off after a record-breaking 35.9% rally the previous day that had pushed the company’s market capitalization to $933 billion, edging it closer to the trillion-dollar elite. If losses hold, Oracle’s valuation will settle near $894 billion.

Ellison’s Billionaire Climb

The surge has also boosted co-founder Larry Ellison’s fortune to $371.7 billion, putting him within striking distance of Elon Musk ($441.2 billion) for the title of world’s richest person, according to Forbes.

What Fueled the Rally

Oracle’s rise has been powered by multi-billion-dollar AI cloud deals as companies race to secure massive computing power to lead in the AI arms race.

  • On Tuesday, Oracle reported its order backlog was on track to hit $500 billion.

  • The Wall Street Journal revealed OpenAI signed a $300 billion cloud deal with Oracle, one of the largest in history.

Market View

Analysts see the pullback as a breather.

  • Dennis Dick, chief strategist at Stock Trader Network: “A bit of buyer exhaustion here. I think the ‘buy the dip’ crowd is likely to re-emerge. The guidance was so incredible, hard to think that this story is over.”

Oracle’s stock has nearly doubled in 2025, making it one of the top S&P 500 performers, outpacing even the Magnificent Seven tech giants.

Valuation Check

  • Stock price: $314.45

  • Median price target: $342 (approx. +9% upside, LSEG data)

  • Forward P/E ratio: 45.3 vs. Amazon (31.3) and Microsoft (31).

Oracle’s premium valuation reflects investors’ conviction that its AI-powered cloud expansion will continue to drive outsized growth, even as short-term pullbacks test market momentum.

Alibaba and Baidu Turn to In-House Chips for AI Training Amid U.S. Restrictions

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Alibaba and Baidu have begun using their own internally designed chips to train AI models, partly replacing Nvidia’s processors, according to a report from The Information. The move signals a major shift in China’s AI development strategy, as U.S. export controls continue to restrict access to advanced American-made semiconductors.

Key Developments

  • Alibaba has used its homegrown chips since early 2025 to train smaller AI models.

  • Baidu is testing its Kunlun P800 chip to train new versions of its Ernie AI model.

  • Both companies still rely on Nvidia for their most advanced models but are working to reduce dependence.

Impact on Nvidia

Nvidia remains dominant in AI training hardware, but China accounts for a large share of its business. The firm’s most powerful U.S.-approved chip for China, the H20, lags behind the H100 and Blackwell series — but still outperforms most Chinese alternatives.

However, employees cited by The Information said Alibaba’s latest AI chip matches the performance of Nvidia’s H20, narrowing the gap between U.S. and Chinese hardware.

An Nvidia spokesperson responded: “The competition has undeniably arrived … We’ll continue to work to earn the trust and support of mainstream developers everywhere.”

Geopolitical Pressure

  • U.S. export restrictions have pushed Chinese companies to accelerate domestic chip design.

  • Beijing has urged firms to rely on home-grown semiconductor technology as part of its strategic autonomy push.

  • Nvidia CEO Jensen Huang recently said talks with the White House over permission to sell a less advanced next-gen chip to China will take time.

According to the report, Nvidia has agreed to give the Trump administration 15% of China sales of its H20 chips in exchange for continued export licenses.

The Bigger Picture

China’s pivot toward domestic AI chips marks both a risk to Nvidia’s China revenues and a milestone for Chinese chipmakers, who are beginning to close the performance gap under intense geopolitical and economic pressure.

FDA to Review AI-Powered Mental Health Devices in November Advisory Panel

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The U.S. Food and Drug Administration (FDA) announced it will convene its Digital Health Advisory Committee (DHAC) on November 6 to evaluate the growing category of AI-enabled digital mental health tools.

The meeting will explore how technologies such as chatbots, virtual therapists, and digital therapeutics could help bridge the nation’s mental health care gap, while also assessing the risks of safety, efficacy, and oversight.

Why It Matters

The U.S. faces a shortage of mental health professionals, and AI-driven platforms promise scalability, accessibility, and rapid intervention. But the speed of innovation has left regulators searching for frameworks to ensure these devices are trustworthy and clinically sound.

FDA’s Approach

  • The DHAC will advise the agency on regulatory pathways for AI/ML tools, remote monitoring, digital therapeutics, and medical device software.

  • The panel discussion is expected to help the FDA identify key areas of concern such as data privacy, bias in algorithms, and standards for clinical validation.

  • The FDA has already begun experimenting with AI in its review processes, reflecting its broader shift toward digital oversight.

Next Steps

  • The FDA has opened a public docket for comments ahead of the session.

  • Supporting materials will be made available at least two business days before the meeting.

The November discussion could shape how future AI mental health devices are classified, monitored, and approved in the U.S., setting an early precedent for regulation in this rapidly expanding sector.