#GPU

words.U.S. AI‑related stocks fell on Friday, extending a three‑day decline. Oracle dropped over 2% after Thursday’s 11% plunge from revenue that missed forecasts, pulling down peers like Micron and CoreWeave. Despite strong demand for AI infrastructure, Oracle’s $16.06 billion revenue fell short of expectations, raising concerns about its debt‑financed AI‑cloud expansion and the tight GPU ecosystem. Morningstar cut Oracle’s fair‑value target to $286 but still sees the shares as undervalued. Market focus now shifts to next week’s earnings for signs of sustainable AI growth.

U.S. authorities dismantled a China‑linked smuggling ring that moved over $160 million of export‑controlled NVIDIA H100 and H200 GPUs. Operation Gatekeeper led to the guilty plea of Texas businessman Alan Hao Hsu and his firm Hao Global, plus charges against New York‑based Fanyue Gong and Canadian Benlin Yuan for using falsified documents and “straw purchasers” to reroute chips to mainland China, Hong Kong and other prohibited sites. The bust underscores heightened enforcement of AI‑hardware export controls and the broader U.S.–China rivalry over advanced semiconductor technology.

.Broadcom’s custom ASICs, used by Google to train Gemini 3 on Broadcom‑designed TPUs, are gaining traction, but Nvidia CEO Jensen Huang argues the company’s general‑purpose GPUs remain more versatile and pose no material threat. Nvidia’s $2 billion stake in Synopsys aims to create AI‑focused design tools across multiple industries. Analysts have raised price targets for both Broadcom and Nvidia, citing strong demand for ASIC efficiency and GPU flexibility. Diversified exposure to Broadcom, Nvidia and Synopsys is recommended to balance the evolving AI‑chip market.

Nvidia’s stock recently dipped amid growing market concerns about AI competition and valuation. Google’s Gemini 3, powered by its own AI chips, poses a challenge to Nvidia’s dominance. Meta’s potential shift to Google’s AI chips could further impact Nvidia’s revenue. Nvidia defends its technology’s versatility against specialized ASICs. This highlights the tension between general-purpose GPUs and application-specific hardware. The company is actively communicating to address concerns while balancing market perception. The UK’s upcoming Autumn Budget also adds to the market’s uncertainty.

Nvidia’s Q3 earnings exceeded expectations, fueled by the AI boom and reinforced by a bullish outlook. CEO Jensen Huang dismissed “AI bubble” concerns, citing increasing GPU adoption, new AI applications, and agentic AI. The company reaffirmed its $500 billion AI chip order forecast for 2025-2026. China sales were “insignificant” due to geopolitical tensions and competition, despite licenses for H20 chip exports. Analysts see continued growth, projecting substantial future cash flow for Nvidia.

Nvidia’s Q3 FY26 revenue surged 62% to $57.01 billion, exceeding expectations, driven by AI demand. Earnings per share also beat estimates, sending shares up 5% after-hours. Management’s guidance for Q4 projects $65 billion in revenue, surpassing consensus. CEO Jensen Huang highlighted the shift to GPU-accelerated computing, the AI tipping point, and the emergence of agentic AI as growth drivers. Strong demand for Blackwell chips and a $500 billion order backlog for Blackwell and Rubin architectures support future growth.

Nvidia’s Q3 earnings exceeded expectations, driving shares up in premarket trading and boosting confidence in the AI sector. Revenue jumped 62% year-over-year, supported by a strong Q4 forecast. CEO Jensen Huang addressed AI bubble concerns, citing robust demand for Nvidia’s GPUs across various sectors. Analysts praised Nvidia’s transparency in tackling potential risks, including supply chain issues and market anxieties. The positive results spurred gains for other chipmakers and related infrastructure providers, signaling renewed optimism in the AI landscape.

Nvidia is expanding its NVLink Fusion technology to seamlessly integrate with Arm-based Neoverse CPUs, enabling custom infrastructure solutions for hyperscalers. This move allows tighter integration between Arm CPUs and Nvidia GPUs, crucial for AI workloads requiring high-speed data transfer. Companies like Microsoft, Amazon, and Google are increasingly using Arm CPUs in their cloud infrastructure. This partnership highlights the increasing importance of Arm technology in AI server infrastructure and signifies Nvidia’s commitment to open innovation and diverse partnerships.

With tech giants investing heavily in AI data centers, depreciation of AI GPUs is a crucial accounting concern. Unlike traditional servers, the lifespan of these rapidly evolving components is uncertain, impacting profitability and investment decisions. While some, like CoreWeave, see long-term value, short seller Michael Burry suggests companies may be inflating useful life for earnings. Factors like new chip releases and wear-and-tear could accelerate depreciation. Companies are adopting varied strategies, and auditors are scrutinizing depreciation claims closely.

Samsung is investing in a 50,000 Nvidia GPU cluster, dubbed the “AI Megafactory,” to enhance chip manufacturing for mobile devices and robotics. This project signifies the escalating demand for AI acceleration and strengthens Nvidia’s position in the AI revolution. In addition to being a customer, Samsung will leverage Nvidia’s Omniverse and optimize chipmaking lithography. Samsung will also collaborate with Nvidia on HBM4 memory technology for future AI chips. These partnerships support Korea’s ambition to become a global AI leader.