3 6 Ke·2025-09-28 01:28Core Insights - Nvidia is transforming itself into a "central bank" for the global AI industry by investing $100 billion in OpenAI and committing to deploy at least 10GW of computing power [1][6][28] - This strategy marks a shift from a traditional chip sales model to a proactive demand creation approach, allowing Nvidia to lock in future orders through long-term contracts [10][12][28] Nvidia's New Strategy - Historically, Nvidia operated as a typical chip company, relying on one-time sales to OEMs and cloud providers, leading to significant revenue volatility [7] - The surge in AI training demand has resulted in Nvidia's revenue and profit skyrocketing, with a gross margin exceeding 75% and a market valuation surpassing $3 trillion [7][10] - The new strategy involves Nvidia investing in capacity building for clients, thus ensuring a steady stream of future orders and reducing revenue volatility [10][12] 10GW Computing Power Scale - The 10GW commitment translates to nearly 1 million AI cabinets, representing an unprecedented scale in the industry [11][13] - This investment could potentially generate a market size of $400 to $500 billion over the next 3 to 5 years, establishing a long-term growth trajectory for Nvidia [11][12] Partnership with Intel - Nvidia's $5 billion strategic investment in Intel aims to create a collaborative ecosystem, enhancing AI training solutions through customized x86 CPUs and deep interconnectivity with Nvidia GPUs [14][17] - This partnership positions Nvidia as a key player in the x86 ecosystem, facilitating a comprehensive solution from cloud to client devices [17][18] Industry Impact - The 10GW expansion and collaboration with Intel are expected to stimulate the entire AI industry chain, benefiting companies involved in cloud infrastructure, memory production, and data center operations [20][21] - Investors are encouraged to diversify their portfolios beyond Nvidia, considering a broader "AI computing ecosystem" to mitigate risks [21] Long-term Growth Potential - The AI infrastructure investment is seen as a core driver of the next capital expenditure cycle, similar to past technological revolutions [22] - As AI model parameters increase, the demand for computing power is expected to grow exponentially, providing Nvidia with further expansion opportunities [22][23] Risks and Challenges - The ambitious 10GW project faces potential bottlenecks related to power supply and site approvals, which could delay implementation [25] - High customer concentration poses risks, particularly if OpenAI faces funding challenges or demand fluctuations [26] - Regulatory scrutiny may arise due to Nvidia's dual role as both an investor and supplier, potentially leading to antitrust investigations [27]