Goldman Sachs Group, Inc. leads the bridge organization for capital as NVIDIA Corporation (NVDA.US) launches $500 billion in AI infrastructure financing: from "selling chips" to "selling assets."

In the context of the global wave of generative AI, computing power infrastructure is transforming from a "cost center" for tech companies into one of the most attractive "asset classes." NVIDIA Corporation (NVDA.US), centered on its GPUs, is attempting to leverage an unprecedented capital movementa $500 billion AI infrastructure financing plan is accelerating, with Wall Street's top investment bank Goldman Sachs Group, Inc. playing a key role as a "bridge builder." On August 10, NVIDIA Corporation announced the establishment of strategic partnerships with global top institutions including Apollo Global Management Inc, BlackRock, Inc., Blackstone, Brookfield Asset Management, Goldman Sachs Group, Inc. and KKR to jointly set up an independent financing platform. The core objective of this plan is clear: to build NVIDIA Corporation-enabled AI infrastructure into a new, investable asset class, gradually shifting the financing entities from tech companies themselves to a broader base of institutional investors. According to previously disclosed information, NVIDIA Corporation may provide up to $125 billion in funding support for potential transactions, accounting for about 25% of the total scale, serving as a "safety net" to attract more third-party capital into the market. Goldman Sachs Group, Inc.: From "subordinated capital" to full-chain services in the "public debt market" According to informed sources, Goldman Sachs Group, Inc. is actively negotiating with potential investors to participate in this financing plan. As one of the six founding partners of this plan, Goldman Sachs Group, Inc.'s role goes far beyond simply referring clients. Reports indicate that Goldman Sachs Group, Inc. can provide subordinated capital and private credit financing through its asset management business, while its investment banking division will assist in allocating debt instruments to private credit funds and ultimately connect to the public debt market. This means that Goldman Sachs Group, Inc. is building a complete financing chain from private placement to public offering, from equity to debt, and from subordinated to senior capital. In terms of investor structure, U.S. insurance companies, asset management institutions, and banks are expected to form the core investor base for this plan, with asset management firms expected to hold a significant proportion of the share. Goldman Sachs Group, Inc. has conducted extensive communication with various investors, including banks, asset management companies, insurance companies, and private credit institutions regarding this structure. NVIDIA Corporation's "light asset" transformation and ecological moat The strategic significance of this financing plan cannot be underestimated. For NVIDIA Corporation, bringing in third-party capital to build AI infrastructure can alleviate the pressure of its own capital expenditures while further consolidating its CUDA ecosystem and the dominance of its GPUs in the computing power marketwhoever finances the construction of data centers centered around NVIDIA Corporation chips is more likely to be bound to NVIDIA Corporation's technology roadmap in the long term. For institutional investors, AI infrastructure is viewed as a core asset in the next "super cycle" following the internet and mobile internet. Hardware assets such as data centers, computing power clusters, and high-speed interconnect networks possess stable cash flow attributes, complementing the high volatility of tech stocks, which aligns with the asset allocation needs of long-term capital like insurance funds and pensions. The $500 billion financing scale is unprecedented in the infrastructure investment field. If the plan proceeds smoothly, it will significantly accelerate the global deployment of AI computing power and reshape the ownership structure of data center investments. However, challenges also exist: investment return cycles of AI infrastructure, energy consumption constraints, technology iteration risks, and potential concerns over computing power oversupply could all impact the final decisions of institutional investors.