Kerman Kohli Highlights Credit Challenges in Computing Power Financing

Cryptocurrency researcher Kerman Kohli has published an article titled "Compute Financing" on Substack, addressing the challenges of financing for computing power construction. In his analysis, Kohli identifies credit availability as a significant bottleneck, noting that initial expenditures are primarily funded through balance sheet cash, which later transitions to equity financing. He references substantial financing efforts by major companies, including Alphabet's $85 billion and Meta's fundraising through shareholder dilution, suggesting that the credit market will be the next focus for financing.

Kohli outlines three prevailing concerns among creditors regarding the computing power market: the potential for an AI bubble, counterparty risks in purchase contracts, and the depreciation of underlying GPUs. Despite these concerns, he argues that demand for agentic AI is rapidly increasing, with growth rates estimated between 2.5 to 5 times annually. He predicts that supply could double by the end of 2030, while memory resources are expected to be depleted by 2027, leading to trillions of dollars in computing power commitments from various sectors, including pharmaceuticals, research, military, and cybersecurity.

The researcher also discusses the rising costs associated with computing power, noting a 50% increase in rental prices over the past six months and a doubling of prices over the past year. Kohli emphasizes that computing power is more substitutable than real estate, allowing for quick market adjustments when commitments are withdrawn. He highlights the need for creditors to secure long-term contracts with substantial down payments, which can lock in discounts and create challenges for lenders.

In his conclusion, Kohli asserts that computing power is poised to become the largest asset class, surpassing real estate. He believes that the current scale of credit-supported computing power is only beginning to emerge, indicating a transformative shift in how computing resources are financed and valued.

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Source: KLEA News