From "cost center" to "revenue-generating asset", Computing Power is entering the financial asset system.
The operating models of tech giants are also changing in sync. Microsoft, AWS, and OpenAI are securing GPU resources in advance in exchange for future training and inference capabilities, creating a new "Computing Power Liability" structure that shifts GPUs from mere equipment procurement to productive capital with a clear return cycle. With the increasing demand for AI inference, the similarity between Computing Power and real-world assets has become more apparent: inference capacity has predictable outputs; Computing Power can be rented out to generate income; future capacity can be used for collateral financing; tasks can be sliced and scheduled, naturally supporting fragmentation.
View Original
This page may contain third-party content, which is provided for information purposes only (not representations/warranties) and should not be considered as an endorsement of its views by Gate, nor as financial or professional advice. See Disclaimer for details.
From "cost center" to "revenue-generating asset", Computing Power is entering the financial asset system.
The operating models of tech giants are also changing in sync. Microsoft, AWS, and OpenAI are securing GPU resources in advance in exchange for future training and inference capabilities, creating a new "Computing Power Liability" structure that shifts GPUs from mere equipment procurement to productive capital with a clear return cycle.
With the increasing demand for AI inference, the similarity between Computing Power and real-world assets has become more apparent: inference capacity has predictable outputs; Computing Power can be rented out to generate income; future capacity can be used for collateral financing; tasks can be sliced and scheduled, naturally supporting fragmentation.