Is the era of machine collateralization coming? An interpretation of how USD.AI is financializing GPUs.

This year, with the popularization of the RWA concept and the rise of the stablecoin market, the number of related projects has rapidly increased.

Last week, the stablecoin protocol USD.AI completed a Series A financing of 13 million USD in the primary market. The project connects DePIN, AI, RWA, and stablecoins by introducing GPU property rights, which can be seen as a form of "Infra-Fi" that may bring new insights to DePIN.

USD.AI is positioned as a decentralized credit protocol: emerging AI enterprises can use their owned GPU hardware as collateral to obtain loans. USD.AI has created the CALIBER standard, which represents GPU ownership in the form of on-chain NFTs and binds insurance, assessment, and redemption mechanisms on-chain.

USD.AI has created the CALIBER standard, which represents GPU ownership in the form of on-chain NFTs, and binds insurance, evaluation, and redemption mechanisms on-chain.

This means that the ownership, collateralization, and redemption of GPUs can all be executed on-chain. Analyzing the business model of USD.AI, which is a yield-generating stablecoin project, the sources of income come from AI hardware devices and US Treasury bonds: GPU hardware generates income through methods such as computing power leasing, and then the loan interest is given to sUSDAI stablecoin holders.

In this model, the GPU is not just hardware and computing power, but the cash flow generated from AI training / inference services, which supports the value of the collateral. If there are no borrowers temporarily, idle funds will be invested in U.S. Treasury bonds to earn returns.

The protocol has designed a dual-token model:

USDai: pegged to the US dollar, serving as a settlement tool for loan issuance and clearing.

sUSDai: A yield-generating stablecoin, its value is backed by the profits generated from GPUs (such as AI training rental income), and it allocates profits to investors.

Based on this, the official target APR was set at 15% to 25% (the current displayed APR is 6.76%, expected to be 7.83%, with a TVL of nearly 50 million USD during the testing period). This decentralized credit model aimed at AI startups uses computable and liquid computing power assets as collateral, which aligns well with the collateral logic and risk models. However, whether this interest rate can be achieved through illiquid property rights raises questions and challenges regarding the black-box nature of RWA and decentralized transparency.

In any case, the financialization of GPU property rights after confirmation, turning "physical property rights" into programmable financial assets, also provides new ideas for DePIN + DeFi. In the DePIN track and the Infra-Fi concept, we can observe the following trends:

1. Machine Mortgage, Computing Power Assetization and Infra-Fi

In on-chain markets, hardware infrastructure such as GPUs can serve as productive assets, transforming from hardware resources into a new category of collateralizable and lendable assets. In the future, the business space of DePIN and RWA may no longer be limited to areas strictly constrained by legal/compliance regulations off-chain. Infrastructure related to DePIN and AI, along with more enterprise-grade hardware behind it, may participate in the market.

2. DePIN + RWA

DePIN involves off-chain assets that typically have practical application scenarios and business revenue. How to transfer the revenue-generating capability of off-chain assets to the on-chain DeFi yield pools is a key focus of DePIN projects. In this case, machinery and equipment serve as both on-chain collateral and RWA assets, indirectly entering the cycle of the DeFi market.

3. The Integration / Acceleration of AI and Crypto

This innovation will make the financing costs of AI companies more market-oriented: for small AI teams, obtaining loans by collateralizing GPUs further lowers the threshold, but also raises higher requirements for interest rate returns; for stablecoin holders, even without understanding the AI market, they can indirectly participate in investments similar to "AI corporate bonds" to earn returns and potential incentives.

4. Parallel Narrative

In the same cycle, market sentiment will switch between different tracks, most likely reflecting different sides of the same logic. Further attention can be paid to the combination and progress of BTCFi with RWA, DePIN, and other directions.

In the original DePIN flywheel, the core logic is "resource sharing", where users transform into resource providers, driving development through "resource sharing + user incentives". GPU property lending, on the other hand, releases liquidity through hardware financialization, enabling enterprises to drive financing and monetize computing power, generating cash flow and forming a new flywheel.

The new model is driven by cash flow repatriation, forming a synergy between the capital of decentralized capital markets and the production capacity of the AI industry (such as GPU clusters and AI model training), shifting from "shared resources" to assetization and financialization. Hardware resources can not only generate cash flow through leasing but can also be used as on-chain collateral to accelerate credit expansion and the circulation of capital markets.

If developed smoothly, this could open a financial market for "machine collateral," transforming Infra into a financialized "machine version" of RWA through on-chain protocols, and entering the DeFi market. The asset scope may also widely include data storage, computing, bandwidth, electricity, etc., driving DePIN to "flow" in the new cycle.