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What are the benefits of tokenization in AI and compute markets?
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In AI, tokenization finances the industry's scarcest inputs: compute capacity and data. GPU time sold as transferable capacity instruments, datacenter buildouts funded against tokenized revenue, dataset licences with programmable royalties, and — at the frontier — model revenue shares. The benefit is capital formation at the speed the buildout actually demands.
Compute is a commodity with a forward curve waiting to exist: tokenized capacity lets buyers hedge and suppliers finance, the way power markets matured. Decentralized compute networks — the portfolio's Alpaca Network among them — are early expressions of the same design.
Data follows the royalty model: licensed training data with on-chain attribution and payment turns a legal risk into a revenue line, and gives the agent economy its provenance layer.
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