Grayscale Maps AI Roles for Crypto Projects
A new analysis categorizes specific cryptocurrency protocols as essential infrastructure for AI development.
Updated on Oct. 24, 2026 in Artificial Intelligence
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Grayscale has identified three cryptocurrency projects that provide critical support to artificial intelligence infrastructure. These protocols focus on training material, equipment financing, and computational assignments.
Why it matters
The classification underscores how blockchain technology is being integrated into the AI supply chain. These projects address distinct needs such as sourcing human-contributed data, financing hardware, and optimizing computation.
The DATA Network, USD.AI, and Pearl platforms each serve specific roles in the AI service chain, including data collection and GPU financing. Researchers analyzed 8,012 mining workers, identifying instances where miners submitted random matrices to accepted shares.
The players
Grayscale
This investment management firm specializes in digital assets and cryptocurrency-focused research.
Zach Pandl
He serves as the Head of Research at Grayscale and authored the recent analysis on AI infrastructure.
Sui Foundation
This organization manages the development and ecosystem growth of the Sui blockchain platform.
Abhinaba Basu
He is an independent researcher who conducted a technical analysis of mining software and worker output.
The details
The DATA Network is shifting to the Sui blockchain, a move that will see the independent DATA chain retired and Walrus adopted as the primary storage layer. Meanwhile, Pearl miners are utilizing matrix multiplication to earn network rewards, while USD.AI relies on the CHIP token for governance and utility functions.
Timeline
Trace launched its operations in June 2026.
The DATA protocol migration to Sui was announced on October 12, 2026.
Grayscale released its infrastructure analysis on October 23, 2026.
The Tech Race
These crypto-AI projects reflect a shift toward decentralized alternatives to centralized cloud computing models. By providing hardware financing and distributed computation, they aim to compete with major tech rivals that dominate AI infrastructure today.
For users and developers, these protocols suggest new ways to access computing resources or contribute data for compensation. However, the complexity of integrating these decentralized tools into existing AI workflows remains a significant adoption hurdle.
The takeaway
Blockchain infrastructure is increasingly positioning itself as a vital utility for the resource-heavy needs of the AI industry. Readers should monitor these projects for signs of mainstream adoption versus the current dominance of established cloud service providers.
Further reading
Learn more about the intersection of blockchain and machine learning on our Artificial Intelligence section page.
Source note: This article includes information reported by TokenPost.
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