Grayscale Looks Beyond AI Tokens To The Data And Credit Behind Computing

Grayscale’s October 23 research note looks at a more specific crypto-and-AI proposition than a general bet on smarter software: who supplies training data, who finances hardware and who receives payment when computing capacity is used. TL;DR The report highlights DATA, USD.AI and Pearl as examples of different infrastructure roles. Hardware financing introduces credit questions alongside blockchain mechanics. A useful service and a valuable token remain separate propositions. Three business models sit behind one broad AI label In the note, research head Zach Pandl describes DATA’s work on contributed training data, USD.AI’s GPU-backed lending and Pearl’s attempt to combine AI computing with blockchain rewards. These are Grayscale’s selected examples and expectations, not independently proven outcomes for the entire sector. Each model has a different customer. A data network needs someone willing to license its datasets. A financing protocol needs borrowers who can service debt. A computing network needs useful workloads and a way to measure delivery. Combining them under an AI-token heading can hide more than it reveals. USD.AI’s documentation makes the credit element explicit. It ...