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Chronicles

The story behind the story

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How some crypto miners want to repurpose their rigs to train AI models, which isn't easy or cheap but may be more affordable than AWS and cloud alternatives

Demand for high-end chips allows cryptocurrency companies to repurpose idle equipment  —  The boom in demand for high-end chips powering …

Wall Street Journal

Context & Ripple Effects

This WSJ piece lands mid-arc in the mining-to-AI conversion story. Earlier in 2023, Hive Blockchain and Hut 8 had already begun repurposing their GPU-based equipment for high-performance computing clients, while analysts flagged that a full pivot to AI cloud services would require specialized processors, hardware and staff beyond what mining rigs offer. The demand side of the trade was visible too: AWS itself has said it lacks sufficient capacity to meet customer demand, which is precisely the gap idle miner GPUs are positioned to fill.

First-order effects

  • Miners holding idle GPU fleets — the same equipment class Hive Blockchain and Hut 8 redirected toward HPC work — gain a revenue path that prices against scarce cloud capacity rather than crypto economics.
  • AI training customers facing AWS's acknowledged capacity shortfall get a marginal alternative supplier, though only for workloads their rig-class hardware can actually serve.

Second-order effects

Third-order effects

  • If the pattern holds, bitcoin mining infrastructure gets structurally repriced as AI real estate and compute supply — visible in the fund tracking mining firms being up 150% year-to-date by late 2025 — collapsing the distinction between 'crypto companies' and 'AI infrastructure companies'.
  • A two-tier AI compute market could emerge: hyperscaler-grade capacity at premium prices, and converted mining capacity serving price-sensitive training workloads, with conversion capability becoming the durable moat rather than chip ownership.

The trend: Crypto mining assets are being converted into AI compute supply as cloud capacity tightens, turning former Bitcoin infrastructure into a secondary market for AI training.

Discussion

  • @vipulved Vipul Ved Prakash on x
    Great story by @WSJ on how @togethercompute is reducing the cost of AI with GPUs in alternate data centers like mining farms. With the combination of hardware and software, we are almost certainly the most efficient infra for building large models today. https://www.wsj.com/...
  • @kylebrussell Kyle Russell on x
    rehabilitating criminal gpus to be productive members of society https://twitter.com/...