Traditionally, the demand for computational power in both ML model training and cryptocurrency mining has been met by centralized cloud computing services. While effective to a degree, this centralization presents multiple drawbacks, including high costs, potential for service outages, and concerns over data privacy and security. Furthermore, the centralized model concentrates power among a few large corporations, creating monopolies that can stifle competition and innovation. Additionally, the environmental footprint of massive data centers, often powered by non-renewable energy sources, exacerbates the sustainability issue, calling into question the long-term viability of this approach.