a. Resource Solution
The Building Blocks of AI Computation
AI applications require three essential types of resources:
Computational Power – The backbone of AI inference and training, traditionally monopolized by cloud giants, creating cost and accessibility barriers.
Storage – Essential for managing datasets, model weights, and AI-generated outputs, requiring decentralized solutions to prevent single-point failures.
Network – A critical component for distributed AI workloads, where latency and bandwidth optimization determine real-time performance and efficiency.
In the centralized model, these resources are controlled by large cloud service providers, creating inefficiencies, high costs, and restricted access. HolmesAI redistributes these resources across a decentralized network, ensuring fair participation, transparency, and efficiency. Contributors of computing power are incentivized through a tokenized rewards system, making decentralized AI both sustainable and economically viable.
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