2.5 Decentralized Compute Network

FileMarket AI will deploy a decentralized compute layer, enabling distributed AI processing, dataset validation, and annotation across a network of independent nodes. This infrastructure reduces reliance on centralized cloud providers while ensuring scalability, security, and cost efficiency. A major future goal is to establish a secure private environment where AI companies can train models on datasets without direct access to the raw data, ensuring both data privacy and regulatory compliance.

Key Functions of the FileMarket AI Compute Network

• AI Agents for Data Preprocessing & Validation – Nodes will run AI-powered agents to automate data filtering, quality checks, and preprocessing before datasets are stored or traded.

• Decentralized Labeling & Annotation – The network will support distributed annotation and human-AI collaborative labeling, ensuring high-quality, structured datasets.

• Scalable AI Model Training & Compute Leasing – AI companies will be able to rent compute power from the network to train and fine-tune their models directly within the FileMarket AI ecosystem.

• Secure Private AI Training (Future Implementation) – FileMarket AI aims to develop a private, encrypted training environment, where AI models can be trained on datasets without the raw data being exposed to companies, ensuring privacy and regulatory compliance.

By integrating AI-powered agents and secure AI training environments into the decentralized compute network, FileMarket AI will enable efficient, large-scale AI data processing while ensuring data security, privacy, and fair compensation for compute providers.