Core Architecture & Key Functions

Key features

• Dynamic Fractional NFTs (dfNFTs) for Computation, AI & Applications

  • Converts computing resources, AI models, and applications into dfNFTs, enabling fractional ownership, leasing, and efficient execution.

  • Provides interoperability across decentralized computing environments, ensuring seamless deployment of AI-powered workloads.

• Smart Contract-Driven Resource Orchestration

  • Automates the allocation and execution of AI, applications, and computational tasks.

  • Uses predictive AI-based scheduling to enhance resource utilization and reduce inefficiencies.

• Modular Computation & AI Integration

  • Supports decentralized execution of AI inference, model training, and dApp services.

  • Allows applications to access distributed computing resources on a pay-per-use basis.

• Cloud-to-Edge AI Computing & Execution

  • Enables AI & application workloads to dynamically shift between cloud, fog, and edge layers.

  • Reduces latency for real-time AI model execution and decentralized application processing.

• AI-Powered Security & Privacy Enhancements

  • Use zero-knowledge proof (ZKP) and homomorphic encryption for secure computation.

  • AI-driven anomaly detection enhances trust and security in decentralized networks.

• Decentralized AI, Application & Computation Marketplace

  • Users can monetize computing, AI models, and application services.

  • Smart contracts facilitate trustless transactions and execution guarantees.

• Decentralized Data Collection & Processing for AI

  • Data sources are tokenized and secured via smart contracts, ensuring privacy and trust.

  • AI models access real-time, distributed data for enhanced learning and adaptive intelligence.

  • Supports privacy-preserving machine learning (PPML), allowing AI models to train without compromising user data security.