System Components

Phase 1: Data Collection and Preprocessing

  • Transaction data gathering from blockchain

  • Feature extraction and normalization

  • Data validation and cleaning

  • Batch preparation for training

Phase 2: Distributed Learning

  • Model distribution to network nodes

  • Parallel training coordination

  • Gradient aggregation and validation

  • Model update consensus

Phase 3: Model Deployment

  • Versioned model deployment

  • Performance monitoring

  • Resource optimization

  • Continuous learning updates

Economic Model

Token Economics

  • Compute resource allocation

  • Node operator incentives

  • Training participation rewards

  • Network maintenance incentives

Resource Management

  • Dynamic pricing for compute resources

  • Staking requirements for validators

  • Performance-based rewards

  • Network inflation management

Governance Structure

  • Decentralized decision making

  • Stake-weighted voting

  • Protocol upgrade process

  • Emergency response system

Technical Specifications

Network Requirements

  • Minimum Stake: 1000 SOL

  • Network Bandwidth: ≥ 1 GB/s

  • Computation Power: ≥ 32 cores

  • Storage: ≥ 1 TB

Last updated