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