πŸ”§Core Functions Overview

Overview

Neural Network's core functions are designed to create a seamless, efficient, and secure decentralized AI computing ecosystem. Our platform integrates multiple sophisticated systems to deliver comprehensive AI training and inference capabilities.

πŸ–₯️ Computing Power Aggregation System

πŸ“‘ Multi-Source Node Support

  • Individual Contributors: Personal GPU/CPU resources from developers and enthusiasts

  • Institutional Partners: Computing resources from organizations and research institutions

  • Data Centers: Professional-grade infrastructure partnerships

  • Hybrid Deployments: Mixed resource configurations for optimal performance

⚑ Dynamic Resource Allocation

  • Real-time computing power assessment and allocation

  • Intelligent load balancing across nodes

  • Automatic scaling based on training requirements

  • Quality assurance through environment detection and compensation algorithms

πŸ€– AI Training Task Distribution and Execution

πŸ“‹ Intelligent Task Management

  • Automatic Task Grouping: Smart categorization of training requests

  • Optimized Resource Configuration: Matching tasks with appropriate computing power

  • Distributed Training Support: Seamless coordination across multiple nodes

  • Pre-deployment Optimization: Testing and debugging before full deployment

πŸ› οΈ Framework Compatibility

  • PyTorch - Full support for dynamic computational graphs

  • TensorFlow - Complete ecosystem integration

  • JAX - High-performance numerical computing

  • HuggingFace Transformers - State-of-the-art NLP models

  • Stable Diffusion & LoRA Training - Advanced image generation

  • Whisper / RWKV / LLM Fine-tuning - Specialized model training

⛓️ Blockchain Computing Power Tracking and Settlement

πŸ’° Smart Contract Settlement

  • Automated Payments: Instant settlement upon task completion

  • Transparent Pricing: Clear cost structure for all participants

  • Multi-token Support: Flexible payment options including native tokens

πŸ” Verification & Auditability

  • On-chain Result Tracking: All training outputs recorded on blockchain

  • Full Trace Paths: Complete audit trail from task submission to completion

  • zk-SNARK Integration: Privacy-preserving verification mechanisms

  • Security Controls: Intelligent dedicated core control for information security

🎯 Computing Node Orchestration & Reward Mechanism

πŸ“Š Performance-Based Classification

  • Computing Power Verification: Hardware capability assessment

  • Execution Efficiency Monitoring: Real-time performance tracking

  • Quality Scoring: Comprehensive node evaluation system

  • Dynamic Orchestration: Intelligent task assignment based on node capabilities

πŸ† Fair Reward Distribution

  • Contribution-Based Rewards: Proportional allocation based on actual contribution

  • Quality Bonuses: Additional rewards for high-performance nodes

  • Multi-chain Settlement: Support for single-chain and cross-chain payments

  • Flexible Token Options: Native tokens or combined currency rewards

πŸ“š AI Model Library and Community Collaboration

🌐 Shared Model Ecosystem

  • Community Model Sharing: Open platform for model distribution

  • Collaborative Training: Joint projects between community members

  • Model Evaluation: Comprehensive review and rating systems

  • Retraining Capabilities: Easy model fine-tuning and adaptation

πŸ”– Specialized Domain Support

  • Facial Recognition: Advanced computer vision applications

  • Text Generation: Natural language processing solutions

  • Video Analysis: Multi-modal content understanding

  • Custom Domains: Extensible framework for specialized use cases

πŸ“‹ System Modules Overview

πŸ”§ Module

🎯 Function Description

πŸ“€ Task Publishing System

Supports AI developers in publishing training/inference tasks, setting budgets, defining model structures, and establishing acceptance criteria

πŸ–₯️ Computing Power Access System

Enables nodes to join the platform through container plugins or dedicated clients, submit device information, and receive task allocations

🧠 Intelligent Scheduling System

On-chain scheduling contracts that automatically allocate computing nodes based on task parameters, supporting pluggable scheduling strategies (e.g., reputation priority)

βœ… Decentralized Training Verification

Real-time on-chain snapshots of node training processes with multi-node re-verification, ensuring authentic and reliable results

πŸ’Ύ Data and Model Storage

Integration with Arweave/IPFS for persistent storage of data and model intermediate results, ensuring long-term accessibility and auditability

πŸ’° Incentive and Settlement Module

Smart contract-driven dynamic settlement mechanism, distributing token rewards based on computing time, result quality, reputation weight, and other dimensions

βš–οΈ Node Governance and Punishment

Automated system for freezing stakes of abnormal behavior nodes and subjecting them to DAO arbitration, maintaining healthy platform operations


These core functions work together to create a robust, scalable, and user-friendly platform that democratizes access to AI computing power while maintaining high standards of security and performance.

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