Gradient Documentation
  • Introduction to Gradient
  • Preface
    • Purpose and Scope of This GitBook
    • How to Use This GitBook
  • Introduction to Liquid Staking
    • What is Liquid Staking?
    • The Importance of Liquid Staking in DeFi
    • Overview of Liquid Staking Tokens (LSTs)
  • The TAO Network and Bittensor
    • Introduction to the TAO Network
    • Bittensor: A Revolution in AI through Blockchain
    • Proof of Intelligence (PoI): A New Consensus Mechanism
    • Operation of the Bittensor Platform
    • Bittensor Use Cases
    • Advantages of Bittensor
  • The Gradient Protocol
    • Overview of Gradient
    • Key Features and Innovations
      • Incentivisation through GDT Tokens
      • The Role of GDT Token and swTAO
      • Seamless Staking Mechanism
      • Bridging the Worlds of Ethereum and the TAO Network
    • Tokenomics
    • Conclusion
  • Technical Architecture
    • Layer 1: The Blockchain
    • Security Protocols
    • Interoperability
    • Layer 2: The AI Integration Layer
    • Layer 3: User Interface and Interaction
    • Conclusion
  • Staking with Gradient
    • Introduction to Staking on Gradient
    • How to Stake wTAO on Gradient
    • Understanding swTAO: Benefits and Use Cases
    • Rewards and Incentives for Stakers
    • Conclusion
  • The TAO Bridge
    • Introduction to the TAO Bridge
    • How the Integrated Bridge Works
    • Use Cases and Advantages
    • Technical Implementation
    • Conclusion
  • Participating in the Gradient Ecosystem
    • Introduction
    • Becoming a Validator or Delegator
    • Governance and the Role of the GDT Token
    • Building on Gradient: Opportunities for Developers
    • Conclusion
  • Security and Risk Management
    • Introduction
    • Security Measures in Gradient
    • Understanding the Risks
    • Conclusion
  • Future Roadmap and Developments on the TAO Network
    • Introduction
    • Enhancements and Innovations
    • User Experience and Accessibility Improvements
    • Strengthening the TAO Network Connection
    • Vision for Gradient on the TAO Network
    • Conclusion
  • Getting Started with Gradient
    • Introduction
    • Setting Up Your Wallet for wTAO and GDT
    • Staking wTAO with Gradient
    • Accessing and Using the Tao Bridge
    • Participating in Governance and the Gradient Community
    • Conclusion
    • Glossary of Terms
    • Frequently Asked Questions (FAQ)
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  1. Technical Architecture

Layer 2: The AI Integration Layer

The centerpiece of Gradient’s innovation is what it calls the AI Integration Layer, or Layer 2: ‘The way in which artificial intelligence capabilities from the TAO Network can be plugged into Layer 2 means you can use AI and machine learning models to make running the staking protocol more efficient and effective.’

  • Integration with TAO Network's AI: Layer 2 utilizes the power of AI on the TAO Network, to provide automated staking strategies and market rewards through intelligent algorithms, including prediction models, staking rewards maximization and user experience factors.

  • Machine Learning Models: These machine learning models work inside Gradient to automatically adjust staking parameters in response to real-time data from the network. This is to ensure the protocol reacts to changes in the wider blockchain and DeFi ecosystem.

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Last updated 1 year ago

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