Singularity Finance
  • Singularity Finance
  • Introduction
  • Background
    • Merger
  • Market Opportunity
    • Tokenise, Monetise and Decentralise the AI Economy
      • Hardware Layer
      • Platforms
      • Foundation Models and Knowledge Graphs
      • Model Hubs
      • Applications
      • Services
      • Data: Monetising Data Contributions
  • SFI Value Proposition
    • Dedicated Layer-2 for AI Economy
    • Core Pillars of the SFI L2
      • AI-Centric dApp
        • Singularity Rep Points
      • Tokenisation Framework
      • Identity Solutions
      • SFI Vaults
        • Architecture
        • Profit Framework
        • Operational Flow
        • Use Cases for SFI Vaults
        • Features
          • Strategies
          • Vault Management Dashboard
          • Risk Engine
          • Execution Engine
          • Fee Infrastructure
          • Governance
          • Router
          • Oracles
          • Zapper Framework
          • Keepers
      • Auxiliary Features
        • AI-Driven Market Making and Liquidity Provisioning
        • Prediction Markets
        • On/Off Ramps
    • Tokenised Data Centres
  • SFI L2
    • Introduction
    • L2 Architecture
      • Operational Model: Optimistic Rollups
      • Data
      • Sequencer
    • Core Features
      • Bridges
      • Indexers
      • Oracles
      • Relays
      • Verifiable Random Function (VRF)
      • Account Abstraction
      • Automation and Offchain Data Integration
  • LAunch
    • Testnet
      • Setup Guide
      • How to Participate in the SFI Testnet
      • FAQs
    • Mainnet
  • Tokenomics and Utility
    • Token Merge & Allocations
      • Allocation & Distribution
    • Token Utility
    • SFI Nodes
      • Details
    • Roadmap
    • Leadership Team
    • Conclusion
    • Appendix
  • Legal
    • SFI Token Terms & Conditions
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  1. Market Opportunity
  2. Tokenise, Monetise and Decentralise the AI Economy

Foundation Models and Knowledge Graphs

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Last updated 5 months ago

Foundation models are large-scale, pre-trained AI models, trained on a large set of data, that can be fine-tuned for specific tasks. They significantly reduce development time and resources by providing a robust general-purpose model for building applications. OpenAI's GPT-4, Google's Gemini, Facebook's Llama, etc., are a few examples of Web2 LLM models. However, these models are not only trained on text but also extend to audio and images, providing an opportunity to build a truly multimodal application. In the Web3 space, SingularityNET is at the forefront of building foundation models, with being a leading example of a fully decentralised AI framework being developed within the blockchain space.

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