Dolphin.fm
  • 🐬Overview
    • Introduction
    • Background
    • The Vision
    • Roadmap
    • Core Components
  • 🌊Product Manual
    • Stage 1: Knowledge Discovery Trading Engine
    • Onboarding Wizard
    • Knowledge Discovery Trading Engine(KDTE)
    • One-Click Trading
    • One-Click Investment
      • Dual Investment with Downside Protection
      • Single Asset Yield Farming with Impermanent Loss Protection
    • Stage 2: Agent Engine and Ecosystem
  • 💡Technology
    • System Architecture
      • Online Service
      • Knowledge Service
      • AI Infrastructure
      • AI Agent Infrastructure
    • Large-Language-Model Specialized in Investing
      • Domain Knowledge
      • Tabular Understanding
    • Quantitative and Machine Learning Models
      • Main Strategy for Hedging Impermanent Loss
      • Time Selection and Loss & Rebalance Strategy
      • Volatility Predictions
  • 💎TOKENOMICS
    • Introduction to $DOLFM
    • $DOLFM Token Utilities
    • Quantitative Token Self-regulating Mechanism
      • Buyback & Burn Mechanism
      • Revenue-based Minting Algorithm
      • veToken Model
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  • Application Layer
  • AI Services Ecosystem
  • Data Services:
  • AI Inference Engine:
  • Infrastructure Layer
  1. Overview

Core Components

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Last updated 9 months ago

Application Layer

This layers includes the suite consumer-facing features we provide:

  • Knowledge Discovery Trading Engine (KDTE): easily search trending tokens, protocols, market news. The information will be updated, curated and filtered to mitigate spam.

  • Onboarding Wizard: a quick and intuitive way to effortlessly onboard to web3 with readily available investment tools.

  • Meme Trading: An expert-trained agent who specializes in meme trading. It analyzes patterns from meme trading activities and provides recommendations on optimal buy and sell points. It helps users manage wallet and place trades.

  • Investment: An expert-trained agent will onboard users to crypto investment products and provide personalized investment strategies and advice. It helps users create crypto investment portfolios.

  • Creator Agents: Creators can develop AI agents with specialized domain knowledge. Users can select their favorite agent in the AI agent marketplace.

AI Services Ecosystem

Data Services:

  • Market Data Services: These services handle the acquisition and management of curated market-related data.

  • Data Streaming Services: This component focuses on real-time data processing, allowing for the immediate analysis and utilization of data as it is generated, which is essential for applications requiring up-to-the-minute information.

  • Knowledge Services: These services are dedicated to organizing, storing, and retrieving knowledge from data, facilitating easier access to information and insights.

AI Inference Engine:

  • Fine-Tuning Engine: This engine is designed to refine AI models, tailoring them to specific tasks or domains to improve their accuracy and performance.

  • Retrieval-Augmented Generation (RAG): RAG integrates retrieval mechanisms into the generation process, enhancing the contextual relevance and precision of AI-generated content by leveraging external information sources.

  • Large Language Models (LLMs): LLMs provide a user-friendly flow, such as bots, using chat as an interface to onboard and empower users.

Infrastructure Layer

  • Database: The Database component is responsible for storing, managing, and retrieving data. It stores all the retrieved market data, user behavior data, and LLM generated answers and user feedback. It will become a massive and valuable asset once the user base scales.

  • Web3 Wallet: The Web3 Wallet component is integral to decentralized applications (dApps) and blockchain ecosystems. Integrated with an auto-generated web3 wallet, our users can avoid the hassle of manually creating wallets, managing private keys, etc. The agent handles all these tasks via a smart contract, ensuring independence and security.

  • Blockchain Governance: In the first stage, blockchain independently governs user reward incentives during onboarding. In the second stage, it ensures fair compensation for creators and verifies that users receive the authentic models they pay for.

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