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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  1. Overview

Background

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Last updated 9 months ago

The crypto investment landscape is highly volatile, rapidly innovative, and full of diverse opportunities, attracting both seasoned investors and newcomers. However, retail users face significant challenges: Information Overload and Operational Complexity.

Information Overload: The market is inundated with news, updates, and analysis from numerous sources. This overwhelming flow makes it hard to discern credible information and stay updated, creating barriers for both new and experienced investors.

Operational Complexity: Managing crypto investments involves multiple platforms, chains and protocols for trading, staking, and yield farming, each with its own rules and security measures. Users must understand technical aspects like wallet management, transaction fees, and cybersecurity best practices. This complexity makes it difficult to efficiently and securely trade and manage portfolios.

Current AI and Tech Development

Recent advancements in Large Language Models (LLMs) and AI mark a new era of innovation. Latest LLMs have evolved from simple predictors to sophisticated tools for better NLP, information gathering, and summarization. However, they still struggle with independent reasoning and self-discovery. Therefore, the best current use case is as a search and answer, which will be applied in 's first-generation agent to facilitate smoother entry and effective information retrieval for retail investors.

We anticipate significant progress in upcoming LLM generations, particularly in cost reduction, on-device deployment, and multimodal capabilities, with improved reasoning being a possible advancement. We will collect data to evolve with these models, preparing to ultimately create optimized, on-device small models for truly intelligent financial tools.

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Dolphin.fm