TensorScan AI Whitepaper
  • 📊Executive Summary
  • 🌎Introduction
  • Project Overview
    • 🚀Project Overview
    • ⚙️Utilizing Bittensor for Decentralized Computing Power
    • 🤖AI-Driven Wallet Analysis
    • 🌐Browser Extension and Etherscan Integration
  • Tokenomics
    • 💰TensorScan AI Tokenomics
  • AI-Driven Wallet Analysis Architecture
    • 🤖AI-Driven Wallet Analysis Architecture
    • 🔄Data Ingestion and Preprocessing Module
    • 🛠️Feature Engineering and Dataset Preparation
    • 🤖Machine Learning Models
    • ⚙️Decentralized Computation with Bittensor
    • 🌐User Interface and Integration
  • Target Audience
    • 🎯Target Audience
    • 💼Casual and Serious Investors
    • 🔎Crypto Analysts and Researchers
    • 📶Traders
    • 👩‍💻Blockchain Developers
    • 🦍DeFi and NFT Communities
  • Challenges and Solutions
    • ⚙️Challenges and Solutions
    • 💻Challenge 1: High Computational Demand
    • 🔄Challenge 2: Dynamic and Evolving Data
    • 🚀Challenge 3: User Accessibility and Engagement
  • 🗺️Roadmap
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  1. Target Audience

DeFi and NFT Communities

Participants in decentralized finance (DeFi) and non-fungible tokens (NFTs) are keenly interested in the dynamics of the market and the credibility of fellow participants. TensorScan AI's analysis can inform better participation strategies in these volatile and innovative segments of the blockchain ecosystem.

By addressing the specific needs of these user groups, TensorScan AI aims to empower a broad spectrum of Ethereum network participants with actionable, AI-driven insights into EVM wallet transactions. Our platform enhances the user experience on Etherscan.io, making blockchain exploration more informative and strategic investment decisions more accessible.

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Last updated 1 year ago

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