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. Challenges and Solutions

Challenge 3: User Accessibility and Engagement

Challenge Description

Despite the depth of analysis provided, the true utility of TensorScan AI hinges on its accessibility and ease of use for the average Ethereum network participant. Complex interfaces or convoluted access methods could hinder user adoption and engagement.

Solution: Browser Extension and Etherscan Integration

To maximize accessibility, TensorScan AI offers a user-friendly browser extension that integrates seamlessly with Etherscan.io, the most popular Ethereum blockchain explorer. This allows users to instantly see wallet categories and scores as they navigate Etherscan, providing a straightforward and intuitive way to access our platform's insights without disrupting their existing workflow.

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Last updated 1 year ago

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