Fake AI
  • Introducing Fake AI
  • Core Features
  • Technical Overview
  • Use Cases
  • Key Benefits
  • Roadmap
  • Conclusion
  • Join Us on the Journey
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Technical Overview

How Fake AI Works

Fake AI employs a combination of machine learning, natural language processing, and blockchain analytics to deliver accurate results:

1. Media Verification:

  • Uses image and video recognition algorithms to identify signs of tampering or synthetic generation.

  • Combines linguistic analysis with metadata extraction to detect AI-generated text and speech patterns.

  • Employs deep neural networks to analyze audio frequencies and visual frames for manipulation.

2. Blockchain Analysis:

  • Integrates with blockchain APIs (e.g., Etherscan, Uniswap, and CoinGecko) to fetch real-time data.

  • Uses proprietary algorithms to identify red flags in trading volume, smart contracts, and wallet activity.

  • Leverages on-chain data to provide sentiment analysis and assess the trustworthiness of crypto projects.

3. Custom Alerts and Notifications:

  • Allows users to set preferences for tokens, wallets, or trends.

  • Delivers real-time notifications via email, SMS, or in-app alerts, ensuring users stay updated on critical events.

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Last updated 2 months ago