Social Authenticity Network
  • Introduction
    • What is #SocAuth?
    • AN Social Authenticity Network
    • Vision & Mission
  • PROBLEM AND SOLUTION
    • Problem Statement
    • Solution Statement
  • Markets and Competitors Analysis
    • Markets & Growth
    • AN vs Competitors
  • AN Social Authenticity Solutions
    • AN Neural Network
      • Network Services
      • Network Scaling
      • Network Clusters
    • AN AI Powerhouse
      • Interactions
      • Network Embedding
      • AI Modular Infrastructure
      • Dimensional Analysis
      • Blau Spaces
      • DeepNet
    • Use Cases
  • AN Social Authenticity Network
    • User Data Sovereignty
    • Community Validation
    • Genuine Reviews
    • Social Trust Metric (STM)
      • STM Features
    • AN ID/DID
      • ID/DID Solutions
  • AN SocAuth Applications
    • AN Mobile App
      • AN Social Feeds
      • App Services & Features
    • AN Interactive
      • Wearable & Mobility Devices
  • Tokenomics and Revenues
    • Tokenomics
      • Token Utility
      • User Rewards
      • Buyback & Burn
    • Revenues
  • User Centric Rewards System
    • Rewards System
      • ANr and ANp Points
      • Rewards Rates
      • User Contributions
  • Roadmap
    • 2023 - 2024
  • OUR TEAM
    • Team Info
  • AANN.ai Lab
    • Research
    • Development
  • Authentica Foundation
    • About Authentica
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  1. AANN.ai Lab

Research

PreviousTeam InfoNextDevelopment

Last updated 1 year ago

AANN.AI Labs research and development team leverages cutting-edge technologies to solve complex problems in various domains such as machine learning pipelines, natural language processing and graph data analysis.

We apply the state-of-the-art technologies to apply them to real-world problems that require extracting valuable insights from data. To achieve these goals, the team performs the following tasks:

  • Researching novel techniques and methods for natural language processing, deep learning and graph data analysis, such as neural networks, large language models, sentiment analysis, named entity recognition, clustering, classification, text generation, fact-checking, and more.

  • Developing and testing AI-based systems and applications that leverage these techniques and methods, such as intelligent assistants, chatbots, recommender systems, social network analysis, and more.

  • Evaluating and improving the performance, usability, and reliability of these systems and applications, using various metrics and feedback mechanisms.

We store and process diverse types of data from both our own application and external sources. This enables us to provide a robust and reliable metric of social authenticity that reflects the quality and credibility of online interactions.