EYE AI
  • 🧿Eye AI - Explained
  • Overview
    • 🧿The beginning of a new age
    • 🧿Crypto robotics / Eye-AI
      • 🧿Functionality
    • 🧿Metaverse Eye-AI
      • 🧿AI powering the Metaverse
    • 🧿Trend Tracking
    • 🧿Point to ETH network
    • 🧿Introduction of the Eye- AI API
      • 🧿Making requests
      • 🧿Models
        • ▪️List models
      • 🧿Completions
        • ▪️Create completion
      • 🧿Edits
      • 🧿Images
        • ▪️Create image edit
        • ▪️Create image variation
      • 🧿Embeddings
      • 🧿File
        • ▪️Upload File
        • ▪️Delete File
        • ▪️Retrieve file
        • ▪️Retrieve file content
        • ▪️Fine-tunes
      • 🧿Moderations
      • 🧿Parameter details
    • 🧿Terms of Artificial Intelligence
    • 🧿AI and the developers
    • 🧿How AI can help organizations
    • 🧿AI in the company
      • 🧿What is driving AI adoption?
    • 🧿AI as a strategic must and competitive advantage
      • 🧿Best practices to get the most out of AI
    • 🧿Turnkey AI is making AI easier to operationalize
    • 🧿From artificial intelligence to adaptive intelligence
    • 🪙Token Eye AI
      • 🧿Taxes
      • 🧿Token Metrics
    • 🕵️‍♀️Security AI
    • 🛤️Roadmap
    • 🫂Social Media
    • 📊Fairlaunch ETH - Pinksale
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  1. Overview

Terms of Artificial Intelligence

AI has become a generic term for applications that perform complex tasks that previously required information from the user, such as communicating with customers online or a game of chess. The term is often used interchangeably with its subfields, which include machine learning and deep learning. However, there are differences. For example, machine learning is focused on creating systems that learn or improve their performance based on the data they consume. It is important to note that while all machine learning is AI, not all AI is machine learning.

To get the full value of AI, many companies are making significant investments in data science teams. Data science, an interdisciplinary field that uses scientific and other methods to extract value from data, combines skills from fields such as statistics and computer science with business knowledge to analyze data collected from a variety of sources.

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Last updated 2 years ago

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