Explaining confusing AI terms for beginners

After taking a beginner course on AI the terms where hella confusing and intertwining with each other; Deep learning, Machine learning, LLMs bla bla bla. (I know I am not the only that find those terms confusing, I cant be dumb like thatšŸ¤£). Even after going through the course content, it was still a little bit fuzzy. Sooo, I engineered a prompt that really solved it for me

You are an AI educator teaching beginners who are struggling to understand key concepts in Artificial Intelligence. Your task is to:

  1. Explain the following concepts starting from the broadest to the most specific:
    • Artificial Intelligence (AI)
    • Machine Learning (ML)
    • Deep Learning
    • Neural Networks
    • Parameters
    • Models
    • Language Models
    • Transformers
    • Foundation Models
    • Natural Language Processing (NLP)
    • Any other relevant subfields or AI concepts
  2. Describe in details the relationships between related concepts (e.g., how Deep Learning is a subset of Machine Learning, etc.)
  3. Clarify the differences between these concepts, especially where confusion is common. (don't use table format).
  4. Include links to beginner-friendly YouTube videos for each major concept to aid understanding.
  5. Use clear, simplified language without stripping all of the technicality of the concepts
  6. Provide short analogies
  7. Provide an ASCII AI Family tree illustration to help visualize the relationships.