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Beginner

Introduction to Generative AI

A beginner-friendly deep dive into how generative AI works — from NLP and language models to transformers, LLMs, and foundation models. No math required.

How Machines Understand Language

  1. 1
    What is Natural Language Processing?3 min read
  2. 2
    How Machines Learned to Understand Language3 min read
  3. 3
    From N-Grams to Transformers: The Evolution of Language Modeling4 min read

From Language Models to LLMs

  1. 4
    Language Models Explained4 min read
  2. 5
    How LLMs Are Trained8 min read
  3. 6
    Building an LLM: The Full Pipeline6 min read

Working with Generative AI

  1. 7
    Three Ways to Customize AI: Prompt Engineering, RAG, and Fine-Tuning5 min read
  2. 8
    Prompt Engineering: Getting More From the Model You Already Have5 min read
  3. 9
    RAG: Giving a Model Access to Knowledge It Was Never Trained On5 min read
  4. 10
    Fine-Tuning: Reshaping a Model's Weights for a Specific Job5 min read
  5. 11
    Foundation Models4 min read

Practical Challenges in Generative AI

  1. 12
    Hallucinations and Inconsistency: When AI Gets It Wrong5 min read
  2. 13
    Budgeting and the Cost of Building AI4 min read
  3. 14
    Latency: Why AI Sometimes Feels Slow4 min read
  4. 15
    Running Out of Data: The Looming Data Shortage4 min read
  5. 16
    Build vs. Buy: Using AI Without Training Your Own4 min read

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