🧠 Generative AI & Amazon Bedrock – Simple Summary

1. What is Generative AI?

  • Generative AI (Gen-AI): A type of deep learning that creates new data similar to what it learned.
  • Can generate:
    • Text
    • Images
    • Audio
    • Code
    • Video
  • Example: ChatGPT generating human-like text.

2. Foundation Models (FM)

  • Large AI models trained on diverse datasets.
  • Expensive to build (can cost tens of millions of dollars).
  • Examples:
    • OpenAI (GPT-4o)
    • Meta (LLaMA)
    • Google (BERT)
    • Amazon (Titan)
    • Anthropic (Claude)
  • Some are open-source (free), others commercial (paid).

3. Large Language Models (LLMs)

  • Special AI for human-like text generation.
  • Trained on huge text datasets (books, websites, articles).
  • Billions of parameters.
  • Tasks:
    • Translation
    • Summarization
    • Q&A
    • Content creation

4. How Generative Language Models Work

  1. Prompt: You give an instruction.
  2. Processing: The model predicts possible next words.
  3. Output: Chooses words based on probability.
  4. Non-deterministic: Same prompt → different answers.

5. Amazon Bedrock Overview

  • AWS service for building Gen-AI apps.
  • No server management – fully managed.
  • Pay-per-use.
  • Unified API for multiple foundation models.
  • Built-in features:
    • RAG (Retrieval-Augmented Generation)
    • LLM Agents
  • Strong focus on security, privacy, and responsible AI.

6. Amazon Bedrock & Foundation Models

  • Gives you a private copy of the model.
  • You can fine-tune it with your data.
  • Your data is not used to train the public model.
  • Amazon Titan:
    • AWS’s high-performance FM.
    • Supports text, image, multimodal.
    • Customizable.
    • Smaller models = more cost-effective.

7. How to Use Amazon Bedrock

  1. Request model access.

  1. Test with a single prompt.

  1. Try image generation playground.

8. Example Models

  • Amazon Titan
  • Meta LLaMA
  • Anthropic Claude
  • Stable Diffusion (image generation)