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3 Week Bootcamp: Building Realtime LLM Application
  • Introduction
    • Timelines and Structure
    • Course Syllabus
    • Meet your Instructors
    • Action Items
  • Basics of LLM
    • What is Generative AI?
    • What is a Large Language Model?
    • Advantages and Applications of Large Language Models
    • Bonus Resource: Multimodal LLMs and Google Gemini
  • Word Vectors Simplified
    • What is a Word Vector
    • Word Vector Relationships
    • Role of Context in LLMs
    • Transforming Vectors into LLM Responses
      • Neural Networks and Transformers (Bonus Module)
      • Attention and Transformers (Bonus Module)
      • Multi-Head Attention, Transformers Architecture, and Further Reads (Bonus Module)
    • Graded Quiz 1
  • Prompt Engineering
    • What is Prompt Engineering
    • Prompt Engineering and In-context Learning
    • Best Practices to Follow in Prompt Engineering
    • Token Limits in Prompts
    • Ungraded Prompt Engineering Excercise
      • Story for the Excercise: The eSports Enigma
      • Your Task
  • Retrieval Augmented Generation and LLM Architecture
    • What is Retrieval Augmented Generation (RAG)?
    • Primer to RAG: Pre-Trained and Fine-Tuned LLMs
    • In-Context Learning
    • High-level LLM Architecture Components for In-context Learning
    • Diving Deeper: LLM Architecture Components
    • LLM Architecture Diagram and Various Steps
    • RAG versus Fine-Tuning and Prompt Engineering
    • Versatility and Efficiency in Retrieval-Augmented Generation (RAG)
    • Key Benefits of RAG for Enterprise-Grade LLM Applications
    • Similarity Search in Vectors (Bonus Module)
    • Using kNN and LSH to Enhance Similarity Search in Vector Embeddings (Bonus Module)
    • Graded Quiz 2
  • Hands-on Development
    • Prerequisites
    • Dropbox Retrieval App in 15 Minutes
      • Building the app without Dockerization
      • Understanding Docker
      • Building the Dockerized App
    • Amazon Discounts App
      • How the Project Works
      • Repository Walkthrough
    • How to Run 'Examples'
  • Bonus Resource: Recorded Interactions from the Archives
  • Bootcamp Keynote Session on Vision Transformers
  • Final Project + Giveaways
    • Prizes and Giveaways
    • Tracks for Submission
    • Final Submission
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  1. Basics of LLM

What is a Large Language Model?

PreviousWhat is Generative AI?NextAdvantages and Applications of Large Language Models

Last updated 1 year ago

As we embark on this educational expedition, it's crucial to start with the fundamental question—What exactly are Large Language Models (LLMs)?

To answer this and set the stage for everything that will follow, we have a special video by our friend, Mike Chambers from Amazon Web Services.

What You'll Learn from the Video

  • An easy-to-understand explanation of what Large Language Models are

  • The diverse range of applications that LLMs empower

  • This video serves as an essential foundation and a smooth start for your learning journey.

(Credits: Build on AWS)