1 Peeking inside the black box

 

In this chapter

  • You will learn what’s needed to develop useful GenAI applications.
  • You will get an intuition of how Large Language Models work.

GenAI is truly one of a kind.

While it feels natural to use tools like ChatGPT or Copilot these days, you realize what a strange animal a GenAI (short for Generative AI) application can be when you try to build one yourself.

How can AI systems communicate in fluent, human-like language? Does ChatGPT really think like we do, or is something else at play? In this book, we’ll explore what makes GenAI so unique, mysterious, and fascinating.

Our goal is to help you understand how GenAI applications work. We’ll consider what tasks they can handle well and where you should steer clear. Along the way, we’ll roll up our sleeves and build a few applications of our own using a low-code tool called LangFlow. To begin our journey, let’s take a look at the fundamental characteristics that set GenAI applications apart and make our ride worth the effort.

The uniqueness of GenAI programming

Let’s consider the key differences between programming a traditional application and a GenAI one. Both aim to define the behavior of an application that does something helpful for the user, generating a useful output given an input. But they get there in very different ways.

Dealing with LLMs

Building a GenAI application

Overcoming the “Stateless” Barrier

Providing Fresh Knowledge in Prompts

Why do you need this book to build real-world applications

Inside the LLM

Learning how to speak

Where everything starts: sentence completions

Understanding GPT-3: how a real LLM works

Embeddings

Context Calculation

Combination Process

Pre-training the model

Keeping the knowledge up to date

Summary