Harness the power of AI with innovative, real-world applications, and unprecedented productivity boosts, powered by the latest advancements in AI technology like ChatGPT and OpenAI

Purchase of the print or Kindle book includes a free PDF eBook

Key Features:

• Explore the theory behind generative AI models and the road to GPT3 and GPT4
• Become familiar with ChatGPT's applications to boost everyday productivity
• Learn to embed OpenAI models into applications using lightweight frameworks like LangChain

Book Description:

Generative AI models and AI language models are becoming increasingly popular due to their unparalleled capabilities. This book will provide you with insights into the inner workings of the LLMs and guide you through creating your own language models. You'll start with an introduction to the field of generative AI, helping you understand how these models are trained to generate new data.

Next, you'll explore use cases where ChatGPT can boost productivity and enhance creativity. You'll learn how to get the best from your ChatGPT interactions by improving your prompt design and leveraging zero, one, and few-shots learning capabilities. The use cases are divided into clusters of marketers, researchers, and developers, which will help you apply what you learn in this book to your own challenges faster.

You'll also discover enterprise-level scenarios that leverage OpenAI models' APIs available on Azure infrastructure; both generative models like GPT-3 and embedding models like Ada. For each scenario, you'll find an end-to-end implementation with Python, using Streamlit as the frontend and the LangChain SDK to facilitate models' integration into your applications.

By the end of this book, you'll be well equipped to use the generative AI field and start using ChatGPT and OpenAI models' APIs in your own projects.

What You Will Learn:

• Understand generative AI concepts from basic to intermediate level
• Focus on the GPT architecture for generative AI models
• Maximize ChatGPT's value with an effective prompt design
• Explore applications and use cases of ChatGPT
• Use OpenAI models and features via API calls
• Build and deploy generative AI systems with Python
• Leverage Azure infrastructure for enterprise-level use cases
• Ensure responsible AI and ethics in generative AI systems

Who this book is for:

This book is for individuals interested in boosting their daily productivity; businesspersons looking to dive deeper into real-world applications to empower their organizations; data scientists and developers trying to identify ways to boost ML models and code; marketers and researchers seeking to leverage use cases in their domain - all by using Chat GPT and OpenAI Models.

A basic understanding of Python is required; however, the book provides theoretical descriptions alongside sections with code so that the reader can learn the concrete use case application without running the scripts.

Get hands-on with GPT 3.5, GPT 4, LangChain, Llama 2, Falcon LLM and more, to build LLM-powered sophisticated AI applications

Embed LLMs into real-world applicationsUse LangChain to orchestrate LLMs and their components within applicationsGrasp basic and advanced techniques of prompt engineering

Building LLM Powered Applications delves into the fundamental concepts, cutting-edge technologies, and practical applications that LLMs offer. Ultimately paving the way for the emergence of Large Foundation Models (LFMs) that extend the boundaries of AI capabilities.

The book begins with an in-depth introduction to LLMs. We then explore various mainstream architectural frameworks, including both proprietary models (GPT 3.5/4) and open-source models (Falcon LLM), and analyze their unique strengths and differences. Moving ahead, with a focus on the Python-based, lightweight framework called LangChain. We guide readers through the process of creating intelligent agents capable of retrieving information from unstructured data and engaging with structured data using LLMs and powerful toolkits. Furthermore, the book ventures into the realm of LFMs, which transcend language modeling to encompass various AI tasks and modalities, such as vision and audio.

Whether you are a seasoned AI expert or a newcomer to the field, this book is your roadmap to unlock the full potential of LLMs and forge a new era of intelligent machines.

Core components of LLMs' architecture, including encoder-decoders blocks, embedding and so onGet well-versed with unique features of LLMs like GPT-3.5/4, Llama 2, and Falcon LLMUse AI orchestrators like LangChain, and Streamlit as frontendGet familiar with LLMs components such as memory, prompts and toolsLearn non-parametric knowledge, embeddings and vector databasesUnderstand the implications of LFMs for AI research, and industry applicationsCustomize your LLMs with fine tuningLearn the ethical implications of LLM-powered applications

Software engineers and data scientists who want hands-on guidance for applying LLMs to build applications. The book will also appeal to technical leaders, students, and researchers interested in applied LLM topics.

We don't assume previous experience with LLM specifically. But readers should have core ML/software engineering fundamentals to understand and apply the content.