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ChatGPT for Conversational AI and Chatbots
ChatGPT for Conversational AI and Chatbots

ChatGPT for Conversational AI and Chatbots: Learn how to automate conversations with the latest large language model technologies

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ChatGPT for Conversational AI and Chatbots

An Introduction to Chatbots, Conversational AI, and ChatGPT

Welcome to the exciting world of chatbots, conversational artificial intelligence (conversational AI), and ChatGPT!

In this introductory chapter, we introduce you to chatbots and conversational AI.

Our journey will begin by exploring the fundamentals of chatbots and their varying types, tracing the evolution of these digital conversationalists, and assessing their impact across multiple industries, such as e-commerce, customer service, and healthcare.

We’ll then look at how the conversational AI landscape has changed over time and the recent rapid rise of large language model (LLM) technologies, specifically the rise of OpenAI’s ChatGPT, Generative Pre-trained Transformer 3 (GPT-3), and GPT-4 models.

While journeying through this chapter, you’ll gain a comprehensive understanding of OpenAI’s ChatGPT. We’ll pull back the curtain on this marvel of technology to examine its development...

What are chatbots and conversational AI?

When we think of conversational AI, we reference an evolving field of AI that equips computer systems with the ability to communicate with humans using natural language (NL) in an interactive manner.

Over the past decade, conversational AI-powered voice- and text-based assistants have become embedded in our daily lives, enhancing user experience across diverse platforms and tackling a wide range of use cases. Revolutionizing the way businesses interact with their customers, they have become critical components of a modern digital strategy.

This section aims to provide a comprehensive overview of the field of conversational AI. It will delve into the history of chatbots and conversational AI, highlighting key milestones that have shaped the progression from rudimentary rule-based systems to sophisticated AI-driven chatbots. We will examine advancements in technology, such as NL understanding (NLU) and the progression from rule-based chatbots...

Evolution of chatbots and conversational AI

When chatbots first entered the scene, they were hailed as a groundbreaking evolution in technology, poised to revolutionize the way businesses communicate with their customers.

The early versions, however, were not as impressive as many had hoped. Coupled with the growth of chatbot platforms and the ease with which anyone could create a chatbot, this led to a bad user experience and an overall lackluster performance, which hampered their reputation.

One of the primary failings of early chatbots was their lack of sophistication and nuance in understanding and responding to human language. These rudimentary versions were generally rule-based, relying heavily on pre-programmed scripts. This meant they were only equipped to handle very specific inputs and could easily be thrown off by anything that deviated from their script. As a result, users often found themselves in frustratingly circular conversations, where the chatbot failed to...

Understanding conversational AI applications

Before looking at ChatGPT, it’s important to consider use cases for conversational AI applications and initially consider them in the context of what’s been possible with traditional conversational AI systems and technology.

Conversational AI has emerged as a powerful tool in numerous industries, from customer service to healthcare, banking, insurance, retail, and human resources. By automating routine tasks and enabling enhanced user interactions, conversational AI applications have changed the landscape of many domains. Let’s look at some existing examples of conversational AI.

Customer service

Conversational AI has been hugely successful in the customer support use case, streamlining processes and improving user experience in myriad ways. By adopting AI-powered chatbots and virtual assistants, businesses can handle large volumes of customer interactions seamlessly and efficiently.

Conversational AI offers...

What is OpenAI’s ChatGPT?

ChatGPT is OpenAI’s chat-specific LLM that uses ML to generate human-like responses to your text inputs.

Within just over a month of launching in November 2022, ChatGPT had over 100 million users. By February 2023, its total website visits had skyrocketed to a billion. This meteoric rise has made ChatGPT the fastest-growing consumer software application in history.

ChatGPT can explain scientific and technical concepts in a desired style or programming language, brainstorm basically anything you can think of asking... and yes, of course, hold complex conversations!

Understanding the large language technology behind ChatGPT

ChatGPT is built on a type of AI called an LLM. Within the domain of LLMs, there are two primary types: basic LLMs and instruction-optimized LLMs. Understanding the difference between these two types is important when examining OpenAI’s ChatGPT.

Exploring basic LLMs

Basic LLMs are programmed to predict...

Capabilities and applications of ChatGPT

LLMs offer a plethora of practical uses, with ChatGPT distinguishing itself through its advanced NLP capabilities. In this section, we unpack the array of applications that this technology brings to the table and a summary of the standout industry areas where ChatGPT holds the most potential. While many of these use cases are not necessarily new for conversational AI applications, it’s true to say that ChatGPT can potentially take on more advanced tasks.

Capabilities of ChatGPT

In the following sections, we’ll explore the various applications of ChatGPT, starting with NLU and NL generation (NLG) for chatbots and virtual assistants. Then, we’ll move on to its capabilities in machine translation, summarization, sentiment analysis, and content creation. Additional topics include its use in spam filtering, language tutoring, and software development. Finally, we’ll discuss the extended features available through...

Limitations of ChatGPT

ChatGPT, as with other LLMs, is not fallible and has several significant risks, limitations, and security considerations that are important to be aware of if you are going to use ChatGPT in production conversational AI use cases.

Limitations

There is no doubt that ChatGPT has some incredible capabilities, but let’s take a look at where things can go wrong.

Accuracy and depth

Probably the most well-known limitation and the one that has garnered the most effort to overcome is ChatGPT’s “information cutoff” date. The early GPT-4 models were trained on publicly available internet data, with cutoff dates as far back as 2021. The latest GPT models have shown improvements. According to OpenAI, the newest GPT-4 Turbo (gpt-4-turbo) has a knowledge cutoff of December 2023. However, beyond this point, it is not updated with the latest information or events. This limitation means that conversational AI implementations using ChatGPT...

Summary

In conclusion, in this chapter, we’ve seen how conversational AI has made steady progress from rule-based to AI-driven intent-based systems. By looking at the applications of ChatGPT, we’ve seen that as the capabilities of modern conversational AI systems have grown, so have the breadth and depth of use cases for conversational experiences. There are thousands of these systems, carrying out complex tasks across multiple industries.

From our initial focus on ChatGPT, we have seen it’s a powerful tool that has the capabilities to revolutionize the field of conversational AI by taking on more complex tasks and use cases that until recently have been difficult to achieve with modern conversational AI platforms. It offers a wide range of applications in many industries, including customer service, healthcare, finance, law, education, and more.

However, the chapter has also highlighted that it’s important to be aware of its limitations and risks...

Further reading

To explore more on the topics related to this chapter, you can visit the following links:

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Key benefits

  • Learn how to leverage ChatGPT to create innovative conversational AI solutions for your organization
  • Harness LangChain and delve into step-by-step LLM application development for conversational AI
  • Gain insights into security, privacy, and the future landscape of large language models and conversational AI
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

ChatGPT for Conversational AI and Chatbots is a definitive resource for exploring conversational AI, ChatGPT, and large language models. This book introduces the fundamentals of ChatGPT and conversational AI automation. You’ll explore the application of ChatGPT in conversation design, the use of ChatGPT as a tool to create conversational experiences, and a range of other practical applications. As you progress, you’ll delve into LangChain, a dynamic framework for LLMs, covering topics such as prompt engineering, chatbot memory, using vector stores, and validating responses. Additionally, you’ll learn about creating and using LLM-enabling tools, monitoring and fine tuning, LangChain UI tools such as LangFlow, and the LangChain ecosystem. You’ll also cover popular use cases, such as using ChatGPT in conjunction with your own data. Later, the book focuses on creating a ChatGPT-powered chatbot that can comprehend and respond to queries directly from your unique data sources. The book then guides you through building chatbot UIs with ChatGPT API and some of the tools and best practices available. By the end of this book, you’ll be able to confidently leverage ChatGPT technologies to build conversational AI solutions.

Who is this book for?

This book is for tech-savvy readers, conversational AI practitioners, engineers, product owners, business analysts, and entrepreneurs wanting to integrate ChatGPT into conversational experiences and explore the possibilities of this game-changing technology. Anyone curious about using internal data with ChatGPT and looking to stay up to date with the developments in large language models will also find this book helpful. Some expertise in coding and standard web design concepts would be useful, along with familiarity with conversational AI terminology, though not essential.

What you will learn

  • Gain a solid understanding of ChatGPT and its capabilities and limitations
  • Understand how to use ChatGPT for conversation design
  • Discover how to use advanced LangChain techniques, such as prompting, memory, agents, chains, vector stores, and tools
  • Create a ChatGPT chatbot that can answer questions about your own data
  • Develop a chatbot powered by ChatGPT API
  • Explore the future of conversational AI, LLMs, and ChatGPT alternatives
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 30, 2024
Length: 250 pages
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Language : English
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Table of Contents

14 Chapters
Part 1: Foundations of Conversational AI Chevron down icon Chevron up icon
Chapter 1: An Introduction to Chatbots, Conversational AI, and ChatGPT Chevron down icon Chevron up icon
Chapter 2: Using ChatGPT with Conversation Design Chevron down icon Chevron up icon
Part 2: Using ChatGPT, Prompt Engineering, and Exploring LangChain Chevron down icon Chevron up icon
Chapter 3: ChatGPT Mastery – Unlocking Its Full Potential Chevron down icon Chevron up icon
Chapter 4: Prompt Engineering with ChatGPT Chevron down icon Chevron up icon
Chapter 5: Getting Started with LangChain Chevron down icon Chevron up icon
Chapter 6: Advanced Debugging, Monitoring, and Retrieval with LangChain Chevron down icon Chevron up icon
Part 3: Building and Enhancing ChatGPT-Powered Applications Chevron down icon Chevron up icon
Chapter 7: Vector Stores as Knowledge Bases for Retrieval-augmented Generation Chevron down icon Chevron up icon
Chapter 8: Creating Your Own LangChain Chatbot Example Chevron down icon Chevron up icon
Chapter 9: The Future of Conversational AI with LLMs Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

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Om S Aug 07, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
As a tech enthusiast curious about conversational AI, I picked up Adrian Thompson's "ChatGPT for Conversational AI and Chatbots." This book starts with the basics of ChatGPT and conversational AI, making it easy to understand the core concepts.Thompson delves into LangChain, covering prompt engineering, chatbot memory, and vector stores. The hands-on approach, guiding you to build a ChatGPT-powered chatbot with your data, is particularly valuable.Pros:Comprehensive coverage from basics to advanced techniques.Practical, step-by-step examples.Insights into the future of conversational AI.Cons:Assumes some coding and web design knowledge.Dense information can be overwhelming.Focuses mainly on ChatGPT and LangChain.
Amazon Verified review Amazon
Paul Pollock Oct 23, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is a fantastic resource for anyone wanting to dive deeper into conversational AI. Adrian Thompson does a great job of breaking down complex concepts into practical, real-world applications. From mastering prompt engineering to deploying AI in production, it covers a lot of ground. I especially appreciated the sections on using LangChain for advanced workflows—it’s like giving your chatbot superpowers! Plus, the tips on managing the quirks of AI, like handling hallucinations, are super handy.The book strikes a great balance between technical detail and readability, making it suitable for both developers and AI enthusiasts. If you're looking to build smarter, more engaging chatbots, this book is definitely worth your time!
Amazon Verified review Amazon
Steven Fernandes Aug 06, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This comprehensive guide explores the intricacies of ChatGPT and its broader implications in conversational AI. Readers will thoroughly understand ChatGPT's capabilities and limitations, along with practical knowledge of conversation design. The book delves into advanced LangChain techniques, deepening into prompting, memory, agents, chains, vector stores, and various tools. It provides step-by-step instructions for creating a ChatGPT-powered chatbot tailored to personal data and utilizing the ChatGPT API for chatbot development. Additionally, the book forecasts the future directions of LLMs and potential alternatives to ChatGPT, making it a must-read for aspiring AI developers and enthusiasts interested in cutting-edge of conversational technology.
Amazon Verified review Amazon
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