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Modern Generative AI with ChatGPT and OpenAI Models

You're reading from   Modern Generative AI with ChatGPT and OpenAI Models Leverage the capabilities of OpenAI's LLM for productivity and innovation with GPT3 and GPT4

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781805123330
Length 286 pages
Edition 1st Edition
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Author (1):
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Valentina Alto Valentina Alto
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Valentina Alto
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Table of Contents (17) Chapters Close

Preface 1. Part 1: Fundamentals of Generative AI and GPT Models
2. Chapter 1: Introduction to Generative AI FREE CHAPTER 3. Chapter 2: OpenAI and ChatGPT – Beyond the Market Hype 4. Part 2: ChatGPT in Action
5. Chapter 3: Getting Familiar with ChatGPT 6. Chapter 4: Understanding Prompt Design 7. Chapter 5: Boosting Day-to-Day Productivity with ChatGPT 8. Chapter 6: Developing the Future with ChatGPT 9. Chapter 7: Mastering Marketing with ChatGPT 10. Chapter 8: Research Reinvented with ChatGPT 11. Part 3: OpenAI for Enterprises
12. Chapter 9: OpenAI and ChatGPT for Enterprises – Introducing Azure OpenAI 13. Chapter 10: Trending Use Cases for Enterprises 14. Chapter 11: Epilogue and Final Thoughts 15. Index 16. Other Books You May Enjoy

ChatGPT: the state of the art

In November 2022, OpenAI announced the web preview of its conversational AI system, ChatGPT, available to the general public. This was the start of huge hype coming from subject matter experts, organizations, and the general public – to the point that, after only 5 days, the service reached 1 million users!

Before writing about ChatGPT, I will let it introduce itself:

Figure 2.25 – ChatGPT introduces itself

Figure 2.25 – ChatGPT introduces itself

ChatGPT is built on top of an advanced language model that utilizes a modified version of GPT-3, which has been fine-tuned specifically for dialogue. The optimization process involved Reinforcement Learning with Human Feedback (RLHF), a technique that leverages human input to train the model to exhibit desirable conversational behaviors.

We can define RLHF as a machine learning approach where an algorithm learns to perform a task by receiving feedback from a human. The algorithm is trained to make decisions...

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