ChatGPT and Bard for business automation : achieving AI-driven growth / Tom Taulli.
Taulli, Tom.
2023
QA76.9.N38 T38 2023
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Title
ChatGPT and Bard for business automation : achieving AI-driven growth / Tom Taulli.
Author
Taulli, Tom.
ISBN
9781484298527 (electronic bk.)
1484298527 (electronic bk.)
1484298519
9781484298510
DOI
https://doi.org/10.1007/978-1-4842-9852-7
Published
Berkeley, CA : Apress L. P., 2023.
Language
English
Description
1 online resource (181 p.)
Item Number
10.1007/978-1-4842-9852-7 doi
Call Number
QA76.9.N38 T38 2023
Dewey Decimal Classification
006.35
Summary
The launch of ChatGPT represents an epochal event. Its on par with the emergence of the Internet or the launch of the iPhone. But the impact could be even more transformative. ChatGPT crossed over 100 million users in two months. This was the fastest to do so ever. It took TikTok nine months. No doubt, building applications with ChatGPT is quickly become strategic and a must-have. This is why developers must understand this technology and now. And this book will show how. It details how ChatGPT technology works, such as with the transformer and diffusion models. It also illustrates how to use the various APIs, such as GPT-4, ChatGPT, Bard, and Bedrock. This includes understanding embeddings, fine tuning of the models, using zero-shot and few-shot learning, and adjusting the parameters like temperature. This book focuses on the practical uses of this powerful technology. There are step-by-step tutorials on how to create apps for blog generation, sentiment analysis, language translation and integration. This book is an indispensable guide for any developer who wants to be a part of the ChatGPT revolution. What You Will Learn How generative AI models work, their uses cases, benefits and risks Learn about the various generative AI APIs like GPT-4, ChatGPT, Bard, Bedrock and Anthropic Learn about the elements of this technology like prompt engineering, embeddings, fine tuning, and zero-shot/no-shot learning See how to develop various applications, such as to detect sentiment, create blogs and translate languages Who This Book is For Data scientists or data engineers who want to learn how to leverage generative AI APIs, Software engineers or developers who are looking for a new job role in generative AI, Software engineers and developers who want to see how they can integrate generative AI APIs into existing IT environments, Founders or those who work at startups who want to see how to use generative AI.
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ChatGPT and Bard for Business Automation
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Intro
Contents
About the Author
Chapter 1: New World of Automation
The Impact
Agenda
Conclusion
Chapter 2: ChatGPT
OpenAI
What Is ChatGPT?
Custom Instructions
Plugins
Advanced Data Analysis
Data Analytics
Optical Character Recognition (OCR)
Image Editing
Web Browsing
Usage Policies
ChatGPT Enterprise
Conclusion
Chapter 3: Bard
The Technology
How Bard Works
Tables
Images
Duet AI
Alternatives
Bing Chat
Claude 2
HuggingChat
Inflection AI
Conclusion
Chapter 4: Prompt Engineering

The Challenges with Prompt Engineering
Hire a Prompt Engineer?
Context
Be Specific
Instructions
Zero and Few-Shot Prompting
Parameters and OpenAI Playground
Resources
Conclusion
Chapter 5: Use Cases
Human Resources
Legal
Customer Support
Sales
Marketing
Finance
Project Management
Product Development
AI Code Development Tools
AI Text-to-Image Systems
Conclusion
Chapter 6: Change Management
Definition
Types of Change Management
The Culture
Roles
Change Advisory Board (CAB)
Training
Change Fatigue
The Plan

Implementation
Tools
Boiling the Ocean
Conclusion
Chapter 7: Understanding AI
Brief History
What Is AI?
Machine Learning
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Deep Learning
Flavors of Deep Learning
The Issues with Deep Learning
Generative AI
What Makes Generative AI Different
GANs
VAEs
Diffusion Models
The Transformer
Conclusion
Chapter 8: Data
Types of Data
Understanding Big Data
Database Systems
The Cloud
Data Strategy for AI
Data Collection
Data Evaluation
Data Wrangling

Data Labeling
How Much Data?
Conclusion
Chapter 9: Risks
Bias and Discrimination
Black Box
Physical Safety
Deepfakes
Cybersecurity
Privacy Laws and Regulations
Junk Content
The Cloud
Data Problem
Intellectual Property
Conclusion
Index

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