This book provides a solid foundation in generative AI, focusing on the principles of prompt engineering to effectively work with AI models like GPT-4 and Stable Diffusion. It covers the structure of AI model interactions, transforming application problems into model training domains, and the influence of LLM and diffusion model architectures. The book includes practical examples and advanced techniques for text and image generation, as well as building AI-powered applications in domains such as natural language processing, text and image generation, and code.
Mike Taylor, co-author of Prompt Engineering for Generative AI and first two-time guest of the pod joins us to "delve" into the important questions around getting the best answers out of ChatGPT and the like.
Learn about the principles of prompt engineering, the role of generative AI in analytics, and how to effectively use AI for data cleaning, code generation, and more.
▶️ Watch on YouTube
Links from the show:
00:00 Introduction and Casual Banter
01:16 Speed Reading and Da Vinci Jokes
02:52 Introducing the Guest: A Modern Day Da Vinci
05:19 Diving into Prompt Engineering
08:35 Generative AI in Analytics and Marketing
14:37 Practical Applications and Challenges
18:38 Prompt Engineering Tips and Tricks
24:54 Crafting Effective Prompts for Social Media
25:37 The Value of Prompt Engineering in Automation
26:39 Exploring Prompt Marketplaces and Tool Use
27:51 Automating Prompt Creation and Its Implications
29:28 The Future of Prompt Engineering as a Skill
32:50 Applications of AI in Copywriting and Image Generation
34:58 AI in Data Extraction and Analytics
45:12 Leveraging AI for Industry Insights and Efficiency
48:45 Conclusion and Book Pitch
Measure Up 
