EP 187 Carlos Perez on A Pattern Language for Generative AI

Jim talks with Carlos Perez about the ideas in his new book A Pattern Language for Generative AI: A Self-Generating GPT-4 Blueprint. They discuss GPT-4's ability to introspect on its capabilities, Christopher Alexander's idea of a pattern language, pattern language design, Jim's script-writing program, moving beyond ChatGPT to the OpenAI API, managing the context window, chain of thought prompting, the skyhook effect, the value of using tables, creation patterns, input-output pairs, the power of examples, punctuation, cloze prompts, compressing text, the mystery of LLM capabilities, an explanation for state emulation, the system prompt, explainability patterns, meta-levels of language, procedural patterns, design thinking prompts, the idea of a GPTpedia, composite patterns, in-painting vs out-painting, corrective patterns, 6 thinking hats, attribute listing prompts, problem restatements, inverted interaction, multiple-discipline prompts, modularity patterns, ChatGPT plugins, katas & meditations, and much more. Episode Transcript A Pattern Language for Generative AI: A Self-Generating GPT-4 Blueprint, by Carlos Perez "ScriptHelper-001: an experimental GPT-4 based Movie Script Writing Program," by Jim Rutt Artificial Intuition: The Improbable Deep Learning Revolution, by Carlos Perez Deep Learning AI Playbook: Strategy for Disruptive Artificial Intelligence, by Carlos Perez Artificial Empathy: A Roadmap for Human-Aligned Artificial Intelligence, by Carlos Perez Carlos E. Perez is a seasoned software architect and developer with 30 years of experience in bringing software systems from concept to production. He has authored books on Artificial Intuition, Fluency, and Empathy, with a primary focus on applying semiotic methods in Deep Learning. Carlos holds a Master's degree in Computer Science from the University of Massachusetts and has U.S. patents in expert systems and social networks.