【AI漫画書き方】NotebookLMで100ページ超えのAI長編漫画をコピペレベルで自動生成！AIスライド機能を限界突破させるAI仮想学習と創発プロンプトの極意を完全伝授！

👇【Basic】How to Create AI Comics with Nano Banana    • 【AI漫画の描き方】GoogleAI Gemini ナノバナナProでAI漫画ノウハ...   👇【Advanced】AI Comics with NotebookLM: Powerful Panel Layout Techniques!    • 【AI漫画家へ】NotebookLMで迫力のあるコマ割りのAI漫画を描くためのプ...   👇【Advanced】Creative Uses of NotebookLM    • NotebookLMのクリエイティブな使い方を解説！使用したプロンプトもお見せします...   👇AI Comics Drawn with NotebookLM This Time https://www.pixiv.net/artworks/141879... 👇AI Picture Books Can Also Be Created with Advanced NotebookLM Slide Techniques!    • 【AI絵本】NotebookLMでAI絵本の描き方を解説！AI絵本の構造やプロンプト...   ■ [Next-Generation AI Manga Production] Long-Form Comic System Using NotebookLM and Gemini This video provides a complete explanation of an innovative workflow for producing long-form AI manga at an overwhelming speed, utilizing Google's "NotebookLM" and the integrated image generation AI "Nano Banana." Traditional image generation AIs primarily create manga page by page, leading to significant challenges such as character and story inconsistencies. However, by applying NotebookLM's "Slide Deck" function and structuring each slide as a single manga page, it becomes possible to generate dozens of pages of manga at once with a single button click. This system is a completely new manga generation approach, fusing story AI (which helps AI understand narratives) with image generation AI. ■ [Core Technology] Virtual Learning and Emergent Prompting To prevent character inconsistencies and world-building breakdowns in AI manga, this video maximizes the use of NotebookLM's source functionality. By adding information such as character images, detailed settings, worldview, and past plot summaries as sources, the AI ​​undergoes "virtual learning." This allows the AI ​​to function as a knowledge base with long-term memory. Furthermore, "emergent prompting" is employed for prompt input. By having the AI ​​read the premise story and setting before instructing it to generate scenes, the AI ​​itself understands the context and automatically connects and emerges the necessary characters, dialogue, and descriptions to create high-quality comics. ■ [Enhancing Stability] The Secret to Context-First Approach To leverage the characteristics of Gemini and NotebookLM, it is crucial to input prompts in a "context-first" order. Instead of writing the context after an instruction like "Turn the following into a comic," as is often seen in ChatGPT, detailed context such as "worldview, characters, and current situation" is described first, and then the instruction "Turn this scene into a comic" is given at the end. In NotebookLM, which excels at understanding long texts and context, adhering to this order allows the AI ​​to deeply understand the situation, resulting in a more stable and consistent story development and image generation. ■ [Practical Workflow] Correction, Combination, and Image Extraction from PDF This section covers practical solutions to issues unique to AI generation, such as "garbled text" and "distortion of character faces and hands." While NotebookLM doesn't allow direct image editing, it enables partial regeneration via prompts, such as "correct the text in the bottom left panel on page 3." To dramatically increase the success rate, we recommend the "montage (combination) method," which involves generating 3-5 copies of the same page and extracting and combining only the panels with good faces or clear text. The completed slides are output in landscape (16:9) PDF or PowerPoint format. A separate AI such as Claude is used to analyze the PDF, and each page is precisely divided and extracted into independent image files to create the final work. ■ [An Unending Story] How to Create a Sequel with Long-Term Memory The secret to continuously drawing a story without interruption as a long-running manga lies in the AI's "memory updating." Once an episode is completed, the story summary and history of that manga are compiled into a text file and added/updated to the NotebookLM source. When generating the next episode, the AI ​​refers to the added past context as an official record, allowing it to generate a sequel that naturally connects the story while accurately carrying over previous events and character situations. By repeating this cycle, NotebookLM functions perfectly as a "story AI with memory" that can endlessly spin long-form manga. [Profile] Wonder Sato Motohiko Born 1977 Founder of MBBS & AI Co-creation Innovation. After working at medical and psychology research institutes, he became independent and is currently researching generative AI (ChatGPT, Claude, Gemini, etc.) and the mind-body relationship. His main works include "Easy Prompts" (Geijutsu Shinbunsha) and "Oriental Medicine and the Latent Motor System" (Taniguchi Shoten). He has also written a series for a specialist journal for two years and is currently developing AI co-creation writing while also writing academic papers. We are developing AI co-creation prompt engineering by applying psychology, counseling, and coaching techniques to AI. We als...