Summary
Highlights
The video introduces Codex, an AI coding agent tool, and highlights its new ability to perform file operations on local PCs. The main goal is to demonstrate how to use Codex to generate multiple variations of images using generative AI and save them to specific folders, automating what would otherwise be a manual task.
Codex is an AI agent tool developed by OpenAI, the creator of ChatGPT. It can automate tasks by allowing AI to handle them. Beyond code generation, it now supports file and application operations. Users can give instructions to Codex, which silently processes them and returns only the results, enabling parallel execution of tasks and automation of repetitive processes, similar to RPA (Robotic Process Automation).
To utilize Codex's file operation features, installing the Codex app is necessary. The app can operate on specific local PC folders or, with full permission, control the entire computer, though the presenter recommends caution for security reasons. The app is free to download, but a paid plan (like the 3,000 yen ChatGPT plan) is recommended for significant use due to limited free quotas.
The demonstration involves creating 10 variations of a character image based on different expressions and poses. An Excel file will be prepared with prompts for each variation. Codex will then use this Excel file and the base character image to sequentially generate images, create numbered folders for each image, and save them accordingly.
The presenter instructs Codex to generate 10 unique prompts for various expressions and poses suitable for YouTube thumbnails, based on an uploaded character image. Codex is asked to compile these prompts into an Excel file within the project folder. The output Excel file contains detailed prompts in both Japanese and English, along with suggested uses for each expression.
Following the prompt generation, Codex is instructed to use the created Excel file to generate images from number 1 to 10, referencing the original character. For each generated image, Codex must create a new numbered subfolder (e.g., 'number01') within an 'image generation' folder and save the respective image there.
Codex successfully generated 10 images with various expressions and organized them into corresponding folders as instructed. The presenter notes that while a human could perform these tasks, Codex excels by executing oral instructions and allowing the user to focus on other work. Limitations include potential for misinterpretations of nuanced instructions, similar to communicating with a new employee.
The presenter shares insights on the broader potential of Codex. The combination of local file operations and generative AI can facilitate diverse tasks, such as generating blog post structures with associated images and tags, or automating video thumbnail creation. Codex also proves valuable for repetitive tasks like organizing data based on content or analyzing codebases for old/unused components or security vulnerabilities.
A crucial point raised is data protection, especially for free or lower-tier plans, where input data may be used for AI learning. Users are advised against using personal or corporate confidential information, and to seek approval from superiors or IT departments for business use. Transparency with clients about AI-assisted work is also recommended.
The video concludes by reiterating the vast potential of Codex, suggesting applications beyond simple image generation, such as code conversion (e.g., jQuery to pure JavaScript) or system version upgrades (e.g., PHP version checks for vulnerabilities). These capabilities can significantly benefit larger enterprises struggling with such tasks, making work more efficient and easier.