Replicating a Language-Learning Comedy Short with Claude Code — Gemini as a Multimodal Sub-Agent
A new approach to generating comedy videos using AI has been developed, focusing on language-learning scenarios. The process utilizes a multimodal sub-agent, Gemini, to create videos that maintain comedic timing and context. This method has proven to be cost-effective and efficient, allowing for quick iterations and publishable quality outputs.
- ▪The project began with a language-learning AI app video that humorously highlighted a phonetic mistake.
- ▪The hybrid approach combines local heavy compute with a frontier model for editorial judgment, enhancing cost-effectiveness.
- ▪Initial attempts using only local models did not achieve publishable quality due to safety tuning issues.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3945785) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } shinji shimizu Posted on May 22 • Originally published at kotonia.ai Replicating a Language-Learning Comedy Short with Claude Code — Gemini as a Multimodal Sub-Agent #ai #productivity #machinelearning #python Introduction It started with a Pingo (language-learning AI app) short video that popped up on X. A Western woman learning Japanese tries to say "I ate a mango" (マンゴーを食べた), drops a dakuten, and instead says something like "I ate p*y" (マ◯コを食べた).
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