Analysis
This is a delightfully creative exploration of using a local Large Language Model (LLM) combined with Retrieval-Augmented Generation (RAG) for personal gaming. The author brilliantly bridges the gap between professional curiosity and practical testing, demonstrating how to safely evaluate AI capabilities before deploying them in a corporate environment. It's a fantastic example of how gaming can drive technological learning and innovation!
Key Takeaways
- •The author used their personal gaming experience to deeply understand how Retrieval-Augmented Generation (RAG) works.
- •Slay the Spire 2's English wiki was utilized as the perfect dataset to test English-to-Japanese translation capabilities.
- •This hands-on experiment highlights the importance of testing local Large Language Models (LLMs) in safe environments before corporate rollout.
Reference / Citation
View Original"申請を通すのに1〜2ヶ月かかる。そこまで苦労して導入してみたら「実用に耐えなかった」では洒落にならない。だから本番投入前に私用環境で本気で触っておきたかった。"
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