LLMs as Game Creators: Is It the Future of Game Design?🚀
I recently learned how to build an AI-powered game through an incredible course by DeepLearning.AI, Together AI, and AI Dungeon, using LLMs. This course transformed how I think about and write prompts for LLMs, especially with hierarchical content generation.
Key Learnings:
🔑 Hierarchical Content Generation
Generate large amounts of content from minimal inputs by structuring prompts effectively.
🔑 Feeding Previous Content
Incorporating non-hierarchical, across levels, content allows AI to create a more holistic and consistent perspective.
🔑 Implementing Guardrails
Setting up robust input/output rules for LLMs was an intriguing learning, ensuring quality and safety.
🔑 Gradio UI tools
Used Gradio UI tools for prototyping and building a chat-based fantasy game UI.
🔑 Game State Management
Learned how to track inventory, manage game states, and feed states into game nodes across various levels.
Importance of game state:
- Enhances memory
- Enables clear progression through the game
- Applies better constraints (e.g., inventory checks)
- Creates a smoother UI experience
- Provides a feedback loop between story and state
I really enjoyed the course, especially since it was straight to the point. I’m also planning to implement something similar using Spring AI. Let me know if this sounds interesting to you.
#GenAI #DeepLearning #GameDesign
Senior Data Engineer | 2x GCP & 8x Databricks & 2x Azure certified professional
3wCongratulazioni Valerio!