Unveiling an Accidental Innovation: How I Built a Sparse Mixture of Experts
In my journey through game development, I stumbled upon a groundbreaking concept: a Sparse Mixture of Experts (MoE). This development emerged while experimenting with boids, a simulation algorithm that mimics flocking behavior. Here’s what I discovered along the way:
- Spatial Partitioning: I initially grappled with spatial hashing to optimize boids, moving from costly O(n²) calculations to efficient O(1) lookups.
- Performance Boosts: Implementing spatial hashing enabled thousands of boids in real-time, transforming performance on low-end devices.
- Procedural Content Generation: I harnessed machine learning to automate level generation, ultimately developing an ensemble method that led to my accidental Sparse MoE.
Key Insights:
- Modular Improvements: Each ensemble learned from limited obstacles, enabling generalization across diverse game modes.
- Real-World Application: My structure mirrored modern AI architectures like GPT-4, showcasing how decomposing complex problems leads to transformative solutions.
Are you exploring innovative AI trends? Join the conversation—share your thoughts and let’s connect!
