LLM-Visualized renders GPT-2 internals in 2D, 3D

This is a strong teaching demo: it turns opaque transformer math into something you can step through, but the biggest win is educational clarity rather than production utility.

• –Showing real forward-pass data gives the project more credibility than a generic “AI visualizer”
• –The KV-cache walkthrough is especially useful because that concept is usually hand-waved in transformer explainers
• –A split 3D/2D interface suggests the product is optimized for exploration and onboarding, not passive consumption
• –It should be especially valuable for students, workshop demos, and engineers who want intuition for attention mechanics
• –The main risk is novelty fatigue: the experience needs to stay fast and readable or the visual layer could overwhelm the lesson