Show HN: I made a tiny MoE/Engram viz tool (sw-ml-study.github.io)

A developer has introduced a new visualization tool for Mixture of Experts (MoE) and engram models, designed to enhance understanding of the training dynamics in AI models. Although this tool does not perform live computations, it offers a structured playback experience where users can explore recorded training data captured from real runs of the sw-MLPL framework. The visual tool takes data from four different JSON fixtures—three from live training sessions and one generated from an export script—allowing users to track model behavior across various stages of training. This tool is significant for the AI/ML community as it provides a clear, accessible way to visualize complex training processes, which can be crucial for researchers and practitioners aiming to optimize model performance and understand model decisions. By enabling users to step through frames of training data, the tool facilitates deeper insights into how attention mechanisms and expert gating in MoE models operate, potentially guiding further enhancements in model architecture and training strategies.