TagMemo Semantic Brain: Visualizing Retrieval Paths

When a question arrives, which concepts are selected first, and which connections are explored next? This 50-second English-language interface demo visualizes knowledge retrieval as a glowing 3D brain-shaped graph. Initial matches light up first, propagation follows the graph, and the side panel displays ranked concepts, regional state, and event logs. The video cycles through four example questions about a wave engine, work stress and sleep, a cat and childhood memories, and the Middle East and energy supply chains. Each query activates a different set of concepts, illustrating possible interfaces for retrieval routing, association expansion, and result filtering. Implementation and limits: the supplied recording is a front-end teaching demonstration. Its accompanying English HTML uses keyword matching, a fixed graph, programmed propagation rules, and automatically typed example questions. The brain shape and energy values are visual metaphors, not a neuroscience model, measured brain activity, or model confidence. The clip alone does not verify live Jev or StartLux calls, retrieval accuracy, or latency. A separate local bridge prototype can connect StartLux Decision to bounded choices for initial concepts, next connections, and stopping. That is a separate implementation path to evaluate; it is not evidence that the model powered this animation. This listing was prepared from the user-supplied video and accompanying local files. No inference service was started and no model experiment was rerun. The submitter previously described the decision layer as handling retrieval routing, relevance ranking, and result filtering. This clip shows the visualization; that model role still requires separate call traces to verify. Original demonstration: https://x.com/Ldou20/status/2114604949275562398