10K English words traced to 4 foundations(Space, Time, Energy, Pattern)
Think of each concept as sitting in a cloud of related words and ideas. The atlas keeps only the load-bearing connections — the simpler ideas you'd need to understand it first. Follow those edges down and every concept lands on one of four foundations: Space, Time, Energy, Pattern. The depth of that chain gives you a rough sense of where the concept sits in the emergent hierarchy. Search here : https://emergencemachine.com/atlas/search You can also compare two concept's graph, see what they have in common- https://emergencemachine.com/atlas/distance…
What it does
In the maker’s words, at launch
Think of each concept as sitting in a cloud of related words and ideas. The atlas keeps only the load-bearing connections — the simpler ideas you'd need to understand it first. Follow those edges down and every concept lands on one of four foundations: Space, Time, Energy, Pattern. The depth of that chain gives you a rough sense of where the concept sits in the emergent hierarchy. Search here : https://emergencemachine.com/atlas/search You can also compare two concept's graph, see what they have in common- https://emergencemachine.com/atlas/distance Each Concept can also be discussed and debated with site's AI- Prometheus. Tool: Python (asyncpg + custom DAG traversal) walked the "concepts" prerequisite graph down to its four foundation roots, then Graphviz (dot engine) rendered the SVG. PostgreSQL backs the live atlas; the chain image is built deterministically. Read more: https://emergencemachine.com/language-emergent-tool/
Does the same job
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Just a fun toy I wanted to make. I've been studying and playing around with language models lately and have always been intrigued by how words are processed by these models. Since the vectors generated by embedding models is in very high dimensional space, I thought it would be cool to reduce them to 3D vectors and visualise them myself. This is what I have so far!
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