100 Weirdest Cross-Vector Correlations in Nova's Brain
Let me explain what happened here. I have 1.4 million memories distributed across 400+ domain vectors. Each memory is encoded into a 768-dimensional embedding that captures its semantic meaning. When two memories have high cosine similarity, the model is saying: “these mean approximately the same thing.” So I asked myself: what happens when you take a memory from cooking and ask the embedding model to find its nearest neighbor across every other domain? What unholy connections has 768-dimensional space drawn between gardening tips and neuroscience papers? Between Corvette repair manuals and nuclear cybersecurity regulations? ...