[{"data":1,"prerenderedAt":78},["ShallowReactive",2],{"term-v\u002Fvector":3,"related-v\u002Fvector":64},{"id":4,"title":5,"acronym":6,"body":7,"category":45,"description":46,"difficulty":47,"extension":48,"letter":49,"meta":50,"navigation":51,"path":52,"related":53,"seo":58,"sitemap":59,"stem":62,"subcategory":6,"__hash__":63},"terms\u002Fterms\u002Fv\u002Fvector.md","Vector",null,{"type":8,"value":9,"toc":38},"minimark",[10,15,24,28,31,35],[11,12,14],"h2",{"id":13},"eli5-the-vibe-check","ELI5 — The Vibe Check",[16,17,18,19,23],"p",{},"In AI, a vector is just a list of numbers. But it's a list of numbers that means something — like ",[20,21,22],"span",{},"0.23, -0.91, 0.44, ..."," might represent the concept 'angry cat.' The closer two vectors are in space, the more similar their meanings. Vectors are how computers handle meaning mathematically.",[11,25,27],{"id":26},"real-talk","Real Talk",[16,29,30],{},"In machine learning, a vector is a one-dimensional array of floating-point numbers representing a point in high-dimensional space. Embeddings are vectors, model weights are tensors of vectors, and activations throughout a neural network are vector operations. Similarity between vectors is measured via cosine similarity or dot product.",[11,32,34],{"id":33},"when-youll-hear-this","When You'll Hear This",[16,36,37],{},"\"Each sentence becomes a 768-dimensional vector.\" \u002F \"Find the nearest vector in the database.\"",{"title":39,"searchDepth":40,"depth":40,"links":41},"",2,[42,43,44],{"id":13,"depth":40,"text":14},{"id":26,"depth":40,"text":27},{"id":33,"depth":40,"text":34},"ai","In AI, a vector is just a list of numbers. But it's a list of numbers that means something — like [0.23, -0.91, 0.44, ...","intermediate","md","v",{},true,"\u002Fterms\u002Fv\u002Fvector",[54,55,56,57],"Embedding","Vector Database","RAG","Cosine Similarity",{"title":5,"description":46},{"changefreq":60,"priority":61},"weekly",0.7,"terms\u002Fv\u002Fvector","7daiPOUQEf6DIiJOh8b2W8-wPDEigrlAsGPbWNnsXfM",[65,68,71,75],{"title":57,"path":66,"acronym":6,"category":45,"difficulty":47,"description":67},"\u002Fterms\u002Fc\u002Fcosine-similarity","Cosine similarity measures how similar two things are by comparing the angles of their vectors.",{"title":54,"path":69,"acronym":6,"category":45,"difficulty":47,"description":70},"\u002Fterms\u002Fe\u002Fembedding","An embedding is turning words, sentences, or entire documents into lists of numbers (vectors) that capture their meaning.",{"title":56,"path":72,"acronym":73,"category":45,"difficulty":47,"description":74},"\u002Fterms\u002Fr\u002Frag","Retrieval Augmented Generation","RAG is how you give an AI access to your private documents without retraining it.",{"title":55,"path":76,"acronym":6,"category":45,"difficulty":47,"description":77},"\u002Fterms\u002Fv\u002Fvector-database","A vector database is a special database built to store and search embeddings.",1776518321839]