📐 Semantic Vector Embeddings

Local High-Speed Vectorization

Rather than sending knowledge to cloud APIs, the ULTRON unified memory core uses local, fast embeddings (ONNX / FastEmbed / BGE-small) running locally on the Intel CPU or NVIDIA dGPU.

Hybrid Search Architecture

To achieve 100% recall precision, retrieval blends:

• Dense Vectors (Cosine Distance): Semantic meaning, conceptual parallels.
• Sparse BM25 (Keyword Match): Exact symbol names, function signatures, command flags.
• Graph Reranking: Distance in the Bi-Temporal_Knowledge_Graphs network.