Data: 503 threat actors → 1,267 semantic chunks Vector DB: Chroma (8.9MB, <100ms search) LLM: llama3:8b (Ollama, local inference) Embeddings: 384-dim (sentence-transformers) Web UI: Flask-based ...

I had good success applying LeJepa to several image classification tasks. Now, I’m wondering whether there is a clever way to use LeJepa to obtain image embeddings that can be used for information ...

Even though traditional databases now support vector types, vector-native databases have the edge for AI development. Here’s how to choose. AI is turning the idea of a database on its head.

Chroma ATE Inc. will participate in SEMICON Taiwan 2025, presenting a full suite of breakthrough semiconductor test solutions. The showcase will focus on applications in AI chips, advanced packaging, ...