Leverage Hazelcast's high-performance vector search for semantic search and fraud detection. Explore our scalable, low-latency solution today.
✅ Sign-up for a free cluster at → https://mdb.link/free-1ZIYVNvRVsY ✅ Get help on our Community Forums → https://mdb.link/community-1ZIYVNvRVsY ** Support for the '$vectorSearch' aggregation pipeline stage is available with MongoDB Atlas 6.0.11 and 7.0.2. ** ...
Oracle’s AI Vector Search supports retrieval-augmented generation (RAG), an advanced generative AI technique that combines LLMs and private business data to deliver responses to natural language questions. RAG provides higher accuracy and avoids having to expose private data by including it in the ...
Semantic_Search_Vector_db.ipynb Repository files navigation README Vector Database AI Apps AI Apps using Vector Database (Pinecone) Vector databses is eseential part of stack for developing LLM base applications. RAG - (retrieval augmented generation), retrieves the relevant data and use it as...
Oracle’s AI Vector Search supports retrieval-augmented generation (RAG), an advanced generative AI technique that combines LLMs and private business data to deliver responses to natural language questions. RAG provides higher accuracy and avoids having to expose private data by including it in the ...
Vector DatabaseSemantic Kernel Jul 4, 2023 Post comments count0 Post likes count2 Revolutionizing AI Search with Weaviate: An Interview with CEO Bob van Luijt John Maeda To use Weaviate with Semantic Kernel, visit the sample notebook on the Semantic Kernel GitHub repo. And if you like ...
一些VectorDB的例子包括Chroma、FAISS、Elastic Search、Milvus、Pinecone、Qdrant和Weaviate。插件（Plug-ins...
“Azure AI Search has provided us a way to use Azure OpenAI embeddings and perform vector similarity searches over our research & development documentation. Using vector search has been a fantastic experience, and the ability to perform hybrid search is amazing because t...
AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for b
Semantic ranker doesn't use generative AI or vectors for secondary level 2 (L2) ranking. If you're looking for vectors and similarity search, see Vector search in Azure AI Search.What is semantic ranking?Semantic ranker is a collection of query-side capabilities that improve the quality of an...