How xMemory cuts token costs and context bloat in AI agents

When standard RAG pipelines retrieve redundant conversational data, long-term AI agents lose coherence and burn tokens.
Morningstar

Zilliz Open Sources Industry-First Bilingual "Semantic Highlighting" Model to Slash RAG Token Costs and Boost Accuracy

REDWOOD CITY, Calif., Jan. 30, 2026 /PRNewswire/ -- Zilliz, the company behind the leading open-source vector database Milvus, today announced the open-source release of its Bilingual Semantic ...
Geeky Gadgets

Llama 2 Retrieval Augmented Generation (RAG) tutorial

If you are interested in learning more about how to use Llama 2, a large language model (LLM), for a simplified version of retrieval augmented generation (RAG). This guide will help you utilize the ...
SD Times

Progress Software Announces General Availability of MarkLogic Server 12 and Breakthrough Results with Semantic RAG

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...
dbta

DataStax Integrates with Microsoft Semantic Kernel to Power RAG App and Agent Development

DataStax, the generative AI data company, is announcing an integration with Microsoft Semantic Kernel—an open-source SDK that simplifies the building of agents with an organization’s existing code.
Geeky Gadgets

How to use Embeddings in RAG with Llama-Index

In the realm of natural language processing (NLP), the concept of embeddings plays a pivotal role. It is a technique that converts words, sentences, or even entire documents into numerical vectors.