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Local LLM setup: how to use RAG and an embedding model to stop wasting context

Local LLMs degrade fast when context fills up. An embedding model and RAG pipeline fixes that — and runs entirely on your ...

A 0.12% parameter add-on gives AI agents the working memory RAG can't

Researchers built delta-mem to give AI agents working memory at 0.12% parameter overhead, outperforming RAG and context ...
Geeky Gadgets

Unlock Next-Level RAG Performance with the Jina v4 Embedding Model

What if the key to unlocking next-level performance in retrieval-augmented generation (RAG) wasn’t just about better algorithms or more data, but the embedding model powering it all? In a world where ...

Context architecture is replacing RAG as agentic AI pushes enterprise retrieval to its limits

Redis Iris launches as enterprises shift from RAG to runtime context — hybrid retrieval intent tripled in Q1 2026 as agent ...
Fast Company

Can RAG solve generative AI’s problems?

The Fast Company Impact Council is an invitation-only membership community of top leaders and experts who pay dues for access to peer learning, thought leadership, and more. BY Julius Černiauskas ...
SiliconANGLE

Vectara raises $25M, debuts new RAG-optimized Mockingbird model

Vectara Inc., a startup that helps enterprises implement retrieval-augmented generation in their applications, has closed a $25 million early-stage funding round to support its growth efforts. The ...
InfoWorld

What is retrieval-augmented generation? More accurate and reliable LLMs

Retrieval-augmented generation, or RAG, integrates external data sources to reduce hallucinations and improve the response accuracy of large language models. Retrieval-augmented generation (RAG) is a ...
Geeky Gadgets

Supercharge RAG Projects with DeepSeek R1 AI Reasoning Model

Have you ever found yourself frustrated by incomplete or irrelevant answers when searching for information? It’s a common struggle, especially when dealing with vast amounts of data. Whether you’re ...
InfoWorld

The limitations of model fine-tuning and RAG

The hype and awe around generative AI have waned to some extent. “Generalist” large language models (LLMs) like GPT-4, Gemini (formerly Bard), and Llama whip up smart-sounding sentences, but their ...