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

Local LLMs are fantastic, and they keep getting better at a staggering pace. I have non-negotiable reasons for preferring a local setup over relying on cloud giants like Claude or ChatGPT. Because of ...
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 ...
How-To Geek on MSN

Setting up a local LLM is the easy part—here's what you need to do with it next

Put your local AI to work.
VentureBeat

Karpathy shares 'LLM Knowledge Base' architecture that bypasses RAG with an evolving markdown library maintained by AI

AI vibe coders have yet another reason to thank Andrej Karpathy, the coiner of the term. The former Director of AI at Tesla and co-founder of OpenAI, now running his own independent AI project, ...
Finextra

What is RAG in fintech and how financial services are using it with LLMs to power AI innovation

To operate, organisations in the financial services sector require hundreds of thousands of documents of rich, contextualised data. And to organise, analyse and then use that data, they are ...
InfoWorld

How to improve the memory of AI agents

Retrieval-augmented generation enhances the performance of AI agents by expanding their recall. It can do this in three ...
Finextra

From RAG to Riches in a GenAI World: Some Jargon Explainers and Current Trends

Here's the simple 30 second definition, A deeper dive will follow. RAG (Retrieval Augmented Generation) is the buzziest word on the GenAI internet right now, more jargon to confuse the uninitiated.