eWeek

What is Retrieval-Augmented Generation? How it Works & Use Cases

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...
Geeky Gadgets

Google’s Embedding Gemma On-Device RAG Made Easy for NLP Efficiency

What if the power of advanced natural language processing could fit in the palm of your hand? Imagine a compact yet highly capable model that brings the sophistication of retrieval augmented ...
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 ...
ascopubs.org

Retrieval-augmented large language models for clinical trial screening.

Exploring AI-generated content and professional guidelines in cancer symptom management: A comparative analysis between ChatGPT and NCCN guidelines. Performance of various RAG-LLMs for clinical trial ...
ascopubs.org

RadOncRAG: A Novel Retrieval-Augmented Generation Framework Improves Large Language Model Benchmark Performance in Radiation Oncology

Large language models (LLMs) show promise in assisting knowledge-intensive fields such as oncology, where up-to-date information and multidisciplinary expertise are critical. Traditional LLMs risk ...
InfoWorld

Retrieval-augmented generation, step by step

RAG is a pragmatic and effective approach to using large language models in the enterprise. Learn how it works, why we need it, and how to implement it with OpenAI and LangChain. Typically, the use of ...
Forbes

How Retrieval-Augmented Generation Could Solve AI’s Hallucination Problem

Large language models (LLMs) like OpenAI’s GPT-4 and Google’s PaLM have captured the imagination of industries ranging from healthcare to law. Their ability to generate human-like text has opened the ...
InfoQ

Reducing False Positives in Retrieval-Augmented Generation (RAG) Semantic Caching: a Banking Case Study

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Business Insider

AI chatbots spew out nonsense too often. But there's a solution: retrieval-augmented generation.

Retrieval-augmented generation is enhancing large language models' accuracy and specificity. However, it still poses challenges and requires specific implementation techniques. This article is part of ...
Forbes

The Power Of RAG: How Retrieval-Augmented Generation Enhances Generative AI

Rahul is the Chief Product and Marketing Officer for Innodata, a global data engineering company powering next-generation AI applications. Generative AI is transforming industries and lives. It ...