2024
- Improving Customer Service with RAG: A Case StudyThis case study explores how implementing RAG drastically improved customer support experiences through better information retrieval and response generation.
- Practical Applications of RAG in Everyday LifeRetrieval-Augmented Generation (RAG) is making significant strides by integrating large language models with the factual reliability of data to applications that can enhance our daily lives.
- Real-World Applications of RAG in Various IndustriesA detailed look at how RAG is being used in different sectors like healthcare, finance, education, and customer service.
- Comparing RAG with Traditional NLP ModelsCompare RAG with traditional NLP models to better understand the advantages and limitations of each approach
- The Key Benefits of Using RAGRAG uses large language models with the reliability of factual data retrieval. RAG offers several advantages to AI applications.
- Markdown syntax guideGet started writing content in Markdown.
- MDX syntax guideUse interactive components in Markdown.
- Introduction to Retrieval-Augmented Generation: What You Need to KnowA comprehensive guide explaining the basics of RAG, its components, and how it works.
- What is Retrieval-Augmented Generation (RAG)? How does it work?Retrieval-Augmented Generation (RAG) is a method that combines two components of AI: retrieval and generation. Let's dive in and explore!
2023
2022