Happy New Year, everyone! Today, I will interpret Baichuan’s RAG approach. Baichuan Intelligent has a profound background in search; let’s see how they navigated the pitfalls of RAG! In general, Baichuan combines a long context model (192k) with search enhancement methods to address knowledge updates and reduce model hallucinations, achieving 95% accuracy on a dataset … Read more
Retrieval-Augmented Generation (RAG) is a technology that combines retrieval and generation, effectively addressing some issues of large language models (LLMs), such as hallucinations and knowledge limitations. With the development of RAG technology, vector technologies involved in RAG have gained attention, and vector databases are gradually being understood by everyone. Some established database vendors have also … Read more
The explosive popularity of ChatGPT proves the capabilities of large language models (LLMs) in generating knowledge and reasoning. However, ChatGPT is a model pre-trained on public datasets, which may not provide specific answers or results related to user businesses. So, how can we maximize the capabilities of LLMs using private data? LlamaIndex can solve this … Read more
✏️ Author Introduction: Huang Wei, Senior R&D Engineer at Trend Micro (China) Preliminary Research Trend Micro is a global leader in information security software, providing security solutions for software vendors and individual users worldwide. The author of this article is currently responsible for building mobile security apps and developing infrastructure. The workflow involves scraping external … Read more