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Apr 25, 2026 · Artificial Intelligence

How to Feed Massive Documents to an RAG System: Mastering the Art of Text Chunking

This article explains why proper text chunking is critical for Retrieval‑Augmented Generation, illustrates common pitfalls with real‑world examples, compares four chunking strategies (fixed length, recursive, structure‑aware, and code‑aware), and provides practical guidelines for chunk size, overlap, metadata handling, and a production‑ready pipeline.

AI retrievalLangChainRAG
0 likes · 21 min read
How to Feed Massive Documents to an RAG System: Mastering the Art of Text Chunking
Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Apr 6, 2026 · Artificial Intelligence

Why Rerank Beats Simple Retrieval in RAG: Practical Tips & Code

This article explains the limitations of Bi‑Encoder retrieval, introduces Cross‑Encoder rerankers, shows how a cascade of recall‑rerank‑generation improves answer quality, and provides concrete code, threshold‑filtering strategies, and domain‑specific fine‑tuning techniques for industrial RAG systems.

AI retrievalBi-EncoderCross-Encoder
0 likes · 20 min read
Why Rerank Beats Simple Retrieval in RAG: Practical Tips & Code
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Feb 25, 2026 · Artificial Intelligence

How Hologres Powers Fast Vector & Full‑Text Search for AI‑Driven Customer Service

The Taobao‑Tmall customer operations team built an integrated vector‑plus‑full‑text retrieval solution on Hologres, achieving millisecond‑level recall for massive unstructured knowledge bases, boosting intelligent客服, rule comparison, and sentiment analysis across multiple business scenarios.

AI retrievalFull-text searchHologres
0 likes · 12 min read
How Hologres Powers Fast Vector & Full‑Text Search for AI‑Driven Customer Service
DataFunSummit
DataFunSummit
Jul 23, 2025 · Artificial Intelligence

Multimodal RAG: Techniques, Challenges, and Scaling the Future of AI

This article presents a comprehensive overview of multimodal Retrieval‑Augmented Generation (RAG), detailing three implementation paths—semantic extraction, Transformer‑based, and Visual Language Model approaches—along with scaling strategies using tensor indexing, performance comparisons, and guidance on selecting the most suitable technical route.

AI retrievalMultimodal RAGTensor Indexing
0 likes · 12 min read
Multimodal RAG: Techniques, Challenges, and Scaling the Future of AI
High Availability Architecture
High Availability Architecture
Jun 18, 2025 · Backend Development

How WeChat Reading Scaled Its Backend Architecture Over a Decade

Marking ten years of WeChat Reading, this article details the backend's evolution from a monolithic service to a multi‑layered, micro‑service architecture with robust storage, RPC frameworks, book data platforms, account system redesign, and AI‑driven content retrieval, highlighting the technical challenges and solutions behind its scalability.

AI retrievalbackend architecturedata platform
0 likes · 18 min read
How WeChat Reading Scaled Its Backend Architecture Over a Decade
Ma Wei Says
Ma Wei Says
Feb 23, 2025 · Artificial Intelligence

How Microsoft’s PIKE‑RAG Builds Knowledge‑Driven AI Across Four Stages

The article explains Microsoft’s open‑source PIKE‑RAG system, detailing its four progressive stages—from knowledge‑base construction to creative multi‑agent reasoning—while describing the underlying modules, chunking strategies, multi‑granularity retrieval, and code snippets that enable specialized domain understanding and inference.

AI retrievalKnowledge GraphLLM
0 likes · 11 min read
How Microsoft’s PIKE‑RAG Builds Knowledge‑Driven AI Across Four Stages
NewBeeNLP
NewBeeNLP
Jan 2, 2025 · Artificial Intelligence

Unlocking Multimodal RAG: From Semantic Extraction to Scalable VLM Solutions

This article examines the implementation paths and future prospects of multimodal Retrieval‑Augmented Generation, covering semantic extraction, transformer‑based OCR, visual language models, scaling challenges, tensor indexing, and practical evaluations with tools like Infinity and ColPali.

AI retrievalDocument UnderstandingInfinity Database
0 likes · 12 min read
Unlocking Multimodal RAG: From Semantic Extraction to Scalable VLM Solutions
Alibaba Cloud Native
Alibaba Cloud Native
Oct 22, 2024 · Operations

How to Build and Manage a High‑Quality Enterprise Knowledge Base for AI‑Powered Q&A

This guide explains why a well‑structured, permission‑controlled enterprise knowledge base is essential for AI‑driven Q&A, outlines document format and naming standards, describes multi‑document organization principles, and provides step‑by‑step instructions for creating and managing knowledge bases in the Cloud Native environment.

AI retrievalDocument StandardsEnterprise Knowledge Base
0 likes · 20 min read
How to Build and Manage a High‑Quality Enterprise Knowledge Base for AI‑Powered Q&A