The Huawei Cloud Developer Alliance creates a tech sharing platform for developers and partners, gathering Huawei Cloud product knowledge, event updates, expert talks, and more. Together we continuously innovate to build the cloud foundation of an intelligent world.
This article explains how static_cast provides compile‑time type safety, clearer intent, and zero runtime overhead compared to C‑style casts, covering basic arithmetic, pointer, and enum conversions, the compiler’s processing steps, practical examples, and best‑practice recommendations for safe C++ coding.
This article explores the rise of AI agents—from their definition as intelligent digital assistants powered by large language models to their evolution through planning, memory, and tool use—highlighting real‑world applications, core technical mechanisms, code implementations, and future trends such as autonomy, multimodal fusion, standardization, and safety considerations.
This article reviews the emerging post‑Transformer research landscape, covering linear state‑space models, efficient attention approximations, MLP/conv/RNN hybrids, sparse and causal attention mechanisms, and outlines future trends that may complement or replace the classic Transformer architecture for handling ultra‑long sequences.
Next.js, a React‑based frontend framework, combines SPA and MPA advantages through hybrid rendering, offering automatic file‑system routing, flexible SSR/SSG/CSR/ISR strategies, built‑in API routes, image optimization, middleware and edge computing, making it ideal for e‑commerce, CMS, enterprise dashboards and SEO‑critical sites.
This article explores the rise of multimodal agents that integrate language, vision, and action, detailing their core architecture, model fusion strategies, decision chain, and a practical Python implementation using GPT‑4o‑mini and BLIP, while also discussing future extensions such as reinforcement learning and robotic control.
This guide explains why HBase may fail to connect to Zookeeper in distributed storage environments and provides step‑by‑step troubleshooting, including service checks, configuration validation, network testing, log analysis, version compatibility, service restarts, and Java code examples with retry logic.
This article presents a structured, step‑by‑step learning path that guides beginners from Python fundamentals through AI API mastery, Retrieval‑Augmented Generation, deep MCP protocol knowledge, and advanced multi‑agent development, complete with practical code examples and performance‑monitoring techniques.
This article breaks down five fundamental concepts of large AI models—parameter count, tokenization, context window, context length, and temperature—explaining their impact on model capability, computational cost, generation quality, and how to balance them for optimal performance.
This article walks developers through three essential upgrades for Retrieval‑Augmented Generation systems—hybrid search combining vector and keyword retrieval, query rewriting to clarify conversational inputs, and re‑ranking with a cross‑encoder—providing step‑by‑step code examples using LangChain to dramatically improve answer quality.
This curated reading list presents must‑read books covering cloud, edge, distributed, high‑performance, parallel, heterogeneous, quantum, and AI computing, offering expert editorial insights, author backgrounds, and publication details to help readers grasp core concepts and advance their technical expertise.
