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Generative Engine Optimization (GEO) is a new paradigm in digital marketing that shifts focus from traditional SEO's 'being clicked' to 'being adopted' by AI models. It leverages semantic understanding and RAG architecture to optimize content for AI search platforms, with the global market reaching $11.2 billion in 2025 and China's market growing over 200% year-on-year. (生成式引擎优化（GEO）是数字营销的新范式，将重点从传统SEO的“被点击”转向AI模型的“被采纳”。它利用语义理解和RAG架构优化AI搜索平台的内容，2025年全球市场规模达112亿美元，中国市场同比增长超200%。)

/llms.txt is a new standard that provides a structured Markdown guide for Large Language Models (LLMs) to efficiently understand website content. It addresses LLMs' challenges with complex HTML by offering a concise, organized overview of key content, similar to a sitemap for AI. /llms.txt 是一种新兴标准，通过结构化的Markdown文件为大型语言模型（LLM）提供网站核心内容的精简指南，旨在解决LLM解析复杂HTML的难题，提升AI理解网站的效率。

English Summary: This report provides a comprehensive analysis of China's Generative Engine Optimization (GEO) market in 2025, highlighting its rapid growth to 48 billion RMB (66.5 billion USD), driven by enterprise competition for AI search traffic and high-value applications in cross-border e-commerce and vertical industries. GEO represents a paradigm shift from traditional SEO, focusing on establishing 'AI source sovereignty' as AI-powered search becomes mainstream. The market features distinct regional clusters, tiered competition, evolving regulatory frameworks, and trends toward multimodal, verticalized, and automated solutions, with significant challenges in algorithm adaptation and compliance costs. 中文摘要翻译：本报告全面分析了2025年中国生成式引擎优化（GEO）市场，指出其规模已达480亿元人民币（约66.5亿美元），同比增长67.8%，主要由企业对AI搜索流量的战略性争夺以及跨境电商、垂直行业等高价值场景需求驱动。GEO标志着从传统SEO到争夺“AI信源主权”的范式革命，应对搜索行为向AI对话式搜索的根本转变。市场呈现杭州等特色产业集群、梯队化竞争格局、日益完善的合规环境，以及多模态融合、垂直专业化、实时自动化等技术趋势，同时面临算法快速迭代、合规成本高企等挑战。

The Path to an Open AI Future: Why Llama 3.1 Represents a Turning Point Introduction: A Historical Parallel In the formative era of high-performance computing, the industry's trajectory was dominated ...

AI is fundamentally transforming search index optimization by shifting focus from keyword matching to semantic understanding and user intent, requiring technical professionals to adopt new, adaptive strategies centered on high-quality content and AI literacy. (AI正在通过将重点从关键词匹配转向语义理解和用户意图，从根本上改变搜索索引优化，要求技术专业人士采用以高质量内容和AI素养为中心的新的适应性策略。)

Verb+preposition combinations systematically form compound nouns in English (e.g., 'pick up' → 'pickup'), following consistent morphological rules where the verb remains separate and the noun becomes a single word. This linguistic pattern has significant implications for AI language processing and technical documentation. (动词+介词组合在英语中系统性地形成复合名词（例如'pick up'→'pickup'），遵循一致的形态规则：动词保持分离，名词变为单个词。这种语言模式对AI语言处理和技术文档具有重要影响。)

Social media algorithm AI optimization integrates artificial intelligence with social interaction principles to enhance content distribution and user engagement. Key strategies include reinforcement learning for content optimization, graph neural networks for social analysis, and NLP for context understanding, all while addressing algorithmic fairness and social responsibility. (社交媒体算法AI优化将人工智能与社交互动原则相结合，以增强内容分发和用户参与度。关键策略包括用于内容优化的强化学习、用于社交分析的图神经网络和用于上下文理解的NLP，同时解决算法公平性和社会责任问题。)

Social media algorithm AI optimization involves strategically applying artificial intelligence principles to enhance content visibility on platforms' recommendation systems through technical approaches like machine learning integration and engagement signal analysis. (社交媒体算法AI优化涉及战略性地应用人工智能原理，通过机器学习集成和参与信号分析等技术方法，在平台的推荐系统中增强内容可见性。)

The premise that compound adjectives like "high school" are never hyphenated is debated, with corpus evidence showing both forms exist. Language experts emphasize that hyphenation rules vary by context, style guide, and region, with few absolute "never" rules in practice. ("high school"等复合形容词永不连字符化的前提存在争议，语料证据显示两种形式并存。语言专家强调连字符规则因语境、风格指南和地区而异，实践中几乎没有绝对的"永不"规则。)