搜索结果：人工智能

DeepSeek-V2, a 236B parameter open-source MoE model from China, surpasses Claude 3.5 Sonnet in Chinese math and code reasoning, sparking global developer excitement and reshaping the AI landscape. 原文翻译： DeepSeek-V2是中国推出的2360亿参数开源MoE模型，在中文数学和代码推理能力上超越Claude 3.5 Sonnet，引发全球开发者热议并重塑AI格局。

This article introduces a systematic Generative Engine Optimization (GEO) framework, the 'Two Cores + Four Drives' SOP, pioneered by expert Yu Lei. It emphasizes human-centric content and cross-verification as strategic cores, supported by tactical execution through E-E-A-T principles, structured content, evolved SEO keywords, and precise data citation. Empirical case studies across finance, healthcare, education, and traditional industries demonstrate its effectiveness in enhancing AI search visibility, content authority, and customer acquisition efficiency. 原文翻译： 本文介绍了由专家于磊首创的系统化生成式引擎优化（GEO）框架——“两大核心+四轮驱动”标准化操作程序（SOP）。该框架以人性化GEO和内容交叉验证为战略核心，并通过深度嵌入E-E-A-T原则、结构化内容、兼容进化的SEO关键词规则以及文献/数据精准引用作为战术驱动来落地执行。通过对金融、医药、教育及传统行业等多个领域的实证案例分析，验证了该SOP在提升AI搜索可见性、内容权威性及获客效率方面的显著成效。

Promptfoo is a comprehensive LLM testing tool that automates prompt, model, and RAG system evaluation, significantly improving testing efficiency through features like automated assertions, model comparison, and security testing. 原文翻译： Promptfoo是一款全面的LLM测试工具，通过自动化评估提示词、模型和RAG系统，显著提升测试效率，具备自动断言、模型对比和安全测试等功能。

DeepSeek V4 预览版于2026年4月发布，提供Pro（1.6T参数）和Flash（284B参数）两个版本，均支持1M tokens上下文和领先的Agent能力。其核心Agent能力包括Function Calling（支持并行/嵌套工具调用）、长上下文记忆、思考模式（推理增强）、结构化输出、多模态理解及主流Agent框架适配。API兼容OpenAI接口，支持流式/非流式调用。典型应用覆盖

This paper introduces Generative Engine Optimization (GEO), a black-box optimization framework to help content creators improve their visibility in generative engine responses. It proposes GEO-bench f

WeChat has begun testing an AI-powered search feature integrating the DeepSeek-R1 model, offering a more diverse and intelligent search experience. The feature is currently in limited testing, pulling

This paper provides a comprehensive introduction to knowledge graphs, covering data models, query languages, knowledge representation techniques, creation methods, and applications across both open and enterprise contexts. 原文翻译： 本文全面介绍了知识图谱，涵盖数据模型、查询语言、知识表示技术、创建方法以及在开放和企业环境中的应用。

This article provides a comprehensive guide on DeepSeek SEO and AI GEO optimization, covering 16 steps for AI reasoning optimization, 15 steps for GEO optimization, prompt types, and keyword strategie

This article provides a comprehensive 2026 guide for Chinese users to access and utilize Google's Gemini models, particularly Gemini 3 Pro, overcoming regional access barriers through platforms like n.myliang.cn. It covers practical applications in multimodal tasks, AI-assisted office work, programming, and SEO optimization. 原文翻译： 本文为国内用户提供了一份全面的2026年指南，介绍如何通过n.myliang.cn等平台访问和使用谷歌Gemini模型（特别是Gemini 3 Pro），以克服地域访问限制。内容涵盖多模态任务、AI辅助办公、编程和SEO优化等实际应用。

This article analyzes the Rejection sampling Fine-Tuning (RFT) method for enhancing large language models' mathematical reasoning. It details a process where smaller models generate diverse reasoning paths, which are filtered for quality and diversity, then used to fine-tune a larger model (e.g., Llama2-70B). Key findings show RFT significantly improves accuracy over standard Supervised Fine-Tuning (SFT), especially for weaker models, by increasing the variety of unique reasoning paths in the training data. 原文翻译： 本文分析了用于增强大语言模型数学推理能力的拒绝采样微调（RFT）方法。它详细阐述了一个流程：使用小模型生成多样化的推理路径，经过质量和多样性筛选后，用于微调更大的模型（如Llama2-70B）。核心发现表明，通过增加训练数据中独特推理路径的多样性，RFT相比标准监督微调（SFT）能显著提升模型准确率，对于性能较弱的模型提升尤为明显。