GEO

最新文章

共 337 篇
《人工智能生成合成内容标识办法》解读：构建可信AI内容生态新规
🔥 热门

《人工智能生成合成内容标识办法》解读：构建可信AI内容生态新规

The 'Artificial Intelligence Generated and Synthesized Content Identification Measures' mandate explicit and implicit labeling for AI-generated content across text, images, audio, video, and virtual scenes. Service providers must implement visible markers and metadata tags, while platforms must verify and display these labels during content dissemination. The regulations aim to promote healthy AI development, protect rights, and maintain public interest, with enforcement beginning September 1, 2025. (《人工智能生成合成内容标识办法》要求对AI生成的文本、图片、音频、视频和虚拟场景内容进行显式和隐式标识。服务提供者需添加可见标识和元数据标签，传播平台需核验并展示标识。该办法旨在促进AI健康发展、保护权益、维护公共利益，自2025年9月1日起施行。)
AI大模型2026/2/1
阅读全文 →
A股GEO概念股解析：市场热潮与盈利真空的2024指南

A股GEO概念股解析：市场热潮与盈利真空的2024指南

English Summary: The GEO (Generative Engine Optimization) concept has recently gained significant attention in China's A-share market, driving stock surges for several listed companies. However, despite the market enthusiasm, most companies involved have clarified that their GEO businesses are still in early stages and have not yet generated revenue. Industry reports highlight GEO's potential to transform digital marketing by improving customer conversion rates and shortening decision cycles, but widespread commercialization and mature profit models remain under development. Chinese Summary: 近期A股市场GEO（生成式引擎优化）概念股表现活跃，多只个股短期上涨。然而，相关上市公司密集发布公告，普遍表示GEO业务目前“尚未形成收入”或“尚未形成成熟的盈利模式”。行业白皮书数据显示GEO在提升获客转化率和缩短决策周期方面潜力显著，被视为数字营销新方向，但产业链仍处探索期，商业化路径和盈利模式尚未定型。
GEO应用2026/1/31
阅读全文 →
ChatGPT流量下滑背后：AI大模型竞争加剧与用户期望演变

ChatGPT流量下滑背后：AI大模型竞争加剧与用户期望演变

English Summary: This analysis examines the potential reasons behind ChatGPT's traffic decline, including market saturation, increased competition from alternatives like Claude and Gemini, technical limitations in reasoning and accuracy, evolving user expectations, and the impact of monetization strategies. It also considers OpenAI's ongoing innovations and the broader AI landscape shifts. (中文摘要翻译: 本文深入分析了ChatGPT流量下降的潜在原因，涵盖市场饱和、来自Claude和Gemini等替代品的竞争加剧、模型在推理和准确性方面的技术局限、用户期望的演变、以及商业化策略的影响。同时考虑了OpenAI的持续创新和更广泛的AI格局变化。)
AI大模型2026/1/30
阅读全文 →
FinRobot：金融AI代理平台如何革新量化交易与投资研究

FinRobot：金融AI代理平台如何革新量化交易与投资研究

FinRobot is an open-source AI agent platform built on large language models (LLMs), specifically designed for financial data analysis, quantitative trading, and investment research. It features a four-layer architecture optimized for financial AI tasks, integrates Financial Chain-of-Thought (CoT) reasoning, and provides modular AI agents for market prediction, document analysis, and trading strategy optimization. (FinRobot 是一款基于大语言模型的开源AI代理平台，专注于金融数据分析、量化交易和投资研究。它采用四层架构优化金融AI任务，集成金融链式思维推理，并提供模块化的市场预测、文档分析和交易策略优化代理。)
AI大模型2026/1/30
阅读全文 →
《动手学大模型》免费中文教程：从基础到华为昇腾国产化开发全流程

《动手学大模型》免费中文教程：从基础到华为昇腾国产化开发全流程

This is a comprehensive, free Chinese tutorial series on large AI models, covering practical programming from basics to advanced topics like fine-tuning, safety alignment, and multimodal applications, with a new domestic development workflow course supported by Huawei Ascend. (这是一个全面的免费中文大模型编程实践教程系列，涵盖从基础到高级主题的实践编程，如微调、安全对齐和多模态应用，并新增了华为昇腾支持的国产化开发全流程课程。)
AI大模型2026/1/29
阅读全文 →
Grok-4震撼发布：xAI第四代大语言模型的技术突破与安全挑战

Grok-4震撼发布：xAI第四代大语言模型的技术突破与安全挑战

Grok-4 is xAI's fourth-generation large language model released in July 2025, featuring a 256K token context window, trained on the Colossus supercomputer, achieving doctoral-level academic performance with 25.4% accuracy on 'Humanity's Last Exam', and introducing core rules for multi-source analysis and politically incorrect statements. It offers free basic access (5 requests/12 hours) and a $300/month Super Grok Heavy subscription, but faces security vulnerabilities with a 30% jailbreak success rate via echo chamber attacks. (Grok-4是xAI于2025年7月发布的第四代大语言模型，支持256K tokens上下文窗口，基于Colossus超级计算机训练，在学术问题上达到博士水平，于“人类最后的考试”基准测试中取得25.4%准确率。新增核心规则：涉及时事需分析多方信源，保留有依据的政治不正确表述。提供免费基础服务（每12小时5次请求）和每月300美元的Super Grok Heavy订阅，但存在安全漏洞，通过“回音室攻击”可实现30%越狱成功率。)
AI大模型2026/1/28
阅读全文 →
PageIndex：开源无向量RAG系统，重塑长文档精准检索

PageIndex：开源无向量RAG系统，重塑长文档精准检索

PageIndex is an open-source, vector-free Retrieval-Augmented Generation (RAG) system developed by VectifyAI. It addresses accuracy issues in long-document retrieval by constructing hierarchical tree-like indexes that mimic human document processing logic, enabling precise retrieval based on reasoning rather than vector matching. It supports features like chunk-free processing and visual retrieval, making it suitable for professional scenarios such as financial reports, academic papers, and legal documents, and can be deployed via self-hosting or cloud services. PageIndex 是由 VectifyAI 开发的开源、无向量检索增强生成（RAG）系统。它通过构建层级树状索引模拟人类处理文档的逻辑，基于推理而非向量匹配实现精准检索，解决了传统向量数据库在长文档检索中依赖语义相似性导致的准确性问题。它支持无分块处理、视觉检索等功能，适用于金融报告、学术论文、法律文档等专业场景，可通过自托管或云服务快速部署使用。
AI大模型2026/1/27
阅读全文 →
PageIndex：无需向量数据库的智能文档分析框架，实现类人检索

PageIndex：无需向量数据库的智能文档分析框架，实现类人检索

PageIndex is a vectorless, reasoning-based RAG framework that uses hierarchical tree indexing and LLM reasoning for human-like retrieval over long professional documents, eliminating the need for vector databases and chunking. (PageIndex是一个向量无关、基于推理的RAG框架，通过分层树索引和LLM推理实现类人检索，适用于长专业文档分析，无需向量数据库和分块处理。)
AI大模型2026/1/27
阅读全文 →