<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>多模态 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/%E5%A4%9A%E6%A8%A1%E6%80%81/</link><description>Recent content in 多模态 on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Thu, 16 Jul 2026 11:09:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/%E5%A4%9A%E6%A8%A1%E6%80%81/index.xml" rel="self" type="application/rss+xml"/><item><title>多模态大模型技术原理：从CLIP到原生统一架构</title><link>https://guijiagi.com/posts/b1-4a19c4f9/</link><pubDate>Thu, 16 Jul 2026 11:09:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-4a19c4f9/</guid><description>系统讲解多模态大模型的技术演进，从CLIP双塔到GPT-4V统一架构再到原生多模态训练</description></item><item><title>多模态大模型技术演进：从CLIP到原生多模态架构</title><link>https://guijiagi.com/posts/b2-19902ccc/</link><pubDate>Thu, 16 Jul 2026 10:07:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-19902ccc/</guid><description>梳理多模态大模型从早期CLIP双塔架构到GPT-4o原生多模态的技术演进路径，分析架构设计选择与工程权衡</description></item><item><title>从单模态到多模态：AI感知的进化之路</title><link>https://guijiagi.com/posts/article-95/</link><pubDate>Mon, 13 Jul 2026 08:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-95/</guid><description>梳理AI从纯文本到图文音视频多模态感知的演进历程，解析关键技术突破与未来方向</description></item><item><title>多模态Agent架构：当AI学会看和听</title><link>https://guijiagi.com/posts/article-09/</link><pubDate>Sun, 12 Jul 2026 18:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-09/</guid><description>探讨多模态AI Agent的架构设计原则，从感知融合到跨模态推理的完整技术栈</description></item><item><title>多模态Agent架构：当AI学会看和听</title><link>https://guijiagi.com/posts/b2-ad8b68bd/</link><pubDate>Sun, 12 Jul 2026 18:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-ad8b68bd/</guid><description>探讨多模态AI Agent的架构设计原则，从感知融合到跨模态推理的完整技术栈</description></item><item><title>Seedance 2.5上线：AI视频进入30秒直出时代</title><link>https://guijiagi.com/posts/seedance-25-video-era/</link><pubDate>Tue, 07 Jul 2026 13:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/seedance-25-video-era/</guid><description>字节豆包视频生成模型Seedance 2.5支持30秒单段视频直出，50个多模态素材联合输入，第三方测评超越GPT-5.6</description></item><item><title>多模态模型2026选型指南：不止于看图说话</title><link>https://guijiagi.com/posts/multimodal-model-2026-guide/</link><pubDate>Thu, 02 Jul 2026 10:58:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-model-2026-guide/</guid><description>2026年多模态大模型全面选型指南，覆盖图文、视频、音频融合理解</description></item><item><title>视觉模型选型2026：从图像理解到多模态推理</title><link>https://guijiagi.com/posts/vision-model-2026-selection/</link><pubDate>Thu, 02 Jul 2026 10:54:00 +0800</pubDate><guid>https://guijiagi.com/posts/vision-model-2026-selection/</guid><description>2026年视觉语言模型全面选型指南，覆盖OCR、图表理解、视频分析等场景</description></item><item><title>OpenAI实时语音API：端到端延迟200ms</title><link>https://guijiagi.com/posts/openai-realtime-api-voice/</link><pubDate>Thu, 02 Jul 2026 10:19:00 +0800</pubDate><guid>https://guijiagi.com/posts/openai-realtime-api-voice/</guid><description>OpenAI发布实时语音API，延迟低至200ms，语音交互体验大幅提升</description></item><item><title>文心一言5.0发布：多模态推理突破</title><link>https://guijiagi.com/posts/baidu-ernie-5-release/</link><pubDate>Thu, 02 Jul 2026 10:14:00 +0800</pubDate><guid>https://guijiagi.com/posts/baidu-ernie-5-release/</guid><description>百度文心一言5.0发布，多模态推理能力实现重大突破</description></item><item><title>Gemini 3 Ultra深度评测：多模态能力碾压？</title><link>https://guijiagi.com/posts/google-gemini-3-ultra-review/</link><pubDate>Thu, 02 Jul 2026 10:03:00 +0800</pubDate><guid>https://guijiagi.com/posts/google-gemini-3-ultra-review/</guid><description>Google Gemini 3 Ultra全面评测：原生多模态是否真正领先</description></item><item><title>AI Agent 用户体验设计 2026：从命令式到对话式交互</title><link>https://guijiagi.com/posts/agent-ux-design-2026/</link><pubDate>Tue, 30 Jun 2026 17:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-ux-design-2026/</guid><description>2026年AI Agent UX设计指南：对话设计、反馈机制、错误处理、多模态交互、信任建立等核心设计原则</description></item><item><title>多模态大模型2026：视觉理解能力大比拼</title><link>https://guijiagi.com/posts/multimodal-vision-benchmark-2026/</link><pubDate>Tue, 30 Jun 2026 09:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-vision-benchmark-2026/</guid><description>2026年多模态大模型深度评测：GPT-5 Vision、Claude 5 Vision、Gemini 3 Pro、Qwen-VL Max在视觉理解、OCR、视频分析等维度的全面对比</description></item><item><title>AI 视频生成 2026 全景：Sora 2 vs Runway Gen-4 vs Pika 2.0 vs 可灵 3.0</title><link>https://guijiagi.com/posts/ai-video-generation-2026-landscape/</link><pubDate>Sun, 28 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-video-generation-2026-landscape/</guid><description>2026年AI视频生成领域四大主流模型的全景对比，从画质、时长、一致性到商业化的深度分析</description></item><item><title>多模态 Agent 实战：让 AI 看图说话和听音做事</title><link>https://guijiagi.com/posts/multimodal-agent-practice/</link><pubDate>Sun, 28 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-agent-practice/</guid><description>手把手教你构建多模态Agent，实现图像理解、语音交互、视频分析等能力，包含完整代码示例和架构设计</description></item><item><title>多模态融合架构：Early Fusion vs Late Fusion vs Cross-Attention</title><link>https://guijiagi.com/posts/multimodal-fusion-architectures/</link><pubDate>Sun, 28 Jun 2026 11:13:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-fusion-architectures/</guid><description>深入对比多模态大模型的三种融合架构：Early Fusion、Late Fusion、Cross-Attention的原理与2026年实践</description></item><item><title>Hermes Agent 爱马仕智能体技术架构深度解析</title><link>https://guijiagi.com/posts/hermes-agent-architecture/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/hermes-agent-architecture/</guid><description>深度解析 Hermes Agent 爱马仕智能体的技术架构设计、核心组件、推理引擎与应用实践</description></item><item><title>2026 年中 AI 行业报告：五大关键趋势</title><link>https://guijiagi.com/posts/2026-mid-year-ai-industry-report-five-key-trends/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/2026-mid-year-ai-industry-report-five-key-trends/</guid><description>2026 年上半年 AI 行业全景扫描：从 Agent 商业化、多模态融合、推理成本下降、AI 科学发现到监管落地，深度解析五大核心趋势</description></item><item><title>多模态 RAG 实战：图文混合检索的工程实现</title><link>https://guijiagi.com/posts/multimodal-rag-image-text-hybrid-retrieval/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-rag-image-text-hybrid-retrieval/</guid><description>深入多模态 RAG 的工程实现，涵盖图文统一编码、混合检索策略、跨模态重排序等核心技术</description></item><item><title>多模态模型 2026 选型：视觉理解能力横评</title><link>https://guijiagi.com/posts/multimodal-vision-models-2026-comprehensive-evaluation/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-vision-models-2026-comprehensive-evaluation/</guid><description>2026年主流多模态大模型视觉理解能力全面横评，覆盖图像理解、视频理解、OCR与空间推理</description></item><item><title>多模态Agent架构设计</title><link>https://guijiagi.com/posts/multimodal-agent-architecture/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-agent-architecture/</guid><description>多模态Agent架构设计</description></item><item><title>多模态RAG架构实践</title><link>https://guijiagi.com/posts/multimodal-rag-practice/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-rag-practice/</guid><description>多模态RAG架构实践</description></item><item><title>多模态模型评测方法论</title><link>https://guijiagi.com/posts/multimodal-eval-methodology/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-eval-methodology/</guid><description>多模态模型评测方法论</description></item><item><title>多模态模型选型指南</title><link>https://guijiagi.com/posts/multimodal-model-selection-guide/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-model-selection-guide/</guid><description>多模态模型选型指南</description></item><item><title>多模态融合架构原理深度解析</title><link>https://guijiagi.com/posts/multimodal-fusion-architecture-2026/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-fusion-architecture-2026/</guid><description>深度解析多模态融合架构原理，从早期融合到晚期融合再到混合架构的技术演进</description></item><item><title>多模态融合架构原理深度解析</title><link>https://guijiagi.com/posts/multimodal-fusion-architecture/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-fusion-architecture/</guid><description>多模态融合架构原理深度解析</description></item><item><title>GPT-5.5 深度评测：多模态推理的新标杆</title><link>https://guijiagi.com/posts/gpt-55-%E6%B7%B1%E5%BA%A6%E8%AF%84%E6%B5%8B-%E5%A4%9A%E6%A8%A1%E6%80%81%E6%8E%A8%E7%90%86%E7%9A%84%E6%96%B0%E6%A0%87%E6%9D%86/</link><pubDate>Sat, 27 Jun 2026 00:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/gpt-55-%E6%B7%B1%E5%BA%A6%E8%AF%84%E6%B5%8B-%E5%A4%9A%E6%A8%A1%E6%80%81%E6%8E%A8%E7%90%86%E7%9A%84%E6%96%B0%E6%A0%87%E6%9D%86/</guid><description>全面评测 GPT-5.5 的推理能力、多模态表现与 Agent 构建能力，对比 GPT-5 提升幅度，分析其在实际应用中的表现</description></item><item><title>多模态智能体设计：图文音视一体化架构</title><link>https://guijiagi.com/posts/multimodal-agent-design/</link><pubDate>Fri, 26 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-agent-design/</guid><description>探讨多模态智能体的架构设计，涵盖视觉语言模型、语音交互、视频理解与跨模态推理，附完整系统架构与代码实现。</description></item><item><title>多模态大模型选型：GPT-5V vs Gemini vs Qwen-VL vs LLaVA</title><link>https://guijiagi.com/posts/multimodal-model-selection/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-model-selection/</guid><description>全面对比 2026 年主流多模态大模型：GPT-5o、Gemini 2.0 Pro、LLaVA-1.6、Qwen-VL2、InternVL3 在图像、视频、文档理解上的表现与选型建议。</description></item><item><title>多模态模型评估：视觉理解与跨模态推理</title><link>https://guijiagi.com/posts/multimodal-eval-method/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-eval-method/</guid><description>系统介绍多模态大模型评估方法，涵盖视觉理解、跨模态推理、图文一致性、OCR、视频理解等核心维度的评估框架与实现。</description></item><item><title>Gemini 3.5 Flash 评测：低延迟 Agent 时代到来</title><link>https://guijiagi.com/posts/gemini-3-5-flash-review/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/gemini-3-5-flash-review/</guid><description>Google 发布 Gemini 3.5 Flash，首 token 延迟 280ms，原生多模态生成，深度集成搜索，Agent 场景全面覆盖</description></item><item><title>多模态模型评估 2026：视觉/音频/视频全面评测</title><link>https://guijiagi.com/posts/multimodal-eval-2026/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-eval-2026/</guid><description>2026 年多模态模型评估全景：视觉、音频、视频理解与跨模态推理</description></item><item><title>视觉语言模型选型：GPT-4V/Gemini/Claude/Qwen-VL 对比</title><link>https://guijiagi.com/posts/vision-language-model-guide/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/vision-language-model-guide/</guid><description>主流视觉语言模型深度对比，涵盖架构原理、OCR/图表/视频理解能力与成本延迟分析</description></item><item><title>Gemini 4.0 预告：谷歌的全模态野心</title><link>https://guijiagi.com/posts/gemini-40-%E9%A2%84%E5%91%8A-%E8%B0%B7%E6%AD%8C%E7%9A%84%E5%85%A8%E6%A8%A1%E6%80%81%E9%87%8E%E5%BF%83/</link><pubDate>Thu, 25 Jun 2026 00:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/gemini-40-%E9%A2%84%E5%91%8A-%E8%B0%B7%E6%AD%8C%E7%9A%84%E5%85%A8%E6%A8%A1%E6%80%81%E9%87%8E%E5%BF%83/</guid><description>Google DeepMind 预告 Gemini 4.0，支持文本/图像/视频/音频/代码原生多模态，分析其技术路线与对行业的影响</description></item><item><title>多模态评估指南：视觉语言模型怎么测？</title><link>https://guijiagi.com/posts/multimodal-eval-guide/</link><pubDate>Wed, 24 Jun 2026 16:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multimodal-eval-guide/</guid><description>从感知到推理到生成，系统性评估视觉语言模型（VLM）的完整框架</description></item><item><title>视觉语言模型选择指南：从 LLaVA 到 GPT-4V</title><link>https://guijiagi.com/posts/vision-model-selection/</link><pubDate>Wed, 24 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/vision-model-selection/</guid><description>全面解析 VLM 架构演进、主流模型对比、OCR 与视频理解能力、部署成本与选型决策。</description></item><item><title>具身智能 2026：当 AI 走出屏幕进入物理世界</title><link>https://guijiagi.com/posts/embodied-ai-2026/</link><pubDate>Tue, 23 Jun 2026 15:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/embodied-ai-2026/</guid><description>2026年具身智能领域的技术突破、代表产品和未来展望</description></item></channel></rss>