Blog Posts

构建智能代理:如何让ai像人类一样操作计算机并完成任务
- Rifx.Online
- AI Applications , Large Language Models , Robotics
- 27 Feb, 2025
免费阅读这个故事: link 在这篇博客中,我们将从零开始构建一个AI代理,以处理交互式任务,例如:从亚马逊给我买一个足球它打开Chrome,搜索一个查询,滚动,并将第一个足球添加到
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构建高效并行工作流:使用langgraph实现llm应用的5个关键步骤
大型语言模型与 LangGraph 大型语言模型 (LLMs) 已成为自然语言处理的强大工具,但使用它们编排复杂的工作流可能会很具挑战性。这就是 LangGraph 进入视野的地方——一个专门设计的框架,旨在为 LLM 应用带来结构和效率。 LangGraph 通过将您的 LLM 应用视为有向图而脱颖而出,其中每个节点代表一个特定操作,边定义数据流。它的强大之处在于能够处理并行处理
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轻松加载llama和其他hugging Face Llms:5个简单步骤实现离线使用
Image generated using DALL-E 你知道吗,你可以直接在本地机器上加载大多数大型语言模型,而无需依赖Ollama、AI Studio、Llama.cpp或任何此类依赖项!Hugging Face提供了一个庞大的开源LLM库,包括流行的Llama系列,你可以通过几个简单的步骤加载。在本指南中,我将带你完成整个过程,从请求访问到本地加载模型并生成模型输出
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蛋白质结构发现的革命性变革:从 Ai-driven 对话式应用开发中获得的 5 个重要启示
- Rifx.Online
- Programming , Generative AI , Chatbots
- 27 Feb, 2025
Please translate the following text to Chinese. Requirements: 1. Keep code blocks (```) unchanged 2. Keep inline code (`) unchanged 3. Keep Markdown formatting
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开启未来:Openai 如何改变日常使用的实时对话式人工智能
对话式人工智能 — 未来已来 我们生活在2025年,这是一个人工智能时代,过去五年中,我们在日常生活中体验着人工智能。早些时候,我们曾预测人工智能将伴随我们,使用人工智能在数字世界中,同时我们也在说人工智能是未来,而现在它已成为现实。 当大型语言模型在五年前向公众发布时,我们开始体验到在软件开发、医疗保健等各个不同领域中一些小任务的自动化。它正在向更准确、改进和高效的模型发展,并已
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14 项基本提示工程技术:释放 Ai 交互的全部潜能
因为有了正确的提示,人工智能的能力没有限制 Photo By Mr. Chamy On Heroscreen Deepseek 再次在全球引发震动……这感觉就像我们回到了 ChatGPT 的早期阶段,即使是不懂技术的人也在讨论人工智能和大型语言模型,尽管他们对神经元和节点一无所知,同时试图将其利用到自己的优势上。 使用任
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伟大的尊敬的哈珀·里德的胡须和他附属的人写了一篇关于LLM代码生成及其技术和方法的优秀博客。 我发现哈珀的做法与我所使用的有很多相似之处,因此我想写一个简短的“+1”来捕捉这些相似性和差异,并总体上突出一些人们可以使用的更多技术和技术,以便在我们的AI朋友的帮助下制作出最佳软件。让我们深入探讨一下! 如果您想跳过所有这些内容并观看关于相同流程的超快速视频,请查看下面: 我方法中的一个
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破解llms防御的攻击策略:揭秘黑客如何突破大型语言模型的安全防线
- Rifx.Online
- Large Language Models , AI Research , Security
- 27 Feb, 2025
Part 1 - 理解黑客在大型语言模型上的攻击策略 Photo by Clint Patterson on [Unsplash](https://unsplash.com/photos/
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将 Openai Ai 助手与 Whatsapp 整合:轻松提供客户支持的 5 个简单步骤
使用WhatsApp和AI自动化客户对话 自动化客户对话已成为任何希望提供快速和个性化支持的企业的必要条件。WhatsApp是最广泛使用的通信平台之一,集成一个AI助手可以将用户体验提升到一个全新的水平。幸运的是,有一些解决方案可以实现这种集成而无需复杂的开发或专用基础设施。 image source: author 在本文中,您将学习如何使用[**WAMM.pr
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提升ai智能:agentic Rar的革命性升级与rag的对比分析
Created by me using canva 嘿,大家好! 所以,我有一些有趣的研究想通过这篇文章来聊聊。 基本上,这一切都关于我们如何让人工智能变得更聪明,特别是在解决问题和给我们更好答案方面。 你可能以前用过聊天机器人或人工智能助手,对吧? 好吧,在2024年甚至2025年初,有一个叫做检索增强生成(RAG)的系统,它真的是一个游戏规则的改变者。 现在在2025年,一些
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深入对比:fine-tuning Distillation与transfer Learning的最佳应用场景解析
微调 vs 蒸馏 vs 迁移学习 微调 vs 蒸馏 vs 迁移学习,作者插图 随着Deepseek-R1及其蒸馏模型的推出,许多机器学习工程师在思考:蒸馏和微调之间有什么区别?而在大语言模型崛起之前非常流行的迁移学习,似乎为何被遗忘了? 在本文中,我们将探讨它们之间的差异,并确定哪种方法最适合哪些情况。 注意: 虽然本文聚焦于大语言模型,但这些概念同样适用于
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提升ai代理工具选择准确性的策略:如何应对工具复杂性挑战
共同作者: Sebastian Carbajales 在我们之前的 讨论 中,我们探讨了AI代理能够处理的工具数量(“数量”)如何影响令牌消耗。现在
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释放 Ai 创造力:使用 Logicstudio 的无代码平台免费创建自己的代理
- Rifx.Online
- Generative AI , Large Language Models , AI Applications
- 27 Feb, 2025
介绍逻辑工作室,终极无代码画布,完全免费构建人工智能代理! LogicStudio.ai — 构建人工智能代理的下一代画布。免费使用双子星、开放AI、克劳德、拉马,所有功能在一个代理工作流程中! 最近我一直在使用人工智能代理,老实说,这是一段疯狂的旅程。潜力令人震惊,但实际上_构建_这些代理系统?常常是一个巨大的头疼。可供使用的框架数量越来越多,有像LangGraph这样的重代码,
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提示链与提示填充:使用 Gemini 2.0 Flash 优化 Llm 性能的 5 个重要见解
我以为我在“提示链”这个想法上很牛逼。 为我辩护的话,过去这曾是个必要的做法。如果你试图让一个主提示做所有事情,它会彻底失败。使用 GPT-3 时,如果你没有通过提示链构建一个深度嵌套的复杂 JavaScript对象表示法 对象,你根本就没有构建它。 GPT 3.5-Turbo 的上下文长度为 4,097,无法处理复杂提示。 但是,在我连续第五天从 OpenRouter 收到超过
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