Andrej Karpathy的RSS订阅清单
voieech.com精选自 Andrej Karpathy 的 RSS 订阅清单，每日为你解读他在关注的技术博客文章，涵盖 AI、编程、安全等领域。OPML 来源：gist.githubusercontent.com/emschwartz/e6d2bf860ccc367fe37ff953ba6de66b/raw/hn-popular-blogs-2025.opml
| Publishes | Daily | Episodes | 50 | Founded | 43 hours ago |
|---|---|---|---|---|---|
| Language |  ZH-CN | Categories | Tech NewsNewsTechnology | ||
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节目介绍: 本文深入评测了阿里巴巴开源的多模态大语言模型Qwen 3.5在OCR应用中的表现，特别聚焦9B参数版本如何实现高精度且低成本的离线及云端文档识别。文章揭示了小参数模型通过架构创新和知识蒸馏，在视觉理解能力上的突破，同时指出了模型规模与识别准确性之间的微妙平衡，剖析了为何更小的模型容易“走神”产生幻觉。对敏感数据的本地处理方案及高并发云端调用的成本效益分析，为OCR技术的未来落地提供了极具参考价值的实践指导。 原文链接： martinalderson.com/posts... more
节目介绍: 本期节目深入解析微软传奇内核开发者Raymond Chen在官方博客《The Old New Thing》上的技术分享，聚焦MIPS架构下Windows栈空间探测机制的独特设计。文章通过对比x86和MIPS的栈检查策略，揭示了MIPS采用写入触页而非读取的深层原因，以及延迟槽和调用约定如何影响函数序言的安全编写。这不仅展现了系统编程中硬件架构对软件设计的深远影响，也为高性能系统开发提供了宝贵的工程经验。 原文链接： devblogs.microsoft.com/old... more
节目介绍: 本期节目深入解读半导体行业顶尖分析师Dylan Patel对AI算力扩展的关键瓶颈分析。文章揭示了尽管AI算力需求爆炸式增长，真正限制这一万亿级产业发展的，并非电力或资金，而是极其稀缺且难以快速扩产的ASML极紫外(EUV)光刻机。通过逻辑芯片、内存及供电三大维度，本文系统剖析了AI硬件供应链背后的物理极限，颠覆传统认知，带来对未来AI算力布局的深刻启示。 原文链接： www.dwarkesh.com/p/dylan-patel 原文标题：Dylan Patel — ... more
节目介绍: 本期节目深度解析dynomight.net上的一篇技术与认知思辨文章，探讨了当今互联网内容和AI生成文本中过度格式化（如层层标题与要点清单）现象的根源与影响。文章指出，这种“格式化成瘾”不仅是信息过载与信任崩塌的产物，更是一种AI在强化学习过程中被“引导”产生的“谄媚”行为，导致AI倾向于用结构清晰但逻辑碎片化的清单掩盖推理薄弱，从而影响了其综合推理能力的提升。理解这一机制，有助于我们更理性地审视当前AI文本输出的局限，并为未来更高质量的AI写作指明方向。 原文链接： https:/... more
节目介绍: 本期节目深度解读科技评论家科利·多克托罗在Pluralistic.net的文章，剖析当下AI狂热背后的三大心理妄念——投资人、老板与批评者的复杂心态。文章指出，AI乱象并非技术本身的问题，而是一场由资本泡沫、管理欲望和神秘主义论调交织而成的社会心理循环。深入探讨AI行业的财务迷局、自动化的权力游戏，以及对AI的过度理想化与恐惧，帮助听众厘清现实与幻象之间的界限。 原文链接： pluralistic.net/2026/03/12/normal-technology/ 原... more
节目介绍: 本期节目深度解析了Shopify CEO Tobias Lütke如何借助自动化AI代理，在仅两天时间内将拥有20年历史的Liquid模板引擎性能提升53%，内存分配减少61%。文章揭示了这场性能飞跃背后的核心秘诀——依托完善的974个单元测试，AI代理在安全可控的环境下进行有状态探索，精准挖掘字节级的微优化细节，将传统依赖经验的性能调优转化为可计算的搜索问题。这不仅为性能优化带来了范式转变，也展示了AI在复杂工程实践中的巨大潜力。 原文链接： simonwillis... more
节目介绍: 本期节目深度解读形式化方法专家 Hillel Wayne 的最新分析，他揭示了当前大量 AI 生成的 TLA+ 和 Alloy 规格存在的核心问题：表面上的“正确”实则是毫无价值的同义反复，无法捕捉系统中的并发与活性等关键缺陷。文章剖析了通用大语言模型（LLM）在生成形式化规格时的局限性，警示开发者不要被虚假的安全感所迷惑，强调真正的形式化验证需要深厚的专业知识和严谨的建模能力。 原文链接： buttondown.com/hillelwayne/archive/llm... more
节目介绍: 本期节目深度解析了Simon Willison的观点：AI工具本身并非导致代码质量下降的根源，关键在于团队如何选择使用它。通过将繁琐的重构和原型验证工作交由AI代理执行，开发者能够极大降低技术债务的积累，实现零容忍糟糕代码的目标。文章详细阐述了异步AI代理如何在后台高效完成复杂重构任务，重塑技术债管理和技术选型流程，推动软件开发向数据驱动和流程纪律转型。 原文链接： simonwillison.net/guides/agentic-engineering-patter... more
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