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#Trends
#Trends
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Steve Yegge@Steve_YeggeAI score22
宝玉@doteyAI score7171SemiAnalysis 实测 Anthropic、OpenAI 等九家 AI 订阅套餐后得出,同样 200 美元,Claude 订阅折算的 Token 用量约为 OpenAI 的 5 倍。
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QuotedSemiAnalysis@SemiAnalysis_Anthropic Subscriptions Offer 5x+ More Value Than OpenAI Limit testing every AI subscription plan from Anthropic, OpenAI, Meta, SpaceXAI, MiniMax, Moonshot, Zdotai, Cursor, and Cognition https://newsletter.semianalysis.com/p/anthropic-subscriptions-offer-5x
Shreya Shankar@sh_reyaAI score2828Awaiting translation
Quoteddex@dexhorthyAI and GTM at Rippling: 🦄 ai that works with @vaibcode and @JohnKutay https://x.com/i/broadcasts/1XxygwaqOpyGM
Thorsten Ball · Register SpillAI score1212 Joy & Curiosity #102:Gemini 4 Argon 智能体优化数据中心内存,GLM-5.3 可绕过安全防护
Google 发布 Gemini 4 Argon,其 Argon 智能体团队通过分析全集群性能遥测数据自主识别并应用内存优化,上线后释放超 300 TiB 内存,预计总节省 500 TiB 至 1 PiB。
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geoff@GeoffreyHuntleyAI score2020Awaiting translation
宝玉@doteyAI score6262剑桥大学 AI 科学与政策项目(CASP)9 月发布一篇论文,Hinton、Bengio 等 20 多位研究者联名讨论 AI 研发被自动化后是否会引发智能爆炸,Hinton 在 X 上推荐了该论文。
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QuotedGeoffrey Hinton@geoffreyhintonThe idea of an intelligence explosion caused by recursive self improvement has been around for a long time but until very recently it did not seem imminent. Now many leading researchers think it may happen quite soon. You can read our paper about it here: https://casp.ac/reports/intelligence-explosion
Thorsten Ball · Register SpillAI score4848 Thorsten Ball 谈 AI 智能体时代编程语言与框架的走向
Thorsten Ball 在 Register Spill 的 Joy & Curiosity #101 中提出,框架已不再是最大的开发者生产力杠杆,AI 智能体比它大一百倍,语法和工具易用性也不再重要。
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Thorsten Ball · Register SpillAI score2020 Thorsten Ball 谈 Jev:把 LLM 决策变成 200ms 的“智能 if 语句”
Thorsten Ball 在 Register Spill 中称 Jev 不是 LLM,而是“为软件直接使用的快速结构化决策”而建的模型,TypeSafe 将其描述为“非结构化状态输入、带类型的概率决策输出”的前沿智能函数调用。
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Sebastian Raschka@rasbtAI score3636Awaiting translation

Sebastian Raschka@rasbtAI score2020Awaiting translation
Thorsten Ball · Register SpillAI score1212 Joy & Curiosity #96:Stripe 以 75 亿美元收购 OpenRouter,GitHub 月提交量增至 29 亿
Stripe 以 75 亿美元收购 OpenRouter,致投资人的信被曝光。GitHub 披露月提交量自 4 月以来从 14 亿增至 29 亿,新增 300 万 CPU 核心和 120 PB 高速存储。作者还回顾了 GitHub 开源贡献、StackOverflow、TDD、文本编辑器等曾被视为基石的开发实践在近两年的式微。
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Andrej Karpathy@karpathyAI score6262Awaiting translation

Augment Code · BlogSelectedAI score6262 What is loop engineering, and how are leading software engineering teams using it?
Augment Code proposes loop engineering: designing agent loops that run from trigger to execution to validation to outcome, with agents handling the intermediate steps and humans stepping in only at checkpoints that require judgment. The article compares loop engineering with prompt engineering and context engineering as distinct layers, lays out five stages—trigger, execution, validation, outcome, and improvement—and describes four team-level loops already running in production: code review, ticket-to-PR, vulnerability remediation, and incident response.
Why it matters: Augment Code breaks loop engineering into five stages—trigger, execution, validation, outcome, and improvement—and lays out four team-level loop patterns already running in production.
Lovable · BlogSelectedAI score7171 Lovable 回应 2026 年 4 月安全事件:公开项目聊天记录与源码曾被越权访问
Lovable 官方回应 2026 年 4 月安全事件:2026 年 2 月 3 日至 4 月 20 日期间,任何持有项目链接的 Lovable 用户都可能访问公开项目的聊天记录和源码,私有项目与 Lovable Cloud 未受影响。
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Why it matters: Lovable 官方复盘公开项目聊天记录与源码被越权访问的完整时间线,并给出产品与流程层面的整改清单。
Augment Code · BlogAI score3636 Augment Code:AI 原生转型的四个阶段,从智能体采纳到智能体编排
Augment Code 将 AI 原生转型划分为四个阶段:约 70% 的组织仍停留在第一阶段(在日常工作流中集成 AI 智能体),不到 10% 让智能体自主承担工作,几乎无人达到完全智能体编排。
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