开启时会模糊预览图，关闭后正常显示
1. 来自最强模型 ChatGPT 5 的判断, 评测标准太细了 https://t.co/ZdIAX4IOUm 2. 来自 Gemini 2.5 Pro 的判断 https://t.co/HrBAzR2dCd
🖥️ Indie Maker 🛠️ 星球「海哥和他的小伙伴们」 📌 油管「海拉鲁编程客」 🌸 沦为程序员的段子手/猫咪
pre-processed thoughts verifiable. As a user might not want a "brain implant" for their AI which gives it skill but also shills specific products (or ideology).
Fourth, it might really solve the issue with AI and copyrighted content: If cognitive core does not contain representations of copyrighted works, control will be back in hands of IP owners. E.g. they can sell "cartridges" or content licenses if they choose.
What if we live in a world where optimal AI is a small "cognitive core" which can dynamically acquire knowledge and skills needed to perform a task? That have been suggested by Andrej Karpathy, Sam Altman and others. I tried to outline future AI landscape under condition
"small but very powerful AI" vision is fully realized, here: https://t.co/mRCG9J8A7F First, Karpathy described it as "the race for LLM "cognitive core"", but it would likely make big AI labs weaker as it's much more feasible to work with smaller AI models.
kimi-k2-thinking 评测，讲点有趣且不一样的 在本赛季赛博斗蛐蛐中， 我让 K2-thinking 和 GPT-5 High 分别润色同一份历史遗留「设计系统文档」，再交给两位裁判（GPT-5 Pro、Gemini 2.5 Pro）打分。 长话短说，Kimi 小胜 两位裁判意见一致：日常“查”用 Kimi，系统“读”看 High。如果追求快而准，用 kimi 版做主文档。 对话记录放在评论区, 可自行查看 GPT-5 Pro 甚至构建了一套专业评审框架(图1)：10 个指标、百分制加权评分。在最关键的"可执行性"指标上（权重 15%），Kimi 版拿到 4.8 分，显著高于 GPT-5 版的 4.5 分。这 2.7 分的差距，直接决定了胜负。 Kimi 在可执行性（Actionability）与可扫读性（Scanability）更强：有表格、有Do/Don’t、速查代码块一目了然； High 在工程对齐（Repo Alignment）略胜，适合做制度级蓝本。 我完整审阅了双方输出，核心结论是：文档的使命是"让人看懂且能用"，而非"堆砌信息追求极致压缩"。在这个维度上，Kimi 的平衡感明显更胜一筹。 另外 K2 thinking Mermaid 图生成能力不错「图2」，而 GPT-5 High 连基础语法都会出错…… Q：Codex 文档已经可用，为何多此一举优化？ A：两个原因 - 文档一致性：随着时间的迁移，codex 会混入大量无需沉淀的细节，甚至会犯一些比较基础的错误，比如文档小节排序排错。定期整理很重要, 而由于 codex + gpt-5 high 过度谨慎, 在整理文档上能力表现很一般..... 用 CC + K2 整合文档的效率高不少 - 可读性：codex 的内容信息密度极高，读起来咯嘴，如果你正在开发这个模块倒还好, 如果是给别人读很容易脱离阅读舒适区 在此强烈推荐大家用 kimi-k2-thinking 规整一下你的开发文档
1. 来自最强模型 ChatGPT 5 的判断, 评测标准太细了 https://t.co/ZdIAX4IOUm 2. 来自 Gemini 2.5 Pro 的判断 https://t.co/HrBAzR2dCd
感觉AI Coding开始往垂直方向发展。 一句话生成互动教学 一句话生成小游戏 ... 如果后续Text Diffusion框架成熟，生成速度大幅提升。 鼠标点击，实时预测生成软件不是梦啊。
喜欢摇滚乐、爱钓鱼的PM 网站：https://t.co/vnUpLt752o
Oh? What changed around 2013 that «factoryless goods producers» became manufacturers? Dunking on «GDP» and «productivity» must continue until Americans stop doing this bullshit and start measuring themselves in a way that allows for comparison with their rival.
We're in a race. It's not USA vs China but humans and AGIs vs ape power centralization. @deepseek_ai stan #1, 2023–Deep Time «C’est la guerre.» ®1
