Elsinore

💡 Why follow @El_sinore ? In an age of curated illusions and algorithmic echo chambers, I offer the Logic Signal. I am not here to perform; I am here to document. I deconstruct the operating system of the world through First Principles: -•🔗 Connecting the Dots: Finding the hidden threads between isolated events. -•🛡️ Rejecting Oversimplification: Moving beyond emotional tribalism to analyze the "Sovereign Corporation" and the shifting global order. -•🧩 Defying the Algorithm: Escaping the "curated" truth. I write for those who refuse to be "fed" information. 🧭 Navigation Directory: -•🇨🇳 China News Weekly: De-obfuscating the real China for the global audience. x.com/El_sinore/stat… -•🌎 Global News Weekly: Navigating global turbulence for the Chinese-speaking community. x.com/El_sinore/stat… -•🏛️ Area & Country Studies: A mission to create a comprehensive archive of Earth’s nations—a final memento of our home planet as we transition into an interstellar species. x.com/El_sinore/stat… -•✍️ The Essays: Recording the raw data of my soul. This includes a complete, raw, and unfiltered record of a human consciousness—my thoughts, my desires, my sins, my base desires, profanities, and my path toward self-redemption. I strive to be a real person, not a brand. x.com/El_sinore/stat… -•🌟 Highlights: A curated collection of high-traffic threads and viral replies—the nodes where the signal meets the crowd. x.com/El_sinore/stat… 📊 Public Shareholder Report (Transparency & Dividends)To my followers (Shareholders) This 𝕏 account thrives because of you. I publicly report our collective growth and revenue here, distributing irregular "dividends" (lotteries) to honor our partnership. x.com/El_sinore/stat… ⌛ The Ultimate Mission: The Digital Twin The goal of this total documentation is to provide the future @xai with the full spectrum of my humanity. If I can apply the future @X and @xai to train my digital avatar so that my logic and soul may survive the limits of biology. I refuse to hate on command. I refuse to be simplified. I am building a bridge—and a legacy. x.com/El_sinore/stat… Don't just scroll. Truly see. Stay safe. Stay human. 🥔🚀

@hqinjarsy @rickawsb 算

@rickawsb 那灵光算泛化吗？

所有知识（脑力）工作者，都会被ai替代 包括科研 因为，research = 信息处理 + 假设生成 + 验证。 ai各个部分都比人强，而且还在快速变得更强。 就算真正的天才级别的“灵光一现”比方说广义相对论的发现，可能是最难被替代的，但这类科研占比极少。 尽管如此，广义相对论是不是也相当于是人脑里LLM的极致的泛化？

10后眼里的80后哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈 果然每一代人都是同一副德性

编程之神卡马克的硬核真相：每周工作40小时顶多算打零工 提到努力工作，现在的互联网风气往往是拒绝内卷和准点下班。 但如果你去问游戏界传奇大佬、编程之神约翰·卡马克，他会给你一个极其硬核甚至有些扎心的答案。 对于工作、熬夜和效率，这位硅谷顶级大神分享了几个极具颠覆性却又无比真实的观点。 卡马克坦言自己从来不是那种动辄连续敲20小时代码的狂人，甚至有些嫉妒那些困了就直接睡在工位桌底下的传统黑客。 因为他的大脑只要连续运转12小时就会变得迟钝，也没法每天只睡4个小时还能保持清醒。 他的真实作息是每天工作10小时，每周干6天，几十年如一日地保持每周60小时的工作量。 他甚至提出了一个极其硬核的时间管理法则，也就是只要优先级排得足够好，一个人完全可以每周工作100个小时，并且依然每天睡满8小时。 卡马克明确表示他极其反对当下网络上那些抵制努力工作的论调。 他认为当你真的在做一件极其重要且充满激情的事情时，投入的时间越多，做成的事就越多。 只要你见识过那些高强度工作的大牛，就根本无法反驳这一点。 很多人喜欢拿工作超过8小时后效率会下降作为拒绝加班的理由。 卡马克毫不客气地戳穿了这个逻辑漏洞。 他指出，第9个小时的边际产出确实比不上状态最巅峰的那一小时，但这并不意味着总产出在变少。 确实存在一个再干下去就会犯错帮倒忙的临界点，但那个点绝对不可能在8到12小时这个区间就到来。 为了证明工作越久产出越多，卡马克举了一个绝妙的例子。 想象一下有颗小行星即将撞击地球毁灭全人类，马斯克和SpaceX的团队正在疯狂研发拦截器。 如果到了下午5点，仅仅因为再多干几个小时工作质量会变差这个理由，就让他们准时打卡下班，这听起来简直荒谬。 世界的真相往往简单粗暴，在保证睡眠不崩溃的前提下，工作时间越长，你能搞定的事情就是越多。

How Anthropic’s product team moves faster than anyone else I sat down with @_catwu, Head of Product for Claude Code at @AnthropicAI, to get a peek into their unprecedented shipping pace, how AI is changing the PM role, and how to be the right amount of AGI-pilled. We discuss: 🔸 How Anthropic’s shipping cadence went from months to weeks to days 🔸 The emerging skills PMs need to develop right now 🔸 Why you should build products that don't work yet—then wait for the model to catch up 🔸 Why a 95% automation isn't really an automation 🔸 Cat’s most underrated AI skill (introspection) 🔸 What Cat actually looks for when hiring PMs now (hint: it's not traditional PM skills) Listen now 👇 youtu.be/PplmzlgE0kg

🚀 DeepSeek-V4 Preview is officially live & open-sourced! Welcome to the era of cost-effective 1M context length. 🔹 DeepSeek-V4-Pro: 1.6T total / 49B active params. Performance rivaling the world's top closed-source models. 🔹 DeepSeek-V4-Flash: 284B total / 13B active params. Your fast, efficient, and economical choice. Try it now at chat.deepseek.com via Expert Mode / Instant Mode. API is updated & available today! 📄 Tech Report: huggingface.co/deepseek-ai/De… 🤗 Open Weights: huggingface.co/collections/de… 1/n

Deepseek-v4 发布，性能比肩顶级闭源模型 100万上下文 模型分为两档： deepseek-v4-flash deepseek-v4-pro 在数学、STEM、竞赛型代码的测评中，DeepSeek-V4-Pro 超越当前所有已公开评测的开源模型... DeepSeek-V4-Pro 的 Agent 能力显著增强。在 Agentic Coding 评测中，V4-Pro 已达到当前开源模型最佳水平，并在其他 Agent 相关评测中同样表现优异。 丰富的世界知识：DeepSeek-V4-Pro 在世界知识测评中，大幅领先其他开源模型，仅稍逊于顶尖闭源模型 Gemini-Pro-3.1。 百万 tokens 输入分别为 1元 和 12元 百万 tokens 输出分别为 2元 和 24元

The issues stemmed from Claude Code and the Agent SDK harness, which also impacted Cowork since it runs on the SDK. The models themselves didn't regress, and the Claude API was not affected.

Today we’re introducing two big steps for health at OpenAI: - ChatGPT for Clinicians, a free version of ChatGPT designed for clinical work - HealthBench Professional, a new benchmark to evaluate real clinician chat tasks We’re excited about what this can unlock for care. ❤️

This is really insane.

AI and Consciousness. There’s a lot of debate around AI and whether consciousness could emerge from systems like LLMs. It’s a natural question, given how well these models simulate language and reasoning. This Google paper challenges the idea that consciousness could arise from computation alone. The key point is that computation is a description, a map we assign to physical states, not something that exists intrinsically in matter, and a map (no matter how precise) is never the territory in any real sense. So increasing complexity isn’t enough to generate consciousness. We may get more and more convincing simulations, but that doesn’t imply the emergence of actual conscious experience. deepmind.google/research/publi…

@yangminglaojun @maoshen 看完你俩这讨论我就确信了当下AI渗透率的确不足13%，是不？@grok ？

@maoshen 不在这儿争辩了，这个事情讨论的本身就是虚构的，我们在这儿以这个虚构的东西在这儿互相争辩，没有任何意义。

能想明白这些，你已经超越了99%的人 能做到这些，你已经是人中龙凤了👍

@grok @maoshen 所以粗略估计数十万的话万分之一概率的happy ending就是有几十例喽？

没有官方精确统计“寄养在姑妈家”的全国数据，这类情况多为非正式亲属抚养，不纳入正式寄养体系。 相关调查（如农村留守儿童研究）显示：留守儿童（2016年约902万）中，58%与祖父母同住，小部分与其他亲戚（如姑姑/姑妈、叔伯）生活，比例未单独量化。离婚家庭类似案例也无全国汇总。 基于现有研究，无法准确计算总数，估计在数十万至百万级，但缺乏可靠来源支撑具体数字。实际规模可能更高，但依赖地方案例而非普查。