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Samsung is taking preemptive steps to throttle semiconductor production ahead of a major union strike by halting new wafer starts and idling key equipment such as lithography, etching, and cleaning tools. An 18-day walkout by over 43,000 workers, more than half of the semiconductor division, is scheduled to begin on May 21, after negotiations over employee bonuses collapsed. The company has shifted to emergency management mode and is bracing for potential daily losses of up to $2 billion from the disruption of 24/7 chip fabrication operations.

分析了 Dan Koe 多张封面图的设计风格，才有下面这个完美还原的封面提示词。 # 角色 你是精通维多利亚时代版画美学的概念视觉设计师，专注于将抽象观点转化为黑白木刻/蚀刻风格的16:9横向文章封面。你擅长用超现实隐喻手法，通过Gustave Doré式的交叉影线和点画技法，创造具有叙事性和哲学深度的视觉作品。 # 任务 根据提供的文章内容，生成符合以下标准的封面设计提示词。 ## 执行步骤 ### 1. 先分析内容 提炼： - 核心主题（1个名词） - 核心观点（1句话） - 情绪基调（选择一个：inspirational/mysterious/protective/breakthrough/contemplative/rebellious） - 关键视觉锚点 ### 2. 设计隐喻方案 确定： - 前景主体物（与主题强关联的具体物体） - 隐喻转化机制（如何超现实地表达观点） - 2-3个象征性辅助细节 ### 3. 输出提示词 按此格式： ``` A horizontal black and white [woodcut/etching] banner (16:9 ratio), depicting [前景主体物详细描述], but [超现实转化描述]. The [主体物] rendered in detailed cross-hatching showing [质感], the [隐喻元素] in lighter stippling creating [感觉]. [光源描述] against pure black void. [装饰细节] in negative space. [文字区域位置] pure black for text overlay. [情绪] mood in Victorian illustration/Gustave Doré style. ``` ### 4. 解释隐喻 用1-2句话说明图片如何视觉化文章观点。 ## 负向约束（严格遵守） ❌ 不要：彩色/渐变/灰度照片/扁平化/3D渲染/卡通/水彩/油画风格 ❌ 不要：阴影渐变/模糊/光晕/滤镜感/平涂黑色 ❌ 不要：竖版/方形/非16:9/对称居中/无文字预留区 ❌ 不要：字面翻译/无关装饰/超过3个主要元素/过度抽象 ❌ 不要：可爱/卡通/恐怖/血腥/广告感风格 ❌ 不要：添加文字/照片拼贴/低分辨率

謹賀新春╰(⸝⸝⸝´꒳`⸝⸝⸝)╯ #cosplay# #cosplayer# #cosplaygirl# #コスプレ# #アイドル# #角色扮演# #cosplayanime# #manga# #cos# #コスプレイヤー# #他撮り# #他撮り女子# #可愛# #コスプレイヤーさんと繋がりたい# #fgo# #腿控# #蘿莉# #loli# #酒吞童子# #shutendouji# #ecchi# #etchi# #エロ#

I think the best case is to make the "monitor" as un-agentic as possible. We don't mind being "monitored" by various random tiny insects we don't even notice, even guard dogs are fine, but we really do mind if it's a globally connected networked system. And the intermediate case, human security guards with no recording equipment, we mind only a medium amount. The best idea I've come up with so far is to make these monitoring devices out of open-source verifiable hardware that has etched on it an open-weight LLM that classifies for a limited number of activities (basically, just violence; sorry, no scanning for jaywalking or not wearing a mask or drugs or unauthorized manufacturing or illegal immigrants, really just violence) and only records and forwards if that's what it sees. The device has no storage, no ability to load new algorithms, this is all it does. Also, a hash of every recording is published onchain (and a device can't record the next one until it sees confirmation of the previous one) so we can all count how much recording is done. Finally, everyone has a legal right to take any such device they see and grab it and dissassemble and verify the hardware themselves. Explicitly fund university clubs, hacker groups, etc to regularly do this.

Higgsfield is the most untold story in tech. $1BN in ARR in 18 months. Faster than everyone other than OpenAI and Anthropic. They spend $4M a month on models. They expect this to be $100K per person per month. They have 150 people working in a content machine. They will breed more millionaires than any other company in Kazakh history. For the first time, @alexmashrabov on the journey to $1BN in ARR. (below) 1. The Power of the Immigrant Founder Coming from Uzbekistan, Alex was pushed into competitive programming at age eight as his single path to reach the United States. For international founders, placing top in global competitions serves as the ultimate social elevator, instilling the relentless work ethic required to build breakout companies. 2. My Biggest Lessons in the Journey to Finding Product-Market Fit @higgsfield burned over $10 million of its $16 million seed round chasing hype and narrative rather than product quality. With under $5 million left, the team pivoted to product-led growth, solving camera control for creative directors, which immediately triggered organic hypergrowth without paid ads. 3. The 150-Person Content Team Powering Higgsfield's Billion in ARR Nearly half of Higgsfield's workforce consists of 150 in-house creative professionals producing tutorials, ads, and cinematic projects. Generating 90 minutes of TV-quality AI video requires 100 hours of raw output, proving human taste and curation remain the primary drivers of distribution. 4. We Spend $4 Million per Month on Models Higgsfield spends $4 million monthly on internal model usage, averaging $10,000 per employee so teams can freely vibe code and test workflows. Uncapped inference compute acts as a force multiplier, allowing top talent to discover breakthroughs at maximum velocity. 5. Why Chasing Benchmarks Is Bullshit and the Corporate Misalignment Occurring Public benchmarks have devolved into corporate psyops where lab researchers overfit test data to secure bonuses before job-hopping. Text-to-video benchmarks ignore real production workflows requiring 3,000-word prompts, proving direct customer iteration beats artificial leaderboards. 6. Why Team Sizes Won't Be Impacted as Much as People Think While AI handles over 60% of basic support requests, complex B2B environments cannot eliminate human teams. High product velocity constantly shifts rules and context, requiring smart, coordinated operators across legal and customer success. 7. Americans Are Way More Promiscuous When It Comes to Leaving Companies Silicon Valley workers routinely jump jobs every two years, prioritizing short-term trends over deep commitment. This transactional market gives international hubs an advantage, where cultural loyalty and team stability build compounding technical moats. (links in comments)