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这位法国 AI 选手 Jeanviet 用 Claude 完成他 80% 的 Youtube 视频制作，果然大家都在设计内容工厂 AI Agent 要不是我把 Claude Token 烧光了，高低把转录好的视频放上来，现就将就着看文字版咯 jeanviet (Romain) 的 YouTube 自动化流水线 视频 URL: 核心步骤拆解 1. 输入脚本/URL — 把视频脚本文本或 YouTube URL 粘贴进自建工具"YouTube Rod"，作为整条流水线的起点。 2. Claude 生成标题 — Claude CLI（一次生成 10 个标题候选，每个附带 CTR 评分和选择理由，挑一个最强的。 3. 关键词→参考缩略图 — 选定标题后 Claude 自动输出关键词，用这些关键词搜出大量高点击率的参考缩略图供灵感选择。 4. AI 批量生成缩略图 — 选一张参考图后，用 GPT Image 2（通过 Replicate）生成 5+1 张变体：第一张忠实还原参考，后五张做创意发散。 5. Photoshop 精修 — 把 AI 缩略图拉进 Photoshop，用生成式填充调尺寸，抠出人物加曝光/对比度/锐度让脸部更突出，最终定稿。 6. 生成描述/标签/章节 — Claude 根据脚本自动生成视频描述、合作伙伴模板、章节标记和 500 字符内的 SEO 标签，直接复制粘贴到 YouTube 后台。 7. 一键触发全平台分发 — 点击"发布 + 创建 Lead Magnet"，系统自动生成 Instagram Story、LinkedIn 帖子、Twitter 推文、Skool 社群帖，全部从一个 URL 出发。 8. Shorts 自动工厂 — 通过 Opus Clip 自动从长视频中裁出多条短视频，顶部加 hook 文字 + CTA（评论关键词即送完整视频链接）。 9. DM 自动回复 — 用户在任何平台评论关键词（如"short"），ManyChat 自动私信发送对应视频链接，跨平台打通。 10. 周报 Newsletter 自动生成 — 每周三自动生成一期 Newsletter，以最新 YouTube 视频为核心内容，推送给邮件订阅用户。 11. YouTube 选题雷达 — 每日自动爬取 241 个同赛道频道，计算每条视频的"病毒系数"（如播放量 vs 日常均值 ×25），筛出爆款供选题参考。 12. Claude CLI 批量出脚本 — 基于选题雷达的结果，Claude 直接在 CLI 中批量产出适配自己风格的脚本和 SEO 长青选题（如"什么是 vibe coding"）。

kimi k3 vs gpt 5.6 sol vs fable 5 vs grok 4.5 @Kimi_Moonshot just dropped kimi k3 – a 2.8t param native multimodal model, the first open 3t-class release. key facts: • 1m token context. stable latentmoe activating 16 of 896 experts, built on kimi delta attention (kda) and attention residuals • quantization-aware training from the sft stage onward – mxfp4 weights, mxfp8 activations. moonshot claims ~2.5x scaling efficiency over k2 • max thinking effort by default. low- and high-effort modes are "coming in updates" – there is no way to turn the thinking down today, and you feel it in every run • pricing: $0.30/mtok cache-hit input, $3.00/mtok cache-miss, $15.00/mtok output. claims >90% cache hit rate on coding workloads • benchmarks: swe marathon 42.0 (1st – fable 5: 35.0, sol: 39.0, opus 4.8: 40.0), terminal bench 2.1 88.3, browsecomp 91.2 (1st), program bench 77.8 (1st), gpqa-diamond 93.5. loses frontierswe 81.2 vs fable's 86.6, and deepswe 67.5 vs sol's 73.0 our test – 3 prompts, single-file html, @threejs, fully procedural, no assets: 1. photorealistic european roulette wheel – 37 pockets in the real sequence, mahogany clearcoat bowl, chrome turret, diamond deflectors, flick-to-spin, ball that spirals inward and settles on a mathematically real number 2. las vegas slot machine – 3 reels behind transmissive glass, drag the chrome lever to play, mechanical odometer counters modelled in 3d, coin physics on win 3. full pinball table – 6.5° tilted playfield, flipper impulse physics, spline ramps, drop targets, 6 bumpers, mechanical score reels in the backbox we ran the test on @aimlapi platform results: - cost #1# grok 4.5 – $0.30 #2# kimi k3 – $0.71 #3# gpt 5.6 sol – $2.05 #4# fable 5 – $7.69 - tokens #1# grok 4.5 – 34,241 #2# gpt 5.6 sol – 51,748 #3# fable 5 – 144,126 #4# kimi k3 – 157,999 - lines of code #1# gpt 5.6 sol – 3,054 #2# grok 4.5 – 3,047 #3# kimi k3 – 2,255 #4# fable 5 – 1,950 - generation time #1# grok 4.5 – 5.1 min #2# gpt 5.6 sol – 22.0 min #3# fable 5 – 31.5 min #4# kimi k3 – 75.6 min observations: • kimi k3 is cheap and it is slow. 75.6 minutes across three prompts against grok's 5.1. it is 2.4x grok's price and 15x grok's wall clock. the roulette took 15 min, the slot 18, the pinball 42 • it failed 2 of 3. only the roulette works. the slot machine has reel cutouts on both faces of the cabinet and the symbols face backwards – you can only read your spin by walking around to the rear of the machine. the pinball table stands vertically on its edge with the legs floating detached beside it. • 81% of kimi's output tokens are reasoning, not code. grok: 22%. you are not paying for a bigger answer, you are paying for a longer argument with itself • price per 100 shipped lines – grok $0.010, kimi $0.031, sol $0.067, fable $0.394. a 39x spread for the same three files kimi k3's code quality: upsides: • the roulette is genuinely good – procedural wood grain with real specular breakup, correct european sequence (0-32-15-19-4...), chrome turret, diamond deflectors, clean console • the pinball artwork is the best in the test – a synthwave "nova strike / deep space" field with six individually coloured neon bumper rings, a retro sun on a grid horizon, a nova burst, and a scoring legend printed on the apron. no other model printed the rules on the machine. it is a beautiful texture on a broken object • physics reasoning is real – it derived a 480hz substep for the collider, worked out ball settle conditions and termination guarantees, and checked every ramp exit vector by hand before writing any of it • it is the only model that saw the importmap trap coming. sol shipped a blank white page twice because three.js addons import the bare specifier 'three' and die without an import map downsides: • it dodged that trap on the slot by loading three.js r128 through classic script tags – a 2021 build with no working transmission. its slot glass rendered fully opaque and buried all three reels behind a white pane. the code asks for transmission: 0.93, ior: 1.5 – correct, and silently ignored by a renderer that predates the feature • after 42 minutes and 212k characters of reasoning, the pinball cabinet is not assembled. the table stands vertically on its edge like a wardrobe – the prompt asked for 6.5° from horizontal, it delivered 90°. the legs float detached in the void beside it. head-on it photographs beautifully; orbit ten degrees and it is a painted slab with four chrome rods hovering nearby • the playfield z-fights with the glass – hard black banding across the whole field as soon as you pull the camera back a note on the pinball, in fairness to kimi: nobody passed it. every model shipped broken ball physics and controls you cannot trust. it is the hardest prompt we have run and the whole field failed it, each in its own way kimi k3 reasons better than anything else here and it shows exactly where reasoning pays – physics constants, sequences, edge cases, traps the others walked into follow @thehypedotnews for 24/7 ai news, analysis and breakdowns

6月26日 bitcoin:native 现货 ETF 总持仓降至 1,217,241.00 BTC。 当日净流出 8,532.84 BTC，这是历史中第九大单日净减持，虽然弱于 6月25日的历史第二大流出，但连续两天大幅减持后，本周累计净流出已经扩大到 30,110.49 BTC。 近 7 个交易日净流出 32,958.48 BTC，已经属于历史非常靠前的连续减持压力区间。 #Bitget# 来了就是VIP！Crypto、美股、CFD，全球先机一站布局

Meanwhile in China? People are living in full “AC freedom” — running it whole day like it’s nothing. Real numbers: A decent 1.5HP inverter air conditioner costs 1,700 RMB (€220). Installation: 300 RMB (€39). Total: just 2,000 RMB (~€260). Even in Beijing with tiered electricity pricing: • 0–240 kWh: 0.49 RMB (~€0.06) • 241–400 kWh: 0.54 RMB (~€0.07) • 400+ kWh: 0.79 RMB (~€0.10) Running the AC 12 hours a day (400 kWh for cooling) still only adds about 200 RMB (€26) to the monthly bill. How do they pull this off? 1. Massive power infrastructure 
China’s total electricity use hit 10.4 trillion kWh in 2025 — more than twice the US, and bigger than EU + Russia + India + Japan combined. Meanwhile, renewable energy now accounts for about 60% of total installed power capacity (23.4 billion kW), and nearly all new electricity demand is being met by fresh renewable generation. 2. They dominate AC manufacturing 
China produces around 80% of the world’s air conditioners. Complete supply chains + huge scale = super affordable prices for normal families. This is what real “AC freedom” looks like.

有个交易员用Claude写了个量化机器人，在Polymarket上赚了3.4万多美元。 从6月2号开始，这个钱包平均每天进账2014美元，每小时要跑34笔交易以上。 17天里一共做了13927次预测，胜率44%。 这是他的Polymarket账户： 这哥们一开始存了大概6000美元，现在收益率差不多572.1%。 机器人的玩法其实挺简单： > 主要就是做空加密市场，趁着赔率还没跟上节奏的时候下手 > 在价格重新调整到位之前就进场，然后反复用这个套路，分散到大量交易里吃差价 赚得最狠的几笔： $332 → $1,899（赚了$1,566，涨幅471.06%） $367 → $1,503（赚了$1,136，涨幅309.28%） $129 → $1,241（赚了$1,112，涨幅862.06%） 最值得注意的，倒不是某一把运气爆棚。

Arkham 监测显示，美国政府地址转移约 80 万美元 Alameda Research 相关资产。该笔资产属于此前美国司法部查封的 Alameda/FTX 资产，后续将用于偿付 FTX 债权人及受损用户。美国政府持有约 32.84 万枚 BTC（约 241.9 亿美元）、1.46 亿枚 USDT（约 1.46 亿美元）、6.24 万枚 ETH（约 1.25 亿美元）及 750 枚 WBTC 等加密资产，总持仓价值约 245.9 亿美元。

把特朗普的持仓报告扒了下挖到两个质量还不错的公司 $ADBE 大名鼎鼎的 Adobe ，目前价格$241， 市盈率只有 13，总市值千亿美金，10.8% 的自由现金流收益率和 89% 的毛利率，还有250 亿美元的回购计划。但是价格这么低不是没有原因的，因为受到 AI 冲击，订阅式的商业模式不再适用。 目前来看Adobe 不是一家正在死掉的公司，是一家正在变慢的公司。 $WDAY 和 SNOW 和 NOW、CRM 等同一赛道，Workday解决的是企业核心管理系统的刚需——人力资本管理（HCM）和财务管理（FMS），目前价格$130 目前正站在一个关键的十字路口，市场既害怕AI颠覆它的商业模式，又期待AI成为它的新增长引擎。 今天晚点会更新一下，投研报告，记得关注 @lianyanshe

Cierre #ETFs# spot #Bitcoin# · 26 may 2026 Top 5 (1.241.656 BTC ≈ 5,91 % del supply): ▸ $IBIT +0,07 % ▸ $FBTC +0,12 % ▸ $GBTC +0,15 % ▸ $BITB +0,17 % ▸ $ARKB +0,14 %

@KsamKera @ilivedbynight @michooki This is directly from douyin. Xiao Zhan 241 Billion Views Zhang Linghe 99 Billion Views. I just SS few minutes ago from douyin, that why you are still clueless to be a cent stan, you can't even search the original app