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JUST IN: A mystery trader has made nearly $200 million betting against Nvidia, $NVDA, weeks before Jensen Huang resigned as CEO, per the FT. Here's how the trade worked: The trader bought 180,000 put options at a $150 strike and sold 280,000 puts at a $100 strike. In simple terms, it was a bet that Nvidia would fall hard. It cost about $8 million to put on. It's now worth around $196 million. That's about 24x their money. Nobody knows who it is yet.

🔴 TÜM ALTCOİN SAHİPLERİ, SÖYLEDİKLERİMİ DİKKATLE DİNLEYİN! Çünkü bu noktadan itibaren, sadece bir tahmin paylaşmıyorum… KENDİ İTİBARIMI VE 9 YILLI ÇALIŞMAMIN TÜMÜNÜ RİSK ALTINA ATIYORUM! SOL'u 5 dolarda, AVAX'ı 2 dolarda, XRP'yi 0.50 dolarda ve MATIC'i 0.003 dolarda çağırdım. Üç yıl önce, 8.000 dolarlık bakiyemi 2.5 milyon dolardan fazlaya çevirdim. Gelecek üç ay, hem benim hem de piyasa için belirleyici olacak. 🔴 KASIM — ARALIK — OCAK Bitcoin → 180.000$ Ethereum → 10.000$ Altcoinlerde → 60X BAŞLANGIÇ İÇİN. Bazı coinlerde 100X, 150X, 200X+ göreceğiz. BU OCAK'TA BİTECEK… Eğer söylediklerim gerçekleşmezse, 9 yıllık emeğimi koyduğum bu işi bırakacağım ve X HESABIMI SONSuza DEK SİLECEĞİM! Bu sözleri unutma. Ekran görüntüleri al. Tarihi işaretle. Çünkü piyasa döndüğünde, herkes her zaman ne kadar haklı olduklarını söyleyecek… AMA EKRAN GÖRÜNTÜLERİ YALAN SÖYLEMEZ! Zirveyi kaçırmak istemiyorsan beni takip et. FİNALDE GÖRÜŞÜRÜZ…

我们那里有个精神小伙18，谈了个精神小妹16.干柴烈火，小妹肚子有了，准备结婚。精神小妹单亲家庭，她妈属于老一辈精神小妹，那时候叫非主流，还是啥。他妈才33.办完婚礼，小妹回家养胎。精神小伙发育很好，185，身上纹着大黑龙，乌龙枪很猛。一来二去和丈母娘擦出火了，成功上垒。丈母娘有了......纸里包不住火，精神小妹知道了，把他们骂了一顿。然后做了一个逆天的举动，把孩子流了，把精神小伙的爷爷给上了，上了好几次，终于也怀了........没想到这个帖子火了，昨天我打听下了后续，相当炸裂。爷爷和精神小妹一胎2个男孩，精神小伙和岳母生了个女儿。二胎精神小伙和精神小妹生了一个男孩。今年精神小伙和精神小妹领证，刚到结婚年龄。爷爷才50多，杀猪出身，185 感觉180多斤吧，会武术。后来混社会，身体素质应该胜过知乎大多数人精神小妹为啥不找精神小伙他爹。因为他爹和别人对象探讨人生的时候被精神小伙他妈发现，用刀一次性卸载了QQ……有朋友问精神小伙奶奶去哪里了？她奶奶和他爷爷经常去别人家偷猪。最后一次的时候，从猪圈跳下去（以前农村猪圈和厕所一体），掉在茅坑里，淹个半死，奄奄一息爬上去的时候，被3头猪攻击，吃了一大半。剩下头和小腿……[捂脸]

场内都带人赚1000万美金，场外根本不敢想那些人赚了多少。 用codex抓了一下币安跟单180天跟随者收益，所有跟随者收益为正的带单交易员这180天内跟随者收益总和都没我多。 。

九十九十法则：AI 写完前 90%，剩下的 90% 谁来写 贝尔实验室的汤姆·卡吉尔有一句流传很广的玩笑话： “前 90% 的代码，花掉了前 90% 的开发时间；剩下 10% 的代码，花掉了另外 90% 的时间。” 你没看错，加起来是 180%。这就是软件项目的真实写照！ AI 时代，这个法则变得格外扎心。 用 AI 搭一个原型，几个小时就出来了：界面有了，主流程跑通了，演示效果惊艳。很多人在这一刻觉得：项目快完成了！ 然后，真正的工作才刚开始：边界情况、错误处理、权限、并发、性能、数据迁移、兼容老版本、监控告警…… 这些“最后的 10%”，往往决定了一个系统能不能真正上线、能不能长期运行。 AI 在前 90% 上帮了大忙，可在后 90% 上，它的帮助要打折扣，因为这部分需要对真实环境、真实约束的深刻理解。 所以下次看到一个惊艳的 AI 原型，先别急着欢呼。问一句：剩下的那个“90%”，谁来写？多久能写完？

Our initial public offering: Legal disclaimer: Anthropic has filed a registration statement (including a prospectus) with the SEC for the offering to which this communication relates. Before you invest, you should read the prospectus in that registration statement (available at: and other documents Anthropic has filed with the SEC for more complete information about Anthropic and this offering. You may get these documents for free by visiting EDGAR on the SEC Web site at Alternatively, copies of the preliminary prospectus may be obtained from: Goldman Sachs & Co. LLC, Attention: Prospectus Department, 200 West Street, New York, NY 10282, by telephone at (866) 471-2526, or by email at prospectus-ny@ny.email.gs.com; or Morgan Stanley & Co. LLC, Attention: Prospectus Department, 180 Varick Street, 2nd Floor, New York, NY 10014. The securities may not be sold, nor may offers to buy be accepted, prior to the time the registration statement becomes effective. This post is not an offer to sell, or a solicitation of an offer to buy, the securities in any jurisdiction where the offer or sale is not permitted.

一个钱包靠5分钟比特币K线，赚了57.3万美元。 每5分钟，Polymarket就开一个“比特币涨还是跌”的市场。 比特币一动得快，总有一边被定价得好像根本不可能发生。 这个钱包就买那一边，一次又一次地买：从2025年8月到现在，已经做了108125个市场。 → 8美分买跌：投180美元，拿回2220美元（+1135%） → 13美分买跌：投227美元，拿回1769美元（+680%） → 14美分买跌：投392美元，拿回2744美元（+600%） → 就这三笔：投进去大约799美元，拿回来大约6733美元 → 屏幕上最赚的5笔：投进去大约1745美元，拿回来大约11115美元 单笔最大盈利：2719美元。 钱包： 大多数人都在追一笔大交易。这个钱包不追，它只做下一个5分钟。

255M views on a 3D Short by Zack D. Films i tried to rebuild his style with ONE Claude prompt, then ran it on Opus 5.5 and Fable 5.2 (they did NOT make the same Short) the full prompt is below ↓ paste it into Claude Code in an empty folder and answer its 2 questions. it shows u the script and waits for ur go. u need Blender + its free MPFB add-on and a graphics card. give it a few hours (the prompt is minus one optional paid-voice line) Ask me 2 things, then wait: 1. The story in one line: a strange TRUE event where one person did one odd physical thing ("He tied 42 weather balloons to a lawn chair."). If I say "you pick", pitch 3 with one source link each and take the first unless I choose. 2. The voice. Default: Kokoro (free, runs on my computer), a calm, warm male narrator. Then tell me everything else is free: Blender (find my install, or tell me the one download), its free MPFB extension for human bodies (ask me before you install it) and into this folder a Python venv with FFmpeg (imageio-ffmpeg), kokoro-onnx + its model files (kokoro-v1.0.onnx and voices-v1.0.bin from the kokoro-onnx GitHub releases), faster-whisper (small.en), numpy and Pillow. It needs no API key or account and renders on my graphics card with EEVEE. The look: a clean, realistic 3D world, like a good game cutscene. Bright, saturated, a little filmic. - People: realistic bodies with generic faces and big readable expressions (shock, a smirk, a scream). Plain clothes, no logos. Never a real person's likeness: for a real person keep the face out of close-ups (hands, back, side, distance, straight top-down). - CALM shots only. Bodies in fast action or contact (running, jumping, fighting, falling) look stiff, so tell the story with frozen moments under a slowly moving camera, macro inserts of hands and objects, rooms, vehicles, the sky, top-down views and the aftermath. - One new picture for every caption chunk (2-4 words, about 1-1.5 s): a new framing, a new action or a camera move. Nothing ever holds still: every shot drifts, pushes in or orbits. - The shot kit: macro insert (extreme close-up of the key object or hands, very shallow depth of field), hero low angle (wide lens at waist height), god's-eye top-down with a slow rotate, tracked object, over the shoulder, smash zoom on the word that matters, whip pan between beats, glow highlight (the named object glows orange with a rim, then fades), a big 3D number lying in the scene, a thought bubble (a cloud ring showing what he hoped for), a TV in the scene replaying the event. - Light: a bright warm sun, blue sky with clouds, soft shadows. Night scenes use hard lamps and a dark sky. Wide lens up close, depth of field on every shot, motion blur on every fast camera move. - Captions: 2-4 words at a time, white bold rounded sans, about 64 px on a 1080 px-wide frame, centred, 78% down the frame, soft dark shadow, no box. Each chunk replaces the last on the same frame as its picture. - Banned: real footage, photos, downloaded textures or 3D models, logos, AI images or AI video, downloaded music, gore. 38-50 s, 100-140 words, 150-180 words a minute. The voice starts at 0.0 s. - Line 1: the most surprising physical act, in past tense, opening with "He" (or "She"). No name, date or setup. Frame 1 shows that act. - Then a cause-and-effect chain: every sentence starts with a hinge word (Then, Suddenly, So, Because, But, Later) and is ONE visible action. - The context arrives late, after "You see,". - A reveal: someone looks closer and the story turns. - The last line is the consequence. No call to action, no question. - Names are rare: use one only when it pays off. Title = "He ..." or "The Man Who ...". The cover is the first frame. Save every stage to disk so a crash never costs more than one stage. - sources.md: every fact with its link and the date you read it. Anything you can't verify stays out. - script.json: the lines and the caption chunks cut by hand (2-4 words, one picture each), each chunk with its shot: the set, the camera, what moves. - Kokoro reads the whole script in one take (speed 1.0-1.1) and pauses are squeezed to 0.35 s at most; faster-whisper times every word (pass it a 16 kHz numpy array, not a path); write chunks.json with each chunk's start and end. A picture and its caption switch together on frame round(start*30)+1. - blender/: Python scripts run headless (blender -b -P). makes one .blend with the sets, the cast, the props and every shot baked with a key on every frame. sets EEVEE with ray tracing, the AgX view with the Punchy look, motion blur, depth of field and bloom in the compositor. Bodies come from MPFB or are built by you; clothes, hair, props and sets are built in code. - Stills first: one half-size still per shot as a contact sheet. Look at every tile and fix what's off before any full render. Time one full-size frame and tell me the estimate. - Render 1080x1920 at 30 fps to PNG frames, skipping frames already on disk. - numpy only: a light music bed, a sound on every action (a whoosh on each whip pan, hits, wind, room tone), ducked under the voice, mastered to -14 LUFS on the whole stereo mix. - burn the captions in from chunks.json. Encode out/_9x16.mp4 (1080x1920, 30 fps, TV-range yuv420p) and out/_x_7x8.mp4 (1008x1152, under 10 MB, 2-pass): a crop of the 9:16 frame that keeps the subject and the caption. - Blender paths: pass absolute output paths (a relative one lands on the drive root). - MPFB headless: enable it with addon_utils.enable("bl_ext.user_default.mpfb"). Bake a body's shape keys before you pose it: the rig is fitted to the baked shape. - Clothes: cut them from the body mesh and push them 7-16 mm out along the normals; keep two rings of body faces under every hem. - Nothing coplanar: keep every resting object 1 cm off its neighbour and draw ground markings into the texture, or they flicker. - Hair: EEVEE draws hair only from a Curves object, hair type STRIP. Use a Principled BSDF on it (the Hair BSDF renders black). - Skin: keep subsurface weight near 0.2 (more turns faces black in EEVEE) and add a soft fill light from below under a noon sun. - Hands: a curled hand reads as a claw from the palm side, so shoot a grip from behind the knuckles. - Motion blur: shutter position START, a key on every frame, plus a key half a frame after each shot's last frame, so blur never reaches across a cut. - Check: run a black-frame and one-frame-flicker check on the render. Make a contact sheet (a frame every 0.5 s) and look at every tile: the act reads in the first 2 s, faces are lit, nothing clips through anything, captions stay off faces and key objects. Then step through the first 2 s, the middle and the end frame by frame. Fix, render only the changed shots again. Pitch (or take my story), then show me the script with the word count, the caption chunks with their seconds and the shot list with what the first frame shows. Build nothing until I say go. how the two runs went: one run each on the same PC, so it's one sample, not a ranking. both took under 3 hours on one shared 8 GB graphics card. the story for both: a man who tied 42 weather balloons to a lawn chair in 1982 where they split: -> Opus opened wide on the balloons over the yard. Fable opened on the man kneeling at the chair with his Jeep behind him -> Opus put 5 big 3D numbers in its scenes, Fable 2 -> Fable followed the caption spec (white text, soft shadow). Opus went ALL CAPS with a thick outline -> Fable pulled the Smithsonian's own record and ended on the chair in the museum. Opus ended on the $1,500 fine -> a few Opus shots are hazy and one opens on a blank grey frame save this for ur next Short. who did it better, Opus or Fable?

20岁出头就这么牛了。。 华盛顿大学计算机金融男 JJ Simon，用打扑克赢的5000美元去做交易，一年多赚了 180 多万美元，相当于1000多万人民币，我把他的策略曝光了😘🤑 他说自己做交易，用的就是大学里学的那一套。 他做交易的逻辑是，价格被一大波买卖订单推出去以后，早晚会回到一个公平的价格，比如纽约早上九点半一开盘，隔夜攒下的单子和大机构的单子一起涌进来，价格第一下经常会冲过头，他把开盘那一刻的价格叫公允价，意思就是公平的价格。 价格冲出去多远，往回做就能赚多少。 所以他每个时段都是一个做法，先定好公允价，开盘顺着方向做一笔，之后就等信号往公允价做回去。 先说公允价怎么定，平常的日子就用九点半开盘的价格，他会把开盘前最后一分钟，九点二十九分那根 K 线框出来，一直往右拉，全天都拿这条横线做参照，开盘以后价格要是直接冲回了开盘前横了很久的那个位置，他就改用那里。 有的日子早上八点半会公布重要数据，比如通胀数据 CPI、PPI，时间都是提前定好的，这种日子公允价就换成数据公布前那一分钟的价格，这种数据大家早就在等，价格提前就消化过了，公布那一下拉出来的大 K 线是冲过头了。 到了九点半，价格要是一下子回到了数据前的价格，开盘价就不用管，就只看数据前的价格。 还有一种是没人料到的突发新闻，比如特朗普突然发帖或者美联储主席突然讲话，这种新闻会真的改变价格，公允价也跟着变，等价格冲完停下来，横着走一阵，横住的那一段就当新的公允价。 公允价定好了，开盘先做一笔顺势，顺势这一笔做完剩下的时间就只往回做。

Since first launching SynthID in 2023, we've watermarked more than 180 billion images and videos, along with 240,000 years of audio content. This tool joins our built-in verification features in Search, @GeminiApp, and @GoogleChrome, which now regularly handle more than 1 million verification requests daily. The SynthID Detector platform is part of our ongoing work to give you more context about the media you see online, so you can navigate the web with confidence. Learn more ↓