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FBI ve Adalet Bakanlığı, Kuzey Kore bağlantılı devlet destekli hackerların FaceStealer adlı düzenle sahte video görüşmeleri üzerinden 400 milyon doların üzerinde kripto para çaldığını açıkladı. Son 18 ayda 900'den fazla kurban var; hedefte kripto ve web3 sektörü, özellikle açık kaynak geliştiricileri. Bu rakamı iki kez okudum. Sahte ya da ele geçirilmiş hesaplardan gelen davet sizi Zoom, Teams veya Google Meet'in taklit sürümüne çekiyor.

🚨 BIG: The US Department of Justice seized infrastructure linked to North Korea’s $400 million FaceStealer crypto theft scheme and froze more than $1.2 billion in cryptocurrency stolen from Binance.

“One of the great rivalries in the NBA.” A NEW CHAPTER of Celtics-76ers commences TONIGHT. 🍿 Jaylen Brown faces former team 🍿 Paul George faces former team 🍿 4th matchup as top 2 teams in East since 1986-87 Tipoff at 8pm/et on NBC and Peacock!

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?

Faces and number plates never leave the phone. Every Vangrid capture is blurred on the device before the video is encoded. Unblurred frames are not uploaded, not stored, not recoverable. Buyers get a 3D model of the physical world. Never the people in it.

Jensen Huang’s affair is just a trigger. What we are witnessing is a pre-planned power grab over Nvidia’s trillion-dollar computing empire, coordinated by Wall Street and Washington. Some sharp Chinese-American commentators call it America’s new Red Scare targeting elite Asian entrepreneurs. Bill Gates, Elon Musk and other white tech billionaires have faced repeated scandals over personal conduct. None were dragged into national security probes or boardroom takeovers. Only Jensen Huang, after a personal relationship misstep, faces an independent board investigation and hostile narrative from intelligence circles. The double standard could not be clearer: For white elites, personal flaws are private matters. For a Chinese-born leader controlling a strategic tech asset, any tiny blemish gets framed as a national security risk. Nvidia is the backbone of global AI computing, valued at roughly $4 trillion. Unlike Meta, where Mark Zuckerberg locks control with dual-class super-voting shares, or Microsoft and Amazon, deeply integrated with the Pentagon and intelligence agencies, Nvidia has no such protective structure. Public filings from 2026 show Jensen Huang holds only 3.58% of shares, and all directors plus executives together hold merely 3.94%. Vanguard and BlackRock own 9.32% and 7.43% respectively, holding decisive voting power. Without institutional shields or deep political backing, this critical tech giant sits exposed on the chessboard of great-power competition. The groundwork for this takeover was laid months ago. Longtime board allies of Huang, Mark Perry and Michael McCaffrey, stepped down from key committees. Insiders tied to Democratic establishment, Wall Street and U.S. intelligence quietly moved in: ✅ Suzanne Nora Johnson, former Goldman Sachs vice chair and co-chair of Brookings Institution, joined Nvidia’s audit committee in July 2026 with direct oversight of internal investigations and compliance. ✅ Kenneth Jacobs, vice chair of Brookings and incoming Vanguard chair, controls the largest institutional voting bloc and operates within the same inner circle as Johnson. ✅ Gilman Louie,founding CEO of CIA-backed venture fund In-Q-Tel and member of the President’s Intelligence Advisory Board, works alongside Johnson on the same national tech fund, overseeing intelligence acquisition of strategic tech firms. The media rollout followed a precise political timeline. Initial trial balloons appeared on Oct 29. On Nov 6, the very day Democrats secured full control of Congress, Julian Barnes of the New York Times (national security beat) and Demetri Sevastopulo of the Financial Times published coordinated reports, citing intelligence memos while breaking the story of the personal scandal. The real offense was never the affair. It was the 2025 deal Jensen struck with the Trump administration: offering a 25% revenue share to win export approval for H200 chips into China. A normal commercial negotiation, reframed by incoming Democrats as a dangerous compromise on U.S. AI sovereignty. This investigation will not crash Nvidia’s stock — Wall Street holds massive stakes here. But it will deliver three strategic wins for the U.S. establishment: 1. De-founder and de-Sinicize Nvidia: A new permanent national security compliance committee, led by Johnson’s faction, will strip Huang of authority over chip exports and overseas strategy. His dual Chairman-CEO role will be split. 2. Lock down China’s AI ceiling: Washington will seize full command of global advanced computing supply, regulating chip flows to slow China’s AI progress. 3. Retroactively target Trump: Once Democrats take over congressional oversight panels in January 2027, this case will be used to accuse the Trump White House of negligence for approving the H200 export deal. Jensen Huang spent 27 years building this computing empire, believing in rules, technical merit and business contracts. But there is a brutal truth in America’s power game: Top-tier strategic technology and wealth without political cover are nothing more than bargaining chips waiting to be carved up. White elites get generous room for error. Asian pioneers who climb to the very top get almost none. This is not a story about infidelity. It is a raw demonstration of racial hierarchy, capital control and partisan power politics in the United States.

13M followers It’s easy to look at that number and forget there was a time when almost nobody knew who CZ was. Back in 2013, he discovered #Bitcoin# through a poker game One conversation changed his direction He studied Bitcoin…He believed in it…He took a massive risk, even selling his apartment to go all in on the industry he believed would change the world Then came @Binance in 2017 No billion dollar brand No millions of followers Just a vision, a small team, and the belief that crypto should be accessible to everyone The rest became history Today, 13 million people follow @cz_binance But to me, the most powerful part isn’t the 13M, It’s remembering the journey from one person discovering Bitcoin and then building #Binance# to becoming one of the most recognized faces in crypto 🫡 Respect, CZ ::

Arizona State cheerleader hit with two misdemeanor charges after allegedly interfering with an arrest. ASU senior Eryn Bonner was thrown to the ground after demanding that officers "let go" of someone they were trying to arrest. Bonner now faces charges of disorderly conduct and hindering or interfering with police. Tempe police accuse Bonner of punching an officer multiple times.