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📢 11/17(월) 무점검 업데이트 안내 11/17(월) 18:00 경에 무점검 업데이트가 진행되었습니다. 게임을 완전히 종료하신 후 재접속하여 업데이트 리소스를 다운로드해 주시기 바랍니다. ​​자세한 내용은 아래를 확인해 주시기 바랍니다.​​​​​​ ✔️ 업데이트 내용 1. 일부 계정에서 미니 게임 REBUILD : EDEN의 주요 임무 [승강기를 건설하기]를 승강기 건설 후에도 완료할 수 없는 현상 수정 👉 공지사항 바로보기 * 인앱 구매(확률형 아이템 포함) #니케# #NIKKE# #업데이트#

📢 11/11(화) 무점검 업데이트 안내 11/11(화) 21:30 ~ 23:00 경에 무점검 업데이트가 진행됩니다. 게임을 완전히 종료하신 후 재접속하여 업데이트 리소스를 다운로드해 주시기 바랍니다. ​​자세한 내용은 아래를 확인해 주시기 바랍니다.​​​​​​ ✔️ 업데이트 내용 1. 지상에서 회복 중이던 스쿼드가 사망할 경우, 스쿼드를 편성하거나 회복할 수 없는 현상 수정 2. 일부 계정에서 미니 게임 REBUILD : EDEN에 진입할 수 없는 현상 수정 3. 일부 계정에서 미니 게임 REBUILD : EDEN의 시설물 건설 관련 업적을 달성할 수 없는 현상 수정 👉 공지사항 바로보기 * 인앱 구매(확률형 아이템 포함) #니케# #NIKKE# #업데이트#

📢 추가적으로 확인된 이슈 안내 1. 일부 계정에서 미니 게임 REBUILD : EDEN의 주요 임무 [기상 예측소를 건설하기]를 기상 예측소 건설 후에도 완료할 수 없는 현상 게임 이용에 불편을 끼쳐드린 점 깊이 사과드리며, 관련 사항은 추후 다시 안내드리겠습니다. 자세한 내용은 아래 링크를 확인해 주시길 바랍니다. 👉 알려진 이슈 바로가기 * 인앱 구매(확률형 아이템 포함)

📢 11/3(월) 무점검 업데이트 안내 11/3(월) 17:00 ~ 19:00 경에 무점검 업데이트가 진행됩니다. 게임을 완전히 종료하신 후 재접속하여 업데이트 리소스를 다운로드해 주시기 바랍니다. ​​자세한 내용은 아래를 확인해 주시기 바랍니다.​​​​​​ ✔️ 업데이트 내용 1. 미니 게임 REBUILD : EDEN에서 특수 시설물을 제외한 모든 시설물을 철거한 상태로 특정 주요 임무를 완료하거나 미니 게임에 재진입할 경우, 원활하게 진행할 수 없는 현상 수정 👉 공지사항 바로보기 * 인앱 구매(확률형 아이템 포함) #니케# #NIKKE# #업데이트#

📢 미니 게임 안내 「🎮 REBUILD : EDEN」 REBUILD : EDEN은 다양한 자원을 관리하여 에덴을 복구해 나가는 경영 시뮬레이션 게임입니다. 고군분투하고 있는 세실을 도와 심각하게 파손된 에덴의 복구를 진행해 보세요. ✔️ 기간 - 11/20(목) 4:59까지 * 인앱 구매(확률형 아이템 포함) #NIKKE3rdAnniversary# #니케3주년# #니케# #NIKKE# #니케주년# #REBUILD_EDEN#

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?

SHOULD THE GREEN BAY #PACKERS# TRADE FOR STAR #STEELERS# T.J. WATT…? Green Bay is dealing with major injuries on defense, and adding Watt alongside Micah Parsons could create the MOST DANGEROUS pass-rushing duo in the #NFL#. This would help start the Pittsburgh rebuild. 👀👀👀

Six months ago, we made a bold decision to rebuild the entire ads platform from scratch - the biggest overhaul in our company’s 20 year history. Sr. Director, SMB Sales at X @LeslieMercado0 is diving into how X Ads drives real results for businesses of all sizes.

Grok 4.7 takes the TOP 3 spots on VulcanBench Frontier v4, outperforming Fable 5.1, Opus 5.5, GPT-6 Astra, GPT-6.1 Sol and other leading frontier models • Grok 4.7 xHigh - 93.15 • Grok 4.7 High - 92.71 • Grok 4.7 Medium - 92.30 VulcanBench Frontier v4 tests whether AI models can handle difficult repository-level software engineering work rather than simply generate isolated code snippets The benchmark contains 23 behavioural-reconstruction tasks where models have to rebuild legacy software to match its actual behaviour, with functional correctness tested through hidden tests alongside security, lint/complexity and code quality And the task results are just as impressive: • Grok 4.7 xHigh - 23/23 passed • Grok 4.7 High - 22/23 passed • Grok 4.7 Medium - 21/23 passed Grok 4.7 took all #1#, #2# and #3# spots

On a Monday night in 2006, Falcons-Saints was more than just a football game. It was an emphatic message that the people of New Orleans would endure and rebuild after Katrina. 20 years later at the Dome, there’s still no place like home.