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BREAKING: 13-year-old boy seen falling down Disneyland waterfall ride in new footage acquired by @TMZ. The teen, riding Tiana’s Bayou Adventure, allegedly crawled out of the water tram and took a tumble down the waterfalls' 50-foot drop. A resort official told The Post the ride, formerly known as Splash Mountain, shut down for the day as the boy was rushed to the hospital, but reopened the following day.

Three products killed in seven days. That's the number that tells you where OpenAI actually is right now. Monday: Instant Checkout scrapped. Only 12 Shopify merchants ever went live. Walmart said conversion rates inside ChatGPT were 3x lower than on their own site. Six months of "agentic commerce" produced almost nothing. Tuesday: Sora shut down entirely. Disney's $1 billion investment collapsed before any money changed hands. Their teams were working on Sora projects Monday evening and got blindsided by the announcement 30 minutes later. Downloads had already fallen 32% month over month by December. Thursday: Erotic chatbot shelved indefinitely. Internally called "Citron mode." They couldn't train models that previously avoided explicit content to reliably exclude illegal behavior. A senior employee quit over it. Their age-verification system has a 10%+ error rate. Now look at the financials behind these decisions. OpenAI hit $25 billion in annualized revenue in February. They're projecting $14 billion in losses for 2026 and $17 billion in cash burn. The IPO is targeting Q4 2026 at an $840 billion valuation. They need to file an S-1 in months. Every one of these killed products was a liability on that S-1. E-commerce checkout with no tax compliance infrastructure. A video app burning compute with falling downloads. An adult chatbot while the FTC is investigating AI harm to minors and Meta just got hit with $375 million in a child exploitation case. This is what pre-IPO cleanup looks like at $840 billion. You kill everything that creates a headline risk, consolidate into a "superapp" that combines ChatGPT, Codex, and Atlas, and pray the coding market is big enough to justify 65x revenue. The Pentagon contract was the tell. OpenAI rushed a $200 million defense deal the same day Anthropic got blacklisted, admitted it was sloppy, then spent a week rewriting the terms. That's a company optimizing for one thing: making the investor deck look inevitable before the roadshow starts.

[VIDEO] [MV] HANA(gugudan) (하나(구구단)) _ Falling Down (Touch your heart(진심이 닿다) OST) ▶ ▶ #구구단# #gugudan# #하나# #HANA# #진심이닿다# #Falling_Down#

[NOTICE] #gugudan# #HANA# 's tvN <Touch Your Heart> OST #Falling_Down# has been released❣ Through HANA's voice Here comes a calm and sorrowful song🎶 Dear Friends, let's listen together💕 🎧 #Touch_Your_Heart# #OST#

[NOTICE] #구구단# #하나# 가 참여한 tvN <진심이 닿다> OST #Falling_Down# 음원이 모든 음원 사이트에 공개되었습니다❣ 하나의 목소리로 전하는 담담하고 슬픈 감성의 곡🎶 단짝들 우리 같이 들어요💕 🎧  #gugudan# #HANA# #진심이닿다# #OST#

[NOTICE] 오늘 오후 6시! #구구단# #하나# 가 참여한 tvN <진심이 닿다> OST #Falling_Down# 음원이 공개됩니다❣ 🎧 2019. 03. 28(목). 6 PM 단짝 여러분의 많은 기대 부탁드립니다💕 #gugudan# #HANA# #진심이닿다# #OST# #20190328_6PM#

When BTC takes a deep dive, I don't want my entire market perspective to turn red with it. 😂 I've just updated my GT Watchlist on @GeckoTerminal with four memes: PEPE, BONK, Nihao and $FOOD. I'm keeping an eye on their communities, pool liquidity and trading volume. When the hype cools down, I want to know which ones still have real market activity. My routine is simple: open GT on my phone, check my saved pools, compare price action and volume, and see what's changed. The best part? Creating a Watchlist is incredibly easy. Just find the tokens or pools you want to follow, add them to your list, and they're all organized in one place. No more searching for the same coins every time I open the app. A falling market isn't a reason to stop paying attention. This isn't the time to surrender and walk away. It's time to stay alert and spot opportunities. 🐸 Do you have any suggestions for me to add to this list?

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?