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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?

Most of us open Google Sheets for budgets, trackers, and tables. With Gemini 4 Hydrogen, we wanted to see if it could paint a moving landscape instead 🍃 In Google @Antigravity, Hydrogen handled the coding to paint and animate thousands of cells — creating coastal trains, drifting clouds, and falling autumn leaves that recalculate frame by frame inside the spreadsheet.

🖤 Happy Thursday 🖤 Fragile but Unbreakable They say the strongest people often look the most defenseless. Today, I feel every mile of the journey I’ve traveled. My hands may tremble from exhaustion, and my eyes may search for a place to lean, but this isn't weakness. This is a recharge before the next leap. Strength isn’t about never falling. It’s about knowing — even when you look as fragile as glass — that you will handle it. Again and again. 1/1 377 tez

Jaden Smith admits that just one night with 82-year-old Michèle Lamy changed so much about him, as he reveals he’s already falling in love with her. The two were spotted together once again, taking a romantic walk in Paris.

Anthropic IPO Consensus Views: - Overvalued at $1.5T - Revenue is flattening - Token are commoditized due to open source - Token prices falling faster than demand - Anthropic shouldn't go public b/c robbing general public of upside and passing on risk. - Anthropic is Twilio but for intelligence. Contrarian - Anthropic is still a 10x from here and has venture upside. - $80B ARR reported by WSJ is just primarily coding agents and will re-accel with Fable / Mythos - Finance, legal, life sciences, Ode are all super early ... - Agents = still early and most businesses think of AI = ChatGPT / Claude app. - Anthropic will zoom past $100B ARR EOY with release of Fable 5.2 / Mythos 5.2 - Retail is starving for direct exposure to frontier labs and will ape in and drive Anthropic to $3T marketcap. - Anthropic is easily a $500B revenue business in 2030 with simple assumption Fortune 500 spent 0.1% of OPEX today ... Stripe spends 1% and not crazy Fortune 500 replace labor with tokens in 2030. 1% of OPEX would imply 10x of the $75b revenue Q3'26 so $750B revenue in 2030. Full thesis + model coming out Wednesday H/T @zhengjielimm

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?

Top Republicans are giving up on races in purple territory and racing to save seats in deep-red states. “If the bottom continues falling out like it has been,” one national Republican strategist said, “this will be worse than 2006.”

PROMPT SHARE: The biggest AI breakthrough isn’t realism. It’s presence. #AIVideo# #Marketing# #Advertising# The people, movement, noise and unpredictability give the world a sense of life beyond the camera. That’s when generation starts becoming experience. ➜ Image Prompt: Photography & Cinematography Create an ultra-realistic nighttime street portrait with the raw, spontaneous look of early-2000s nightlife photography. Direct on-camera flash illuminates the subject sharply against a much darker city background, with natural grain, slight highlight blowout, deep shadows, imperfect exposure and authentic point-and-shoot character. No fake or plastic skin, no beauty filtering, no CGI or animated appearance. Character & Pose A striking young man with rugged, high-fashion model features, lean athletic build, sharply defined jawline and cheekbones, strong brows, full lips and short dark hair styled wet and tousled with loose curls falling onto his forehead. Natural pores, subtle facial texture and realistic imperfections. He sits casually on the edge of a city curb at night, legs spread asymmetrically, one knee raised toward the camera. One forearm rests loosely across the raised knee while his other hand reaches down beside him toward a small shaggy brown dog partially entering the bottom of the frame. He looks directly into the camera with a serious, confident expression. Outfit Fitted black long-sleeve turtleneck, faded distressed gray-blue jeans with worn areas and small rips, and a black leather belt. Silver pendant necklace, small hoop earring, chunky silver cuff bracelet, dark oversized wristwatch, and a thin bracelet. Styling feels slightly rebellious, understated and naturally lived-in rather than polished. Environment A busy urban nightlife street after dark. Several casually dressed people walk behind him, cropped naturally by the frame, while parked and passing cars create scattered headlights and small pools of distant light. The pavement is gritty and imperfect with curbs, cracks and ordinary street details visible. Keep the background activity believable and incidental—the image should feel like a real moment caught outside a club or late-night gathering, not a staged fashion shoot. Wide horizontal composition, intimate close-range flash photography, authentic real-world energy.