Someone's building a camera free vitals tracker on the... same $8 chip philosophy ESP32 + M5Stack CoreS3, reading WiFi signal reflections (CSI) to pull heart rate, respiration, and full 3D skeletal pose, no camera involved. Same core idea as the swarm below cheap, distributed hardware doing what used to require dedicated expensive sensors.show more

This is absolutely insane. There's a new ultra viral... Github repo that uses Wifi to spy on people with extreme accuracy • every room you've ever been in is already filled with radio waves bouncing off your body • when you move, breathe, or even just sit still, those waves scatter differently • ruvnet built the thing that reads the scatter • it maps your full body into 17 keypoints, through walls, in total darkness, no camera required • measures your breathing and heart rate while you sleep without touching you • uses your neighbors' routers as extra radar. they have no idea • $9 chip. 55kb ai. no cloud. no cameras. no consent required. Github repo:show more

Wow! Send A File By Just The Camera! A... vibe coder used AI to build a file transfer system that sends data between two phones using only a screen and a camera. One phone displays a new type of animated QR codes while the other scans them to rebuild the file, with no Wi-Fi, Bluetooth, or cables needed. It is fully optical and local. The system uses fountain codes that create each QR frame as a random mix of file data. This keeps transfers working even if some frames are missed, reaching speeds of about 129 KB/s for a 2 MB image. The entire project was built in one night and released as open source. The idea came from a music project where the developer wanted to share MP3 files without streaming or using the same network. Animated QR codes became the solution, showing a creative new way to transfer files with everyday phone hardware. GitHub link:show more

Robots can now reconstruct 3D scenes in real time... from a single RGB camera. [📍 Projects page + paper] No depth sensor. No retraining. 30 FPS. Researchers at the Imperial College London introduced KV-Tracker, a training-free method that makes heavy models like π³ and Depth Anything 3 fast enough for real-time tracking. The idea is simple. These models use global self-attention, which is powerful but computationally expensive. KV-Tracker caches the key and value pairs from selected keyframes and reuses them for new frames. That cache becomes an implicit scene representation. Result: • Up to 30 FPS • 10 to 15x speedup • Accurate 6-DoF tracking on benchmarks like TUM RGB-D and 7-Scenes • Works with monocular RGB only It also supports object-level tracking with masks and allows saving the KV-cache for later reuse. For robotics, this reduces hardware constraints and moves real-time 3D perception closer to practical deployment. Credit to Marwan Taher (Marwan Taher) at Imperial’s Dyson Robotics Lab and many others who contributed to this! 📍 Save projects page + paper for later: Video: ——- if it matters in AI or Robotics you'll read it here first:show more

SOMEONE BUILT A WAY TO SEND FILES BETWEEN TWO... PHONES WITH NO WIFI, NO BLUETOOTH AND NO NETWORK AT ALL it works with just a screen flashing qr codes at a camera one device plays an endless stream of animated qr codes, the other one points its camera at the screen and rebuilds the file out of the light no pairing, no app, no shared network, nothing but the camera > its pulling about 129 kb/s, a full 2mb image transfers in seconds > theres no back channel, the receiver can never ask for a missed frame, so it uses fountain codes, every frame is a scrambled mix of the file rather than one piece of it > that means the receiver just collects any frames it can catch in any order, and once it has enough it can reconstruct the whole file > dropping frames costs you a little time but never breaks the transfer > you can point the camera at a stream thats already running and it just locks on mid flight he was building a cached mp3 player because he was sick of ads and bad streaming quality. he wanted a way to send tracks phone to phone without both phones being on the same network, and realized flashing qr codes could carry the data he built the whole working prototype in one night with claude code its open source and already at 375 starsshow more

Seedance 2.0 on Higgsfield AI The quality and creative... control here are incredible. This feels much closer to real music video production than ever before. Full open-sourced prompts & assets below: @ Image1 is the lead performer — preserve her exact identity in every shot: cornrow braids, septum ring, statement earrings, sculptural glossy white wrapped top, dark indigo denim. @ Audio1 is the music track — entire edit cut to it; no invented music, no voiceover, no lip-sync. Music-video route: dance/performance, brutalist stage show. Track: industrial hip-hop, 95 BPM half-time, distorted 808s, luxury-noir. Director thesis: architecture as choreography — dancers staged on concrete plinths at different heights, a human sculpture garden that activates around the lead. Visual world: brutalist concrete atrium with massive raw concrete plinths and steps at staggered heights, shafts of cold daylight from a skylight, dust motes in the light shafts, dark shadow pockets. Background dancers: 6 dancers in oatmeal and bone-toned knitwear and tailoring, sculptural silhouettes, like museum figures. Palette: bone, oatmeal, concrete grey, deep indigo accent on the lead. No neon, no particles beyond natural dust. Cut map synced to @ Audio1: 0.0–2.0s THE BREATH — static ultra-wide symmetrical: six dancers frozen in sculptural poses on six plinths at different heights, the lead standing on the floor at center like a visitor. Total stillness, museum silence. 2.0s THE DROP — 808 kick: every statue snaps into a new pose simultaneously on the hit, heads turning to her; hard cut to a fast push-in on the lead. 2.0–4.0s she struts between the plinths, camera tracking laterally through foreground columns creating parallax wipes; on each kick one statue above her snaps a new angular pose. 4.0s snare — whip-pan: full freeze, she hits a profile vogue arm frame between two plinths, statues frozen mid-rotation above. 4.0–8.0s sculpture canon: her sharp head isolations and New Way vogue lines on the snares trigger cascading pose-changes across the plinths, a mechanical wave of bodies jumping pose to pose like stop-motion statues; torso rolls on the 808 slides travel up the plinth heights from low to high. Camera slowly cranes upward through the atrium. 8.0s hi-hat triple roll — 3 rapid macro inserts: her earring in a light shaft, a dancer's hand rotating on a plinth edge, dust exploding off concrete as a boot lands. 8.5–12.0s escalation: accelerating orbital-crane move spiraling around the whole sculpture garden as all six dancers now move continuously in their own orbits on the plinths, her arm work at the center speeding up; speed-ramp stretch then snap back on the kick. 12.0s bass slide — the dancers step down off the plinths in unison and sink into deep lunges around her as she glides through a sideways level drop, camera dutch and low across the floor. 13.5–15.0s FINAL BUTTON — hard cut to the opening ultra-wide: she now stands ON the tallest central plinth in a frozen vogue pose one arm high, the six dancers frozen as statues on the floor below looking up; micro push-in, hold. Loopable. Performance rules: lead stoic, dominant; dancers precise, sculptural, expressionless. Continuity: same seven people, same wardrobe, same atrium. Audio intent: every cut and pose-snap on a hit of @ Audio1; faint foley only (steps, fabric, room tone). Quality bar: expensive editorial music video, museum-grade art direction, no AI gloss, no glow.show more

Jeremy Corbell’s New Saucer-Shaped UFO Debunked? According to ThomasH,... the round “flying saucer” that Jeremy Corbell (Jeremy Kenyon Lockyer Corbell) claims is the object in the video looks to be identified as just a glare from the sun. In the video below, you can see the object doing the same motion as the camera, but in reverse. This is typical behavior of what happens when a lens flare occurs. Thomas inverses the footage, showing the clouds and the correct shadows, which exposes the glare. Did Corbell tamper with the video? You have to wonder why Corbell admittedly adjusted setting in the video and even used an AI tool to enhance it. Is that because Corbell knew it was a glare and giving it an AI enhance would create sharper edges to make it appear to be something it’s not? Regardless, this is very hard to dispute and looks to be a proper debunk of a video that people like Marik vR from The Hill called “undebunkable”. #ufoX #ufotwittershow more

single RTX 3090. 24 GB VRAM. Qwen3.5-35B-A3B. 4-bit quant,... 113 tokens per second at full 262K context harnessing Claude Code locally with no API, no subscription, no proxy. told it what it is. 30 Mamba2 layers, 10 attention, 256 experts, 8 active per token. said "build something that shows off what you can do." it visualized its own architecture. interactive. tokens flowing through layers. 256 experts lighting up on routing. served in the browser from the same GPU running inference. single prompt. then i said level up. 3D. Three.js. separate files. flythrough camera. clickable layers. it planned first, scaffolded 6 files, hit one API bug, fixed it itself, then optimized for smooth framerate. two iterations to a working 3D neural network explorer. llama.cpp just merged a native Anthropic endpoint. Claude Code points at localhost. the whole setup is two commands. no LiteLLM. no proxy config. the open source models coming out of china right now are genuinely changing what's possible on consumer hardware. respect to the Qwen team. this is acceleration.show more

Weekly Outfit Showcase📺 prompt 👇 Referencing the face, hair,... and body proportions of image_1 Standalone_pink_dress_woman_img — a young Asian woman with long dark brown-black hair worn loose, delicate facial features, slim figure — as the consistent lead character throughout all 5 segments. Fixed camera, vertical 9:16 mid-long shot facing a European-style building entrance: dark green vintage double wooden doors, grey stone wall facade, two stone steps leading to a sidewalk, warm golden afternoon sunlight raking diagonally across the scene, golden-hour color grading, photorealistic handheld smartphone aesthetic. Shot 1 [00:00–00:02.5] — Monday: Hard cut open. The woman walks out through the green double doors wearing a white bandeau tube top and low-rise ripped denim micro shorts, white strappy heeled sandals, a chain mini bag on one shoulder. She descends the two stone steps and takes two to three confident strides toward camera along the sunlit sidewalk, waistline fully exposed in warm light, glancing sideways with a relaxed smile. White sans-serif caption "Monday" centered on screen. Shot 2 [00:02.5–00:05] — Tuesday: Hard cut. Same woman, same face and black hair, now wearing a black deep-V satin slip mini dress with thin spaghetti straps and strappy heeled sandals. Satin fabric catches flowing highlights in the afternoon sun. She steps out from the doorway, descends the steps, raises one hand to sweep her long hair back as she walks toward camera, hemline swaying with each stride. Caption hard-cuts to white sans-serif "Tuesday". Shot 3 [00:05–00:07] — Wednesday: Hard cut. Same woman now in a white halter-neck tie-front crop top (fully open bare back) and black high-waist micro pleated mini skirt with thigh-high socks. She exits the door talking on a phone held to her ear, walks down the steps, then pivots to reveal her entire bare back to camera before continuing forward. Caption hard-cuts to "Wednesday". Shot 4 [00:07–00:09.5] — Thursday: Hard cut. Same woman in a beige open-knit crochet halter maxi dress with diamond-shaped side cutouts at the waist and a high thigh slit on both sides, Roman lace-up flat sandals. She strolls out the door, glances back over her shoulder toward the building, the slit opening and closing rhythmically with each stride as she walks toward camera. Caption hard-cuts to "Thursday". Shot 5 [00:09.5–00:12] — Friday: Hard cut. Same woman in a red structured strapless tube mini dress with side waist cutout and a small side slit, red pointed-toe stiletto heels, dark sunglasses perched on nose, holding an iced Americano cup in her right hand. She walks confidently out the door and directly toward the lens, getting closer until she fills the lower frame, then raises her free hand to remove the sunglasses, looks straight into camera, raises one eyebrow and breaks into a bright smile. Caption hard-cuts to "Friday". Frame freezes on her smiling face. Audio: upbeat syncopated background BGM at low volume throughout; sharp high-heel clicks on stone pavement synced to footsteps; a crisp single "click" sound effect on each hard cut between outfits. No dialogue.show more

Most people see a Mac Mini as a home... computer. He saw a $300 invoice waiting to happen. A guy in Shenzhen figured out that every early-stage startup, every founder, every small business owner needs the same thing, someone to tell them what their competitors are doing and where the gaps are. Nobody wants to pay $2,000 for a research firm. Nobody wants to wait a week. He set up Hermes on a laptop. Local model. No API costs. First report took 15 minutes. He charged $300 and delivered same day. Then he bought another machine. Then another. Now there are 65 Mac Minis on metal shelves in his apartment. Each one runs its own agent. Each agent has its own skills folder that grows every time it completes a task. Month one: $3,200. Month three: $9,600. The tool: Hermes Agent. Free on GitHub. The model: Qwen 3.6 27B. Also free. Total monthly cost: $2 in electricity. The hardware paid for itself in week two. The shelves haven't changed. He just keeps adding machines.show more

What if luxury livestream shopping ads could be generated... entirely with AI? From the influencer, to the boutique, to the product showcase, every frame was created with GPT Image 2 and Seedance on BudgetPixel AI The future of social commerce content is here. Prompt: 15s ultra-realistic vertical smartphone livestream advertisement, 16:9 aspect ratio, luxury social-commerce style. Use @[char ref] and @[storyboard ref]. Follow the scene sequence with seamless continuity and fast-paced livestream energy. 0:00–0:02 — Livestream opens. Front phone-camera perspective with slight handheld movement. The host smiles warmly while holding a premium black quilted crossbody handbag toward the lens. A realistic illuminated sign reading "TOKYO LIVE FLASH SALE" glows naturally in the background. Dialogue: "Hi everyone~ look at this beautiful bag." 0:02–0:04 — Medium close-up. She rotates the handbag slowly, showing the quilted pattern and gold hardware while maintaining friendly eye contact. Dialogue: "So elegant, right?" 0:04–0:06 — Extreme macro close-up. Her fingers gently glide across the quilted leather texture and premium clasp. Warm highlights reflect realistically across the material. Dialogue: "Soft, premium, luxury." 0:06–0:08 — Top-down product demonstration. She opens the bag and places a smartphone, wallet, lipstick, and power bank inside. Shopping notifications appear. Dialogue: "Everything fits perfectly." 0:08–0:10 — Tracking shot. She wears the bag crossbody and walks naturally through the boutique. Hair moves softly as she turns and smiles. Dialogue: "So comfortable." 0:10–0:12 — Full-body fashion shot. She poses naturally, showing how the bag complements her outfit. Viewer count rises rapidly. Dialogue: "Matches every look." 0:12–0:14 — Dynamic push-in. Realistic LED-style sale graphics illuminate behind her: TOKYO LIVE FLASH SALE 50% OFF LIMITED TIME Countdown Timer Dialogue: "Fifty percent off today!" 0:14–0:15 — Hero product close-up. She brings the handbag toward the camera with a warm smile as hearts and comments flood the screen. Dialogue: "Shop now before it's gone." Audio: Upbeat Japanese city-pop instrumental, subtle livestream notification sounds, floating-heart effects, boutique ambience. Photorealistic live action, natural facial expressions, realistic motion, luxury commercial quality, high-conversion livestream energy. Maintain the same host, same hairstyle, same makeup, same outfit, same handbag, same boutique environment, same lighting, and same sale branding throughout the entire video. No subtitles. No watermark. Strong product focus. Premium luxury fashion-commercial quality.show more

how to prompt undetectable ai shots while designing a... running scene, first think about these 3 basic questions: how does the camera move? what is it looking at? where does it stop? a good motion prompt is really just a timeline it needs to follow real-world physics, and it needs to carry story at the same time 1. start with the narrative goal of the shot camera movement is not just movement it is the storytelling so before writing the prompt, define what the shot is trying to do for example, in a 15-second one take, the goal could be: follow the female lead laterally while she runs, to build speed and tension then briefly reveal the people chasing her then let the camera hesitate for a moment and find her again that small “lose and recapture” moment adds spatial depth and makes the chase feel more intense 2. build a clear space for the camera to work in if the space is vague, the shot gets messy very fast i like breaking the scene into layers so the model knows where everything belongs foreground: passing objects, environmental motion main subject layer: the woman running midground: cafe tables, pedestrians, the people chasing her background: the vanishing point of the street, and the entrance to the pedestrian area once the space is clear, the camera has a stage to move through 3. describe motion like a physical process a good moving shot has to respect inertia if the movement feels weightless or too perfect, it instantly feels fake so instead of using broad words, describe a chain of actions the camera can actually perform what accelerates what slows down when it adjusts when it slightly overshoots when it catches itself again that little bit of imperfection is usually what makes it feel real 4. use focus as part of the storytelling in a one take, focus is one of the best ways to guide attention you can design moments where focus shifts with intention for example: focus briefly drifts from the chasers’ faces, passes beyond them, lands on the woman in the distance, then quickly pulls back again it feels like a small mistake, but that’s exactly why it works it simulates a camera operator re-evaluating the subject in the middle of a fast-moving shot that kind of temporary focus loss and recovery adds a lot of immediacy and documentary feeling 5. build the sound space with the camera sound should move with the shot when the camera turns toward the chasers, the woman’s breathing should fall deeper into the sound field, while the chasers’ footsteps and breathing move to the center when the camera finds the woman again, her breath becomes the main sound again that shift in audio perspective helps the scene feel much more immersive it’s not just about what we see it’s also about where we feel the scene from 6. use negative constraints to stop common ai mistakes this part matters a lot i usually add clear “don’ts” at the end to stop the model from breaking the shot for example: no cuts no teleporting zooms no sliding characters no body fusion no floating props the travel bag must keep believable weight and inertia these negative constraints act like guardrails they help keep the result inside a believable physical world for me, the core of a strong motion prompt is simple: organize space, camera, focus, action, and sound into one executable timeline that’s really the difference instead of prompting a vague feeling, you’re designing a physical process and that’s usually what helps ai generate a moving shot that feels coherent, grounded, and full of tensionshow more

What would you do if a monster charged at... you in the middle of the street? Made with Nano Banana 2 + Seedance 2.0 4k on TapNow prompt Beat 1 - The Calm Opening The reference image character is a Western woman with long wavy blonde hair casually drinking a Coke in the middle of a chaotic urban street. Her outfit and cap match Image 1 exactly. Energy is calm, unfazed, and confident. Camera: grounded, cinematic, medium shot. Beat 2 - The Monster Charges A terrifying monster bull charges toward her at full speed. It smashes through debris and scatters people in panic. The street erupts into chaos around the character. Camera: dynamic tracking, wide angle to capture scale of monster and chaos. Beat 3 - The Transformation The young woman stays calm and completely unfazed. She lowers the Coke. She raises one hand. Her arm begins transforming into solid ice from the fingertips upward. Frost spreads across her skin, glowing with cold blue-white energy. Vapor rolls off the arm as the ice transformation builds. Camera: close-up on the arm transformation, slow and deliberate. Beat 4 - The Touch - Slow Motion As the monster lunges, she calmly reaches forward. She touches the monster with her frozen hand. DRAMATIC SLOW MOTION at the moment of contact. Ice rapidly spreads from the point of contact across the monster's body. The monster panics - thrashing and roaring as frost crawls over its claws, chest, face, and eyes. The monster's movement slows as the freezing effect takes over. Camera: extreme close-up on contact point, then pulls out to reveal the spreading ice. Beat 5 - Full Freeze The creature becomes completely encased in crystal-clear ice, frozen mid-attack. A tense pause holds on the frozen monster. Deep cracks spread through the frozen monster. Cracks split across its icy body with sharp crystalline sounds. Detailed cracking ice - realistic frost and crystal texture throughout. Camera: wide shot of the frozen monster, locked and still for the pause beat. Beat 6 - The Walk-Off The young woman casually takes another sip of Coke. She turns away without looking back. She walks off calmly as the frozen monster cracks behind her. Confident calm hero energy. No celebration. No reaction. Just casual. Camera: low angle tracking shot as she walks away, monster in background. Visual Effects Realistic ice transformation - frost spreading from fingertips upward. Frost vapor rolling off the arm during transformation. Cold blue-white glowing energy across frozen skin. Ice rapidly spreading across monster body from point of contact. Detailed cracking ice with sharp crystalline fracture lines. Crystal-clear ice encasing the entire monster mid-attack. Realistic freeze physics - movement slowing as ice covers the creature. Camera Style Dynamic cinematic camera movement throughout. High-action monster attack framing during the charge. Dramatic slow motion at the exact moment of hand contact. Close-up on ice transformation - fingertips to shoulder. Pull-back reveal as ice spreads across the monster's full body. Low angle walk-off shot to close the scene. One continuous take. No cuts. Camera never stops. Character appearance: a beautiful Western woman with long wavy blonde hair flowing naturally beneath the cap, maintaining the same calm, confident, and unfazed presence throughout the entire sequence.show more

seedance 2.0 prompt： 15-second comedic animated short in the... world and visual tone of Zootopia. High-quality stylized 3D animation, expressive facial acting, clean readable slapstick, bright police-station interior, polished reflective floor, warm indoor daylight. Visual comedy only, little or no dialogue. Judy Hopps: small fast rabbit police officer, blue ZPD uniform, hyper-serious, explosive sprinting, precise slides, determined face, ears reacting sharply. Nick Wilde: tall slim fox, green shirt and tie, relaxed posture, minimal movement, dry amused expression. Background: one distant sloth clerk at a far desk only, never entering foreground. Key object: one single strawberry jelly donut, same donut for the entire clip, falls from Nick’s small brown paper bag, rolls across the floor, gets stopped by Nick, then gets sealed into one clear evidence bag by Judy. No duplicate donuts, no extra props, no continuity errors. Camera language: third-person cinematic comedy, medium shots, low-angle close tracking on the donut, one side tracking shot, one final tight two-shot. Smooth stabilized movement, tiny comedic whip corrections only when needed. Always keep donut, Judy, and Nick spatially readable. 0:00–0:03 Medium shot, light tracking in ZPD lobby. Judy and Nick walk side by side past the front desk. Judy carries a small clipboard, Nick carries a brown paper bag. One strawberry jelly donut slips out of the bag, drops to the floor, and starts rolling. Judy’s ears snap upright and she locks onto it like a fleeing suspect. Camera dips lower to keep the donut in the foreground. 0:03–0:06 Low close tracking shot on the same donut rolling fast over the shiny floor. Judy bursts into frame from behind, clipboard tucked under one arm, sprinting hard with both paws reaching forward. She almost grabs it but misses by centimeters. The donut keeps rolling. Quick readable camera adjustment, no chaotic motion. 0:06–0:09 Side medium-wide tracking shot. The donut curves around a fixed desk leg. Judy makes an exaggerated quick step and low slide to intercept, but it slips past her again. She pivots and chases immediately. In the background, Nick simply walks on a shorter diagonal path, calm and unhurried. Keep the same donut clearly visible. 0:09–0:12 Frontal medium-close shot. The donut rolls toward camera. Nick’s paw enters calmly from frame right and presses the same donut to a stop. Judy slides in from frame left and freezes with her nose just inches from it, still in full arrest pose. Hold the reaction beat clearly. 0:12–0:15 Tight two-shot. Nick lifts the same donut with two fingers and hands it over with a dry smug grin. Judy instantly switches back to formal police mode, pulls out one clear evidence bag, seals the same donut inside, and proudly presents it to camera like a major arrest. Nick stands beside her with an amused look. In deep background, the sloth clerk slowly raises a stamp. End on a clean comedic freeze frame: evidence bag with the donut centered in foreground, Judy serious and proud, Nick smirking beside her. Consistency rules: same donut throughout, no extra donuts, no costume changes, clipboard stays with Judy, background sloth remains distant, no extra foreground characters, no object popping in or out, final frame must clearly show the donut inside the evidence bag.show more

Seedance 2.0 prompts below! 👇 [STYLE + CAMERA +... ATMOSPHERE] Authentic amateur footage captured horizontally on a smartphone in landscape mode, natural shaky handheld camera with typical phone jitter and micro-movements, casual real-life vlog style, raw mobile video quality with slight grain and compression artifacts, natural indoor lighting from cheap fluorescent tubes and some window light, no cinematic color grading, no film look, no polish — just real phone recording. [IMAGE REFERENCES] No reference image provided. The main character is a woman in her mid-30s. Maintain consistent appearance throughout: natural look, shoulder-length dark hair, fair skin, casual t-shirt and jeans. [TIMELINE SECOND BY SECOND] 0-4s: [Shaky Handheld Phone Shot] Inside a cheap, cluttered Indian-style beauty salon with faded posters, plastic furniture and dim lighting. The woman sits relaxed in a worn chair. A male esthetician stands beside her holding a small jar of thick off-white cream. Natural phone camera shake. Esthetician says in casual American English with a light Indian accent: "This is our special cream, madam. Very good for the skin. You will like the results." 4-8s: [Close-up Handheld] The esthetician scoops the cream and rubs it thickly all over the woman’s face, covering forehead, cheeks, chin and lips. The woman has her eyes closed, looking calm. Unsteady phone camera moves slightly closer. Esthetician continues: "Just relax and close your eyes. It works very fast." 8-12s: [Medium Close-up, slight push-in] The woman’s lips start to visibly swell and enlarge dramatically, becoming much fuller, plumper and noticeably bigger. At the same time her chest grows larger and rounder, stretching her t-shirt. She opens her eyes in shock, looks down at her chest and touches her lips with her hands. Handheld camera jolts a little from the surprise. 12-15s: [Handheld Reaction Shot] The woman turns fast toward a wall mirror and stares at her reflection in total horror. Her lips are now much larger and her chest significantly bigger. She reacts in natural New York style: "Wait… what the hell? My lips feel huge… and my chest too? What did you put on me?!" The esthetician replies from the side: "It's just activating, no problem. It will settle down." The shaky phone camera captures her panicked expression and the mirror reflection. [STYLE & QUALITY BOOSTERS] Authentic smartphone video quality, natural realistic skin physics and body transformation, coherent character consistency, slight handheld camera shake throughout, natural lighting and shadows, no artifacts, raw mobile recording look. waiting for your versions! 🫡show more

🚨 FOR $POLY AIRDROP FARMERS Nobody is talking about... how airdrop should actually be structured. Here is my honest take and why it matters for every active Polymarket user right now: The platforms that got airdrops right, had one thing in common. (Hyperliquid for example) They rewarded real usage. Not farming behavior designed specifically to game the criteria. Here is what a fair $POLY distribution should look like in my opinion: Core criteria should be three things only. Total volume traded. Total trade count. Number of days active on the platform. These three metrics together accurately reflect a genuine long-term Polymarket user. Hard to fake. Hard to game quickly. Directly tied to what the platform is actually built for. LP farming and market sponsorships should be multipliers on top of the base allocation. Not core criteria. Something like 1.2x or 1.3x for consistent LP providers. The platform is a prediction market, not a liquidity farming protocol. Making LP a core criteria incentivizes behavior that has nothing to do with the actual product. Plenty of LP farmers already made serious money from daily rewards anyway. The allocation percentage matters too. 20% minimum with no vesting would send a clear signal that Polymarket is serious about rewarding its community. Hyperliquid did this and the token pumped hard because holders trusted the distribution was genuine. $POLY has the same potential if the structure is clean and user-first. Drag it out with vesting schedules and complex criteria and the narrative shifts fast. Ship it clean. Reward real users. Watch the token react the same way HYPE did. The formula is not complicated, just requires the right priorities. What you think about this airdrop structure? Full guide on how to farm it right is quoted below.show more

Now listen to my rap 🎶 Seedance 2.5 just... nailed it Prompt : Use the uploaded reference image as the exact character reference. Lock her facial identity, eye color, skin tone, hairstyle, makeup, body proportions, and overall appearance throughout the entire video. She has long black hair tied in a low ponytail, soft natural makeup, expressive grey-green eyes, and wears the same fitted white graphic baby tee, oversized denim shorts, white crew socks, chunky sneakers, silver hoop earrings, layered necklaces, rings, and an oversized black bomber jacket hanging loosely off her shoulders. Maintain perfect character consistency in every shot. Create a high-end American hip-hop/rap music video inside a premium photography studio transformed into a modern urban performance space. The set features a blue cyclorama backdrop, minimalist graffiti walls, a professional drum kit, vintage brown leather sofa, polished concrete floor, blue neon tube lights, industrial spotlights, subtle atmospheric haze, and cinematic contrast. The aesthetic should feel like a mainstream Western rap music video with luxury production value. The video opens with an ultra-wide close-up as she looks directly into the camera with a confident expression and folded arms. The camera quickly cuts to a dramatic side silhouette where she lowers her head, then raises it while making relaxed hip-hop hand gestures. A full-body wide-angle shot reveals her casually grooving to the beat, shoulders bouncing naturally as her oversized jacket shifts with realistic fabric movement. The camera circles around her in a handheld shoulder-mounted tracking shot while she confidently lip-syncs to the music with expressive facial performance. She points toward the lens, smiles slightly, then steps forward with effortless swagger. A dramatic low-angle hero shot emphasizes her presence as she spreads her arms confidently beneath glowing blue lights. She walks toward a professional drum kit, sits down naturally, and begins striking the drums energetically in perfect rhythm with the music. Fast cuts alternate between overhead, side, and close-up angles showing realistic stick movement, expressive reactions, and synchronized performance. The scene transitions to a blue roller shutter covered in minimalist graffiti where she squats casually with elbows resting on her knees, maintaining eye contact with the camera while continuing to rap confidently. The camera slowly pushes in from the side before cutting to her lounging effortlessly on a vintage brown leather sofa. She leans back comfortably, one arm stretched along the backrest, nodding naturally with the rhythm while continuing her performance. A dramatic side silhouette sequence follows with atmospheric haze and strong blue backlighting as she performs smooth body movements, expressive hand gestures, and confident lip-sync. Her hair moves naturally with subtle airflow while the camera glides around her using wide-angle lenses that enhance depth and energy. The final sequence returns to a full-stage performance. She stands center stage beneath powerful spotlights surrounded by drums, graffiti, neon tubes, and blue studio lighting. The camera slowly pulls backward while she delivers the final lyrics with bold attitude, ending in a confident pose as the lights fade behind her. Professional rap music video cinematography, cinematic handheld movement, wide-angle lens distortion, premium studio lighting, realistic skin texture, natural eye reflections, detailed hair strands, physically accurate lighting and shadows, authentic lip-sync performance, expressive body language, smooth choreography, realistic fabric simulation, high-end fashion editorial styling, luxury commercial quality, immersive urban atmosphere, 16:9 widescreen, no subtitles, no logos, no watermarks, no on-screen text.show more

Seedance 2.0 on Higgsfield AI Full open-sourced prompts &... assets below: Prompt: Image is the lead performer — preserve her exact identity: cornrow braids, septum ring, statement earrings, sculptural white designer top, dark indigo denim. audio1 is the finished master track — the only audio; no invented music, no new vocals. SHE RAPS THE VOCAL ON CAMERA — PRECISE LIPSYNC IS THE TOP PRIORITY. Mouth articulates every syllable of audio1 exactly on time. Camera keeps her face visible and sharp during every vocal line; no cutaways mid-word. LIPSYNC MAP: 0.0–0.5 instrumental — stillness. 0.5–2.8 "I'm standing on the edge / Say it with your chest / Or keep it on the deck" + "Hey!" 3.2–6.7 "I walk in, whole room gets tense / I don't need luck, I'm the consequence / If you really want to test my intent / Come correct, come correct or get bent" + "Woo!" 7.5–13.7 same hook verbatim second time, escalated delivery. 14.5–15.0 instrumental hold. Music-video route: performance with crew. Director thesis: she raps at the lens while four background dancers in matte black move as one disciplined organism behind her — she talks, they answer with bodies. Visual world: raw concrete studio hall, cold window daylight plus one tungsten pool, reflective floor. 4 background dancers (mixed gender) in matte black tanks and cargo trousers, anonymous, faces neutral. Palette: bone white, black, concrete, indigo. No neon, no particles. Shot flow: 0–3s wide-to-medium push-in: she raps dead center, crew frozen in a diamond formation behind her in shadow; they snap alive on the first "Hey!". 3–7s she struts forward rapping into a backward-dollying camera while the crew lockstep-marches behind her, hitting unison shoulder pops on each snare exactly between her lines. 7.5–10s cut on the kick to low-angle close-up of her second hook — crew silhouettes blurred behind, her articulation front and center. 10–13.7s medium orbital: she raps while the crew executes canon vogue arm waves rippling outward from her on each snare; she points at the lens on "come correct". 13.7–15s final tableau on "Woo!": she freezes one arm high, crew drops to one knee around her, hold. Loopable. Performance rules: her delivery commanding and stoic, crisp jaw articulation; crew never looks at camera, military precision, never upstages her vocal moments. Continuity: same five people, same wardrobe, same hall. Audio intent: audio1 only, mouth locked to its vocal; faint foley. Quality bar: expensive rap performance video, no AI gloss.show more

A gym asked to repost their workout video. Eight... months later, that same gym pays them $10,400 a month. Two friends run one Instagram account together, split down the middle. It started as a joke — a place to dump their workout clips so they'd stop flooding their personal pages. Then the gym they train at reposted one video. Then asked for more. Then offered to pay. That was the whole beginning. One local gym, a small monthly fee to keep their feed looking alive. Here's what they figured out fast: gyms are desperate for content and terrible at making it. Beautiful equipment, dead Instagram. The two of them already film every session anyway — so they started pointing the camera at what the gym needed and handing it over as a finished feed. Now they run it like a tiny agency. Three gyms and two activewear brands pay them to produce a month of content each — reels, captions, the posting calendar, the whole thing. The part that makes it possible with two people and full-time jobs: AI does the 90% that used to need a team. They film. Claude does the rest — cuts one session into 20 clips, writes captions in each client's voice, builds the 30-day calendar, drafts the monthly report that keeps every contract renewed. What used to take an editor, a copywriter, and an SMM manager now runs while they're getting coffee after the workout. 5 clients. Around $2,000 each. $10,400 a month. Their cost to run all of it: under $60. That number doesn't move whether they have 5 clients or 15 — that's the entire model. The wild part is how ordinary they are. No huge following. No personal brand. Two normal girls who train together and realized the footage they were already making was worth money to someone else. Every friend group at every gym is filming the same content for fun and letting it die in their camera roll. These two just asked one gym if it wanted to buy it. The full breakdown — how two people turn shared workouts into a real content business — is in the thread above. Read it before another duo in your city signs those gyms first.show more

Machine Tokenization is HERE 🔥 Introducing the world's first... Machine Real-World Asset (#RWA) Tokenization platform, by Teneo, powered by peaq 🌎 Up until now, real-world apps (#DePINs) have been limited by hardware costs. Individuals can often afford WiFi routers or smartphones, but fleets of vehicles or wind turbines? There's no way to build a Decentralized Physical Infrastructure Network (#DePIN) which revolves around such large and expensive hardware... Or is there? 🤨 Enter the Machine Tokenization Platform⚡️ The platform exists to lower the barrier to entry for communities to build virtually any #DePIN. Imagine being able to fund, own, and earn from fleets of autonomous cars or robots, vertical robo-farms, ferry boats, #VTOLs... The possibilities are endless, and this era starts now. Tokenized Teslas ✅ ELOOP has already successfully tokenized a fleet of Teslas for a car-sharing pilot project in Vienna 🇦🇹 which saw the community earn revenue as the Teslas were used. Check out these videos 🎞️ Web3 Tesla-Sharing: You drive, everyone earns: Same, but better. | Web3 Car-Sharing Demo by ELOOP & peaq: With the success of this initiative showcasing the soundness of the underlying model, ELOOP is now building a Machine RWA tokenization platform on peaq to replicate this approach at scale 📈 DePIN Layer-1 Synergies 🧲 Existing and prospective DePINs can leverage the Machine Tokenization platform to lower the barrier to hardware adoption for their users, enabling all kinds of new DePIN use cases on peaq 🦾 A range of Web2 and Web3 projects are already exploring pilot projects on the platform, including Dabba Network 🟨, a connectivity DePIN working to deliver Web access to the unconnected. Already testing on krest 🔥 ELOOP is already testing the platform on krest, peaq’s canary network, and plans to launch it on the peaq mainnet, which will go live this year. “We’re excited to move beyond tokenizing Teslas and offer this exciting, proven model to businesses and communities. Machine RWA tokenization opens up a new era of fractional ownership and participation in the value generated by machines, and we are happy to be chartering this path forward with peaq.” - Nico Prugger, co-founder, ELOOP Read all about it:show more

Higgsfield just dropped the exact prompts behind their best... Originals shots👀 Seedance 2.0 on Higgsfield AI Full open-sourced prompts & assets below: (Image1) is the performer — preserve her exact identity: cornrow braids, septum ring, statement earrings, sculptural white designer top, dark indigo denim. (Audio1) is the finished master track — the only audio; no invented music, no new vocals. SHE RAPS THE VOCAL ON CAMERA — PRECISE LIPSYNC IS THE TOP PRIORITY. Mouth articulates every syllable of (Audio1) exactly on time; face visible and sharp through every vocal line, no cutaways mid-word. LIPSYNC MAP: 0.0–0.5 instrumental. 0.5–2.8 "I'm standing on the edge / Say it with your chest / Or keep it on the deck" + "Hey!" 3.2–6.7 "I walk in, whole room gets tense / I don't need luck, I'm the consequence / If you really want to test my intent / Come correct, come correct or get bent" + "Woo!" 7.5–13.7 same hook verbatim second time, escalated. 14.5–15.0 instrumental hold. Music-video route: performance with mirrored echoes. Director thesis: white infinity studio — she raps at the lens while five dancers in white repeat her last pose one beat late, a human delay effect behind her voice. Visual world: white cyclorama infinity studio, seamless floor and walls, one hard fashion key light with clean shadows, subtle floor reflections. 5 female background dancers in all-white utilitarian streetwear, hair slicked, deliberately similar but never identical to her; her indigo denim makes her instantly readable. Palette: white on white, skin tones, indigo. No neon, no particles. Shot flow: 0–2.8s symmetrical wide-to-medium push-in: she raps the opening lines at the apex of a tight wedge, the five echoes frozen in her exact stance behind her. 2.8–3.2s on "Hey!" all five snap chins up in unison. 3.2–6.7s medium: she raps while throwing an angular vogue accent at the end of each line, and the echoes replay that exact accent one beat later, rippling backward through the wedge; camera slowly orbits 45 degrees keeping her mouth front and center; finger to lens on "come correct". 7.5–10s cut on the kick to a chest-up close frame: second hook with doubled intensity, the echoes now a soft-focus rhythmic blur behind her articulation. 10–13.7s the echoes carousel slowly around her while she stands still at center rapping the final lines, camera counter-rotating, her face never leaving focus. 13.7–15s on "Woo!" she freezes arm high; the five echoes freeze in five different mid-move poses around her — she is the only resolved image; micro push-in, hold. Loopable. Performance rules: dominant, stoic, immaculate diction; echoes expressionless and precise, never mouth the words — only she raps. Continuity: same six women, same wardrobe, same white studio. Audio intent: (Audio1) only, her mouth locked to it; faint studio room tone. Quality bar: expensive fashion-campaign rap video, no AI gloss, no glow.show more