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MiniMax H3 - Prompt Share This prompt turns any reference image into a video showing how the subject could be made by hand from scratch. I tried it with my profile picture. It should work with any subject. Prompt: A cinematic creation film follows one maker reconstructing the main...

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Kōda

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📖THE STEP MOST CREATORS SKIP IS WHY THEIR AI ANIMATION LOOKS INCONSISTENT Consistency across clips doesn't come from prompting — it comes from the reference image. The pipeline, step by step: ▪ Start with ChatGPT Image 2 — generate a full character design sheet first, not just a single frame. Multiple angles, expressions, and outfit variations in one image keeps the character consistent across every scene ▪ Build a storyboard inside ChatGPT Image 2 as well — define each shot, camera angle, action, and mood before touching Seedance at all. This is the step most people skip and it's the reason clips look disconnected ▪ Define a color palette and lighting mood early — golden afternoon light, soft warm tones, dramatic shadows. Lock those values and repeat them across every prompt ▪ Take each storyboard frame into Seedance 2.0 as the reference image — one frame becomes one clip ▪ Write the Seedance prompt around the character action, not the scene description. The scene is already in the image. The prompt handles motion, camera behavior, and timing ▪ Keep clip duration between 4-6 seconds per shot — shorter clips give more control over pacing and reduce motion drift on character faces ▪ Match camera movement type across consecutive clips — if one shot dollies in, the next should hold or pull back, not dolly again The consistency across these frames comes from the character design sheet, not from luck. Seedance reads the reference image and the prompt together — if the reference is detailed enough, the output stays on-model. This video was created by ALOKXMEHTA 📥 tomorrow: the exact ChatGPT Image 2 prompt structure used to generate a multi-angle character design sheet like this one 🔖One article covers the entire workflow — it is pinned below, do not scroll past it.
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📖THE STEP MOST CREATORS SKIP IS WHY THEIR AI ANIMATION LOOKS INCONSISTENT Consistency across clips doesn't come from prompting — it comes from the reference image. The pipeline, step by step: ▪ Start with ChatGPT Image 2 — generate a full character design sheet first, not just a single frame. Multiple angles, expressions, and outfit variations in one image keeps the character consistent across every scene ▪ Build a storyboard inside ChatGPT Image 2 as well — define each shot, camera angle, action, and mood before touching Seedance at all. This is the step most people skip and it's the reason clips look disconnected ▪ Define a color palette and lighting mood early — golden afternoon light, soft warm tones, dramatic shadows. Lock those values and repeat them across every prompt ▪ Take each storyboard frame into Seedance 2.0 as the reference image — one frame becomes one clip ▪ Write the Seedance prompt around the character action, not the scene description. The scene is already in the image. The prompt handles motion, camera behavior, and timing ▪ Keep clip duration between 4-6 seconds per shot — shorter clips give more control over pacing and reduce motion drift on character faces ▪ Match camera movement type across consecutive clips — if one shot dollies in, the next should hold or pull back, not dolly again The consistency across these frames comes from the character design sheet, not from luck. Seedance reads the reference image and the prompt together — if the reference is detailed enough, the output stays on-model. This video was created by ALOKXMEHTA 📥 tomorrow: the exact ChatGPT Image 2 prompt structure used to generate a multi-angle character design sheet like this one 🔖One article covers the entire workflow — it is pinned below, do not scroll past it.

Zentrix⌚️

14,015 Aufrufe • vor 2 Monaten

Successfully generated this with Seedance 2.5—without any face-related moderation restrictions. The result is amazing! prompt： For the target video, at 0.00 seconds into the target video, (from [Shot 1]) is fully referenced. integrated_multimodal_description: [Shot 1] A continuous live-action first-person smartphone recording based entirely on . is the only visual reference for the adult female dancer's appearance, face, hairstyle, hair color, costume, body proportions, environment, room layout, wall, floor, lighting, color and initial spatial composition. Preserve the original visual identity and environment of . The camera closely reproduces the distinctive perspective of : a strong high-angle first-person smartphone POV looking substantially downward at the woman. The camera is clearly above her eye level. The top of her head, shoulders and upper body are visibly seen from above. Keep substantial ceiling visible in the upper part of the frame. Do not use an eye-level view, third-person view, orbiting camera or cuts. A single adult arm belonging to the camera operator enters naturally from the lower-right foreground. Show a connected forearm, wrist, palm and fingers. The hand is a moderate-size foreground element, not a giant object. Keep the hand primarily within the lower-right quadrant, occupying approximately 10–18% of the image area. The hand must never extend across the center, cover the woman's face or cover her torso. The woman remains the primary visual subject and the hand is only the foreground controller. Keep the woman physically close to the smartphone, approximately 1.0–1.2 meters away. Her full body occupies approximately 70–80% of the vertical frame. Do not pull the camera backward, do not place her deep in the room and do not progressively make her smaller. The foreground index finger directly controls the woman's dance movement. The woman does not independently freestyle. The hand is the visible movement cue and the woman's body immediately follows it. Maintain these exact control relationships throughout the entire video: UP → WOMAN RISES. DOWN → WOMAN LOWERS. LEFT → WOMAN MOVES LEFT. RIGHT → WOMAN MOVES RIGHT. For UP, the index finger moves clearly upward and the woman's body immediately rises. Her torso extends upward, her posture becomes taller, her arms naturally rise and her center of gravity moves upward. For DOWN, the index finger moves clearly downward and the woman's body immediately lowers. Her knees bend slightly, hips lower, center of gravity drops and torso lowers into a controlled dance position. For LEFT, the index finger moves toward screen-left and the woman's body immediately shifts and sways toward screen-left. Her weight, torso and hips follow the same direction. The entire body movement must be clearly visible. For RIGHT, the index finger moves toward screen-right and the woman's body immediately shifts and sways toward screen-right. Her weight, torso and hips follow the same direction. The entire body movement must be clearly visible. LEFT and RIGHT must not become tiny hip twitches. The woman's body must visibly move from side to side. Keep the horizontal movement simple so the connection between finger direction and body direction remains unmistakable. The hand gesture and corresponding body movement are tightly synchronized. The woman's movement begins as the corresponding finger gesture begins and develops within the same musical beat. No noticeable reaction delay, no one-beat delay, no anticipation and no independent movement. The dance is a confident, sexy viral short-form influencer dance: energetic rhythmic hip movement, controlled waist isolation, subtle torso waves, attractive shoulder movement, pronounced but tasteful hip accents, confident posture, playful facial expression, direct eye contact and natural hair movement. The dance should feel like a polished viral social-media dance challenge. Make the movement sexy, stylish, rhythmic and visually captivating while keeping it non-explicit. During LEFT and RIGHT movements, maintain the direct horizontal hand control while adding sensual hip accents. During UP and DOWN movements, maintain the direct vertical hand control while adding smooth waist and body movement. Never sacrifice hand-to-body control for complicated choreography. Use a fast modern viral dance rhythm with strong clear beats. Command sequence: UP → DOWN → LEFT → RIGHT → LEFT → RIGHT → UP → DOWN → LEFT → RIGHT. Each command produces one clearly visible corresponding body movement. Do not add unrelated freestyle movements, spins, walking or complicated footwork. The index finger moves with strong, deliberate gestures. The wrist and forearm naturally follow the finger. Use short, clear upward, downward, leftward and rightward gestures. Do not use weak floating gestures. Keep the hand in the lower-right foreground and never allow it to dominate the center of the frame. Maintain one continuous handheld smartphone recording with subtle natural camera instability. Preserve the strong high-angle perspective and close composition throughout the entire shot. Do not zoom out, pull backward, lower the camera or lose either the hand or the woman's full body. At the end, use LEFT → RIGHT → UP. The woman performs a left body movement with a sensual hip accent, a right body movement with a sensual hip accent, then rises into a confident final dance pose. The hand remains in the lower-right foreground and does not move into the center. Hold the final pose briefly. overall_soundscape: Natural indoor room ambience, subtle foot movement, fabric movement and quiet smartphone handling sounds, preserving the acoustic character of . non_diegetic_music: A modern viral short-form dance track with strong punchy beats, crisp percussion and clear rhythmic accents. Each major beat provides a timing point for the hand gesture and its corresponding dance movement.
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Successfully generated this with Seedance 2.5—without any face-related moderation restrictions. The result is amazing! prompt： For the target video, at 0.00 seconds into the target video, (from [Shot 1]) is fully referenced. integrated_multimodal_description: [Shot 1] A continuous live-action first-person smartphone recording based entirely on . is the only visual reference for the adult female dancer's appearance, face, hairstyle, hair color, costume, body proportions, environment, room layout, wall, floor, lighting, color and initial spatial composition. Preserve the original visual identity and environment of . The camera closely reproduces the distinctive perspective of : a strong high-angle first-person smartphone POV looking substantially downward at the woman. The camera is clearly above her eye level. The top of her head, shoulders and upper body are visibly seen from above. Keep substantial ceiling visible in the upper part of the frame. Do not use an eye-level view, third-person view, orbiting camera or cuts. A single adult arm belonging to the camera operator enters naturally from the lower-right foreground. Show a connected forearm, wrist, palm and fingers. The hand is a moderate-size foreground element, not a giant object. Keep the hand primarily within the lower-right quadrant, occupying approximately 10–18% of the image area. The hand must never extend across the center, cover the woman's face or cover her torso. The woman remains the primary visual subject and the hand is only the foreground controller. Keep the woman physically close to the smartphone, approximately 1.0–1.2 meters away. Her full body occupies approximately 70–80% of the vertical frame. Do not pull the camera backward, do not place her deep in the room and do not progressively make her smaller. The foreground index finger directly controls the woman's dance movement. The woman does not independently freestyle. The hand is the visible movement cue and the woman's body immediately follows it. Maintain these exact control relationships throughout the entire video: UP → WOMAN RISES. DOWN → WOMAN LOWERS. LEFT → WOMAN MOVES LEFT. RIGHT → WOMAN MOVES RIGHT. For UP, the index finger moves clearly upward and the woman's body immediately rises. Her torso extends upward, her posture becomes taller, her arms naturally rise and her center of gravity moves upward. For DOWN, the index finger moves clearly downward and the woman's body immediately lowers. Her knees bend slightly, hips lower, center of gravity drops and torso lowers into a controlled dance position. For LEFT, the index finger moves toward screen-left and the woman's body immediately shifts and sways toward screen-left. Her weight, torso and hips follow the same direction. The entire body movement must be clearly visible. For RIGHT, the index finger moves toward screen-right and the woman's body immediately shifts and sways toward screen-right. Her weight, torso and hips follow the same direction. The entire body movement must be clearly visible. LEFT and RIGHT must not become tiny hip twitches. The woman's body must visibly move from side to side. Keep the horizontal movement simple so the connection between finger direction and body direction remains unmistakable. The hand gesture and corresponding body movement are tightly synchronized. The woman's movement begins as the corresponding finger gesture begins and develops within the same musical beat. No noticeable reaction delay, no one-beat delay, no anticipation and no independent movement. The dance is a confident, sexy viral short-form influencer dance: energetic rhythmic hip movement, controlled waist isolation, subtle torso waves, attractive shoulder movement, pronounced but tasteful hip accents, confident posture, playful facial expression, direct eye contact and natural hair movement. The dance should feel like a polished viral social-media dance challenge. Make the movement sexy, stylish, rhythmic and visually captivating while keeping it non-explicit. During LEFT and RIGHT movements, maintain the direct horizontal hand control while adding sensual hip accents. During UP and DOWN movements, maintain the direct vertical hand control while adding smooth waist and body movement. Never sacrifice hand-to-body control for complicated choreography. Use a fast modern viral dance rhythm with strong clear beats. Command sequence: UP → DOWN → LEFT → RIGHT → LEFT → RIGHT → UP → DOWN → LEFT → RIGHT. Each command produces one clearly visible corresponding body movement. Do not add unrelated freestyle movements, spins, walking or complicated footwork. The index finger moves with strong, deliberate gestures. The wrist and forearm naturally follow the finger. Use short, clear upward, downward, leftward and rightward gestures. Do not use weak floating gestures. Keep the hand in the lower-right foreground and never allow it to dominate the center of the frame. Maintain one continuous handheld smartphone recording with subtle natural camera instability. Preserve the strong high-angle perspective and close composition throughout the entire shot. Do not zoom out, pull backward, lower the camera or lose either the hand or the woman's full body. At the end, use LEFT → RIGHT → UP. The woman performs a left body movement with a sensual hip accent, a right body movement with a sensual hip accent, then rises into a confident final dance pose. The hand remains in the lower-right foreground and does not move into the center. Hold the final pose briefly. overall_soundscape: Natural indoor room ambience, subtle foot movement, fabric movement and quiet smartphone handling sounds, preserving the acoustic character of . non_diegetic_music: A modern viral short-form dance track with strong punchy beats, crisp percussion and clear rhythmic accents. Each major beat provides a timing point for the hand gesture and its corresponding dance movement.

underwood

245,132 Aufrufe • vor 13 Tagen

gemini omniflash is actually f*cking cracked. you can animate/edit any video with a text prompt. character swaps, object transforms, full environment changes without regenerating/rotoscoping. everyone using AI to to animate and edit videos right now hits the same wall. the clip comes out 90% right and you regenerate from scratch hoping the 10% fixes itself. it never does. the fix is using your video as the input. omniflash edits what's already there instead of rolling the dice again. here's what's in the system: > the two-layer premiere trick: generate the same shot twice (one with background removed), stack them, cut at one frame, instant scene change > character swap with a single reference image (plus the one line you need or the model keeps the original's features) > object transforms that leave the rest of the frame untouched: stone into glowing sphere, candles into flowers > style transfer from an image reference instead of text, way more accurate > why stacking edits in one prompt breaks everything and the exact step order that doesn't > the audio limitation nobody mentions and how to work around it i packaged every prompt, the edit sequence, and the premiere layering setup. RT + reply "OMNI" and i'll send it over.
0:19

gemini omniflash is actually f*cking cracked. you can animate/edit any video with a text prompt. character swaps, object transforms, full environment changes without regenerating/rotoscoping. everyone using AI to to animate and edit videos right now hits the same wall. the clip comes out 90% right and you regenerate from scratch hoping the 10% fixes itself. it never does. the fix is using your video as the input. omniflash edits what's already there instead of rolling the dice again. here's what's in the system: > the two-layer premiere trick: generate the same shot twice (one with background removed), stack them, cut at one frame, instant scene change > character swap with a single reference image (plus the one line you need or the model keeps the original's features) > object transforms that leave the rest of the frame untouched: stone into glowing sphere, candles into flowers > style transfer from an image reference instead of text, way more accurate > why stacking edits in one prompt breaks everything and the exact step order that doesn't > the audio limitation nobody mentions and how to work around it i packaged every prompt, the edit sequence, and the premiere layering setup. RT + reply "OMNI" and i'll send it over.

Sulfur

36,571 Aufrufe • vor 2 Monaten

They did not take cursive from the schools because children no longer needed it. They took it because of what it was quietly building in them. Consider what the exercise actually is. A child, six years old, is handed a pen and asked to draw a single unbroken line that becomes a word. The wrist must float. The fingers must hold a living pressure, never quite the same twice, always correcting. The eye must follow the ink forward and trust the hand to finish what it has begun. There is no lifting, no stopping, no starting over mid-word. The loop must close. The ascender must rise and return. The sentence must travel from one margin to the other as a single continuous gesture, and at the end of it the hand must still be steady. Twelve years of this. Every day. Ten thousand small acts of sustained, self-correcting attention, carried out below the level of conscious thought, until the motion belongs to the body and the body belongs to the motion. This is not penmanship. It is the slow construction of an interior form. The hand that has learned to carry a line without breaking it is the hand of a mind that has learned to carry a thought without breaking it. The two are not metaphors for one another. They are the same faculty, trained in the same child, by the same daily discipline. Continuity of the stroke becomes continuity of the reasoning. The patience of the loop becomes the patience of the argument. The commitment to finish a word one has started becomes the commitment to finish a sentence, a paragraph, a life's idea, without reaching for the nearest distraction halfway through. Print is a different creature entirely. Print lifts. Print stops. Print assembles a word out of separate, stamped, interchangeable pieces, each one beginning and ending in isolation. A mind raised only on print learns to think the way print is made, in discrete tokens, in replaceable units, in fragments that can be recombined by any outside hand without the owner noticing the substitution. It is precisely the shape of thought a language model produces. It is precisely the shape of thought a language model can steer. Cursive is kata. This is the whole of it. A form repeated daily, for years, not for the sake of the form but for what the repetition lays down in the practitioner beneath the form. The swordsman does not train kata so that one day he may fight in kata. He trains it so that when the moment comes and there is no time to think, the movement is already inside him, older and deeper than thought, and it rises on its own. Cursive was the kata of the literate mind, the daily quiet drilling of continuity, of patience, of a line held steady under the long pressure of its own length. And the signature it produced at the end, that small flourished mark unique to a single human being on earth, was only the outward proof of an inward form no machine and no other hand could ever reproduce. Take the kata away and the practitioner is left with vocabulary in place of faculty. He can recognise a whole thought when he encounters one. He cannot carry one himself. He can admire a finished argument. He cannot sustain one long enough to close its loop. He begins books he does not finish, sentences he does not end, ideas he abandons the moment the screen in his palm offers him a brighter one. And when the machine begins feeding him tokens in the exact shape his schooling taught him to receive, he meets it with no interior resistance at all, because no interior form was ever built in him to push back with. They removed it quietly, across a generation, and they removed it in the last years before the machines arrived. Twelve years of daily practice in unbroken, embodied, self-authored thought, gone from the curriculum of almost every child in the Western world, just as the instruments designed to complete their sentences for them came online. The hand forgets. The mind, having never been taught the kata, forgets a thing it never knew it had. That is what cursive was. That is what was taken. And that is why the thought of anyone who still writes by hand, in long unlifted lines, remains, quietly, stubbornly, and without their ever needing to announce it, their own. Now the question stands open. What else has been banned, phased out, quietly retired from the curriculum and from common life over these same decades, under the same soft excuses? Mental arithmetic. Memorisation of poetry. Latin. Logic as a formal subject. Map reading. Knot work. The keeping of a commonplace book. The reading aloud of long passages in class. Singing in parts. What was each of those actually building in the child, beneath the surface of the lesson, and whose interest was served by its disappearance?
0:10

They did not take cursive from the schools because children no longer needed it. They took it because of what it was quietly building in them. Consider what the exercise actually is. A child, six years old, is handed a pen and asked to draw a single unbroken line that becomes a word. The wrist must float. The fingers must hold a living pressure, never quite the same twice, always correcting. The eye must follow the ink forward and trust the hand to finish what it has begun. There is no lifting, no stopping, no starting over mid-word. The loop must close. The ascender must rise and return. The sentence must travel from one margin to the other as a single continuous gesture, and at the end of it the hand must still be steady. Twelve years of this. Every day. Ten thousand small acts of sustained, self-correcting attention, carried out below the level of conscious thought, until the motion belongs to the body and the body belongs to the motion. This is not penmanship. It is the slow construction of an interior form. The hand that has learned to carry a line without breaking it is the hand of a mind that has learned to carry a thought without breaking it. The two are not metaphors for one another. They are the same faculty, trained in the same child, by the same daily discipline. Continuity of the stroke becomes continuity of the reasoning. The patience of the loop becomes the patience of the argument. The commitment to finish a word one has started becomes the commitment to finish a sentence, a paragraph, a life's idea, without reaching for the nearest distraction halfway through. Print is a different creature entirely. Print lifts. Print stops. Print assembles a word out of separate, stamped, interchangeable pieces, each one beginning and ending in isolation. A mind raised only on print learns to think the way print is made, in discrete tokens, in replaceable units, in fragments that can be recombined by any outside hand without the owner noticing the substitution. It is precisely the shape of thought a language model produces. It is precisely the shape of thought a language model can steer. Cursive is kata. This is the whole of it. A form repeated daily, for years, not for the sake of the form but for what the repetition lays down in the practitioner beneath the form. The swordsman does not train kata so that one day he may fight in kata. He trains it so that when the moment comes and there is no time to think, the movement is already inside him, older and deeper than thought, and it rises on its own. Cursive was the kata of the literate mind, the daily quiet drilling of continuity, of patience, of a line held steady under the long pressure of its own length. And the signature it produced at the end, that small flourished mark unique to a single human being on earth, was only the outward proof of an inward form no machine and no other hand could ever reproduce. Take the kata away and the practitioner is left with vocabulary in place of faculty. He can recognise a whole thought when he encounters one. He cannot carry one himself. He can admire a finished argument. He cannot sustain one long enough to close its loop. He begins books he does not finish, sentences he does not end, ideas he abandons the moment the screen in his palm offers him a brighter one. And when the machine begins feeding him tokens in the exact shape his schooling taught him to receive, he meets it with no interior resistance at all, because no interior form was ever built in him to push back with. They removed it quietly, across a generation, and they removed it in the last years before the machines arrived. Twelve years of daily practice in unbroken, embodied, self-authored thought, gone from the curriculum of almost every child in the Western world, just as the instruments designed to complete their sentences for them came online. The hand forgets. The mind, having never been taught the kata, forgets a thing it never knew it had. That is what cursive was. That is what was taken. And that is why the thought of anyone who still writes by hand, in long unlifted lines, remains, quietly, stubbornly, and without their ever needing to announce it, their own. Now the question stands open. What else has been banned, phased out, quietly retired from the curriculum and from common life over these same decades, under the same soft excuses? Mental arithmetic. Memorisation of poetry. Latin. Logic as a formal subject. Map reading. Knot work. The keeping of a commonplace book. The reading aloud of long passages in class. Singing in parts. What was each of those actually building in the child, beneath the surface of the lesson, and whose interest was served by its disappearance?

SiriusB

443,811 Aufrufe • vor 4 Monaten

19-year-old from china makes $9,000/month designing product sites and ships each one in an afternoon. here's his exact setup the whole thing runs on two tools that each do one job: > brief written by hand: 5 min > Moonchild builds the design system, then every screen from it: 20 min > MCP hands the design to Claude as real structure, not a screenshot: instant > Claude Code reads those exact tokens and builds the live app: 20 min > second Claude session reviews the build for drift: 10 min total: about an hour. screen five still matches screen one. no agency, no dev, no design team the trick is MCP. the design tool passes Claude the actual colors, components and layout, so it builds from the source instead of guessing from a picture. full pipeline, every prompt, in the article above.
0:12

19-year-old from china makes $9,000/month designing product sites and ships each one in an afternoon. here's his exact setup the whole thing runs on two tools that each do one job: > brief written by hand: 5 min > Moonchild builds the design system, then every screen from it: 20 min > MCP hands the design to Claude as real structure, not a screenshot: instant > Claude Code reads those exact tokens and builds the live app: 20 min > second Claude session reviews the build for drift: 10 min total: about an hour. screen five still matches screen one. no agency, no dev, no design team the trick is MCP. the design tool passes Claude the actual colors, components and layout, so it builds from the source instead of guessing from a picture. full pipeline, every prompt, in the article above.

Ridark

19,477 Aufrufe • vor 2 Monaten

We have released Seedance 2.0. Due to the 2500-character limit, please translate the following prompts into Chinese before use. [Technical Specs] Generate a 10-second, 16:9, 720p cinematic video. Smooth continuous camera motion with no cuts. The overall pacing is fast and tightly compressed, with rapid escalation from start to finish. Audio evolves quickly from a high-performance engine idle into intricate mechanical shifting and clicks, culminating in a soft electronic chime and the distinct sound of a "mwah" blowing kiss. [Global Constraints] Only the evolving mechanical character appears; no other humans or characters. All transformations must follow physical logic and maintain structural continuity. No object should pass through or intersect with other solid objects. Every robotic component must originate from visible parts of the Porsche 911 (doors, hood, wheels, chassis) through unfolding, splitting, or reconfiguration. [Scene Setup — 0:00–0:01] A sleek, metallic silver Porsche 911 sits on a rain-slicked futuristic city street at night, neon lights reflecting off its polished surface. The camera starts at a low-angle front-quarter view and begins a fast, smooth tracking-arc towards the side. [Rapid Transformation Initiation — 0:01–0:03] Transformation triggers instantly. The car’s suspension drops, and the frame begins to fracture into a complex grid of panels. The doors swing open and begin to segment into articulated arm structures. The front hood splits down the center, folding inward to reveal a glowing internal core. The headlights flicker and start to reorient as the "eyes." [Accelerated Feminine Reconfiguration — 0:03–0:07] The mechanical action is dense, overlapping, and fluid, emphasizing graceful but powerful motion. Lower Body: The rear wheels and wheel arches split and rotate downward, reassembling into slender, high-heeled mechanical legs. Torso: The roof and rear engine cover slide and compress, forming a sleek, curvaceous hourglass torso that retains the car’s aerodynamic lines. Arms & Hands: The side mirrors and door panels unfold into delicate but strong hands and fingers. Head: The front bumper and emblem area segment and rise, folding into a feminine-shaped head with a sleek metallic "helmet" visor. [Logical Transformation Constraints — No Spontaneous Appearance] The robot’s "skin" is composed of the car's outer silver panels. The internal frame and wiring emerge from the engine and undercarriage. No parts appear out of thin air; every joint is a reconfigured automotive component. [Transformation Completion — 0:07–0:08.5] The robot stands tall and elegant. The silver panels lock into place with a satisfying "click," revealing glowing blue LED accents in the seams. The silhouette is clearly feminine, humanoid, and sophisticated, reflecting the premium design of the original vehicle. [Final Hero Ending — 0:08.5–0:10] As the robot stabilizes, the camera performs a rapid, smooth zoom-in (Dolly-In) directly to her face. The robot tilts its head slightly, and the optic sensors (eyes) brighten. It brings its mechanical hand to its metallic lips and performs a graceful blowing kiss (fly-kiss) gesture toward the camera. The video ends with a close-up of the face, capturing the reflection of neon lights in its visor just as the kiss is released. [Cinematography Notes] Continuous Motion: No cuts or fades; the camera must transition from the car-tracking shot to the face-zoom seamlessly. Material Consistency: The robot must maintain the exact metallic silver paint, texture, and reflections of the Porsche. Energy: The transformation should feel high-energy and "force-driven," while the final gesture is soft and charismatic.
0:10

We have released Seedance 2.0. Due to the 2500-character limit, please translate the following prompts into Chinese before use. [Technical Specs] Generate a 10-second, 16:9, 720p cinematic video. Smooth continuous camera motion with no cuts. The overall pacing is fast and tightly compressed, with rapid escalation from start to finish. Audio evolves quickly from a high-performance engine idle into intricate mechanical shifting and clicks, culminating in a soft electronic chime and the distinct sound of a "mwah" blowing kiss. [Global Constraints] Only the evolving mechanical character appears; no other humans or characters. All transformations must follow physical logic and maintain structural continuity. No object should pass through or intersect with other solid objects. Every robotic component must originate from visible parts of the Porsche 911 (doors, hood, wheels, chassis) through unfolding, splitting, or reconfiguration. [Scene Setup — 0:00–0:01] A sleek, metallic silver Porsche 911 sits on a rain-slicked futuristic city street at night, neon lights reflecting off its polished surface. The camera starts at a low-angle front-quarter view and begins a fast, smooth tracking-arc towards the side. [Rapid Transformation Initiation — 0:01–0:03] Transformation triggers instantly. The car’s suspension drops, and the frame begins to fracture into a complex grid of panels. The doors swing open and begin to segment into articulated arm structures. The front hood splits down the center, folding inward to reveal a glowing internal core. The headlights flicker and start to reorient as the "eyes." [Accelerated Feminine Reconfiguration — 0:03–0:07] The mechanical action is dense, overlapping, and fluid, emphasizing graceful but powerful motion. Lower Body: The rear wheels and wheel arches split and rotate downward, reassembling into slender, high-heeled mechanical legs. Torso: The roof and rear engine cover slide and compress, forming a sleek, curvaceous hourglass torso that retains the car’s aerodynamic lines. Arms & Hands: The side mirrors and door panels unfold into delicate but strong hands and fingers. Head: The front bumper and emblem area segment and rise, folding into a feminine-shaped head with a sleek metallic "helmet" visor. [Logical Transformation Constraints — No Spontaneous Appearance] The robot’s "skin" is composed of the car's outer silver panels. The internal frame and wiring emerge from the engine and undercarriage. No parts appear out of thin air; every joint is a reconfigured automotive component. [Transformation Completion — 0:07–0:08.5] The robot stands tall and elegant. The silver panels lock into place with a satisfying "click," revealing glowing blue LED accents in the seams. The silhouette is clearly feminine, humanoid, and sophisticated, reflecting the premium design of the original vehicle. [Final Hero Ending — 0:08.5–0:10] As the robot stabilizes, the camera performs a rapid, smooth zoom-in (Dolly-In) directly to her face. The robot tilts its head slightly, and the optic sensors (eyes) brighten. It brings its mechanical hand to its metallic lips and performs a graceful blowing kiss (fly-kiss) gesture toward the camera. The video ends with a close-up of the face, capturing the reflection of neon lights in its visor just as the kiss is released. [Cinematography Notes] Continuous Motion: No cuts or fades; the camera must transition from the car-tracking shot to the face-zoom seamlessly. Material Consistency: The robot must maintain the exact metallic silver paint, texture, and reflections of the Porsche. Energy: The transformation should feel high-energy and "force-driven," while the final gesture is soft and charismatic.

underwood

19,462 Aufrufe • vor 5 Monaten

Batch Normalization by hand ✍️ ~ 7 steps walkthrough below Batch normalization is common practice for improving training and achieving faster convergence. It sounds simple. But it is often misunderstood. 🤔 Does batch normalization involve trainable parameters, tunable hyper-parameters, or both? 🤔 Is batch normalization applied to inputs, features, weights, biases, or outputs? 🤔 How is batch normalization different from layer normalization? So I drew and calculated one entirely by hand. Goal: normalize a mini-batch of 4 examples to mean 0 and variance 1, then let the network scale it back. = 1. Given = A mini-batch of 4 training examples, each with 3 features. = 2. Linear layer = Let us multiply by the weights and add the biases. Batch norm sits after this, which answers the second question: what gets normalized is features, not inputs, weights or biases. = 3. ReLU = We apply the activation, and -2 becomes 0. Negative values are suppressed before any statistic is taken. = 4. Batch statistics = Let us compute the sum, mean, variance and standard deviation, one row at a time. A row is a feature and the four columns are the four examples, so every number here measures one feature against the rest of the batch. That is the "batch" in batch normalization, and it is exactly what layer normalization does not do. The statistics are rounded to whole numbers, which is what keeps the rest of the page doable in pen. = 5. Shift to mean 0 = We subtract the mean, in green. The four values in each feature now average to zero. = 6. Scale to variance 1 = Let us divide by the standard deviation, in orange. Each feature now has variance one, whatever scale it arrived at. = 7. Scale and shift = We multiply by a linear transformation and pass the result on. The diagonal and the last column are trainable, so having just forced every feature to mean 0 and variance 1, we hand the network the means to undo it. The outputs: Mean of each feature = [2, 1, 2] Std dev of each feature = [1, 1, 2] To the next layer = [2, -2, 2, 0], [-3, 3, 6, -3], [2, 0, 1, 2] The answers: 🤔 Both. The scale and shift are trainable, the statistics are not. Epsilon and the momentum on the running statistics are the hyper-parameters, and one mini-batch by hand needs neither. 🤔 Features, after the linear layer, not inputs, weights or biases. 🤔 Batch norm measures across the batch, one feature at a time. Layer norm measures across the features, one example at a time. 💾 Save this post!
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Batch Normalization by hand ✍️ ~ 7 steps walkthrough below Batch normalization is common practice for improving training and achieving faster convergence. It sounds simple. But it is often misunderstood. 🤔 Does batch normalization involve trainable parameters, tunable hyper-parameters, or both? 🤔 Is batch normalization applied to inputs, features, weights, biases, or outputs? 🤔 How is batch normalization different from layer normalization? So I drew and calculated one entirely by hand. Goal: normalize a mini-batch of 4 examples to mean 0 and variance 1, then let the network scale it back. = 1. Given = A mini-batch of 4 training examples, each with 3 features. = 2. Linear layer = Let us multiply by the weights and add the biases. Batch norm sits after this, which answers the second question: what gets normalized is features, not inputs, weights or biases. = 3. ReLU = We apply the activation, and -2 becomes 0. Negative values are suppressed before any statistic is taken. = 4. Batch statistics = Let us compute the sum, mean, variance and standard deviation, one row at a time. A row is a feature and the four columns are the four examples, so every number here measures one feature against the rest of the batch. That is the "batch" in batch normalization, and it is exactly what layer normalization does not do. The statistics are rounded to whole numbers, which is what keeps the rest of the page doable in pen. = 5. Shift to mean 0 = We subtract the mean, in green. The four values in each feature now average to zero. = 6. Scale to variance 1 = Let us divide by the standard deviation, in orange. Each feature now has variance one, whatever scale it arrived at. = 7. Scale and shift = We multiply by a linear transformation and pass the result on. The diagonal and the last column are trainable, so having just forced every feature to mean 0 and variance 1, we hand the network the means to undo it. The outputs: Mean of each feature = [2, 1, 2] Std dev of each feature = [1, 1, 2] To the next layer = [2, -2, 2, 0], [-3, 3, 6, -3], [2, 0, 1, 2] The answers: 🤔 Both. The scale and shift are trainable, the statistics are not. Epsilon and the momentum on the running statistics are the hyper-parameters, and one mini-batch by hand needs neither. 🤔 Features, after the linear layer, not inputs, weights or biases. 🤔 Batch norm measures across the batch, one feature at a time. Layer norm measures across the features, one example at a time. 💾 Save this post!

Tom Yeh

20,848 Aufrufe • vor 1 Monat

Megan Fox really knows how to draw everyone's attention, don't you think?🤩😏 VIdeo by Kling 3.0 via Higgsfield AI (More videos for my subscribers!) Video & Image prompts below👇🏻 🔴 Video Prompt: Subject slowly rises from kneeling position on fluffy white rug — movement begins with a natural, fluid push upward from knees to standing. As she rises, hips sway gently and playfully, body moves naturally with soft feminine energy, not exaggerated. Hair still mid-ponytail, hands finish tying it as she stands. Camera rises simultaneously with her, tracking from chest level up to face level as she reaches full standing height. Full body visible throughout the rise. At 8 seconds: she leans slightly forward toward camera, eyes locked, and softly tongue out to the camera lens. At 9-10 seconds: she pulls back, gives one final direct look into camera, then flashes a peace sign with a slight smirk. Style: Cinematic, smooth camera movement, natural bedroom lighting with soft daylight from window, warm neon glow from "Keor" sign in background. Realistic, no sudden cuts, fluid motion throughout. 10 seconds total. 🔴 Image Prompt: A Megan Fox with fair skin, freckles across her face and shoulders, and striking blue eyes is kneeling on a thick, fluffy white rug in a messy bedroom. She has long, black hair that she is actively gathering with both hands to tie into a high ponytail; her right hand holds the base of the ponytail near the crown of her head while her left hand pulls the length of her hair through. She is wearing a fitted light green lime ribbed tank top with V neckline and fuchsia gym shorts bottoms. Her expression is direct and slightly serious as she looks straight at the camera from a high angle. The bedroom background features an unmade pink bed with rumpled light-colored sheets and pillows, scattered clothes on the floor and bed, a white nightstand with a modern lamp, a stack of books, a big poster of Inuyasha manga characters, a little neon written 'Keor' on wall, and a window with sheer curtains letting in natural daylight. The overall scene has a casual, lived-in atmosphere with soft natural lighting."
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Megan Fox really knows how to draw everyone's attention, don't you think?🤩😏 VIdeo by Kling 3.0 via Higgsfield AI (More videos for my subscribers!) Video & Image prompts below👇🏻 🔴 Video Prompt: Subject slowly rises from kneeling position on fluffy white rug — movement begins with a natural, fluid push upward from knees to standing. As she rises, hips sway gently and playfully, body moves naturally with soft feminine energy, not exaggerated. Hair still mid-ponytail, hands finish tying it as she stands. Camera rises simultaneously with her, tracking from chest level up to face level as she reaches full standing height. Full body visible throughout the rise. At 8 seconds: she leans slightly forward toward camera, eyes locked, and softly tongue out to the camera lens. At 9-10 seconds: she pulls back, gives one final direct look into camera, then flashes a peace sign with a slight smirk. Style: Cinematic, smooth camera movement, natural bedroom lighting with soft daylight from window, warm neon glow from "Keor" sign in background. Realistic, no sudden cuts, fluid motion throughout. 10 seconds total. 🔴 Image Prompt: A Megan Fox with fair skin, freckles across her face and shoulders, and striking blue eyes is kneeling on a thick, fluffy white rug in a messy bedroom. She has long, black hair that she is actively gathering with both hands to tie into a high ponytail; her right hand holds the base of the ponytail near the crown of her head while her left hand pulls the length of her hair through. She is wearing a fitted light green lime ribbed tank top with V neckline and fuchsia gym shorts bottoms. Her expression is direct and slightly serious as she looks straight at the camera from a high angle. The bedroom background features an unmade pink bed with rumpled light-colored sheets and pillows, scattered clothes on the floor and bed, a white nightstand with a modern lamp, a stack of books, a big poster of Inuyasha manga characters, a little neon written 'Keor' on wall, and a window with sheer curtains letting in natural daylight. The overall scene has a casual, lived-in atmosphere with soft natural lighting."

KeorUnreal

106,851 Aufrufe • vor 4 Monaten

What did you do to my friend !! 😡 This is the trending “Fight Prompt” going viral Prompt : Use the first uploaded image as the main reference for the school uniform, body proportions, pose, posture, background, camera angle, framing, and overall composition. Use the second uploaded image as the identity reference for the face and hairstyle. Create a realistic Korean influencer-style school uniform portrait where the person from the second image naturally appears wearing the school uniform from the first image, photographed in the same studio setting. Important: Keep the school uniform, blazer, shirt, tie, skirt or pants, and overall outfit design from the first image. Keep the body proportions, standing pose, hand placement, posture, camera angle, framing, and studio background from the first image. Replace the face with the person from the second image. Also preserve the hairstyle from the second image, including bangs, hairline, hair part, hair length, hair framing around the face, and overall hair silhouette. Do not use the hairstyle from the first image if it differs from the second image. Identity: The face from the second image must remain clearly recognizable. Preserve the second person’s face shape, eyes, nose, lips, skin tone, jawline, and overall facial impression. Do not turn the face into a generic attractive face. Do not beautify too heavily. Preserve the person’s recognizable identity, but do not copy the face too rigidly. Reinterpret it naturally so it looks like a realistic photo of the same person in this new school-uniform scene. Keep the same overall facial impression and identity while allowing natural refinement and seamless adaptation to the lighting, angle, and mood of the target image. Hair: Follow the hairstyle from the second image. Preserve the second person’s bangs, hairline, hair part, hair texture, hair length, and overall hairstyle impression. Only adapt the hair naturally so it fits the pose, lighting, and composition of the first image. Korean influencer mood: clean modern Korean influencer portrait polished but natural beauty soft photogenic expression subtle editorial mood stylish, slightly chic, youthful, and confident atmosphere refined but believable skin texture clear eyes with soft catchlights naturally pretty, not over-retouched avoid stiff ID-photo mood Lighting: soft Korean beauty lighting gentle facial brightness clean skin tone soft natural highlights on the face natural shadow transition subtle glow, but realistic skin texture avoid harsh flash avoid flat passport-photo lighting avoid dramatic studio glamour lighting Style: realistic photography clean studio portrait quality Korean influencer-style school portrait mood natural skin texture high detail seamless face and hair integration polished but believable Negative prompt: no identity loss no generic attractive face no over-beautified face no first-image hairstyle if different no awkward face blending no mismatched skin tone no mismatched hairline no distorted facial features no blurry eyes no deformed hands no extra fingers no change to the school uniform no change to the body pose no change to the background no cartoon style no anime style no text no watermark
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What did you do to my friend !! 😡 This is the trending “Fight Prompt” going viral Prompt : Use the first uploaded image as the main reference for the school uniform, body proportions, pose, posture, background, camera angle, framing, and overall composition. Use the second uploaded image as the identity reference for the face and hairstyle. Create a realistic Korean influencer-style school uniform portrait where the person from the second image naturally appears wearing the school uniform from the first image, photographed in the same studio setting. Important: Keep the school uniform, blazer, shirt, tie, skirt or pants, and overall outfit design from the first image. Keep the body proportions, standing pose, hand placement, posture, camera angle, framing, and studio background from the first image. Replace the face with the person from the second image. Also preserve the hairstyle from the second image, including bangs, hairline, hair part, hair length, hair framing around the face, and overall hair silhouette. Do not use the hairstyle from the first image if it differs from the second image. Identity: The face from the second image must remain clearly recognizable. Preserve the second person’s face shape, eyes, nose, lips, skin tone, jawline, and overall facial impression. Do not turn the face into a generic attractive face. Do not beautify too heavily. Preserve the person’s recognizable identity, but do not copy the face too rigidly. Reinterpret it naturally so it looks like a realistic photo of the same person in this new school-uniform scene. Keep the same overall facial impression and identity while allowing natural refinement and seamless adaptation to the lighting, angle, and mood of the target image. Hair: Follow the hairstyle from the second image. Preserve the second person’s bangs, hairline, hair part, hair texture, hair length, and overall hairstyle impression. Only adapt the hair naturally so it fits the pose, lighting, and composition of the first image. Korean influencer mood: clean modern Korean influencer portrait polished but natural beauty soft photogenic expression subtle editorial mood stylish, slightly chic, youthful, and confident atmosphere refined but believable skin texture clear eyes with soft catchlights naturally pretty, not over-retouched avoid stiff ID-photo mood Lighting: soft Korean beauty lighting gentle facial brightness clean skin tone soft natural highlights on the face natural shadow transition subtle glow, but realistic skin texture avoid harsh flash avoid flat passport-photo lighting avoid dramatic studio glamour lighting Style: realistic photography clean studio portrait quality Korean influencer-style school portrait mood natural skin texture high detail seamless face and hair integration polished but believable Negative prompt: no identity loss no generic attractive face no over-beautified face no first-image hairstyle if different no awkward face blending no mismatched skin tone no mismatched hairline no distorted facial features no blurry eyes no deformed hands no extra fingers no change to the school uniform no change to the body pose no change to the background no cartoon style no anime style no text no watermark

Ai Arainz

104,348 Aufrufe • vor 3 Monaten

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.
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This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

Blaze

38,242 Aufrufe • vor 3 Monaten

The main bronze door of Milan Cathedral weighs 37 tons and took a single sculptor 10 years to complete. The Duomo of Milan is one of the largest and most intricate cathedrals on earth, and its five bronze doors were built to be worthy of it. Every inch of the great central door is covered in sculpted bronze, dozens of scenes from the life of the Virgin Mary, faces caught mid-emotion, figures that seem to press forward out of the metal as if trying to step into the world... It was designed by the sculptor Ludovico Pogliaghi, who received the commission in the 1880s and did not see his door installed until 1906, having poured a decade of his life into modelling every figure by hand. And his was just the beginning. The five doors of the cathedral were not made together, or even in the same lifetime. They were created across nearly seventy years, by a succession of different sculptors, each carving their panels with the same obsessive care. The final door was not completed until 1965, its unveiling taken as the symbolic close of a cathedral that had been under construction, in one form or another, for 579 years... More than a century ago, the English polymath John Ruskin tried to put into words what it means to build something like this. He managed it in a single sentence. "When we build," he wrote, "let us think that we build for ever."
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The main bronze door of Milan Cathedral weighs 37 tons and took a single sculptor 10 years to complete. The Duomo of Milan is one of the largest and most intricate cathedrals on earth, and its five bronze doors were built to be worthy of it. Every inch of the great central door is covered in sculpted bronze, dozens of scenes from the life of the Virgin Mary, faces caught mid-emotion, figures that seem to press forward out of the metal as if trying to step into the world... It was designed by the sculptor Ludovico Pogliaghi, who received the commission in the 1880s and did not see his door installed until 1906, having poured a decade of his life into modelling every figure by hand. And his was just the beginning. The five doors of the cathedral were not made together, or even in the same lifetime. They were created across nearly seventy years, by a succession of different sculptors, each carving their panels with the same obsessive care. The final door was not completed until 1965, its unveiling taken as the symbolic close of a cathedral that had been under construction, in one form or another, for 579 years... More than a century ago, the English polymath John Ruskin tried to put into words what it means to build something like this. He managed it in a single sentence. "When we build," he wrote, "let us think that we build for ever."

James Lucas

83,782 Aufrufe • vor 2 Monaten

For the first time in the history of automation, the people most likely to be replaced are the ones building their own replacement, frame by frame, for a few dollars an hour. Across India, Nigeria, China, and Argentina, workers are strapping cameras to their heads and recording every fold of laundry, every stitch, every washed dish, and that footage is training the robots designed to do those exact jobs. This is documented, not rumor. No jokes! Garment workers in Tamil Nadu, India have been filmed wearing head-mounted cameras on the factory floor, sending point-of-view footage to data firms whose clients include Fortune 500 companies. One US company alone has hired thousands of workers across more than 50 countries to record themselves cooking, cleaning, and folding clothes. More than 6 billion dollars poured into humanoid robots last year, and the one ingredient every maker is starved for is precisely this: real human hands doing real human work. The endpoint is stated plainly by the buyers. In China, one supplier said his pitch to factories is to let workers wear the cameras now, because trained robots will eventually work there instead. The quiet part is the exchange itself. The worker is paid for the hour and keeps nothing after it. No share, no royalty, no ownership of the movements their own body is teaching the machine. The skill leaves their hands and becomes someone else's product, and almost no one along the chain sees the full shape of the trade, not always the person filming, not the millions who watch the clip and scroll on. One scene holds all of it. A humanoid robot spent an hour folding three shirts while a human housekeeper, hired to guide it, quietly finished the rest of the chores. Every automation before this arrived from the outside. A machine showed up and took the job. This one is being built from the inside, by the workers themselves, handing over the last thing they had left to sell. UBI ? or something totally else should pave the way in the future? Thoughts?
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For the first time in the history of automation, the people most likely to be replaced are the ones building their own replacement, frame by frame, for a few dollars an hour. Across India, Nigeria, China, and Argentina, workers are strapping cameras to their heads and recording every fold of laundry, every stitch, every washed dish, and that footage is training the robots designed to do those exact jobs. This is documented, not rumor. No jokes! Garment workers in Tamil Nadu, India have been filmed wearing head-mounted cameras on the factory floor, sending point-of-view footage to data firms whose clients include Fortune 500 companies. One US company alone has hired thousands of workers across more than 50 countries to record themselves cooking, cleaning, and folding clothes. More than 6 billion dollars poured into humanoid robots last year, and the one ingredient every maker is starved for is precisely this: real human hands doing real human work. The endpoint is stated plainly by the buyers. In China, one supplier said his pitch to factories is to let workers wear the cameras now, because trained robots will eventually work there instead. The quiet part is the exchange itself. The worker is paid for the hour and keeps nothing after it. No share, no royalty, no ownership of the movements their own body is teaching the machine. The skill leaves their hands and becomes someone else's product, and almost no one along the chain sees the full shape of the trade, not always the person filming, not the millions who watch the clip and scroll on. One scene holds all of it. A humanoid robot spent an hour folding three shirts while a human housekeeper, hired to guide it, quietly finished the rest of the chores. Every automation before this arrived from the outside. A machine showed up and took the job. This one is being built from the inside, by the workers themselves, handing over the last thing they had left to sell. UBI ? or something totally else should pave the way in the future? Thoughts?

Shanaka Anslem Perera ⚡

95,549 Aufrufe • vor 2 Monaten

Would you dare chase justice while swinging thousands of feet above traffic below? Seedance 2 prompt on BudgetPixel AI Create a 15-second ultra-realistic cinematic high-altitude tether-swinging action sequence in strict 16:9 landscape, native 4K, 24fps. Use one seamless continuous drone follow shot with no cuts, no teleporting, and no time skips. The motion must feel physically continuous, dynamic, thrilling, and always readable. REFERENCE: image1 = main heroine reference. Use image1 as the strict identity reference for the heroine’s face, facial proportions, hairstyle, hair color, body proportions, age impression, outfit, shoes, accessories, styling, and overall recognizable appearance. Preserve her identity consistently throughout the whole video. Keep her as an original urban tether-swinging action heroine. Do not redesign her into a branded superhero character. Do not add franchise logos, copyrighted chest emblems, or recognizable third-party superhero symbols. CORE CONCEPT: This is an original urban tether-swinging action short. The heroine moves through the city using thin wrist-launched fiber lines, momentum, wall-running, rooftop movement, and real parkour body mechanics. She travels at high altitude between tall buildings, then lands on a rooftop, defeats one villain, and ends with a powerful shout. HOOK: The first second must be an instant scroll-stopping hook. Start with the heroine already falling backward off the edge of a very tall skyscraper. For a brief moment, it looks like she may actually fall. Then she instantly fires one thin tether line upward, it catches, and her body snaps into a huge high-altitude swing between buildings. STYLE: Photorealistic live-action realism. Premium cinematic action quality. Bright daytime Los Angeles atmosphere with realistic haze, realistic motion blur, realistic fabric movement, realistic body weight, real inertia, and practical environmental interaction. The sequence should feel like a premium action movie shot, not animation, not a game cutscene, and not a cartoon. CAMERA: One uninterrupted drone follow shot only. No cuts. No resets. No jumpy edits. No impossible viewpoint teleporting. The drone camera must stay wide enough to show both the heroine and the environment together. It may tilt, roll, arc, climb, and dive with the motion, but it must always feel like one real flying camera tracking her. Keep the framing intense and fast, but always readable. ENVIRONMENT: Bright daytime in a dense modern city inspired by Los Angeles and Hollywood. Show: - tall glass and concrete high-rises - rooftop edges - billboards and signage - palm trees far below where visible - busy roads and traffic far beneath - bright haze and sunny atmosphere - believable large-scale urban depth The action must happen mainly high above the street between tall buildings, not low near the ground for most of the video. VILLAIN RULE: Only one villain appears in the entire video. The villain is one adult male enemy only. He wears a fitted black suit, black shirt, and black shoes. No mask, no armor, no fantasy costume. He appears only in the rooftop combat section. Do not generate multiple enemies. Do not generate background enemies. Do not clone or duplicate the villain. ACTION RULES: The heroine’s movement must feel hand-and-foot driven, not magical floating. She must visibly: - fire thin tether lines from her hands - swing with real tension and momentum - push off building surfaces - run along walls with clear foot placement - absorb landings with bent knees - sprint briefly on a rooftop - fight one villain using fast practical action - finish in control Her body mechanics must stay realistic: - core engaged during swings - arms extended or flexed according to line tension - knees bend on landing and push-off - visible transfer of momentum between swing, wall-run, leap, landing, and combat Do not make her hover weightlessly. Do not make the tether line act like magic. Do not make her float in place unnaturally. EMOTIONAL ARC: - opening: shock and immediate control - mid-swing: intense focus - rooftop approach: rising confidence - rooftop fight: sharp aggression and urgency - ending: victorious adrenaline and fearless release AUDIO: No music. Effects and ambience only: - rushing wind - tether firing and tension snaps - air pass-by - foot impacts on walls and rooftop surfaces - city ambience far below - distant traffic and horns - fabric movement - breathing - one short rooftop fight impact sequence - one powerful final shout from the heroine TIMELINE: 0:00–0:01 Start from black into a shocking rooftop-edge fall. The heroine is already dropping backward off a skyscraper. For a fraction of a second it feels dangerous and uncontrolled. She immediately flicks her wrist and fires one thin tether line upward. It catches instantly. The drone yanks back and reveals the start of a huge swing. 0:01–0:04 The heroine swings at high altitude between tall buildings. The city is far below. Her body forms a long aerodynamic arc, one arm holding tension through the line, legs trailing cleanly behind. The drone follows wide and slightly rolled, emphasizing height, speed, and scale. 0:04–0:06 At the swing’s forward rise, she releases the line and redirects toward a nearby glass-and-concrete building. She plants onto the wall and runs across it diagonally with 4 to 5 clear steps. Her feet hit the wall with visible force. Her jaw is set and focused. The drone stays close but wide enough to keep the city depth visible. 0:06–0:08 She pushes explosively off the wall, fires a new tether line, and swings again through a narrower corridor between tall buildings. The movement should feel faster and more controlled now. She threads cleanly through the urban gap and angles toward a rooftop landing zone ahead. 0:08–0:09.5 She releases the line and lands hard but controlled on a rooftop. Knees bend deeply to absorb impact. She rolls into a short forward recovery step, then rises immediately into a sprint across the rooftop surface. 0:09.5–0:12 One villain in a black suit steps in to stop her. Keep only this single enemy. The heroine engages him in a short, sharp rooftop fight. She avoids his first attack with a quick slip, grabs or redirects his arm, drives one fast body shot or elbow, then uses his off-balance momentum to throw or slam him down onto the rooftop. The fight must feel quick, practical, and decisive. Real impact reactions. No slow choreography. No extra enemies. 0:12–0:13.5 The villain is down and no longer a threat. The heroine steps past him and moves to the rooftop edge. Wind moves her hair and outfit. She looks outward over the city with intense adrenaline and triumph. 0:13.5–0:15 At the rooftop edge, she turns slightly toward the open skyline, lifts her chest, and shouts one powerful final line: “가자!” She immediately launches forward off the rooftop edge into another leap just as the clip ends. End on the feeling that the action is continuing beyond the cut. IMPORTANT RULES: - one continuous drone follow shot only - no cuts - no teleporting - no cloning - no multiple villains - only one black-suited villain - no giant web canopy - use only thin functional tether lines - no franchise logos - no copyrighted chest symbols - preserve the uploaded identity consistently - action must stay realistic and momentum-driven - rooftop fight must be short, sharp, and readable - final shout must be “가자!” NEGATIVE: no cartoon, no anime, no game-engine look, no fake CGI stiffness, no floating, no weightless hovering, no random disconnected acrobatics, no city-wide web canopy, no superhero logo, no copyrighted spider emblem, no extra enemies, no masked villain, no armored villain, no cloned villain, no empty city, no dark night setting, no rain, no slow motion, no blurred identity, no outfit drift, no face drift, no extra limbs, no broken anatomy, no unrealistic hand deformation, no collision with buildings during swings, no messy unreadable fight.
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Would you dare chase justice while swinging thousands of feet above traffic below? Seedance 2 prompt on BudgetPixel AI Create a 15-second ultra-realistic cinematic high-altitude tether-swinging action sequence in strict 16:9 landscape, native 4K, 24fps. Use one seamless continuous drone follow shot with no cuts, no teleporting, and no time skips. The motion must feel physically continuous, dynamic, thrilling, and always readable. REFERENCE: image1 = main heroine reference. Use image1 as the strict identity reference for the heroine’s face, facial proportions, hairstyle, hair color, body proportions, age impression, outfit, shoes, accessories, styling, and overall recognizable appearance. Preserve her identity consistently throughout the whole video. Keep her as an original urban tether-swinging action heroine. Do not redesign her into a branded superhero character. Do not add franchise logos, copyrighted chest emblems, or recognizable third-party superhero symbols. CORE CONCEPT: This is an original urban tether-swinging action short. The heroine moves through the city using thin wrist-launched fiber lines, momentum, wall-running, rooftop movement, and real parkour body mechanics. She travels at high altitude between tall buildings, then lands on a rooftop, defeats one villain, and ends with a powerful shout. HOOK: The first second must be an instant scroll-stopping hook. Start with the heroine already falling backward off the edge of a very tall skyscraper. For a brief moment, it looks like she may actually fall. Then she instantly fires one thin tether line upward, it catches, and her body snaps into a huge high-altitude swing between buildings. STYLE: Photorealistic live-action realism. Premium cinematic action quality. Bright daytime Los Angeles atmosphere with realistic haze, realistic motion blur, realistic fabric movement, realistic body weight, real inertia, and practical environmental interaction. The sequence should feel like a premium action movie shot, not animation, not a game cutscene, and not a cartoon. CAMERA: One uninterrupted drone follow shot only. No cuts. No resets. No jumpy edits. No impossible viewpoint teleporting. The drone camera must stay wide enough to show both the heroine and the environment together. It may tilt, roll, arc, climb, and dive with the motion, but it must always feel like one real flying camera tracking her. Keep the framing intense and fast, but always readable. ENVIRONMENT: Bright daytime in a dense modern city inspired by Los Angeles and Hollywood. Show: - tall glass and concrete high-rises - rooftop edges - billboards and signage - palm trees far below where visible - busy roads and traffic far beneath - bright haze and sunny atmosphere - believable large-scale urban depth The action must happen mainly high above the street between tall buildings, not low near the ground for most of the video. VILLAIN RULE: Only one villain appears in the entire video. The villain is one adult male enemy only. He wears a fitted black suit, black shirt, and black shoes. No mask, no armor, no fantasy costume. He appears only in the rooftop combat section. Do not generate multiple enemies. Do not generate background enemies. Do not clone or duplicate the villain. ACTION RULES: The heroine’s movement must feel hand-and-foot driven, not magical floating. She must visibly: - fire thin tether lines from her hands - swing with real tension and momentum - push off building surfaces - run along walls with clear foot placement - absorb landings with bent knees - sprint briefly on a rooftop - fight one villain using fast practical action - finish in control Her body mechanics must stay realistic: - core engaged during swings - arms extended or flexed according to line tension - knees bend on landing and push-off - visible transfer of momentum between swing, wall-run, leap, landing, and combat Do not make her hover weightlessly. Do not make the tether line act like magic. Do not make her float in place unnaturally. EMOTIONAL ARC: - opening: shock and immediate control - mid-swing: intense focus - rooftop approach: rising confidence - rooftop fight: sharp aggression and urgency - ending: victorious adrenaline and fearless release AUDIO: No music. Effects and ambience only: - rushing wind - tether firing and tension snaps - air pass-by - foot impacts on walls and rooftop surfaces - city ambience far below - distant traffic and horns - fabric movement - breathing - one short rooftop fight impact sequence - one powerful final shout from the heroine TIMELINE: 0:00–0:01 Start from black into a shocking rooftop-edge fall. The heroine is already dropping backward off a skyscraper. For a fraction of a second it feels dangerous and uncontrolled. She immediately flicks her wrist and fires one thin tether line upward. It catches instantly. The drone yanks back and reveals the start of a huge swing. 0:01–0:04 The heroine swings at high altitude between tall buildings. The city is far below. Her body forms a long aerodynamic arc, one arm holding tension through the line, legs trailing cleanly behind. The drone follows wide and slightly rolled, emphasizing height, speed, and scale. 0:04–0:06 At the swing’s forward rise, she releases the line and redirects toward a nearby glass-and-concrete building. She plants onto the wall and runs across it diagonally with 4 to 5 clear steps. Her feet hit the wall with visible force. Her jaw is set and focused. The drone stays close but wide enough to keep the city depth visible. 0:06–0:08 She pushes explosively off the wall, fires a new tether line, and swings again through a narrower corridor between tall buildings. The movement should feel faster and more controlled now. She threads cleanly through the urban gap and angles toward a rooftop landing zone ahead. 0:08–0:09.5 She releases the line and lands hard but controlled on a rooftop. Knees bend deeply to absorb impact. She rolls into a short forward recovery step, then rises immediately into a sprint across the rooftop surface. 0:09.5–0:12 One villain in a black suit steps in to stop her. Keep only this single enemy. The heroine engages him in a short, sharp rooftop fight. She avoids his first attack with a quick slip, grabs or redirects his arm, drives one fast body shot or elbow, then uses his off-balance momentum to throw or slam him down onto the rooftop. The fight must feel quick, practical, and decisive. Real impact reactions. No slow choreography. No extra enemies. 0:12–0:13.5 The villain is down and no longer a threat. The heroine steps past him and moves to the rooftop edge. Wind moves her hair and outfit. She looks outward over the city with intense adrenaline and triumph. 0:13.5–0:15 At the rooftop edge, she turns slightly toward the open skyline, lifts her chest, and shouts one powerful final line: “가자!” She immediately launches forward off the rooftop edge into another leap just as the clip ends. End on the feeling that the action is continuing beyond the cut. IMPORTANT RULES: - one continuous drone follow shot only - no cuts - no teleporting - no cloning - no multiple villains - only one black-suited villain - no giant web canopy - use only thin functional tether lines - no franchise logos - no copyrighted chest symbols - preserve the uploaded identity consistently - action must stay realistic and momentum-driven - rooftop fight must be short, sharp, and readable - final shout must be “가자!” NEGATIVE: no cartoon, no anime, no game-engine look, no fake CGI stiffness, no floating, no weightless hovering, no random disconnected acrobatics, no city-wide web canopy, no superhero logo, no copyrighted spider emblem, no extra enemies, no masked villain, no armored villain, no cloned villain, no empty city, no dark night setting, no rain, no slow motion, no blurred identity, no outfit drift, no face drift, no extra limbs, no broken anatomy, no unrealistic hand deformation, no collision with buildings during swings, no messy unreadable fight.

Sharon Riley

59,224 Aufrufe • vor 1 Monat

a contractor in Shenzhen priced a ¥12,470,900 hospital contract, about $1.7m, in one afternoon and beat firms carrying forty people he explained how he did it: the bid consultancy he used to pay took three days and ¥46,000 for the same envelope. he did this one alone, off one screen, at 11.4% margin, uploaded before the 17:00 cutoff 214 pages of tender documents read, 68 binding clauses pulled out, 9,485 building parts loaded, 14 places found where a duct and a beam sit in the same cubic metre, deepest one 38mm, all of them fixed, 3,318 lines of quantities priced and the package encrypted and uploaded before the 17:00 cutoff this is Graph Engineering: the job gets cut into small nodes, one narrow task each, wired so that one node's output is the next node's input, and any node is allowed to stop the whole run. it turns a model that answers you into a machine that finishes the job: - give every node one job and one output. a node doing two things fails at both and you cannot tell which one broke - put the cheapest rejection first. his qualification node reads clause 7.4, foreign-owned firms barred, and ends the run four seconds in, before anything expensive touches the model - what moves between nodes is a file. the model travels as a model, the quantities as a table, the price as a number - build exactly one loop: the checker finds 14 collisions, the fixer drops the duct 550mm, the checker runs again, and nothing moves on until the count is zero - cap that loop, or a graph will grind on three impossible clashes until the deadline passes - keep one node whose only job is to say no, and give it authority over everything above it - log each node's output on its own, because when the price comes out wrong you need to know which node believed the wrong thing - run the expensive nodes last, always the catch is that a graph is an extremely confident machine: point it at an outdated rate book and it prices an entire hospital off it without a single node noticing, because no node is asked to doubt the input, only to process it so the nodes that earn their keep are the ones that reject, and almost nobody builds those first bookmark this, the full build with all nine nodes and what each one hands to the next is written out in the article ↓
0:16

a contractor in Shenzhen priced a ¥12,470,900 hospital contract, about $1.7m, in one afternoon and beat firms carrying forty people he explained how he did it: the bid consultancy he used to pay took three days and ¥46,000 for the same envelope. he did this one alone, off one screen, at 11.4% margin, uploaded before the 17:00 cutoff 214 pages of tender documents read, 68 binding clauses pulled out, 9,485 building parts loaded, 14 places found where a duct and a beam sit in the same cubic metre, deepest one 38mm, all of them fixed, 3,318 lines of quantities priced and the package encrypted and uploaded before the 17:00 cutoff this is Graph Engineering: the job gets cut into small nodes, one narrow task each, wired so that one node's output is the next node's input, and any node is allowed to stop the whole run. it turns a model that answers you into a machine that finishes the job: - give every node one job and one output. a node doing two things fails at both and you cannot tell which one broke - put the cheapest rejection first. his qualification node reads clause 7.4, foreign-owned firms barred, and ends the run four seconds in, before anything expensive touches the model - what moves between nodes is a file. the model travels as a model, the quantities as a table, the price as a number - build exactly one loop: the checker finds 14 collisions, the fixer drops the duct 550mm, the checker runs again, and nothing moves on until the count is zero - cap that loop, or a graph will grind on three impossible clashes until the deadline passes - keep one node whose only job is to say no, and give it authority over everything above it - log each node's output on its own, because when the price comes out wrong you need to know which node believed the wrong thing - run the expensive nodes last, always the catch is that a graph is an extremely confident machine: point it at an outdated rate book and it prices an entire hospital off it without a single node noticing, because no node is asked to doubt the input, only to process it so the nodes that earn their keep are the ones that reject, and almost nobody builds those first bookmark this, the full build with all nine nodes and what each one hands to the next is written out in the article ↓

Argona

38,189 Aufrufe • vor 1 Monat

Sadie Sink. Nano Banana Pro → Grok Imagine Prompt: { "aspect_ratio": "4:5", "prompt": { "subject": { "description": "An adult woman Sadie Sink. Fair skin with a warm glow and visible light freckles across the cheeks and chest. Soft glam makeup with defined brows, subtle eyeliner/mascara, and a natural rosy-nude lip. Strawberry-auburn hair pulled into a high ponytail with a few loose face-framing strands. She wears large silver hoop earrings and oversized black rectangular eyeglasses. Expression is playful and confident, giving a flirty side-eye toward the camera.", "clothing": "A fitted deep-green short-sleeve cropped top with a front zipper that’s partially unzipped, ribbed knit texture. A red/orange plaid mini skirt with a structured fit and visible plaid pattern. Layered silver necklaces (one sits like a choker chain). Long pale manicure. She’s holding a large white starbucks coffee cup.", "pose": "She is reclined across the passenger seat of a car, leaning back into the seat with one arm raised behind her head, elbow bent. Her torso angles toward the camera, hips slightly turned. The other hand holds the coffee cup near her lap. Medium shot framed from head to mid-thigh, camera positioned close from the driver-side angle for an intimate in-car perspective." }, "environment": { "location": "Inside a car parked in an indoor parking garage.", "details": "Black leather car seats and door panel, visible stitching, dark interior trim. Through the window, a parking garage corridor is visible with brightly colored wall panels (yellow, teal, and red) and a white door in the background.", "background": "Clean indoor garage setting with geometric color blocks and soft depth; background slightly out of focus to keep attention on the subject." }, "lighting_and_quality": { "lighting": "Direct on-camera flash creating crisp highlights on skin, hair, and the ribbed green fabric; strong subject separation from the darker car interior with mild shadow falloff.", "resolution": "4K HD quality, highly detailed textures on freckles, hair strands, ribbed knit fabric, plaid skirt weave, leather seat grain, eyeglass reflections, and cup surface.", "style": "Realistic candid smartphone photo taken by someone else (not a selfie), reference-faithful composition and pose, sharp subject focus with slightly softer background depth, no text, no watermark, no extra people." } } }
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Sadie Sink. Nano Banana Pro → Grok Imagine Prompt: { "aspect_ratio": "4:5", "prompt": { "subject": { "description": "An adult woman Sadie Sink. Fair skin with a warm glow and visible light freckles across the cheeks and chest. Soft glam makeup with defined brows, subtle eyeliner/mascara, and a natural rosy-nude lip. Strawberry-auburn hair pulled into a high ponytail with a few loose face-framing strands. She wears large silver hoop earrings and oversized black rectangular eyeglasses. Expression is playful and confident, giving a flirty side-eye toward the camera.", "clothing": "A fitted deep-green short-sleeve cropped top with a front zipper that’s partially unzipped, ribbed knit texture. A red/orange plaid mini skirt with a structured fit and visible plaid pattern. Layered silver necklaces (one sits like a choker chain). Long pale manicure. She’s holding a large white starbucks coffee cup.", "pose": "She is reclined across the passenger seat of a car, leaning back into the seat with one arm raised behind her head, elbow bent. Her torso angles toward the camera, hips slightly turned. The other hand holds the coffee cup near her lap. Medium shot framed from head to mid-thigh, camera positioned close from the driver-side angle for an intimate in-car perspective." }, "environment": { "location": "Inside a car parked in an indoor parking garage.", "details": "Black leather car seats and door panel, visible stitching, dark interior trim. Through the window, a parking garage corridor is visible with brightly colored wall panels (yellow, teal, and red) and a white door in the background.", "background": "Clean indoor garage setting with geometric color blocks and soft depth; background slightly out of focus to keep attention on the subject." }, "lighting_and_quality": { "lighting": "Direct on-camera flash creating crisp highlights on skin, hair, and the ribbed green fabric; strong subject separation from the darker car interior with mild shadow falloff.", "resolution": "4K HD quality, highly detailed textures on freckles, hair strands, ribbed knit fabric, plaid skirt weave, leather seat grain, eyeglass reflections, and cup surface.", "style": "Realistic candid smartphone photo taken by someone else (not a selfie), reference-faithful composition and pose, sharp subject focus with slightly softer background depth, no text, no watermark, no extra people." } } }

HighkeySynth

22,098 Aufrufe • vor 6 Monaten

Beauty ads just changed forever. Free Claude Opus 4.8 + GPT Image 2 + Seedance 2.0 workflow to spin up 100s of video ads. No studio, no model, no macro lens, no shoot day. Here's what nobody in beauty marketing wants to say out loud. That glossy lip shot. The droplet hitting the surface in slow motion. The whip-pan into the next scene. The crystalline product splash. All the stuff that used to need a real set, a real camera op, and a full shoot day. You can generate every frame of it from a text prompt now, and stitch it into a finished ad before your coffee goes cold. The workflow is almost stupidly simple: → Tell Claude Opus 4.8 the beauty shot you want (dewy skin macro, gloss-on-lips contact, ripple transition, the works) → Claude turns it into a shot-by-shot storyboard plus a prompt for every frame → GPT Image 2 generates the photoreal stills, frame by frame → Seedance 2.0 animates each one into a clip with that buttery slow-mo glide → You drop the clips into HeyOz and assemble the full ad in one place The real unlock is volume. This isn't one hero video. Once the workflow is dialed, you spin up hundreds of variations. Different shades, different models, different hooks, different transitions. The exact creative volume Meta rewards, minus the production cost that used to make it impossible. Old way: one shoot, one look, $10k+, weeks of waiting. New way: a hundred angles, any look, a few dollars each, same afternoon. I wrote up the entire workflow. The Claude storyboard prompt, the GPT Image 2 frame prompts, the Seedance motion settings, the full assembly flow. Completely free, no email gate. Want it? Comment "GLOSS" and I'll send it straight over. (make sure you're following so it can actually reach you)
0:18

Beauty ads just changed forever. Free Claude Opus 4.8 + GPT Image 2 + Seedance 2.0 workflow to spin up 100s of video ads. No studio, no model, no macro lens, no shoot day. Here's what nobody in beauty marketing wants to say out loud. That glossy lip shot. The droplet hitting the surface in slow motion. The whip-pan into the next scene. The crystalline product splash. All the stuff that used to need a real set, a real camera op, and a full shoot day. You can generate every frame of it from a text prompt now, and stitch it into a finished ad before your coffee goes cold. The workflow is almost stupidly simple: → Tell Claude Opus 4.8 the beauty shot you want (dewy skin macro, gloss-on-lips contact, ripple transition, the works) → Claude turns it into a shot-by-shot storyboard plus a prompt for every frame → GPT Image 2 generates the photoreal stills, frame by frame → Seedance 2.0 animates each one into a clip with that buttery slow-mo glide → You drop the clips into HeyOz and assemble the full ad in one place The real unlock is volume. This isn't one hero video. Once the workflow is dialed, you spin up hundreds of variations. Different shades, different models, different hooks, different transitions. The exact creative volume Meta rewards, minus the production cost that used to make it impossible. Old way: one shoot, one look, $10k+, weeks of waiting. New way: a hundred angles, any look, a few dollars each, same afternoon. I wrote up the entire workflow. The Claude storyboard prompt, the GPT Image 2 frame prompts, the Seedance motion settings, the full assembly flow. Completely free, no email gate. Want it? Comment "GLOSS" and I'll send it straight over. (make sure you're following so it can actually reach you)

Ahad Shams

11,259 Aufrufe • vor 2 Monaten

i just open sourced the workflow behind $2M AI video productions... i built 7 skills that run the pipeline end to end, built for Seedance 2.5 and they work in Claude Code, Codex, Hermes or any harness (works best with 1080p using Higgsfield CLI) here's how to use them, in order: /setup writes which image and video models you run into your project, once, so every skill reads the same stack /studio-init scaffolds the whole studio as a file tree from one question, the project name /film-breakdown walks your script scene by scene and writes a 22-field card for every shot /reference-board locks your references into a visual bible, a caption on every image and a ban list for the rest /asset-passport writes the exhaustive descriptor every later prompt will quote word for word /stress-test combat-tests each asset and flips it to locked only at 10 out of 10 repeatability /shot-prompt refuses to run until everything in frame is locked, then writes the 15-block prompt and logs every attempt get access to the skills and full breakdown of the pipeline in the article below:
0:12

i just open sourced the workflow behind $2M AI video productions... i built 7 skills that run the pipeline end to end, built for Seedance 2.5 and they work in Claude Code, Codex, Hermes or any harness (works best with 1080p using Higgsfield CLI) here's how to use them, in order: /setup writes which image and video models you run into your project, once, so every skill reads the same stack /studio-init scaffolds the whole studio as a file tree from one question, the project name /film-breakdown walks your script scene by scene and writes a 22-field card for every shot /reference-board locks your references into a visual bible, a caption on every image and a ban list for the rest /asset-passport writes the exhaustive descriptor every later prompt will quote word for word /stress-test combat-tests each asset and flips it to locked only at 10 out of 10 repeatability /shot-prompt refuses to run until everything in frame is locked, then writes the 15-block prompt and logs every attempt get access to the skills and full breakdown of the pipeline in the article below:

Machina

59,905 Aufrufe • vor 20 Tagen

Contact sheet prompting is the hottest AI video technique right now 🤯 If you've seen this technique blowing up, here's why it works: You feed AI one image, and it generates a grid of consistent shots—same face, same outfit, different angles and poses. Instant storyboarding. Full creative control. No reshoots. But doing it manually is brutal: → Write the prompt from scratch → Generate the contact sheet → Crop each frame by hand → Feed frames into a video model one at a time → Repeat for every single product That's hours of work per campaign. This n8n automation handles everything: → Upload a character image + product image → AI analyzes both and writes the contact sheet prompt → Nano Banana Pro generates a 6-frame grid → System extracts each frame automatically → Kling 2.5 creates smooth transitions between frames → 5 video clips land in Airtable ready to use No manual cropping. No frame-by-frame prompting. No tedious busywork. What you get in Airtable: - AI-generated creative prompt - Hero image (model + product) - Full 6-frame contact sheet - 5 cinematic video clips - Approval gates before each step All inside n8n + Airtable. Contact sheet prompting on complete autopilot. I recorded a 20-minute Loom showing exactly how I built this. Want the walkthrough + the full n8n workflow + Airtable base? > Like this post > Comment "CONTACT" And I'll send it over (must be following so I can DM)
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Contact sheet prompting is the hottest AI video technique right now 🤯 If you've seen this technique blowing up, here's why it works: You feed AI one image, and it generates a grid of consistent shots—same face, same outfit, different angles and poses. Instant storyboarding. Full creative control. No reshoots. But doing it manually is brutal: → Write the prompt from scratch → Generate the contact sheet → Crop each frame by hand → Feed frames into a video model one at a time → Repeat for every single product That's hours of work per campaign. This n8n automation handles everything: → Upload a character image + product image → AI analyzes both and writes the contact sheet prompt → Nano Banana Pro generates a 6-frame grid → System extracts each frame automatically → Kling 2.5 creates smooth transitions between frames → 5 video clips land in Airtable ready to use No manual cropping. No frame-by-frame prompting. No tedious busywork. What you get in Airtable: - AI-generated creative prompt - Hero image (model + product) - Full 6-frame contact sheet - 5 cinematic video clips - Approval gates before each step All inside n8n + Airtable. Contact sheet prompting on complete autopilot. I recorded a 20-minute Loom showing exactly how I built this. Want the walkthrough + the full n8n workflow + Airtable base? > Like this post > Comment "CONTACT" And I'll send it over (must be following so I can DM)

Mike Futia

24,589 Aufrufe • vor 7 Monaten

john wick seedance text to video prompt： [STYLE / CINEMATIC SETUP] A 10.5-second, 16:9 photorealistic AAA action-game cinematic rendered at real-time speed with no slow motion. The setting is a cramped, cluttered late-night Asian restaurant connected to a rain-soaked street. Cyan-green fluorescent light, red neon and warm practical lamps create a high-contrast mixed-light environment, with reflections across wet floors and pavement. Shoot with a 35mm spherical lens, shallow-to-moderate depth of field and cinematic motion blur appropriate to the actual speed of movement. Use close shoulder-mounted and handheld coverage, connecting seven short close-combat shots with fast hard cuts. The camera instinctively pans, retreats or drops with each block, takedown and collision while keeping the action and contact points readable. No dialogue, no subtitles and no BGM. Generate only synchronized rain, appliance hum, urgent footsteps, fabric movement, body impacts, gunshots, metal contact and breaking glass. [IMAGE REFERENCES] No external still-image reference. Follow the written character and environment descriptions consistently. If the platform supports reference video, use the supplied video only as a reference for editing rhythm, camera distance, action direction and lighting atmosphere, not for copying a specific actor’s identity. The protagonist remains the same lean, agile man in his early forties throughout the sequence: neck-length black hair swept back, a short beard, a tired but focused face, a slightly wrinkled black suit, white shirt and narrow black tie, all carrying faint rain and wear marks. Preserve his face, hairstyle, body proportions, clothing and screen direction across all seven shots. Keep every opponent visually distinct: a man in a blue work uniform, a bald man in a navy jacket, a heavy man in a black jacket, a bald counter attacker, a red-headband attacker, a red-jacketed armed attacker and a heavy man in a dark green coat outside. [TIMELINE SECOND BY SECOND] 0–1.9s: [Shoulder-height medium close-up, tight lateral handheld tracking, real-time speed] The protagonist stands on screen left, pinning the blue-uniformed attacker against a glass refrigerator with his left forearm and palm. He delivers two compact, weighted elbow and palm-heel strikes. Each impact drives the attacker’s head into the refrigerator door, loosening his white headband and leaving a small blood trace on the glass; the attacker finishes sliding down the door while the protagonist remains standing. 1.9–4.3s: [Medium shot transitioning into a high-angle overhead, shoulder-mounted drop, real-time speed] Hard cut near the restaurant’s rear entrance. The bald attacker in a navy jacket locks the protagonist from behind. The protagonist lowers his center of gravity, traps the attacker’s arm and rotates his hips, throwing him heavily over the shoulder onto the wet floor. The camera drops with them into an overhead view. Kneeling across the attacker’s torso, the protagonist draws a compact black pistol and fires one downward shot; recoil travels through his wrist and the attacker jolts once before becoming still. 4.3–5.9s: [Tight medium shot, lateral handheld follow, real-time speed] Hard cut with both men already upright. A heavy attacker in a black jacket swings from screen right. The protagonist slips outside the punch, allowing it to pass close to his face, circles behind the attacker and locks his shoulder and neck off balance. He presses the pistol close to the side of the attacker’s head and fires. The muzzle flash briefly illuminates both faces; the attacker’s head and shoulders snap backward and his body begins to collapse. 5.9–7.9s: [Counter-height medium close-up, subtle handheld push-in, real-time speed] Hard cut to the restaurant counter. Another bald attacker bends forward and clamps around the protagonist’s waist. The protagonist pins the attacker’s head and neck under his left arm while grabbing a short, rigid pointed utensil from the counter. He drives two compact downward thrusts into the upper shoulder and side of the neck. Each contact bends the attacker’s knees further; a restrained amount of blood marks the shirt and counter edge before the attacker hangs helplessly beneath the protagonist’s controlling arm. 7.9–9.0s: [Two-person medium close-up, fast pan with a short retreat, real-time speed] Hard cut as the red-headband attacker rushes into close range. He throws a wide hook from screen right. The protagonist raises his forearm to block, catches the wrist and pulls it outward, then drives a palm heel and forearm into the attacker’s face. The camera retreats with the impact as the attacker loses his balance and staggers toward the rear right of the frame. 9.0–9.9s: [Low-angle wide shot, slight arc around the action, real-time speed] Hard cut to a wider section of the restaurant. The red-jacketed armed attacker advances from screen left. Holding a long black firearm with both hands, the protagonist uses it as a blunt weapon and swings horizontally from right to left. The weapon strikes the attacker’s upper chest and shoulder, rotating his torso, crossing his feet and sending him off balance toward screen left. 9.9–10.5s: [Exterior rainy-street medium shot, fast parallel tracking, real-time speed] Hard cut outside the restaurant. The protagonist already controls a heavy attacker in a dark green coat and uses his forward momentum to drive the man’s head and upper body into the side window of a parked black station wagon. The glass bursts inward at the contact point, scattering both large and fine fragments. The attacker folds through the broken window while the protagonist regains stable footing beside the car, ending with glass fragments still falling. [STYLE & QUALITY BOOSTERS] Maintain the protagonist’s face, black suit, white shirt, tie, hairstyle and body proportions through every hard cut. The pistol, pointed utensil, injuries and blood marks must appear only in their designated shots and must never morph or change ownership. Throws, recoil, strike reactions, loss of balance and window breakage must show believable weight, inertia and precise contact. Apply motion blur only to rapidly moving arms, weapons, glass fragments and camera-relative backgrounds. No sudden face or costume changes; no extra fingers, fused limbs or inverted joints; no morphing weapons, utensils or vehicles; no foot sliding or rubber-like collision reactions; no blood, bullet damage or glass fragments appearing before physical contact.
0:11

john wick seedance text to video prompt： [STYLE / CINEMATIC SETUP] A 10.5-second, 16:9 photorealistic AAA action-game cinematic rendered at real-time speed with no slow motion. The setting is a cramped, cluttered late-night Asian restaurant connected to a rain-soaked street. Cyan-green fluorescent light, red neon and warm practical lamps create a high-contrast mixed-light environment, with reflections across wet floors and pavement. Shoot with a 35mm spherical lens, shallow-to-moderate depth of field and cinematic motion blur appropriate to the actual speed of movement. Use close shoulder-mounted and handheld coverage, connecting seven short close-combat shots with fast hard cuts. The camera instinctively pans, retreats or drops with each block, takedown and collision while keeping the action and contact points readable. No dialogue, no subtitles and no BGM. Generate only synchronized rain, appliance hum, urgent footsteps, fabric movement, body impacts, gunshots, metal contact and breaking glass. [IMAGE REFERENCES] No external still-image reference. Follow the written character and environment descriptions consistently. If the platform supports reference video, use the supplied video only as a reference for editing rhythm, camera distance, action direction and lighting atmosphere, not for copying a specific actor’s identity. The protagonist remains the same lean, agile man in his early forties throughout the sequence: neck-length black hair swept back, a short beard, a tired but focused face, a slightly wrinkled black suit, white shirt and narrow black tie, all carrying faint rain and wear marks. Preserve his face, hairstyle, body proportions, clothing and screen direction across all seven shots. Keep every opponent visually distinct: a man in a blue work uniform, a bald man in a navy jacket, a heavy man in a black jacket, a bald counter attacker, a red-headband attacker, a red-jacketed armed attacker and a heavy man in a dark green coat outside. [TIMELINE SECOND BY SECOND] 0–1.9s: [Shoulder-height medium close-up, tight lateral handheld tracking, real-time speed] The protagonist stands on screen left, pinning the blue-uniformed attacker against a glass refrigerator with his left forearm and palm. He delivers two compact, weighted elbow and palm-heel strikes. Each impact drives the attacker’s head into the refrigerator door, loosening his white headband and leaving a small blood trace on the glass; the attacker finishes sliding down the door while the protagonist remains standing. 1.9–4.3s: [Medium shot transitioning into a high-angle overhead, shoulder-mounted drop, real-time speed] Hard cut near the restaurant’s rear entrance. The bald attacker in a navy jacket locks the protagonist from behind. The protagonist lowers his center of gravity, traps the attacker’s arm and rotates his hips, throwing him heavily over the shoulder onto the wet floor. The camera drops with them into an overhead view. Kneeling across the attacker’s torso, the protagonist draws a compact black pistol and fires one downward shot; recoil travels through his wrist and the attacker jolts once before becoming still. 4.3–5.9s: [Tight medium shot, lateral handheld follow, real-time speed] Hard cut with both men already upright. A heavy attacker in a black jacket swings from screen right. The protagonist slips outside the punch, allowing it to pass close to his face, circles behind the attacker and locks his shoulder and neck off balance. He presses the pistol close to the side of the attacker’s head and fires. The muzzle flash briefly illuminates both faces; the attacker’s head and shoulders snap backward and his body begins to collapse. 5.9–7.9s: [Counter-height medium close-up, subtle handheld push-in, real-time speed] Hard cut to the restaurant counter. Another bald attacker bends forward and clamps around the protagonist’s waist. The protagonist pins the attacker’s head and neck under his left arm while grabbing a short, rigid pointed utensil from the counter. He drives two compact downward thrusts into the upper shoulder and side of the neck. Each contact bends the attacker’s knees further; a restrained amount of blood marks the shirt and counter edge before the attacker hangs helplessly beneath the protagonist’s controlling arm. 7.9–9.0s: [Two-person medium close-up, fast pan with a short retreat, real-time speed] Hard cut as the red-headband attacker rushes into close range. He throws a wide hook from screen right. The protagonist raises his forearm to block, catches the wrist and pulls it outward, then drives a palm heel and forearm into the attacker’s face. The camera retreats with the impact as the attacker loses his balance and staggers toward the rear right of the frame. 9.0–9.9s: [Low-angle wide shot, slight arc around the action, real-time speed] Hard cut to a wider section of the restaurant. The red-jacketed armed attacker advances from screen left. Holding a long black firearm with both hands, the protagonist uses it as a blunt weapon and swings horizontally from right to left. The weapon strikes the attacker’s upper chest and shoulder, rotating his torso, crossing his feet and sending him off balance toward screen left. 9.9–10.5s: [Exterior rainy-street medium shot, fast parallel tracking, real-time speed] Hard cut outside the restaurant. The protagonist already controls a heavy attacker in a dark green coat and uses his forward momentum to drive the man’s head and upper body into the side window of a parked black station wagon. The glass bursts inward at the contact point, scattering both large and fine fragments. The attacker folds through the broken window while the protagonist regains stable footing beside the car, ending with glass fragments still falling. [STYLE & QUALITY BOOSTERS] Maintain the protagonist’s face, black suit, white shirt, tie, hairstyle and body proportions through every hard cut. The pistol, pointed utensil, injuries and blood marks must appear only in their designated shots and must never morph or change ownership. Throws, recoil, strike reactions, loss of balance and window breakage must show believable weight, inertia and precise contact. Apply motion blur only to rapidly moving arms, weapons, glass fragments and camera-relative backgrounds. No sudden face or costume changes; no extra fingers, fused limbs or inverted joints; no morphing weapons, utensils or vehicles; no foot sliding or rubber-like collision reactions; no blood, bullet damage or glass fragments appearing before physical contact.

underwood

12,588 Aufrufe • vor 27 Tagen

I just dropped myself into a Taylor Swift-style music video without writing a single prompt, timeline, or storyboard. I uploaded one photo and the song. That's it. Atlabs AI took over from there: • Built the character sheet • Planned the scenes • Generated the prompts • Synced every cut to the beat • Delivered a finished edit Most AI video tools promise automation, but the tradeoff is usually creative control. This was the opposite. The agents handled the production work while I focused on direction. Every scene, transition, framing choice, and creative decision stayed in my hands. When the edit was ready, I could jump in, swap shots, rework sequences, change the mood, and fine-tune the story. It felt less like using a tool and more like working with an AI production crew. We're moving beyond prompting. The next wave is directing autonomous creative workflows that understand the music, build the narrative, and still leave the final call to you. Character: ChatGPT Image Video: Seedance This is the most fun I've had making a music video in a long time.
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I just dropped myself into a Taylor Swift-style music video without writing a single prompt, timeline, or storyboard. I uploaded one photo and the song. That's it. Atlabs AI took over from there: • Built the character sheet • Planned the scenes • Generated the prompts • Synced every cut to the beat • Delivered a finished edit Most AI video tools promise automation, but the tradeoff is usually creative control. This was the opposite. The agents handled the production work while I focused on direction. Every scene, transition, framing choice, and creative decision stayed in my hands. When the edit was ready, I could jump in, swap shots, rework sequences, change the mood, and fine-tune the story. It felt less like using a tool and more like working with an AI production crew. We're moving beyond prompting. The next wave is directing autonomous creative workflows that understand the music, build the narrative, and still leave the final call to you. Character: ChatGPT Image Video: Seedance This is the most fun I've had making a music video in a long time.

Sharon Riley

36,280 Aufrufe • vor 2 Monaten