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Demonstrating 3D Motion Generation in Alchemist AI Alchemist AI’s 3D generation capabilities now extend to motion comprehension, delivering realistic, physics-driven animations for game design, simulations, and virtual environments. Dynamic Movement Frameworks • Humans: Models support essential animations such as walking, jumping, and object interaction. Inverse kinematics ensures natural limb... motion for actions like picking up objects or interacting with the environment. • Animals (Horses): Animations incorporate defined speed parameters and stride length calculations, creating fluid and realistic movement patterns. Physics-Based Rigging Weight Mapping: Adds realistic mass and balance to characters, especially during complex actions like jumping, running, or carrying objects. Alchemist AI continuously evolves and improves with every prompt it processes, adapting and learning to deliver increasingly refined results.show more

ALCHEMIST AI 🔮

42,433 subscribers

20,046 Aufrufe • vor 1 Jahr •via X (Twitter)

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10 Kommentare

Profilbild von ALCHEMIST AI 🔮

ALCHEMIST AI 🔮vor 1 Jahr

Built By: @3iside Download App:

Profilbild von Moescape AI

Moescape AIvor 1 Jahr

Sign up & create wholesome anime art on Moescape AI now!

Profilbild von Syrate

Syratevor 1 Jahr

the fact that all of this is being done simply with prompts and zero coding is insane

Profilbild von Rex

Rexvor 1 Jahr

$ALCH is always building despite price action. Better than most AI coins, yet it is undervalued. We will reach billions in due time.

Profilbild von @JAX7

@JAX7vor 1 Jahr

wen moon?

Profilbild von Ciph Xyz

Ciph Xyzvor 1 Jahr

Nice! Looking forward to try the new physics features! I made this before the update

Profilbild von Cody Apple 🪨

Cody Apple 🪨vor 1 Jahr

I am so wrong $ALCH is a tool not gaming specific $ALCH is da best brand

Profilbild von Vortecia

Vorteciavor 1 Jahr

Any plans for a UI/UX overhaul soon?

Profilbild von Shaikh Yasin

Shaikh Yasinvor 1 Jahr

I got liquideted worst coin scam

Profilbild von Z

Zvor 1 Jahr

It’s kinda insane how fast alch evolving $ALCH

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Prompt: Create a 43-second cinematic, photorealistic action-comedy sequence inside an old, cramped, slightly abandoned apartment/bathroom with realistic worn walls, tiled surfaces, warm practical lighting, and natural shadows. A young adult man in a light gray T-shirt is standing in front of a bathroom mirror. Suddenly, another man wearing a black-and-white striped shirt appears and aggressively grabs him. The two struggle physically through the small bathroom, with realistic body movement, pushing, pulling, stumbling and fighting. The action continues dynamically through the bathroom. One character crashes against the wall and breaks through a damaged section, creating a large opening into the adjacent room. Dust and small debris fall naturally as the wall breaks. Continue with a fast-paced chase through the apartment. The gray-shirted man runs toward a window while the striped-shirted man follows. Use handheld camera movement, realistic motion blur, quick tracking shots and dramatic close-ups to make the sequence feel like a real action movie. The characters then escape outside into an old brick courtyard/alley. One character climbs onto a rusty metal fire escape while the other follows from below. Show realistic physics, footsteps, clothing movement and environmental interaction. Final scene: transition to a large outdoor dumpster filled with cardboard and garbage. The gray-shirted man is inside the dumpster, looking exhausted and confused, holding a small green plush toy. He slowly looks around as the camera pushes in toward his face. End on a slightly comedic reaction shot. Visual style: ultra-photorealistic, cinematic action film, realistic human anatomy, natural skin texture, detailed environments, practical lighting, subtle film grain, realistic physics, believable facial expressions. Camera: dynamic handheld cinematography, wide establishing shots, medium tracking shots, close-ups during the struggle, smooth camera transitions, natural depth of field, 35mm/50mm cinematic lenses. Motion: realistic human movement, accurate weight and momentum, natural collisions, realistic debris and dust simulation, no slow-motion unless used very briefly for dramatic impact. Important: Maintain consistent character appearance, clothing, hairstyle and body proportions throughout the entire video. No random character changes, no extra limbs, no distorted faces, no cartoon appearance, no text, no subtitles, no watermark.

Prompt: Create a 43-second cinematic, photorealistic action-comedy sequence inside an old, cramped, slightly abandoned apartment/bathroom with realistic worn walls, tiled surfaces, warm practical lighting, and natural shadows. A young adult man in a light gray T-shirt is standing in front of a bathroom mirror. Suddenly, another man wearing a black-and-white striped shirt appears and aggressively grabs him. The two struggle physically through the small bathroom, with realistic body movement, pushing, pulling, stumbling and fighting. The action continues dynamically through the bathroom. One character crashes against the wall and breaks through a damaged section, creating a large opening into the adjacent room. Dust and small debris fall naturally as the wall breaks. Continue with a fast-paced chase through the apartment. The gray-shirted man runs toward a window while the striped-shirted man follows. Use handheld camera movement, realistic motion blur, quick tracking shots and dramatic close-ups to make the sequence feel like a real action movie. The characters then escape outside into an old brick courtyard/alley. One character climbs onto a rusty metal fire escape while the other follows from below. Show realistic physics, footsteps, clothing movement and environmental interaction. Final scene: transition to a large outdoor dumpster filled with cardboard and garbage. The gray-shirted man is inside the dumpster, looking exhausted and confused, holding a small green plush toy. He slowly looks around as the camera pushes in toward his face. End on a slightly comedic reaction shot. Visual style: ultra-photorealistic, cinematic action film, realistic human anatomy, natural skin texture, detailed environments, practical lighting, subtle film grain, realistic physics, believable facial expressions. Camera: dynamic handheld cinematography, wide establishing shots, medium tracking shots, close-ups during the struggle, smooth camera transitions, natural depth of field, 35mm/50mm cinematic lenses. Motion: realistic human movement, accurate weight and momentum, natural collisions, realistic debris and dust simulation, no slow-motion unless used very briefly for dramatic impact. Important: Maintain consistent character appearance, clothing, hairstyle and body proportions throughout the entire video. No random character changes, no extra limbs, no distorted faces, no cartoon appearance, no text, no subtitles, no watermark.

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"#AI will never create clean meshes" AI 👇 This is the new #AI model from NVIDIA called Meshtron (jeez what a name 😅). It generates meshes of complex 3D objects closely resembling those created by professional artists. It opens the door to a more realistic generation of detailed 3D assets for animation, gaming, and virtual environments. The current version accepts the following control inputs: - Point cloud: Determines the shape of the output mesh. - Face count: Determines the density of the output mesh. - Quad ratio: Switches between quad and triangle tessellation. - Creativity: Can be adjusted to generate extra details in the model. Meshtron can either serve as a stand-alone remesher to improve the quality of existing models, or be used in tandem with a text-to-3D or image-to-3D model to generate artist-grade meshes from scratch.

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🌐 New website is now live! First up is the light mode, with dark mode coming soon. We're thrilled about what's next— ready to scream for these upcoming updates? 🌀 Brand New Roadmap (some product timelines may be adjusted based on development progress) 🌀 Kingnet AI V2 Official Release – A completely revamped dApp experience! Next week, we’ll officially open access to the Animation Generator and Agent, making interactions smarter and simpler than the first-gen version 🌀 Public Docs & GitHub Code Open-Source 🌀 Official Deployment on Solana & BNB Chain – Users will be able to pay on-chain to generate custom assets and export them (FBX format for direct download and use). TON integration will follow. 🌀$KNET’s First Utility Feature As always, we’ve included a surprise at the end of our video, showcasing the full workflow of AI text-to-3D model to in-game motion model: 1️⃣ Enter the Agent virtual assistant, use text prompts to generate a 3D character motion model. 2️⃣ The Agent generates a 3D base model, automatically bakes and saves textures. 3️⃣ Auto-rigging, joint adjustments, and natural motion generation. 4️⃣ Users can pay to download the FBX file with animations. 5️⃣ The file can be directly imported into Unity or Unreal Engine, with options to import animations, set animation cuts & loops—ready for in-game use! Continuous Delivery.

Kingnet AI

31,023 Aufrufe • vor 1 Jahr

Generated with seedance 2 on PixVerse Prompt :- Create a 21-second vertical 9:16 cinematic stop-motion animation. A tiny humanoid figure made entirely from naturally shaped smooth beach stones comes to life in a shallow tidal pool on a rocky seashore. Each body part is constructed from individual stones—large oval stone as the head, stacked rounded stones for the torso, smaller stones forming arms and legs. The scene is filmed through a slightly out-of-focus chain-link fence, creating a natural foreground frame. Behind the character is a calm shoreline, shallow seawater, barnacle-covered rocks, seaweed, and a softly blurred forest under an overcast sky. Photorealistic textures, natural muted colors, shallow depth of field, realistic water reflections. Animation: The stone figure slowly balances itself and begins moving like a playful little human. It shifts its weight, raises one leg, bends its knees, swings its stone arms, and performs a quirky little dance while carefully maintaining balance on the wet surface. Tiny ripples form beneath every footstep, and its reflection moves naturally in the water. The movements should feel hand-crafted stop-motion, slightly imperfect but believable, with realistic stone physics and weight. Toward the final seconds, the figure loses its balance, stumbles, and collapses naturally, with the individual stones separating and tumbling onto the shallow wet ground. The character completely disassembles into ordinary stones. End with the camera holding on the scattered stones and their reflections. Camera: locked-off smartphone-style vertical composition, subtle natural camera movement, medium-full shot, low angle close to water level, strong foreground bokeh from the fence, cinematic depth of field. Lighting: soft diffused daylight, overcast coastal atmosphere, realistic reflections and wet stone highlights. Style: ultra-realistic live-action environment + whimsical photorealistic stone stop-motion character, tactile stone textures, physically believable movement, cinematic macro photography, no CGI-looking surfaces, no text, no humans. Negative prompt: cartoon, plastic-looking stones, exaggerated facial features, smooth CGI character, floating objects, unrealistic physics, extra limbs, changing environment, camera cuts, text, watermark, oversaturated colors.

Generated with seedance 2 on PixVerse Prompt :- Create a 21-second vertical 9:16 cinematic stop-motion animation. A tiny humanoid figure made entirely from naturally shaped smooth beach stones comes to life in a shallow tidal pool on a rocky seashore. Each body part is constructed from individual stones—large oval stone as the head, stacked rounded stones for the torso, smaller stones forming arms and legs. The scene is filmed through a slightly out-of-focus chain-link fence, creating a natural foreground frame. Behind the character is a calm shoreline, shallow seawater, barnacle-covered rocks, seaweed, and a softly blurred forest under an overcast sky. Photorealistic textures, natural muted colors, shallow depth of field, realistic water reflections. Animation: The stone figure slowly balances itself and begins moving like a playful little human. It shifts its weight, raises one leg, bends its knees, swings its stone arms, and performs a quirky little dance while carefully maintaining balance on the wet surface. Tiny ripples form beneath every footstep, and its reflection moves naturally in the water. The movements should feel hand-crafted stop-motion, slightly imperfect but believable, with realistic stone physics and weight. Toward the final seconds, the figure loses its balance, stumbles, and collapses naturally, with the individual stones separating and tumbling onto the shallow wet ground. The character completely disassembles into ordinary stones. End with the camera holding on the scattered stones and their reflections. Camera: locked-off smartphone-style vertical composition, subtle natural camera movement, medium-full shot, low angle close to water level, strong foreground bokeh from the fence, cinematic depth of field. Lighting: soft diffused daylight, overcast coastal atmosphere, realistic reflections and wet stone highlights. Style: ultra-realistic live-action environment + whimsical photorealistic stone stop-motion character, tactile stone textures, physically believable movement, cinematic macro photography, no CGI-looking surfaces, no text, no humans. Negative prompt: cartoon, plastic-looking stones, exaggerated facial features, smooth CGI character, floating objects, unrealistic physics, extra limbs, changing environment, camera cuts, text, watermark, oversaturated colors.

Marcos

15,852 Aufrufe • vor 22 Tagen

Made with seedance 2.5 Prompt: Create a highly cinematic, realistic action sequence inside a crowded traditional Asian wet market during heavy rain and flooding. A young Asian woman with long dark wet hair, wearing a pink waterproof rain suit and black rubber boots, runs rapidly through the narrow market aisles while trying to escape from a massive rushing wave of water behind her. The market is packed with seafood and vegetable stalls, plastic crates, fish tanks, metal counters, hanging tarps, fluorescent ceiling lights, vendors and crowds. The floor is completely flooded with ankle-to-knee-deep dirty rainwater, creating strong reflections and splashes everywhere. Water violently rushes through the market, knocking over crates and flooding the stalls. Start with a close-up tracking shot of the frightened woman looking back over her shoulder while running. Follow her with a fast handheld camera as she runs through the narrow aisle. Use dynamic low-angle shots close to the water, capturing her boots hitting the flooded floor and creating dramatic splashes. Show water crashing through the market behind her, people running in panic, overturned crates floating in the water, and objects being swept away. Use realistic physics, natural human movement, detailed wet clothing, wet hair sticking to her face, realistic water droplets, splashes, reflections and motion blur. The camera should move dynamically with fast tracking shots, low-angle shots, side tracking shots and occasional wide shots revealing the scale of the flooding. At one point, show the woman jumping over obstacles and running across a market counter/raised surface while the floodwater continues rushing behind her. Keep her appearance, hairstyle, pink outfit and facial features consistent throughout the entire sequence. Dark cinematic atmosphere, overcast rainy lighting, cool blue-gray tones mixed with warm fluorescent market lights, dramatic contrast, realistic skin texture, photorealistic environment, volumetric lighting, atmospheric mist, cinematic depth of field, subtle film grain, high-detail textures, realistic reflections and physically accurate water simulation. The sequence should feel like a high-budget survival/action movie, extremely immersive and intense, with realistic camera shake and fast-paced movement. Add large cinematic white brush-stroke typography reading “RUN” briefly across the center of the screen during the action sequence. Photorealistic, ultra-detailed, cinematic Hollywood-style action scene, realistic physics, natural motion, 4K film quality, anamorphic lens look, dynamic composition, dramatic pacing, no cartoon look, no CGI appearance, no distorted anatomy, no extra fingers, no duplicated people, no face changes.

Made with seedance 2.5 Prompt: Create a highly cinematic, realistic action sequence inside a crowded traditional Asian wet market during heavy rain and flooding. A young Asian woman with long dark wet hair, wearing a pink waterproof rain suit and black rubber boots, runs rapidly through the narrow market aisles while trying to escape from a massive rushing wave of water behind her. The market is packed with seafood and vegetable stalls, plastic crates, fish tanks, metal counters, hanging tarps, fluorescent ceiling lights, vendors and crowds. The floor is completely flooded with ankle-to-knee-deep dirty rainwater, creating strong reflections and splashes everywhere. Water violently rushes through the market, knocking over crates and flooding the stalls. Start with a close-up tracking shot of the frightened woman looking back over her shoulder while running. Follow her with a fast handheld camera as she runs through the narrow aisle. Use dynamic low-angle shots close to the water, capturing her boots hitting the flooded floor and creating dramatic splashes. Show water crashing through the market behind her, people running in panic, overturned crates floating in the water, and objects being swept away. Use realistic physics, natural human movement, detailed wet clothing, wet hair sticking to her face, realistic water droplets, splashes, reflections and motion blur. The camera should move dynamically with fast tracking shots, low-angle shots, side tracking shots and occasional wide shots revealing the scale of the flooding. At one point, show the woman jumping over obstacles and running across a market counter/raised surface while the floodwater continues rushing behind her. Keep her appearance, hairstyle, pink outfit and facial features consistent throughout the entire sequence. Dark cinematic atmosphere, overcast rainy lighting, cool blue-gray tones mixed with warm fluorescent market lights, dramatic contrast, realistic skin texture, photorealistic environment, volumetric lighting, atmospheric mist, cinematic depth of field, subtle film grain, high-detail textures, realistic reflections and physically accurate water simulation. The sequence should feel like a high-budget survival/action movie, extremely immersive and intense, with realistic camera shake and fast-paced movement. Add large cinematic white brush-stroke typography reading “RUN” briefly across the center of the screen during the action sequence. Photorealistic, ultra-detailed, cinematic Hollywood-style action scene, realistic physics, natural motion, 4K film quality, anamorphic lens look, dynamic composition, dramatic pacing, no cartoon look, no CGI appearance, no distorted anatomy, no extra fingers, no duplicated people, no face changes.

Elisia

31,234 Aufrufe • vor 1 Monat

🔴 Finally! NVIDIA has finally made the code for Neuralangelo public! It has the ability to transform any video into a highly detailed 3D environment, and it's a technology related to but DIFFERENT from NeRF. 💡 Here's how it works: It takes a 2D video as input, showing an object, monument, building, landscape, etc., from various perspectives and analyzes details such as depth, size, and the shapes of objects. From this, the AI sketches an initial 3D model, similar to how an artist molds a figure. This representation is then refined to highlight more details, just as an artist would make the final touches when sculpting. The result is a 3D environment/model, perfect for use in any environment. Imagine the applications it will have for video games, cinema, virtual environments, VR, and more! 📽️🎮 💡 More details: A year ago, an article was presented on a groundbreaking technique called NVIDIA's Instant NeRF. This technique turns images into stunning 3D scenes in a short time, ideal for creating realistic models for video games and other applications. Although Instant NeRF had a lot of potential, the generated models were not perfect and often lacked detailed structures, appearing somewhat cartoonish. A year on, NVIDIA releases a new technique based on Instant NeRF, named Neuralangelo. This enhances the fidelity of surface structures. While NeRF reconstructs real objects in virtual environments from images or videos, Instant NeRF speeds up this process, and Neuralangelo further improves the quality, making the generated objects appear even more realistic when examined up close. Neuralangelo improves Instant NeRF's approach in two key ways related to the hash grid encoding technique: 1⃣ Numerical gradients have been used to compute higher-order derivatives as a smoothing operation. This optimizes the "hash grid" encoding using numerical rather than analytical gradients, providing a smoother input to the network that produces the 3D model. 2⃣ A "coarse-to-fine" optimization has been implemented in the hash grids to control different levels of detail. That is, they first focus on a smoothed version of the scene, and then refine it with more detailed updates. Well, as Arthur C. Clarke said, "Any sufficiently advanced technology is indistinguishable from magic."

🔴 Finally! NVIDIA has finally made the code for Neuralangelo public! It has the ability to transform any video into a highly detailed 3D environment, and it's a technology related to but DIFFERENT from NeRF. 💡 Here's how it works: It takes a 2D video as input, showing an object, monument, building, landscape, etc., from various perspectives and analyzes details such as depth, size, and the shapes of objects. From this, the AI sketches an initial 3D model, similar to how an artist molds a figure. This representation is then refined to highlight more details, just as an artist would make the final touches when sculpting. The result is a 3D environment/model, perfect for use in any environment. Imagine the applications it will have for video games, cinema, virtual environments, VR, and more! 📽️🎮 💡 More details: A year ago, an article was presented on a groundbreaking technique called NVIDIA's Instant NeRF. This technique turns images into stunning 3D scenes in a short time, ideal for creating realistic models for video games and other applications. Although Instant NeRF had a lot of potential, the generated models were not perfect and often lacked detailed structures, appearing somewhat cartoonish. A year on, NVIDIA releases a new technique based on Instant NeRF, named Neuralangelo. This enhances the fidelity of surface structures. While NeRF reconstructs real objects in virtual environments from images or videos, Instant NeRF speeds up this process, and Neuralangelo further improves the quality, making the generated objects appear even more realistic when examined up close. Neuralangelo improves Instant NeRF's approach in two key ways related to the hash grid encoding technique: 1⃣ Numerical gradients have been used to compute higher-order derivatives as a smoothing operation. This optimizes the "hash grid" encoding using numerical rather than analytical gradients, providing a smoother input to the network that produces the 3D model. 2⃣ A "coarse-to-fine" optimization has been implemented in the hash grids to control different levels of detail. That is, they first focus on a smoothed version of the scene, and then refine it with more detailed updates. Well, as Arthur C. Clarke said, "Any sufficiently advanced technology is indistinguishable from magic."

Javi Lopez ⛩️

689,325 Aufrufe • vor 3 Jahren

Seedance 2.5 is now available on Pollo AI I tested its 30-second video generation with a realistic Japanese city vlog, and the results are impressive consistent characters, natural motion, detailed environments, and an authentic smartphone feel. Plus, Seedance 2.5 is currently 50% OFF for a limited time on Pollo AI. Prompt: Create an ultra-realistic 30-second 16:9 vertical UGC smartphone vlog featuring the same young Japanese woman spending a casual day in a Japanese city. She wears a plain bright orange jacket matching Pollo AI’s #FF4900 brand color, dark casual pants, simple sneakers, and premium bright orange wireless headphones with no logos or text. Start inside a cozy Japanese apartment where her phone is placed stationary on a table; she picks up the headphones, puts them on naturally, smiles at the camera, then picks up the phone and switches into handheld selfie footage. She walks through the apartment, adjusts her headphones, grabs her keys and leaves. Outside, show authentic Japanese streets with vending machines, bicycles, utility poles, small shops, pedestrians, cars and crosswalks, naturally switching between selfie and rear-camera footage. While walking, she notices a small convenience store, enters casually, picks a cold bottled drink from the refrigerator, briefly smiles toward the camera, pays at the counter and walks back outside. She opens the drink and takes a sip while continuing to walk, creating a spontaneous everyday Japanese vlog moment. During golden hour, warm sunlight naturally reflects on the orange headphones as she walks, smiles and touches them while enjoying her music. Add realistic shop lighting, refrigerator reflections, Japanese shelves and products, natural pedestrians, hair movement, footsteps and city ambience. End at a lively street corner where she smiles at the camera, briefly turns the phone toward the orange headphones for a casual close-up, then continues walking as the recording naturally stops. Use realistic smartphone autofocus, slight focus hunting, exposure changes, subtle handheld shake, natural motion blur, imperfect framing, realistic skin and hair texture, authentic expressions and natural body movement. Make it cinematic through beautiful real-world lighting and atmosphere, but never polished or commercial. No gimbal shots, studio lighting, beauty filters, excessive bokeh, slow motion, artificial colors, perfect compositions or staged acting. Keep the same woman, hairstyle, outfit, orange jacket and headphones perfectly consistent throughout.

𝗦𝗮𝗻𝗶𝗮

188,141 Aufrufe • vor 1 Monat

I’ve been craving a video editor with motion baked in, designed to work with my own AI agents. Claude, Codex, whatever I want to use. I don’t want to be blocked by someone else’s credit system for every little interaction. I also wanted a Figma-like canvas/editor for when I want to jump in and tweak any little detail. So we built it: Video & audio editing: cut, zoom, speed up, add B-roll. Motion, animation, 3D, custom shaders & effects, custom 3D models, dynamic components & templates, audio and beat matching. And it’s all programmable. Design your own assets directly on the canvas, bring them in from Figma or the web, or just let the agent find them, mock them up, or record what it needs automatically. You can even drop in your screen recordings and just let loose. Supercut users: yes, it’ll have first-class support for your recordings, but it’ll work with anything. I’m going to be dropping a lot more examples and tutorials, so follow along. DM me for early access if you’re willing to give feedback. We’ll open it up to everyone very soon.

I’ve been craving a video editor with motion baked in, designed to work with my own AI agents. Claude, Codex, whatever I want to use. I don’t want to be blocked by someone else’s credit system for every little interaction. I also wanted a Figma-like canvas/editor for when I want to jump in and tweak any little detail. So we built it: Video & audio editing: cut, zoom, speed up, add B-roll. Motion, animation, 3D, custom shaders & effects, custom 3D models, dynamic components & templates, audio and beat matching. And it’s all programmable. Design your own assets directly on the canvas, bring them in from Figma or the web, or just let the agent find them, mock them up, or record what it needs automatically. You can even drop in your screen recordings and just let loose. Supercut users: yes, it’ll have first-class support for your recordings, but it’ll work with anything. I’m going to be dropping a lot more examples and tutorials, so follow along. DM me for early access if you’re willing to give feedback. We’ll open it up to everyone very soon.

Neil

23,042 Aufrufe • vor 1 Monat

🚀We are thrilled to open-source Hunyuan-GameCraft, a high-dynamic interactive game video generation framework built on HunyuanVideo. It generates playable and physically realistic videos from a single scene image and user action signals, empowering creators and developers to "direct" games with first-person or third-person perspectives. Key Advantages: 🔹High Dynamics: Unifies standard keyboard inputs into a shared continuous action space, enabling high-precision control over velocity and angle. This allows for the exploration of complex trajectories, overcoming the stiff, limited motion of traditional models. It can also generate dynamic environmental content like moving clouds, rain, snow, and water flow. 🔹Long-term Consistency: Uses hybrid history condition to preserve the original scene information after significant movement. 🔹Significant Cost Reduction: No need for expensive modeling/rendering. PCM distillation compresses inference steps, boosting speed and lowering costs. This allows the quantized 13B model to run on consumer-grade GPUs like the RTX 4090. Project Page: Code: Technical Report: Hugging Face：

🚀We are thrilled to open-source Hunyuan-GameCraft, a high-dynamic interactive game video generation framework built on HunyuanVideo. It generates playable and physically realistic videos from a single scene image and user action signals, empowering creators and developers to "direct" games with first-person or third-person perspectives. Key Advantages: 🔹High Dynamics: Unifies standard keyboard inputs into a shared continuous action space, enabling high-precision control over velocity and angle. This allows for the exploration of complex trajectories, overcoming the stiff, limited motion of traditional models. It can also generate dynamic environmental content like moving clouds, rain, snow, and water flow. 🔹Long-term Consistency: Uses hybrid history condition to preserve the original scene information after significant movement. 🔹Significant Cost Reduction: No need for expensive modeling/rendering. PCM distillation compresses inference steps, boosting speed and lowering costs. This allows the quantized 13B model to run on consumer-grade GPUs like the RTX 4090. Project Page: Code: Technical Report: Hugging Face：

Tencent Hy

169,757 Aufrufe • vor 1 Jahr

Finally got our hands on Seedance 2.0 (through YouArt) and ran it head-to-head with Kling AI 3.0. Here’s what stood out: Seedance 2.0’s physics feel stronger right away. The movement just looks more natural and realistic, especially in bigger physical actions. It also handles continuity across multiple shots from a single prompt better than I expected, which makes scene building a lot easier. And on the audio side, the lip sync generally holds up better than Kling. But here’s the tradeoff: Both models struggle with fine details. Background faces and smaller elements still get a bit messy. Seedance currently outputs at 720p, while Kling 3.0 supports 1080p, so Kling has the edge in overall sharpness. Even with upscaling, Seedance doesn’t fully recover those tiny details. Verdict🏆: Seedance 2.0 is a real step forward, especially for motion realism, but it’s definitely not the “end of Hollywood.” Check out our latest tutorial where we show you how to get access to this new model and take a deep look at the quality of this new AI Video Generator:

Finally got our hands on Seedance 2.0 (through YouArt) and ran it head-to-head with Kling AI 3.0. Here’s what stood out: Seedance 2.0’s physics feel stronger right away. The movement just looks more natural and realistic, especially in bigger physical actions. It also handles continuity across multiple shots from a single prompt better than I expected, which makes scene building a lot easier. And on the audio side, the lip sync generally holds up better than Kling. But here’s the tradeoff: Both models struggle with fine details. Background faces and smaller elements still get a bit messy. Seedance currently outputs at 720p, while Kling 3.0 supports 1080p, so Kling has the edge in overall sharpness. Even with upscaling, Seedance doesn’t fully recover those tiny details. Verdict🏆: Seedance 2.0 is a real step forward, especially for motion realism, but it’s definitely not the “end of Hollywood.” Check out our latest tutorial where we show you how to get access to this new model and take a deep look at the quality of this new AI Video Generator:

Curious Refuge

58,989 Aufrufe • vor 7 Monaten

Thrilled to announce Kingnet AI V2 is now officially live ! We have officially deployed on the BNB Chain first ! Whether you're an enthusiast or a professional game developer, come and try it out now： Each generated asset costs approximately $3 and supports export in professional game-editing formats. We will soon support exporting assets in NFT on-chain formats, empowering Web3 users and partners with seamless integration. Jump down more rabbit holes next.👇 📔 Product Introduction： By conversing naturally with agent Joi, users can achieve a complete automated game development cycle - from requirement proposal to finished product delivery. Users simply need to describe their game concepts and design requirements in natural language, and Joi will automatically utilize built-in generator including: • Animation Generator： AI-driven motion generation with auto-rigging technology for instant character animation • Map Generator： Procedural map generation with built-in logic validation for consistent world-building • Numerical Generator： Automated game economy tuning for fair yet challenging gameplay systems • Editable Code Generator： Generates clean, maintainable game logic code with multi-platform/multi-language support • Interface Generator： Intelligent layout engine that optimizes user experience and interaction flow Joi intelligently generates all necessary game components, performs multi-dimensional feasibility checks, and ultimately completes game synthesis, packaging and deployment. Users can directly click to try the game on the chat interface, or download the complete editable code package to achieve rapid iteration and secondary development. 🎯 Core Architecture： 1/ Natural Language Understanding & Multimodal Intent Parsing: Utilizing advanced deep learning NLP models (e.g., Transformer-based language understanding models), Joi precisely interprets user natural language inputs and extracts core game design intents and parameters. Through semantic segmentation and entity recognition, complex requirements are decomposed into specific tasks for animation, map, numerical systems, UI, and code modules. 2/ Modular Editor System & API Integration: Joi employs a unified API framework to enable seamless collaboration between editor modules, ensuring high compatibility in data formats and workflows. 3/ Intelligent Validation & Quality Assurance: The system incorporates multi-dimensional verification mechanisms including animation continuity checks, map pathfinding and physical logic validation, game balance analysis, UI interaction consistency verification, and static/dynamic code security testing. Automated testing and feedback loops ensure outputs meet high-standard game design specifications. 4/ Automatic Synthesis, Packaging & Instant Deployment: Verified resources are automatically integrated to complete game compilation, packaging and deployment. Supports one-click generation of playable online links and downloadable complete code packages for immediate testing or deep customization/iterative development. 5/ Interactive Chat Interface & Seamless UX: The entire workflow is completed within the chat interface, significantly reducing traditional game development's communication and operational barriers. Users accomplish complex game design and development through conversation while receiving real-time feedback and adjustment suggestions, democratizing game creation. 6/ Industry-Disrupting Value: Transforms traditional manual development into AI-driven automated pipelines.

Thrilled to announce Kingnet AI V2 is now officially live ! We have officially deployed on the BNB Chain first ! Whether you're an enthusiast or a professional game developer, come and try it out now： Each generated asset costs approximately $3 and supports export in professional game-editing formats. We will soon support exporting assets in NFT on-chain formats, empowering Web3 users and partners with seamless integration. Jump down more rabbit holes next.👇 📔 Product Introduction： By conversing naturally with agent Joi, users can achieve a complete automated game development cycle - from requirement proposal to finished product delivery. Users simply need to describe their game concepts and design requirements in natural language, and Joi will automatically utilize built-in generator including: • Animation Generator： AI-driven motion generation with auto-rigging technology for instant character animation • Map Generator： Procedural map generation with built-in logic validation for consistent world-building • Numerical Generator： Automated game economy tuning for fair yet challenging gameplay systems • Editable Code Generator： Generates clean, maintainable game logic code with multi-platform/multi-language support • Interface Generator： Intelligent layout engine that optimizes user experience and interaction flow Joi intelligently generates all necessary game components, performs multi-dimensional feasibility checks, and ultimately completes game synthesis, packaging and deployment. Users can directly click to try the game on the chat interface, or download the complete editable code package to achieve rapid iteration and secondary development. 🎯 Core Architecture： 1/ Natural Language Understanding & Multimodal Intent Parsing: Utilizing advanced deep learning NLP models (e.g., Transformer-based language understanding models), Joi precisely interprets user natural language inputs and extracts core game design intents and parameters. Through semantic segmentation and entity recognition, complex requirements are decomposed into specific tasks for animation, map, numerical systems, UI, and code modules. 2/ Modular Editor System & API Integration: Joi employs a unified API framework to enable seamless collaboration between editor modules, ensuring high compatibility in data formats and workflows. 3/ Intelligent Validation & Quality Assurance: The system incorporates multi-dimensional verification mechanisms including animation continuity checks, map pathfinding and physical logic validation, game balance analysis, UI interaction consistency verification, and static/dynamic code security testing. Automated testing and feedback loops ensure outputs meet high-standard game design specifications. 4/ Automatic Synthesis, Packaging & Instant Deployment: Verified resources are automatically integrated to complete game compilation, packaging and deployment. Supports one-click generation of playable online links and downloadable complete code packages for immediate testing or deep customization/iterative development. 5/ Interactive Chat Interface & Seamless UX: The entire workflow is completed within the chat interface, significantly reducing traditional game development's communication and operational barriers. Users accomplish complex game design and development through conversation while receiving real-time feedback and adjustment suggestions, democratizing game creation. 6/ Industry-Disrupting Value: Transforms traditional manual development into AI-driven automated pipelines.

Kingnet AI

46,437 Aufrufe • vor 1 Jahr