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AI video is hitting the same wall AI agents hit a year ago: The tech works. The economics don't. That's why Vivix.AI caught my attention. Their new real-time interactive video model, W1, generates video for just $0.003/sec while staying surprisingly fast and competitive on quality. To put that in...

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Bishal Nandi

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30,268 Aufrufe • vor 3 Tagen •via X (Twitter)

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I spent the morning running cost projections for live interactive video, and the math on conventional models is completely broken for production. That is why Vivix.AI's W1 model caught my attention. At $0.003/sec, I can trigger nearly 77 equal-length W1 generations for the API cost of a single Seedance 2.5 call. When you build applications where video generates non-stop as users interact, unit economics dictate whether your project survives. This affordability is what makes W1’s identity as a real-time interactive video model practically usable. API access is active today, though browser playground tools are currently offline generation only while real-time updates roll out. Looking at their 4-way comparison with Seedance 2.5, Kling 3.0, and H3 Max fal featuring the slow-motion sneeze window shatter, W1 holds its visual fidelity remarkably well. You still see minor physical artifacts in high-density glass debris while full-scale model training progresses, but solving the real-time inference cost curve is the exact infrastructure breakthrough I was waiting for. The numbers that put W1 on my production shortlist 👇
0:15

I spent the morning running cost projections for live interactive video, and the math on conventional models is completely broken for production. That is why Vivix.AI's W1 model caught my attention. At $0.003/sec, I can trigger nearly 77 equal-length W1 generations for the API cost of a single Seedance 2.5 call. When you build applications where video generates non-stop as users interact, unit economics dictate whether your project survives. This affordability is what makes W1’s identity as a real-time interactive video model practically usable. API access is active today, though browser playground tools are currently offline generation only while real-time updates roll out. Looking at their 4-way comparison with Seedance 2.5, Kling 3.0, and H3 Max fal featuring the slow-motion sneeze window shatter, W1 holds its visual fidelity remarkably well. You still see minor physical artifacts in high-density glass debris while full-scale model training progresses, but solving the real-time inference cost curve is the exact infrastructure breakthrough I was waiting for. The numbers that put W1 on my production shortlist 👇

Eleftheria Batsou

40,025 Aufrufe • vor 3 Tagen

this changes what AI video can even be $0.003 per second of AI video. that's not a typo. for the price of ONE Seedance 2.5 video, you can generate almost 80 W1 videos of the same length. and here's the part that makes it insane: it's not slower and it's not lower quality. an 8 second video generates in about 8 seconds, at quality comparable to the top models. cheaper, fast, and good. usually you pick two. Vivix.AI just brought all three together. but the price isn't even the real story. W1 is a real-time interactive video model. video that generates as an experience unfolds, so you can interact with what happens next. real-time means it keeps generating the whole time someone's using it. longer sessions, more users, more video, more cost. that only works if every second is cheap. $0.003/sec is what finally makes interactive video practical to actually run. i want to make a scene where even i don't know how it ends. honestly, giving up that control sounds fun. (real-time is live via the API now, browser tools coming soon) save this.
0:15

this changes what AI video can even be $0.003 per second of AI video. that's not a typo. for the price of ONE Seedance 2.5 video, you can generate almost 80 W1 videos of the same length. and here's the part that makes it insane: it's not slower and it's not lower quality. an 8 second video generates in about 8 seconds, at quality comparable to the top models. cheaper, fast, and good. usually you pick two. Vivix.AI just brought all three together. but the price isn't even the real story. W1 is a real-time interactive video model. video that generates as an experience unfolds, so you can interact with what happens next. real-time means it keeps generating the whole time someone's using it. longer sessions, more users, more video, more cost. that only works if every second is cheap. $0.003/sec is what finally makes interactive video practical to actually run. i want to make a scene where even i don't know how it ends. honestly, giving up that control sounds fun. (real-time is live via the API now, browser tools coming soon) save this.

Khairallah AL-Awady

29,796 Aufrufe • vor 3 Tagen

LTX 2.5 JUST WENT FASTER THAN REAL TIME LTX (LTX.io) is already one of the world's most widely used open video models. We just made its latest release, LTX 2.5, fast enough for rapid iteration and affordable enough for production at scale. It’s live on TensorScaleAI now, generating a 5-sec 1080p video in just 3.12s at $0.04 per second. That's faster than real time, at a fraction of the cost! For creative teams, that means less waiting time, more ideas explored, and lower production costs. For robotics and physical AI teams, that means more data generated at scale, more scenarios tested, and shorter development and deployment cycles. Request early access today and we’ll get you onboarded! (link:
0:12

LTX 2.5 JUST WENT FASTER THAN REAL TIME LTX (LTX.io) is already one of the world's most widely used open video models. We just made its latest release, LTX 2.5, fast enough for rapid iteration and affordable enough for production at scale. It’s live on TensorScaleAI now, generating a 5-sec 1080p video in just 3.12s at $0.04 per second. That's faster than real time, at a fraction of the cost! For creative teams, that means less waiting time, more ideas explored, and lower production costs. For robotics and physical AI teams, that means more data generated at scale, more scenarios tested, and shorter development and deployment cycles. Request early access today and we’ll get you onboarded! (link:

Yao Zhang

16,733 Aufrufe • vor 1 Monat

The AI video race is getting crowded. 👀 Seedance, Kling, H3, and now Vidu's Q-series finally gets an update after 8 months. Vidu Q4 Preview just dropped, and there are a few things that caught my attention. The standout for me: consistency. Q4 Preview supports up to 15 reference images to keep characters, products, and visuals consistent. That’s a lot more control when building a scene. It also supports up to 3 reference audio tracks, with generations of 4K output. Starting at $0.014/second, much cheaper than seedance That’s where the economics get interesting. The AI video race isn’t just about who can generate the best-looking clip anymore. It’s also about how easily creators can experiment, iterate, and turn more ideas into actual videos. Vidu Q4 Preview is definitely one to watch. The AI video race is getting interesting. 👀 With more capable models and lower generation costs, creators have more room to experiment. Which AI video model are you betting on right now? #ViduQ4Preview #ViduAI
0:15

The AI video race is getting crowded. 👀 Seedance, Kling, H3, and now Vidu's Q-series finally gets an update after 8 months. Vidu Q4 Preview just dropped, and there are a few things that caught my attention. The standout for me: consistency. Q4 Preview supports up to 15 reference images to keep characters, products, and visuals consistent. That’s a lot more control when building a scene. It also supports up to 3 reference audio tracks, with generations of 4K output. Starting at $0.014/second, much cheaper than seedance That’s where the economics get interesting. The AI video race isn’t just about who can generate the best-looking clip anymore. It’s also about how easily creators can experiment, iterate, and turn more ideas into actual videos. Vidu Q4 Preview is definitely one to watch. The AI video race is getting interesting. 👀 With more capable models and lower generation costs, creators have more room to experiment. Which AI video model are you betting on right now? #ViduQ4Preview #ViduAI

RAVI KUMAR SAHU

135,615 Aufrufe • vor 7 Tagen

I still see AI video framed in simple terms: prompt in, clip out. What caught my attention about PixVerse Live Party, an early experiment that explores a more interactive direction. It features Reina, an AI fan host, in a football themed experience where users can join in around cheering and share AI generated moments. This is the experiment I was looking at: I would not describe it as a finished livestreaming product. To me, it is an early look at how AI video could move beyond standalone clips and become part of a more social, character driven experience.
0:14

I still see AI video framed in simple terms: prompt in, clip out. What caught my attention about PixVerse Live Party, an early experiment that explores a more interactive direction. It features Reina, an AI fan host, in a football themed experience where users can join in around cheering and share AI generated moments. This is the experiment I was looking at: I would not describe it as a finished livestreaming product. To me, it is an early look at how AI video could move beyond standalone clips and become part of a more social, character driven experience.

D-Coder

49,496 Aufrufe • vor 3 Monaten

Google dropped a new AI paper called LUMIERE. It's remarkably flexible, supporting video inpainting, image-to-video, AND stylized video generation tasks. Say hello to “space-time diffusion” for video generation! Now what the heck does that mean exactly?! 🌐⏳ → TL;DR it utilizes a “Space-Time UNet” architecture that generates the full duration of the video in one pass, rather than generating distant keyframes and interpolating between them like prior works. Because the computation is done in this “compressed space-time representation” to generate the full clip at once, it's far more temporally consistent. → Another benefit of generating the full video at once is that you can “direct” the video generation, making it easier to hand off to other models/tasks without having to stitch together partial solutions. You can condition generations on additional inputs, meaning you get the full stack of AI video capabilities – from video inpainting to image-to-video and beyond. → New SOTA for AI video generation? User study results in the paper suggest human evaluators preferred Lumiere over Runway Gen-2, Pika Labs, and Stable Video Diffusion in terms of quality, text alignment AND motion. But as always, we need to get hands-on with this tech when Google *actually* decides to ship it. → Could this end up inside YouTube? Y’all know i’m obsessed with blending reality and imagination – so it’s the video inpainting tech I'm most excited about. I really hope this model finds its way into YouTube's Generative AI efforts, and based on their prior announcements and the list of acknowledgments in the paper I think it might! 🤞🏽 Links: 🔗Paper: 🔗Project:
0:13

Google dropped a new AI paper called LUMIERE. It's remarkably flexible, supporting video inpainting, image-to-video, AND stylized video generation tasks. Say hello to “space-time diffusion” for video generation! Now what the heck does that mean exactly?! 🌐⏳ → TL;DR it utilizes a “Space-Time UNet” architecture that generates the full duration of the video in one pass, rather than generating distant keyframes and interpolating between them like prior works. Because the computation is done in this “compressed space-time representation” to generate the full clip at once, it's far more temporally consistent. → Another benefit of generating the full video at once is that you can “direct” the video generation, making it easier to hand off to other models/tasks without having to stitch together partial solutions. You can condition generations on additional inputs, meaning you get the full stack of AI video capabilities – from video inpainting to image-to-video and beyond. → New SOTA for AI video generation? User study results in the paper suggest human evaluators preferred Lumiere over Runway Gen-2, Pika Labs, and Stable Video Diffusion in terms of quality, text alignment AND motion. But as always, we need to get hands-on with this tech when Google *actually* decides to ship it. → Could this end up inside YouTube? Y’all know i’m obsessed with blending reality and imagination – so it’s the video inpainting tech I'm most excited about. I really hope this model finds its way into YouTube's Generative AI efforts, and based on their prior announcements and the list of acknowledgments in the paper I think it might! 🤞🏽 Links: 🔗Paper: 🔗Project:

Bilawal Sidhu

44,822 Aufrufe • vor 2 Jahren

Most AI video tools are stuck in a loop, you generate, change the prompt, and wait again. Vidu S2 is pushing things forward by making generation interactive. You can edit the video while it is being created. Change the style, swap the background, or switch outfits in real time. If you drop in a new image, the video adjusts instantly without awkward cuts. Under the hood, it combines real time 720P output with an AI agent that actively watches the video to plan what happens next. It allows you to change reference images on the fly, powered by a model optimized specifically for live streaming. This opens up massive possibilities. Imagine viewers controlling visual changes during a livestream, people transforming into game characters, or shoppers trying on different looks live. The entire S Series is available for a free trial right now so you can test it yourself. Use my code PANDAS2 with the link below to grab 300 bonus credits to explore the other features. Vidu Stream: 300 Bonus Credits: Vidu AI #ViduAI #ViduS #ViduS2
0:18

Most AI video tools are stuck in a loop, you generate, change the prompt, and wait again. Vidu S2 is pushing things forward by making generation interactive. You can edit the video while it is being created. Change the style, swap the background, or switch outfits in real time. If you drop in a new image, the video adjusts instantly without awkward cuts. Under the hood, it combines real time 720P output with an AI agent that actively watches the video to plan what happens next. It allows you to change reference images on the fly, powered by a model optimized specifically for live streaming. This opens up massive possibilities. Imagine viewers controlling visual changes during a livestream, people transforming into game characters, or shoppers trying on different looks live. The entire S Series is available for a free trial right now so you can test it yourself. Use my code PANDAS2 with the link below to grab 300 bonus credits to explore the other features. Vidu Stream: 300 Bonus Credits: Vidu AI #ViduAI #ViduS #ViduS2

AI Panda

98,066 Aufrufe • vor 28 Tagen

This week is already so hot. 🔥 Massive release from Decart : Lucy 2.0 a World Editing Model running at 1080p, 30FPS in realtime. This is truly exciting, the era of real-time generative reality is here. We are moving from watching AI video to living inside AI video. A breakthrough model capable of transforming the visual world in real-time. Moving beyond offline rendering, Lucy 2.0 delivers high-fidelity 1080p video generation with near-zero latency. Lucy 2.0 literally "redraws" the entire world pixel-by-pixel, while you are watching it. e.g. If you want to be an anime character, it doesn't just put a mask on you. It turns your skin into anime skin, your hair into anime hair, and the lighting in your room into anime lighting. Lucy 2.0 is also trained to stop the generated video from slowly falling apart over time, so the same stream can run much longer without faces and details drifting. So why is this a "Massive Deal"? Traditional AI video-generation model takes a prompt, you wait 10–20 minutes, and the computer "bakes" a video for you. You couldn't touch it or change it while it was happening. But Lucy 2.0 works like a mirror. It happens in real-time (30 frames per second). There is no waiting. You move your hand, the AI character moves its hand instantly. The craziest part isn't the visuals; it's the physics. Usually, AI hallucinations are glitchy—hands merge into faces, walls melt. Lucy 2.0 understands how the world works without being told. It knows that if you take off a helmet, there is hair underneath. It knows that if you splash water, droplets fly. It learned "physics" just by watching millions of videos. The physical behavior you see emerges from learned visual dynamics, not from engineered geometry or explicit physics engines. Their official technical report explicitly states that the model does not use traditional 3D engines, depth maps, or wireframes. It is a "pure diffusion model."
0:14

This week is already so hot. 🔥 Massive release from Decart : Lucy 2.0 a World Editing Model running at 1080p, 30FPS in realtime. This is truly exciting, the era of real-time generative reality is here. We are moving from watching AI video to living inside AI video. A breakthrough model capable of transforming the visual world in real-time. Moving beyond offline rendering, Lucy 2.0 delivers high-fidelity 1080p video generation with near-zero latency. Lucy 2.0 literally "redraws" the entire world pixel-by-pixel, while you are watching it. e.g. If you want to be an anime character, it doesn't just put a mask on you. It turns your skin into anime skin, your hair into anime hair, and the lighting in your room into anime lighting. Lucy 2.0 is also trained to stop the generated video from slowly falling apart over time, so the same stream can run much longer without faces and details drifting. So why is this a "Massive Deal"? Traditional AI video-generation model takes a prompt, you wait 10–20 minutes, and the computer "bakes" a video for you. You couldn't touch it or change it while it was happening. But Lucy 2.0 works like a mirror. It happens in real-time (30 frames per second). There is no waiting. You move your hand, the AI character moves its hand instantly. The craziest part isn't the visuals; it's the physics. Usually, AI hallucinations are glitchy—hands merge into faces, walls melt. Lucy 2.0 understands how the world works without being told. It knows that if you take off a helmet, there is hair underneath. It knows that if you splash water, droplets fly. It learned "physics" just by watching millions of videos. The physical behavior you see emerges from learned visual dynamics, not from engineered geometry or explicit physics engines. Their official technical report explicitly states that the model does not use traditional 3D engines, depth maps, or wireframes. It is a "pure diffusion model."

Rohan Paul

12,761 Aufrufe • vor 8 Monaten

I spent the first few seconds trying to find the AI artifacts, but I couldn't find them. Seedance 2.5. I wasn't expecting AI video generation to feel this effortless, but Dola makes the whole process as simple as describing what you want in natural language. The rain had weight. Notice how it lingers on the windshield. The biggest surprise for me was the audio-visual consistency. The sound, the pacing, and the motion all worked together like a real commercial. And the interesting part is how little I had to explain. I just described the scene I had in mind, and let it cook. Try Seedance 2.5 free on Dola and see where AI video is heading. #dola #ai #seedance2.5
0:15

I spent the first few seconds trying to find the AI artifacts, but I couldn't find them. Seedance 2.5. I wasn't expecting AI video generation to feel this effortless, but Dola makes the whole process as simple as describing what you want in natural language. The rain had weight. Notice how it lingers on the windshield. The biggest surprise for me was the audio-visual consistency. The sound, the pacing, and the motion all worked together like a real commercial. And the interesting part is how little I had to explain. I just described the scene I had in mind, and let it cook. Try Seedance 2.5 free on Dola and see where AI video is heading. #dola #ai #seedance2.5

ᗩshhh

81,505 Aufrufe • vor 2 Monaten

🚨 THIS IS END OF AI BUBBLE The S&P 500 keeps hitting all-time highs. But almost nobody sees the systemic crisis brewing. Wall Street has built a giant debt pyramid. Just like in 2000. How it works: Companies borrow billions using inflated assets as collateral. Then they give that money right back to buy more of the same assets. On paper, it's a masterpiece: Stocks report record valuations. Buybacks show explosive returns. Markets keep skyrocketing. In reality, a big part of the demand is fake. It's a circular loop. And it only works as long as cheap money keeps flowing. When rates stay high long enough, the collateral loses value fast. Even worse: most companies still aren't making enough to justify these huge costs. This is not "if". It's already starting. Remember, I warned about the last three major reversals before they happened. My next call will be the biggest one this cycle. Turn on notifications. Most people will follow me too late.
0:17

🚨 THIS IS END OF AI BUBBLE The S&P 500 keeps hitting all-time highs. But almost nobody sees the systemic crisis brewing. Wall Street has built a giant debt pyramid. Just like in 2000. How it works: Companies borrow billions using inflated assets as collateral. Then they give that money right back to buy more of the same assets. On paper, it's a masterpiece: Stocks report record valuations. Buybacks show explosive returns. Markets keep skyrocketing. In reality, a big part of the demand is fake. It's a circular loop. And it only works as long as cheap money keeps flowing. When rates stay high long enough, the collateral loses value fast. Even worse: most companies still aren't making enough to justify these huge costs. This is not "if". It's already starting. Remember, I warned about the last three major reversals before they happened. My next call will be the biggest one this cycle. Turn on notifications. Most people will follow me too late.

Wimar.X

66,459 Aufrufe • vor 4 Monaten

AI video is getting very good at generating impressive clips. But the harder question is: can you actually control what happens inside the shot? That’s why I find the 3D-first approach interesting. GPT-6 Astra maps the space and helps establish camera + character movement within the Viewport before rendering. Then I manually bring the scene into CapCut PC for Seedance 2.5 rendering. And the part I didn’t expect to care about as much? The render is still not the final answer. I can keep editing and shaping it in CapCut PC. Maybe AI video is moving from “generate a clip” to “build a shot.” #CapCutPC #GPT6Astra #AIVideo #Seedance25
0:12

AI video is getting very good at generating impressive clips. But the harder question is: can you actually control what happens inside the shot? That’s why I find the 3D-first approach interesting. GPT-6 Astra maps the space and helps establish camera + character movement within the Viewport before rendering. Then I manually bring the scene into CapCut PC for Seedance 2.5 rendering. And the part I didn’t expect to care about as much? The render is still not the final answer. I can keep editing and shaping it in CapCut PC. Maybe AI video is moving from “generate a clip” to “build a shot.” #CapCutPC #GPT6Astra #AIVideo #Seedance25

Katyayani Shukla

84,107 Aufrufe • vor 1 Monat

We may be overestimating the importance of the generation step in AI video. Getting a model to produce a beautiful 10-second clip is impressive. But filmmaking has never been just about producing footage. It’s about deciding what happens before the camera rolls, controlling the shot, and shaping the material afterward. That’s why this workflow is interesting: GPT-6 Astra establishes the 3D space and camera + character movement in the Viewport. The scene is manually brought into CapCut PC. Seedance 2.5 renders the video. Then CapCut PC takes the result through post-production. Generation becomes one stage in a larger pipeline rather than the finish line. Maybe that’s the direction AI video needs to take if it’s going to move beyond “cool clips” and toward actual filmmaking workflows. And CapCut PC is a pretty natural place to experiment with that full process. #CapCutPC #GPT6Astra #AIVideo #Seedance25
0:12

We may be overestimating the importance of the generation step in AI video. Getting a model to produce a beautiful 10-second clip is impressive. But filmmaking has never been just about producing footage. It’s about deciding what happens before the camera rolls, controlling the shot, and shaping the material afterward. That’s why this workflow is interesting: GPT-6 Astra establishes the 3D space and camera + character movement in the Viewport. The scene is manually brought into CapCut PC. Seedance 2.5 renders the video. Then CapCut PC takes the result through post-production. Generation becomes one stage in a larger pipeline rather than the finish line. Maybe that’s the direction AI video needs to take if it’s going to move beyond “cool clips” and toward actual filmmaking workflows. And CapCut PC is a pretty natural place to experiment with that full process. #CapCutPC #GPT6Astra #AIVideo #Seedance25

AIMATRIX

16,778 Aufrufe • vor 1 Monat

you are making video games all wrong for decades almost all game art time went into reverse-engineering the end result you start with concept art of what you WANT it to look like. then for YEARS you walk the computer backwards into something it can process: a rendering engine, 3d assets that fit that engine, and a gamer’s local hardware that has to turn all of that back into a high fidelity image incredibly slow. incredibly expensive. but it was the best we had ai makes that pipeline faster as everyone is figuring out today. but they’re missing the real unlock: YOU DON’T NEED THAT PIPELINE AT ALL if you have a reference for the end look, you don’t model it in 3d. you don’t reverse-engineer into an engine you keep a very basic greybox model of the world as the source of truth, and track every entity in real time. it doesn’t need to look good at all… the player never sees it! a fast video model turns that into the “game” in real time. it doesn’t have to look like a game. it can look like a 2d cartoon or cinematic live action fal’s h3 max is very fast. astra 6 low-effort too. neither is fully realtime yet but together they can generate continuous, coherent, player-controlled scenes, faster than playback early demo:
0:19

you are making video games all wrong for decades almost all game art time went into reverse-engineering the end result you start with concept art of what you WANT it to look like. then for YEARS you walk the computer backwards into something it can process: a rendering engine, 3d assets that fit that engine, and a gamer’s local hardware that has to turn all of that back into a high fidelity image incredibly slow. incredibly expensive. but it was the best we had ai makes that pipeline faster as everyone is figuring out today. but they’re missing the real unlock: YOU DON’T NEED THAT PIPELINE AT ALL if you have a reference for the end look, you don’t model it in 3d. you don’t reverse-engineer into an engine you keep a very basic greybox model of the world as the source of truth, and track every entity in real time. it doesn’t need to look good at all… the player never sees it! a fast video model turns that into the “game” in real time. it doesn’t have to look like a game. it can look like a 2d cartoon or cinematic live action fal’s h3 max is very fast. astra 6 low-effort too. neither is fully realtime yet but together they can generate continuous, coherent, player-controlled scenes, faster than playback early demo:

Udi Wertheimer

125,097 Aufrufe • vor 1 Monat

As always everyone is blind staring at the progress of LLMs for coding and chat But meanwhile the new SOTA video model Seedance 2.5 has been slowly rolling out and it's really quite exceptional It's made by ByteDance (TikTok) who of course have lots of training data With just a few reference pics, it can get quite close to how you look IRL and you can do quite professional video shots with just a prompt I'd say it's the first video model that's now at the level of image models with the level of character likeness, cracking that in image models also took about 3 years (2022-2025) Generating 15 seconds takes about 4 minutes I put it live now on Photo AI, you can use it under [ Make video ] from the sidebar with just a prompt and your model selected! So you don't need to take an AI photo first and then turn that into a video! Saves lots of time :D It's more expensive than but I kept the credits the same (30 for 1 video) It also works inside the new video editor and you can make changes in your video with [ Magic edit ] in both the main app and the video editor Also a message for my server guy Daniel Lockyer (it can do voice too and you can even submit a voice sample of yourself, but I didn't here)
0:15

As always everyone is blind staring at the progress of LLMs for coding and chat But meanwhile the new SOTA video model Seedance 2.5 has been slowly rolling out and it's really quite exceptional It's made by ByteDance (TikTok) who of course have lots of training data With just a few reference pics, it can get quite close to how you look IRL and you can do quite professional video shots with just a prompt I'd say it's the first video model that's now at the level of image models with the level of character likeness, cracking that in image models also took about 3 years (2022-2025) Generating 15 seconds takes about 4 minutes I put it live now on Photo AI, you can use it under [ Make video ] from the sidebar with just a prompt and your model selected! So you don't need to take an AI photo first and then turn that into a video! Saves lots of time :D It's more expensive than but I kept the credits the same (30 for 1 video) It also works inside the new video editor and you can make changes in your video with [ Magic edit ] in both the main app and the video editor Also a message for my server guy Daniel Lockyer (it can do voice too and you can even submit a voice sample of yourself, but I didn't here)

@levelsio

711,938 Aufrufe • vor 2 Monaten

this video is 100% AI generated everyone has access to the same tools right now. sora, veo, kling. they're all publicly available. but most people are getting trash outputs while a small group is getting very-realistic results the only difference is your prompt whatever goes in comes out. if you put junk in, only junk will come out we have developed a very unique prompting framework and it's giving us results that don't look AI generated at all we reverse engineered thousands of realistic UGC videos and trained our prompt framework on the exact specifications of what makes those videos feel real the framework forces realistic imperfections into every generation. > breathing sway, micro-shake, grip adjustments. the subtle things that make footage feel human it has anti-glitch safety rules built in that prevent AI artifacts before they even happen. > specific camera behavior emulation like autofocus breathing and exposure shifts. > environmental audio layering. natural speech patterns with timing precision. the goal isn't perfection. it's believable imperfection that's what makes AI video pass as real
0:15

this video is 100% AI generated everyone has access to the same tools right now. sora, veo, kling. they're all publicly available. but most people are getting trash outputs while a small group is getting very-realistic results the only difference is your prompt whatever goes in comes out. if you put junk in, only junk will come out we have developed a very unique prompting framework and it's giving us results that don't look AI generated at all we reverse engineered thousands of realistic UGC videos and trained our prompt framework on the exact specifications of what makes those videos feel real the framework forces realistic imperfections into every generation. > breathing sway, micro-shake, grip adjustments. the subtle things that make footage feel human it has anti-glitch safety rules built in that prevent AI artifacts before they even happen. > specific camera behavior emulation like autofocus breathing and exposure shifts. > environmental audio layering. natural speech patterns with timing precision. the goal isn't perfection. it's believable imperfection that's what makes AI video pass as real

Miko

56,365 Aufrufe • vor 8 Monaten

Dustin Hollywood gives us a peek inside his first prompt in Video Studio for the CapCut CRE[AI]TE AI Festival. What's yours? Dustin Hollywood leverages his background as a traditional photographer and director to create moody, character-driven narrative shorts. As the founder of NAKID Pictures, he focuses on creative accountability while pushing cinematic boundaries, ranging from festival-screened AI pieces to live, sensor-driven cinema that shifts dynamically in real time. What are you making for the CapCut CRE[AI]TE AI Festival? Submit your work by August 10, 2026 to
0:11

Dustin Hollywood gives us a peek inside his first prompt in Video Studio for the CapCut CRE[AI]TE AI Festival. What's yours? Dustin Hollywood leverages his background as a traditional photographer and director to create moody, character-driven narrative shorts. As the founder of NAKID Pictures, he focuses on creative accountability while pushing cinematic boundaries, ranging from festival-screened AI pieces to live, sensor-driven cinema that shifts dynamically in real time. What are you making for the CapCut CRE[AI]TE AI Festival? Submit your work by August 10, 2026 to

CapCut

559,726 Aufrufe • vor 2 Monaten

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.
0:18

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 4 Monaten

AI VIDEOS ARE BECOMING SCARILY NORMAL At first, this looks like a simple clip from a sunny day on campus. A girl is sitting on the grass with a notebook, people are relaxing around her, and the whole scene feels like something someone casually filmed on their phone. Nothing about it instantly feels fake. And that’s exactly the point. AI video is no longer only about creating robots, fantasy worlds or crazy impossible scenes. It’s getting better at copying the most normal parts of real life: sunlight, background movement, random people, small gestures and natural-looking camera shots. Not long ago, AI clips were easy to expose. The face would feel off, the hands would glitch, or the motion would look weird after a few seconds. Now those signs are becoming harder to catch. The real breakthrough isn’t that AI can make something shocking. It’s that it can make an ordinary everyday moment look so real that most people would scroll past without questioning it.
0:13

AI VIDEOS ARE BECOMING SCARILY NORMAL At first, this looks like a simple clip from a sunny day on campus. A girl is sitting on the grass with a notebook, people are relaxing around her, and the whole scene feels like something someone casually filmed on their phone. Nothing about it instantly feels fake. And that’s exactly the point. AI video is no longer only about creating robots, fantasy worlds or crazy impossible scenes. It’s getting better at copying the most normal parts of real life: sunlight, background movement, random people, small gestures and natural-looking camera shots. Not long ago, AI clips were easy to expose. The face would feel off, the hands would glitch, or the motion would look weird after a few seconds. Now those signs are becoming harder to catch. The real breakthrough isn’t that AI can make something shocking. It’s that it can make an ordinary everyday moment look so real that most people would scroll past without questioning it.

Inspector

4,007,347 Aufrufe • vor 1 Monat