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$0.003/sec changes the economics of running real-time AI video. I’ve been testing Vivix W1, and that number is hard to ignore. The comparison shows visual quality on par with the models alongside W1. About a second of generation time per second of footage, too. But W1 isn’t just another...

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33,578 просмотров • 5 часов назад •via X (Twitter)

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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
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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 просмотров • 24 дней назад

As announced in partnership with NVIDIA at CES, we’re excited to introduce Stable Point Aware 3D (SPAR3D), setting a new standard in 3D generation. Ideal for running on NVIDIA RTX AI PCs, SPAR3D enables real-time editing and complete structure generation of 3D objects from a single image in under a second. You can download the weights on Hugging Face and code on GitHub, or access the model through the Stability AI API. Learn more here: (1/3)
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As announced in partnership with NVIDIA at CES, we’re excited to introduce Stable Point Aware 3D (SPAR3D), setting a new standard in 3D generation. Ideal for running on NVIDIA RTX AI PCs, SPAR3D enables real-time editing and complete structure generation of 3D objects from a single image in under a second. You can download the weights on Hugging Face and code on GitHub, or access the model through the Stability AI API. Learn more here: (1/3)

Stability AI

182,082 просмотров • 1 год назад

Cool new work on real-time video generation with motion control. MotionStream enables sub-second latency streaming on a single GPU. You can also control what parts of an image do & don't move, like the video below. 👏 to Xun Huang, Joonghyuk Shin, and team!
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Cool new work on real-time video generation with motion control. MotionStream enables sub-second latency streaming on a single GPU. You can also control what parts of an image do & don't move, like the video below. 👏 to Xun Huang, Joonghyuk Shin, and team!

Justine Moore

21,862 просмотров • 11 месяцев назад

I made a second version of the transformation video. This time I moved the character into a real environment instead of using a plain white background. I also changed the opening and showed the final transformation result first. The overall flow feels much stronger now. Full workflow + prompts: The interesting part is that this type of video is much easier to make than it looks. You only need a base image, then generate the next keyframe through simple edits or outfit changes on the canvas. The entire transformation sequence is built from those keyframes.
0:18

I made a second version of the transformation video. This time I moved the character into a real environment instead of using a plain white background. I also changed the opening and showed the final transformation result first. The overall flow feels much stronger now. Full workflow + prompts: The interesting part is that this type of video is much easier to make than it looks. You only need a base image, then generate the next keyframe through simple edits or outfit changes on the canvas. The entire transformation sequence is built from those keyframes.

underwood

315,219 просмотров • 4 месяцев назад

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:
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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 просмотров • 2 лет назад

Second batch of Actor’s Truth, and the masks keep coming off. Every time I walk in, I peel another layer the one I show the world, the one I hide even from myself. Truth is harder to find than any performance. But I’m running behind it anyway, chasing the version of me with nothing left to hide. Grateful to Saurabh Sachdeva sir for a space that doesn’t let you act, only feel. This is just the second batch. But I can already feel myself becoming… real. 🤍
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Second batch of Actor’s Truth, and the masks keep coming off. Every time I walk in, I peel another layer the one I show the world, the one I hide even from myself. Truth is harder to find than any performance. But I’m running behind it anyway, chasing the version of me with nothing left to hide. Grateful to Saurabh Sachdeva sir for a space that doesn’t let you act, only feel. This is just the second batch. But I can already feel myself becoming… real. 🤍

Poonam Panddey

177,825 просмотров • 3 месяцев назад

Dreamina has unveiled the world-first global launch of Dreamina Seedance 2.5 - with early access live on Dreamina and US availability expected roughly one week later. For AI marketing teams, the question is no longer: “Can AI generate a video?” We already know it can. The real question is: “Can one workflow turn a single campaign brief into enough consistent variations to actually ship?” With up to 50 multimodal references, 30-second single-generation video, and the lowest-cost access to the full Seedance family, Dreamina is the most cost-effective place to put that workflow to the test.
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Dreamina has unveiled the world-first global launch of Dreamina Seedance 2.5 - with early access live on Dreamina and US availability expected roughly one week later. For AI marketing teams, the question is no longer: “Can AI generate a video?” We already know it can. The real question is: “Can one workflow turn a single campaign brief into enough consistent variations to actually ship?” With up to 50 multimodal references, 30-second single-generation video, and the lowest-cost access to the full Seedance family, Dreamina is the most cost-effective place to put that workflow to the test.

Chidanand Tripathi

167,283 просмотров • 2 месяцев назад

The next phase of AI video needs infrastructure, not more tools.. This isn’t just a product update. It’s a new category. Topview 4.0 is the world’s first AI video collaboration board, built for how creators and teams actually work. One shared workspace to create, review, and iterate together without switching tools. Prompt → Image → Video → Avatar in a single flow. Real-time collaboration. All top image and video models in one place. Creator-friendly pricing, cheaper than official APIs. If AI video is part of your workflow, this is the board it belongs on. TopviewAI
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The next phase of AI video needs infrastructure, not more tools.. This isn’t just a product update. It’s a new category. Topview 4.0 is the world’s first AI video collaboration board, built for how creators and teams actually work. One shared workspace to create, review, and iterate together without switching tools. Prompt → Image → Video → Avatar in a single flow. Real-time collaboration. All top image and video models in one place. Creator-friendly pricing, cheaper than official APIs. If AI video is part of your workflow, this is the board it belongs on. TopviewAI

Kuria | AI

12,854 просмотров • 8 месяцев назад

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 просмотров • 8 месяцев назад

Super excited about Hydra-0 from Hongyu Li and team! The key idea is to use flow as a shared visual interface across embodiments/objects for controllable video generation, allowing a single generalist world model to learn from human, handheld-gripper, and robot interaction data. My favorite result is the video below: start from a real video of a human doing the task (left), extract the desired object flow, and condition the model on that flow (right). The model then hallucinates a plausible robot motion that could produce the same object motion. Very cool glimpse of how a generalist world model can bridge human demonstrations and robot control.
0:13

Super excited about Hydra-0 from Hongyu Li and team! The key idea is to use flow as a shared visual interface across embodiments/objects for controllable video generation, allowing a single generalist world model to learn from human, handheld-gripper, and robot interaction data. My favorite result is the video below: start from a real video of a human doing the task (left), extract the desired object flow, and condition the model on that flow (right). The model then hallucinates a plausible robot motion that could produce the same object motion. Very cool glimpse of how a generalist world model can bridge human demonstrations and robot control.

Yunzhu Li

10,850 просмотров • 1 месяц назад

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
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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 просмотров • 1 месяц назад

You can actually interact with the world simulator directly in the browser. 🤖 Here is a quick screen recording (8x speed) of me playing with it: real-time action-conditioned video prediction across rigid objects, deformable objects, rope, and object piles. Try it yourself (no install required): Huge kudos to my student Yixuan Wang for making the interactive demo happen!
0:18

You can actually interact with the world simulator directly in the browser. 🤖 Here is a quick screen recording (8x speed) of me playing with it: real-time action-conditioned video prediction across rigid objects, deformable objects, rope, and object piles. Try it yourself (no install required): Huge kudos to my student Yixuan Wang for making the interactive demo happen!

Yunzhu Li

41,513 просмотров • 7 месяцев назад

What if a network could deliver AI results closer to where data is created, instead of sending it to far‑off data centers? In collaboration with NVIDIA and Decart, we’re making that a reality by bringing GPU‑powered computing to the network edge — closer to homes and businesses — so AI applications respond in real-time. This is how we're laying the foundation for the next generation of AI‑driven services:
0:16

What if a network could deliver AI results closer to where data is created, instead of sending it to far‑off data centers? In collaboration with NVIDIA and Decart, we’re making that a reality by bringing GPU‑powered computing to the network edge — closer to homes and businesses — so AI applications respond in real-time. This is how we're laying the foundation for the next generation of AI‑driven services:

Comcast

15,708 просмотров • 6 месяцев назад

My 7-year-old son thinks it’s completely normal for me to play chess with him while Tesla FSD drives us. But the more I think about this… it hit me. To him, Tesla FSD may not look like some amazing piece of technology... to him it’s just normal life. He never experienced a world where every second in a car required the driver to be fully focused on steering, braking, and navigating. For him, he sees a car that safely handles the driving while Dad spends that time talking with him, teaching him, laughing with him, or playing a game of chess. That’s a pretty big shift when you really think about it. Every generation grows up taking for granted things that once seemed impossible. The internet. Smartphones. Video calls. Now we’re watching the beginning of that same transition with autonomy. For many adults, FSD still feels futuristic. For kids growing up today, it’s become the way cars work. What’s fascinating is that the biggest change is what people do with the time it gives back. Instead of staring at the road for hours, families can spend more time together, learn, work, relax, or simply enjoy the ride. My son doesn’t see autonomy as a breakthrough, like me. He sees this as normal. And that’s how I know the future is here.
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My 7-year-old son thinks it’s completely normal for me to play chess with him while Tesla FSD drives us. But the more I think about this… it hit me. To him, Tesla FSD may not look like some amazing piece of technology... to him it’s just normal life. He never experienced a world where every second in a car required the driver to be fully focused on steering, braking, and navigating. For him, he sees a car that safely handles the driving while Dad spends that time talking with him, teaching him, laughing with him, or playing a game of chess. That’s a pretty big shift when you really think about it. Every generation grows up taking for granted things that once seemed impossible. The internet. Smartphones. Video calls. Now we’re watching the beginning of that same transition with autonomy. For many adults, FSD still feels futuristic. For kids growing up today, it’s become the way cars work. What’s fascinating is that the biggest change is what people do with the time it gives back. Instead of staring at the road for hours, families can spend more time together, learn, work, relax, or simply enjoy the ride. My son doesn’t see autonomy as a breakthrough, like me. He sees this as normal. And that’s how I know the future is here.

Teslaconomics

45,231 просмотров • 3 месяцев назад

There is nothing more valuable than your time. And yet it is time that most goes to waste. Money can’t give you more time. But money can get you the time of others. And that time is worth much much more than most folks are being compensated in exchange for it. You can’t get that time back. The majority believing there is little value for their time is part of how those who do assign high value to their own time keep their control. Time is a real resource. Money is a social construct. One of the two is much more valuable. But what do I know, I’m just a silly girl with hand puppets.
0:18

There is nothing more valuable than your time. And yet it is time that most goes to waste. Money can’t give you more time. But money can get you the time of others. And that time is worth much much more than most folks are being compensated in exchange for it. You can’t get that time back. The majority believing there is little value for their time is part of how those who do assign high value to their own time keep their control. Time is a real resource. Money is a social construct. One of the two is much more valuable. But what do I know, I’m just a silly girl with hand puppets.

Liz Katz

85,995 просмотров • 2 месяцев назад

THIS GUY GOT SICK OF UK TRAIN STATIONS HIDING THE PLATFORM NUMBER UNTIL THE LAST SECOND, SO HE VIBE CODED AN APP THAT PREDICTS IT BEFORE THEY REVEAL IT if youve ever stood in a crowded station like london euston, you know the pain the platform stays hidden until 15 minutes before boarding, then it flashes up and hundreds of people sprint for the same gate so he built something that fixes this: > a clean departures and arrivals app pulling live data straight from the network rail apis > live train tracking so you can watch where your train actually is on the route and whether its running on time > the main feature is a predictive engine that guesses your platform before the station reveals it, and its right about 75% of the time heres how it predicts: every time a train finishes its journey, it logs which platform it actually pulled into and compares that to the platform network rail originally advertised it saves every one of those comparisons, and over time it builds up enough history to predict the platform with a real confidence score he built the whole thing with claude, mostly opus with some fable
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THIS GUY GOT SICK OF UK TRAIN STATIONS HIDING THE PLATFORM NUMBER UNTIL THE LAST SECOND, SO HE VIBE CODED AN APP THAT PREDICTS IT BEFORE THEY REVEAL IT if youve ever stood in a crowded station like london euston, you know the pain the platform stays hidden until 15 minutes before boarding, then it flashes up and hundreds of people sprint for the same gate so he built something that fixes this: > a clean departures and arrivals app pulling live data straight from the network rail apis > live train tracking so you can watch where your train actually is on the route and whether its running on time > the main feature is a predictive engine that guesses your platform before the station reveals it, and its right about 75% of the time heres how it predicts: every time a train finishes its journey, it logs which platform it actually pulled into and compares that to the platform network rail originally advertised it saves every one of those comparisons, and over time it builds up enough history to predict the platform with a real confidence score he built the whole thing with claude, mostly opus with some fable

Om Patel

176,154 просмотров • 3 месяцев назад

I’m probably one of the only Teslanaires out there, if not one of the very few, still cutting my own hair. I cut my own hair again today, and it reminded me that becoming a multi-millionaire usually isn’t a random coincidence. People see the $ and think it just happened. What they usually don’t see are the small habits behind it. Of course, I could go spend $25–$50 on a haircut that probably looks better than the one I give myself. But that’s not really what matters to me. I don’t care that much about looking perfect. I care about controlling my time. I care about staying grounded. I care about keeping the kind of habits that helped me build wealth in the first place. And honestly, I enjoy doing it. I’ve been cutting my own hair for so many years that I don’t even think about going to the barber anymore. It’s just normal to me now. It saves time, keeps me frugal, and reminds me that wealth is usually built in the small choices nobody claps for. That’s the part people miss. A lot of people see wealth and assume it was luck. But a lot of the time, it’s really the result of small disciplined habits repeated for years. Not wasting $ just bc you can. Not wasting time just bc other people do. And the funny part is, one day my fleet of Tesla Bots will probably be doing it for me anyway. But until then, I’m good doing it myself. Bc to me, being wealthy was never about trying to look rich. It was about building a mindset. A mindset that values time, discipline, and freedom more than appearances. And once you really live that way, it shows up in a lot of things, even something as simple as cutting your own hair.
0:11

I’m probably one of the only Teslanaires out there, if not one of the very few, still cutting my own hair. I cut my own hair again today, and it reminded me that becoming a multi-millionaire usually isn’t a random coincidence. People see the $ and think it just happened. What they usually don’t see are the small habits behind it. Of course, I could go spend $25–$50 on a haircut that probably looks better than the one I give myself. But that’s not really what matters to me. I don’t care that much about looking perfect. I care about controlling my time. I care about staying grounded. I care about keeping the kind of habits that helped me build wealth in the first place. And honestly, I enjoy doing it. I’ve been cutting my own hair for so many years that I don’t even think about going to the barber anymore. It’s just normal to me now. It saves time, keeps me frugal, and reminds me that wealth is usually built in the small choices nobody claps for. That’s the part people miss. A lot of people see wealth and assume it was luck. But a lot of the time, it’s really the result of small disciplined habits repeated for years. Not wasting $ just bc you can. Not wasting time just bc other people do. And the funny part is, one day my fleet of Tesla Bots will probably be doing it for me anyway. But until then, I’m good doing it myself. Bc to me, being wealthy was never about trying to look rich. It was about building a mindset. A mindset that values time, discipline, and freedom more than appearances. And once you really live that way, it shows up in a lot of things, even something as simple as cutting your own hair.

Teslaconomics

16,514 просмотров • 6 месяцев назад

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

16,706 просмотров • 1 месяц назад

From product image to video with just one tool - Dzine As you may have noticed, this is one of my favorite tools. It is also very underrated, as probably 50% of my tutorials include some workflow. I was testing the new image-to-video option today, and I love it. Step - by step guide in comments 🔽 I can do 95% of a workflow without switching between apps. Image generation, Image to image with style reference, background removal, background generation, and 2 frames image to video. The only other app I have been using for this video is CapCut so that I can stitch it together. Step by step 🔽
0:11

From product image to video with just one tool - Dzine As you may have noticed, this is one of my favorite tools. It is also very underrated, as probably 50% of my tutorials include some workflow. I was testing the new image-to-video option today, and I love it. Step - by step guide in comments 🔽 I can do 95% of a workflow without switching between apps. Image generation, Image to image with style reference, background removal, background generation, and 2 frames image to video. The only other app I have been using for this video is CapCut so that I can stitch it together. Step by step 🔽

Teodora P L

28,523 просмотров • 2 лет назад