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$0.003 per second for video generation, without compromising on speed or visual quality? The supplied comparisons put Vivix W1 alongside leading models on visual quality. It also delivers eight seconds of video in roughly eight seconds. But the bigger story is that W1 is a real-time interactive video model....

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Kalsoom (ghotai )

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60,525 просмотров • 1 день назад •via X (Twitter)

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1 video with Seedance 2.5. Or 77 with Vivix W1. Same $1.85 budget. 20× faster generation. Comparable quality. Just $0.003 per second. The playground is live: W1 is built for interactive video. Making it an everyday medium is impossible without high quality, low latency, and low cost. W1 is the first to deliver all three. Under 1/50 the cost. 20× faster generation. Comparable quality. There are still gaps in cinematic fidelity, complex motion, and dense scenes. Full-scale training is underway.
0:18

1 video with Seedance 2.5. Or 77 with Vivix W1. Same $1.85 budget. 20× faster generation. Comparable quality. Just $0.003 per second. The playground is live: W1 is built for interactive video. Making it an everyday medium is impossible without high quality, low latency, and low cost. W1 is the first to deliver all three. Under 1/50 the cost. 20× faster generation. Comparable quality. There are still gaps in cinematic fidelity, complex motion, and dense scenes. Full-scale training is underway.

Vivix.AI

211,310 просмотров • 3 дней назад

Everyone is competing on realism, resolution, and generation quality. And that makes sense. But once the visuals become good enough, what becomes the next competitive edge? Maybe it’s reasoning. Can the system understand what happened in a scene, what should happen next, and keep those relationships consistent? Rhapsody 1.0 ( Induce AI ) is built around that idea, adding reasoning, story-state tracking, and verification around video generation. The next leap in AI video might not be making prettier pixels. It might be making the process more controllable. Worth watching: Mahesh KMB
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Everyone is competing on realism, resolution, and generation quality. And that makes sense. But once the visuals become good enough, what becomes the next competitive edge? Maybe it’s reasoning. Can the system understand what happened in a scene, what should happen next, and keep those relationships consistent? Rhapsody 1.0 ( Induce AI ) is built around that idea, adding reasoning, story-state tracking, and verification around video generation. The next leap in AI video might not be making prettier pixels. It might be making the process more controllable. Worth watching: Mahesh KMB

Liam Turner

14,576 просмотров • 1 месяц назад

What is the fuss all about? Even real pilots are acting like retard here, Crabbing is a real thing you do that to fight strong cross winds, yes it's bit exaggerated here for cinema, but it's not drifting. Even in Top Gun they dodged SAR Pechoras with flares and that's stupid. Movies or shows use their creative freedom for visuals, most of them make stuff stupid, this series is far more accurate than those. Rather watch the series and then make comment. Here is the video of MiG 21 Crabbing in real:
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What is the fuss all about? Even real pilots are acting like retard here, Crabbing is a real thing you do that to fight strong cross winds, yes it's bit exaggerated here for cinema, but it's not drifting. Even in Top Gun they dodged SAR Pechoras with flares and that's stupid. Movies or shows use their creative freedom for visuals, most of them make stuff stupid, this series is far more accurate than those. Rather watch the series and then make comment. Here is the video of MiG 21 Crabbing in real:

Defence Matrix

55,647 просмотров • 1 месяц назад

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 • 26 дней назад

THIS $2 AI VISUAL SETUP JUST MADE A $250/MONTH CREATIVE STACK LOOK STUPID he moves his hand, the particles react, and the whole scene updates in real time. no cloud render farm, no paid visual API, no expensive plugin chain quietly eating money every month most people still think ai visuals require a stack of $39 tools, $89 subscriptions, and constant API usage. but here the loop is simple: TouchDesigner handles the visuals, a local model handles the logic, and the laptop does the rest the important part is not that the particles look cool. the important part is that the “brain” behind the visual no longer has to live on someone else’s server once that moves local, the monthly bill falls off a cliff this is probably how a lot of small studios start building visuals soon: not by renting 6 tools forever, but by owning one system that runs almost for free
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THIS $2 AI VISUAL SETUP JUST MADE A $250/MONTH CREATIVE STACK LOOK STUPID he moves his hand, the particles react, and the whole scene updates in real time. no cloud render farm, no paid visual API, no expensive plugin chain quietly eating money every month most people still think ai visuals require a stack of $39 tools, $89 subscriptions, and constant API usage. but here the loop is simple: TouchDesigner handles the visuals, a local model handles the logic, and the laptop does the rest the important part is not that the particles look cool. the important part is that the “brain” behind the visual no longer has to live on someone else’s server once that moves local, the monthly bill falls off a cliff this is probably how a lot of small studios start building visuals soon: not by renting 6 tools forever, but by owning one system that runs almost for free

Ridark

15,948 просмотров • 4 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:
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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

Most video tools can generate clips. Very few can maintain identity. That has been the real bottleneck in AI video creation. Kling O1 changes that. For the first time, creators can carry a character, style, and visual language across scenes without constant fixes. You can reference past clips, assets, or images and the output stays consistently on-model. No visual drift. No rework loops. No “this doesn’t look like the last shot” moments. It feels less like prompting a tool and more like working with a creative collaborator that remembers context. The impact is practical, not theoretical: → Faster production cycles → Lower iteration costs → Noticeably higher output quality This is what mature AI tooling looks like. Not louder features. Not bigger claims. Just reliability where it actually matters. Consistency is no longer the problem.
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Most video tools can generate clips. Very few can maintain identity. That has been the real bottleneck in AI video creation. Kling O1 changes that. For the first time, creators can carry a character, style, and visual language across scenes without constant fixes. You can reference past clips, assets, or images and the output stays consistently on-model. No visual drift. No rework loops. No “this doesn’t look like the last shot” moments. It feels less like prompting a tool and more like working with a creative collaborator that remembers context. The impact is practical, not theoretical: → Faster production cycles → Lower iteration costs → Noticeably higher output quality This is what mature AI tooling looks like. Not louder features. Not bigger claims. Just reliability where it actually matters. Consistency is no longer the problem.

Darshal Jaitwar

141,038 просмотров • 9 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

one of the easiest ways to make your AI videos look 10x better is by just increasing the saturation a bit > left is the original output > right is saturation + contrast increased for some reason AI video models love making everything feel cold and blue, which makes the video look obviously AI very quickly a bit of saturation fixes a lot of that then pair it with Topaz and a bitrate cleaner and the video starts looking like it was shot on a real iphone cam obviously you still need a good system behind the actual video, but this takes a good generation to a completely different level
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one of the easiest ways to make your AI videos look 10x better is by just increasing the saturation a bit > left is the original output > right is saturation + contrast increased for some reason AI video models love making everything feel cold and blue, which makes the video look obviously AI very quickly a bit of saturation fixes a lot of that then pair it with Topaz and a bitrate cleaner and the video starts looking like it was shot on a real iphone cam obviously you still need a good system behind the actual video, but this takes a good generation to a completely different level

Miko

17,295 просмотров • 1 месяц назад

The next leap in AI video isn't just better visuals. It's having far more control over how those videos are created. Dreamina Seedance 2.5 is coming soon to the Dreamina platform, and what stands out isn't only the quality it's the workflow built around creators. Here's what's coming: • Multimodal input — combine up to 50 reference assets in a single generation. • Longer video generation — create continuous videos of up to 30 seconds. • Structured control — use white-model and green-screen references for more predictable results. • Multilingual creation — build content for international audiences with localization support. • Targeted refinement — edit specific parts of a video instead of regenerating the entire scene. These upgrades make Dreamina Seedance 2.5 feel less like another prompt-to-video model and more like a complete, controllable AI video production pipeline. Learn more: #dreamina #dreaminapartner #seedance #dreaminaseedance25
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The next leap in AI video isn't just better visuals. It's having far more control over how those videos are created. Dreamina Seedance 2.5 is coming soon to the Dreamina platform, and what stands out isn't only the quality it's the workflow built around creators. Here's what's coming: • Multimodal input — combine up to 50 reference assets in a single generation. • Longer video generation — create continuous videos of up to 30 seconds. • Structured control — use white-model and green-screen references for more predictable results. • Multilingual creation — build content for international audiences with localization support. • Targeted refinement — edit specific parts of a video instead of regenerating the entire scene. These upgrades make Dreamina Seedance 2.5 feel less like another prompt-to-video model and more like a complete, controllable AI video production pipeline. Learn more: #dreamina #dreaminapartner #seedance #dreaminaseedance25

Md Riyazuddin

33,164 просмотров • 2 месяцев назад

A single impressive AI video is a demo. A real production workflow needs much more: Enough references to define the creative direction. Enough duration to complete the shot. Enough control to revise what doesn’t work. Dreamina has unveiled the world-first global launch of Dreamina Seedance 2.5, with early access already live on Dreamina and US availability expected roughly one week later. 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 move from “generate something interesting” to “build something usable.”
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A single impressive AI video is a demo. A real production workflow needs much more: Enough references to define the creative direction. Enough duration to complete the shot. Enough control to revise what doesn’t work. Dreamina has unveiled the world-first global launch of Dreamina Seedance 2.5, with early access already live on Dreamina and US availability expected roughly one week later. 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 move from “generate something interesting” to “build something usable.”

D-Coder

39,817 просмотров • 2 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.
0:15

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

For years, AI video has forced creators to choose: More creative freedom — or more control. More references — or a manageable workflow. Longer scenes — or consistent characters, lighting, and story. That trade-off is exactly what Dreamina Seedance 2.5 is here to challenge. Dreamina, ByteDance’s proprietary AI product, has unveiled the **world-first global launch** of Seedance 2.5. Early access is live on Dreamina, while US availability is expected roughly one week later. 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 experience Seedance 2.5 at full power.
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For years, AI video has forced creators to choose: More creative freedom — or more control. More references — or a manageable workflow. Longer scenes — or consistent characters, lighting, and story. That trade-off is exactly what Dreamina Seedance 2.5 is here to challenge. Dreamina, ByteDance’s proprietary AI product, has unveiled the **world-first global launch** of Seedance 2.5. Early access is live on Dreamina, while US availability is expected roughly one week later. 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 experience Seedance 2.5 at full power.

Adarsh Chetan

24,305 просмотров • 2 месяцев назад

I kept refreshing waiting for this. Seedance 2.5 is now live on CapCut and it delivers. The amount of control is unreal. Generate and edit without switching platforms, control every scene with timestamps, use up to 50 references, create videos up to 90 seconds, unlock viewport render and green screen workflows, and enjoy much stronger multilingual performance. This is what next generation AI video feels like. Web: App: #CapCut #Seedance25 #CapCutai #CapCutDidThat
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I kept refreshing waiting for this. Seedance 2.5 is now live on CapCut and it delivers. The amount of control is unreal. Generate and edit without switching platforms, control every scene with timestamps, use up to 50 references, create videos up to 90 seconds, unlock viewport render and green screen workflows, and enjoy much stronger multilingual performance. This is what next generation AI video feels like. Web: App: #CapCut #Seedance25 #CapCutai #CapCutDidThat

JOY JULIET

65,357 просмотров • 2 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."
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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

Kling AI 3.0 is here And it’s a serious step forward for AI video. This update isn’t about small tweaks. It’s about refinement, realism, and making AI video feel ready for real-world use. What stands out with Kling 3.0? Stronger visual quality. Movements feel smoother. Lighting looks more natural. Scenes feel intentional instead of generated. Better prompt understanding. You can describe complex scenes, moods, or camera directions, and Kling 3.0 interprets them with much more accuracy. Less trial and error. More usable results. Improved motion and consistency. Characters stay consistent. Objects behave logically. Shots flow more naturally from start to finish. Greater creative control. From product-style visuals to cinematic storytelling, Kling 3.0 gives creators the flexibility to move beyond simple clips and into structured, high-quality sequences. The difference is subtle until you see it, and then it’s obvious. AI video is evolving quickly, and Kling AI 3.0 shows how far the technology has come. It’s not just about generating video anymore. It’s about generating video that’s usable, polished, and ready for campaigns, storytelling, and branded content. If you’re building with AI, this is one of the tools worth paying attention to, best AI video model for pro & commercial production
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Kling AI 3.0 is here And it’s a serious step forward for AI video. This update isn’t about small tweaks. It’s about refinement, realism, and making AI video feel ready for real-world use. What stands out with Kling 3.0? Stronger visual quality. Movements feel smoother. Lighting looks more natural. Scenes feel intentional instead of generated. Better prompt understanding. You can describe complex scenes, moods, or camera directions, and Kling 3.0 interprets them with much more accuracy. Less trial and error. More usable results. Improved motion and consistency. Characters stay consistent. Objects behave logically. Shots flow more naturally from start to finish. Greater creative control. From product-style visuals to cinematic storytelling, Kling 3.0 gives creators the flexibility to move beyond simple clips and into structured, high-quality sequences. The difference is subtle until you see it, and then it’s obvious. AI video is evolving quickly, and Kling AI 3.0 shows how far the technology has come. It’s not just about generating video anymore. It’s about generating video that’s usable, polished, and ready for campaigns, storytelling, and branded content. If you’re building with AI, this is one of the tools worth paying attention to, best AI video model for pro & commercial production

Future Stacked

183,095 просмотров • 7 месяцев назад

Dreamina Seedance 2.5 is officially live globally (yes, including the US) right on Dreamina - offering the full Seedance lineup at the absolute lowest price on the market. ByteDance just pushed the limits of AI video generation once again. Dreamina is actually the very first platform on the planet to roll out Seedance 2.5. This is far more than just a standard model update. It is a massive leap towards true professional AI filmmaking. Here is exactly what makes it stand out 👇
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Dreamina Seedance 2.5 is officially live globally (yes, including the US) right on Dreamina - offering the full Seedance lineup at the absolute lowest price on the market. ByteDance just pushed the limits of AI video generation once again. Dreamina is actually the very first platform on the planet to roll out Seedance 2.5. This is far more than just a standard model update. It is a massive leap towards true professional AI filmmaking. Here is exactly what makes it stand out 👇

Oluwatimileyin✨🦋

57,796 просмотров • 2 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

I just ran Gemma 4 31B on @CerebrasSystems at 1,800+ tokens/sec and it's multimodal. For context: that's 35x faster than a typical GPU endpoint, and the first token (reasoning included) lands in 1.5 seconds. This isn't a benchmark slide, I recorded the inference live. Prompt I used: "Create a simulation of an iPhone. Include at least one working dummy note taking app, a functional notification pulldown, high quality graphics, single HTML file, any libs via CDN." - Generation time: 3 seconds. - Notes app worked. - Notification panel worked. - Rendered first try. This is what wafer-scale inference unlocks, not just "faster," but a different category of product. When generation is this fast, you stop waiting and start iterating in real time. Why this matters: Gemma 4 31B is Google DeepMind's flagship open weight model, Apache 2.0 licensed, dense (not MoE), and built for efficiency over raw parameter count. It scores close to Claude Haiku 4.5 on the Artificial Analysis Intelligence Index (30 vs 29) but runs ~18x faster on Cerebras. It's also the first multimodal model on Cerebras's platform, meaning you can now feed it screenshots, documents, charts, and UI states at wafer scale speed. # Applications I'm most excited about: - Screenshot → Insight: Drop in a dashboard or document screenshot, get structured findings back instantly. no waiting, no batching. - Live UI generation: Full interactive interfaces (like my iPhone sim) generated and rendered in under 2 seconds. - Screenshot -> Patch: Feed it a broken UI + console error, get a minimal code fix and verification steps back. - Computer use & agentic loops: See -> reason -> act - verify, fast enough to keep a human in the loop instead of waiting on the model. - Long context summarization: Full research reports condensed into decision ready summaries you can read and requery in one sitting. The bigger unlock isn't the speed number itself, it's that agentic and multimodal loops (see -> reason -> output -> tool call -> verify -> retry) finally run in real time instead of feeling sluggish. As Logan Kilpatrick (Logan Kilpatrick) put it: "If every model was doing 2,000 tokens per second, you wouldn't build the same product and just have it be faster, you'd build different products." Gemma 4 31B is live now on Cerebras Inference Cloud in public preview. If you're building multimodal, agentic, or real time apps, this is worth testing today. What would you build with such insane inference throughput?
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I just ran Gemma 4 31B on @CerebrasSystems at 1,800+ tokens/sec and it's multimodal. For context: that's 35x faster than a typical GPU endpoint, and the first token (reasoning included) lands in 1.5 seconds. This isn't a benchmark slide, I recorded the inference live. Prompt I used: "Create a simulation of an iPhone. Include at least one working dummy note taking app, a functional notification pulldown, high quality graphics, single HTML file, any libs via CDN." - Generation time: 3 seconds. - Notes app worked. - Notification panel worked. - Rendered first try. This is what wafer-scale inference unlocks, not just "faster," but a different category of product. When generation is this fast, you stop waiting and start iterating in real time. Why this matters: Gemma 4 31B is Google DeepMind's flagship open weight model, Apache 2.0 licensed, dense (not MoE), and built for efficiency over raw parameter count. It scores close to Claude Haiku 4.5 on the Artificial Analysis Intelligence Index (30 vs 29) but runs ~18x faster on Cerebras. It's also the first multimodal model on Cerebras's platform, meaning you can now feed it screenshots, documents, charts, and UI states at wafer scale speed. # Applications I'm most excited about: - Screenshot → Insight: Drop in a dashboard or document screenshot, get structured findings back instantly. no waiting, no batching. - Live UI generation: Full interactive interfaces (like my iPhone sim) generated and rendered in under 2 seconds. - Screenshot -> Patch: Feed it a broken UI + console error, get a minimal code fix and verification steps back. - Computer use & agentic loops: See -> reason -> act - verify, fast enough to keep a human in the loop instead of waiting on the model. - Long context summarization: Full research reports condensed into decision ready summaries you can read and requery in one sitting. The bigger unlock isn't the speed number itself, it's that agentic and multimodal loops (see -> reason -> output -> tool call -> verify -> retry) finally run in real time instead of feeling sluggish. As Logan Kilpatrick (Logan Kilpatrick) put it: "If every model was doing 2,000 tokens per second, you wouldn't build the same product and just have it be faster, you'd build different products." Gemma 4 31B is live now on Cerebras Inference Cloud in public preview. If you're building multimodal, agentic, or real time apps, this is worth testing today. What would you build with such insane inference throughput?

Alok

12,962 просмотров • 3 месяцев назад