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working towards action-conditioned video diffusion models for now this is just cs2 gameplay, and i parse the keypresses from the .dem game file next steps will be to work on a scalable data loader then coding the model

Arnie Ramesh

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31,090 次观看 • 4 个月前 •via X (Twitter)

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New Stage2 PoC payload loader commit fixes the USB Loader and can now goldhen (or any payload/HEN) from payload.bin from USB root or from /data, the USB Loader has now been set to the default loader, this is the end game Offsets file to port to 11.00

New Stage2 PoC payload loader commit fixes the USB Loader and can now goldhen (or any payload/HEN) from payload.bin from USB root or from /data, the USB Loader has now been set to the default loader, this is the end game Offsets file to port to 11.00

LM

78,913 次观看 • 2 年前

Glad that our work “Inference-Time Enhancement of Generative Robot Policies via Predictive World Modeling”, led by Han Qi, has been accepted to IEEE Robotics and Automation Letters! 🎉 We propose Generative Predictive Control (GPC): sample action proposals from a pretrained diffusion policy (“look back”), roll them out with a diffusion-based action-conditioned video world model (“look forward”), then rank or optimize the actions using either a learned reward model or VLM preferences. Conceptually, this is trajectory optimization / MPC with hybrid sampling + gradient optimization, interpreted through modern diffusion priors and video world models. Interestingly, we first posted the paper on arXiv in Feb 2025, when action-conditioned video world models for planning were still rare—now this direction is rapidly gaining traction. Still many open questions, e.g., • how to avoid local minima in planning • what representations work best for world models • how to balance physics priors vs. data-driven learning Paper:

Glad that our work “Inference-Time Enhancement of Generative Robot Policies via Predictive World Modeling”, led by Han Qi, has been accepted to IEEE Robotics and Automation Letters! 🎉 We propose Generative Predictive Control (GPC): sample action proposals from a pretrained diffusion policy (“look back”), roll them out with a diffusion-based action-conditioned video world model (“look forward”), then rank or optimize the actions using either a learned reward model or VLM preferences. Conceptually, this is trajectory optimization / MPC with hybrid sampling + gradient optimization, interpreted through modern diffusion priors and video world models. Interestingly, we first posted the paper on arXiv in Feb 2025, when action-conditioned video world models for planning were still rare—now this direction is rapidly gaining traction. Still many open questions, e.g., • how to avoid local minima in planning • what representations work best for world models • how to balance physics priors vs. data-driven learning Paper:

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Wow, diffusion models (used in AI image generation) are also game engines - a type of world simulation. By predicting the next frame of the classic shooter DOOM, you get a playable game at 20 fps without any underlying real game engine. This video is from the diffusion model.

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Ethan Mollick

1,768,802 次观看 • 1 年前

Diffusion has shown great promise for generating robot **actions**, can it act as a **world model** to generate the future conditioned on actions? In our work led by han qi Haocheng Yin and in collaboration with Yilun Du, we show a **controllable** action-conditioned video diffusion model can produce photorealistic and (near) physics-accurate future predictions. This ability strengthens the policy via: - ranking different action proposals and selecting the best, or - **visual** trajectory optimization by optimizing the action proposals using gradient ascent. Learn more about Generative Predictive Control (GPC) at:

Diffusion has shown great promise for generating robot actions, can it act as a world model to generate the future conditioned on actions? In our work led by han qi Haocheng Yin and in collaboration with Yilun Du, we show a controllable action-conditioned video diffusion model can produce photorealistic and (near) physics-accurate future predictions. This ability strengthens the policy via: - ranking different action proposals and selecting the best, or - visual trajectory optimization by optimizing the action proposals using gradient ascent. Learn more about Generative Predictive Control (GPC) at:

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The ultimate form of agentic coding will not be the terminal. This is an experiment. An ADE (Agentic Coding Environment), designed from the ground up to work with agentic coding tools. Right now, this only supports Claude Code and runs on a Mac.

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Santiago

40,126 次观看 • 4 个月前

I finally released my new video on YouTube about Diffusion Models / Score-Based Generative Models. Literally planned this for a year and put so much work in. I think this approach to diffusion models is so intuitive and highly recommend giving that a go! Video is 38min long, so you will need some time to watch that haha.

I finally released my new video on YouTube about Diffusion Models / Score-Based Generative Models. Literally planned this for a year and put so much work in. I think this approach to diffusion models is so intuitive and highly recommend giving that a go! Video is 38min long, so you will need some time to watch that haha.

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54,560 次观看 • 1 年前

Gemini Diffusion will be one of the steps that will define how user interfaces will evolve within the next several years. This is a huge prerequisite for the next level of generative UIs. There won't be a need to build a frontend UIs soon. Insane 🤯

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TestingCatalog News 🗞

18,924 次观看 • 1 年前

After building out a game of my own and using Retro Diffusion for every piece of art, I'm really curious to see what other people can come up with. So I'm going to host a mini game jam. $500 of Retro Diffusion credits in prizes (1st = $300, 2nd & 3rd = $100 each). Build a game over the next week that uses RD for the artwork. Whatever genre, whatever type of gameplay. On Tuesday March 10th I'll gather up all the games (video of gameplay is fine) and decide which I think is the most interesting. Make sure to repost this and/or @ me so I know what you're making! I'd love to see progress along the way as well :) TLDR: Make a game, $500 in prizes, you've got until the 10th, gotta use Retro Diffusion for the art, it has to be a *new* game, not something you've been working on.

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Astropulse

30,716 次观看 • 4 个月前

Check out the Gameplay Video for #AtelierYumia A free public demo will be available from March 17th on PlayStation Store, Nintendo e-shop, Microsoft Store and Steam®. In addition, save data from the demo can be carried over to the full version of the game! #KTfamily

Check out the Gameplay Video for #AtelierYumia A free public demo will be available from March 17th on PlayStation Store, Nintendo e-shop, Microsoft Store and Steam®. In addition, save data from the demo can be carried over to the full version of the game! #KTfamily

KOEI TECMO AMERICA

34,760 次观看 • 1 年前

Vibe coding a javascript loader for the custom 3D file format we used in a demo I did back in 2001.

Vibe coding a javascript loader for the custom 3D file format we used in a demo I did back in 2001.

mrdoob

48,390 次观看 • 5 个月前

Another video! This weeks goal is to get the outfit in game and working, after that ill push an update to the testing discord and we can iron out bugs that will appear from the quest. then its just spell checking, and I will throw this bad boy up for public use.

Another video! This weeks goal is to get the outfit in game and working, after that ill push an update to the testing discord and we can iron out bugs that will appear from the quest. then its just spell checking, and I will throw this bad boy up for public use.

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12,213 次观看 • 1 年前

📢 Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation Got only one or a few images and wondering if recovering the 3D environment is a reconstruction or generation problem? Why not do it with a generative reconstruction model! We show that a camera-conditioned video diffusion model can be transformed into a generative reconstruction model that directly outputs a high-quality 3D Gaussian Splatting representation through self-distillation, without requiring real-world training data. Check out our results in the video (wait for dynamic scenes in the second half!) : Project Page: Code and Models: Paper:

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367,000 次观看 • 1 年前

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Destra Network

37,135 次观看 • 1 年前

“ xAI team is currently working heavily on coding models. Right now, the main focus is training a specialized coding model that will be both fast and smart. I believe we’ll share it with you guys in a few weeks. That’s exciting. Second ,after coding, we all see that the main weakness of Grok 4 is its multimodal capabilities. In fact, it was so bad that Grok was effectively looking at the world while squinting through glass trying to see blurry features and make sense of them. The most immediate improvement we’re stepping on with the next generation pre trained model is huge gains in image understanding, video understanding, and audio. Right now, the model can hear and see the world just like any of you. And with all the tools and other agents it can talk to, we’re going to see a huge unlock for many different application layers once multimodal agents arrive.” — xAI Team

“ xAI team is currently working heavily on coding models. Right now, the main focus is training a specialized coding model that will be both fast and smart. I believe we’ll share it with you guys in a few weeks. That’s exciting. Second ,after coding, we all see that the main weakness of Grok 4 is its multimodal capabilities. In fact, it was so bad that Grok was effectively looking at the world while squinting through glass trying to see blurry features and make sense of them. The most immediate improvement we’re stepping on with the next generation pre trained model is huge gains in image understanding, video understanding, and audio. Right now, the model can hear and see the world just like any of you. And with all the tools and other agents it can talk to, we’re going to see a huge unlock for many different application layers once multimodal agents arrive.” — xAI Team

Apurv Kochara

88,142 次观看 • 4 个月前

I tested GLM 5.2 on three real builds. A horror house game. A 3D stealth game. A Remotion marketing video. The results are exactly what I expect from Chinese open source coding models right now. The horror house has broken game logic. Collect all three keys, complete the objective, and the front door still won't open. The stealth game shipped with lighting so dark you can't see your own character. The Remotion video is rough. GLM 5.2 is faster than 5.1 and 10x cheaper than the frontier. But Opus 4.8 and GPT 5.5 are still in a different league for serious coding work. Chinese models keep missing the attention to detail that matters. I MISS FABLE 5 ALREADY. Full review live now.

I tested GLM 5.2 on three real builds. A horror house game. A 3D stealth game. A Remotion marketing video. The results are exactly what I expect from Chinese open source coding models right now. The horror house has broken game logic. Collect all three keys, complete the objective, and the front door still won't open. The stealth game shipped with lighting so dark you can't see your own character. The Remotion video is rough. GLM 5.2 is faster than 5.1 and 10x cheaper than the frontier. But Opus 4.8 and GPT 5.5 are still in a different league for serious coding work. Chinese models keep missing the attention to detail that matters. I MISS FABLE 5 ALREADY. Full review live now.

BridgeMind

24,527 次观看 • 1 个月前

Not the flashiest demos, but what’s under the hood represents a foundational shift for general-purpose robotics. World models are the next-gen foundation of Physical AI, not the VLM backbones found in typical VLAs. DreamZero is a 14B-parameter World Action Model (WAM) by NVIDIA that treats robotics as a joint video-and-action prediction task. Unlike traditional Vision-Language-Action (VLA) models that map images directly to motor commands, DreamZero leverages a pretrained video diffusion backbone to predict future world states and actions simultaneously. - achieves 2× better zero-shot generalization to unseen tasks and environments compared to state-of-the-art VLAs. - learns effectively from heterogeneous, non-repetitive data (500 hours), breaking the need for thousands of repeated demonstrations. - adapts to new robot embodiments with just 30 minutes of play data. - enables 7Hz closed-loop control via system optimizations and "DreamZero-Flash," making high-capacity diffusion models viable for real-time use.

Not the flashiest demos, but what’s under the hood represents a foundational shift for general-purpose robotics. World models are the next-gen foundation of Physical AI, not the VLM backbones found in typical VLAs. DreamZero is a 14B-parameter World Action Model (WAM) by NVIDIA that treats robotics as a joint video-and-action prediction task. Unlike traditional Vision-Language-Action (VLA) models that map images directly to motor commands, DreamZero leverages a pretrained video diffusion backbone to predict future world states and actions simultaneously. - achieves 2× better zero-shot generalization to unseen tasks and environments compared to state-of-the-art VLAs. - learns effectively from heterogeneous, non-repetitive data (500 hours), breaking the need for thousands of repeated demonstrations. - adapts to new robot embodiments with just 30 minutes of play data. - enables 7Hz closed-loop control via system optimizations and "DreamZero-Flash," making high-capacity diffusion models viable for real-time use.

The Humanoid Hub

35,204 次观看 • 5 个月前

🎬This is from a static MJ 7 image + HeyGen 4! The voice over is human performance, but the nuances the diffusion model picks up is pretty next level for the character. I masked in a video of the cars moving from Kling. Pretty impressive.

🎬This is from a static MJ 7 image + HeyGen 4! The voice over is human performance, but the nuances the diffusion model picks up is pretty next level for the character. I masked in a video of the cars moving from Kling. Pretty impressive.

Dave Clark

11,224 次观看 • 1 年前

Contract is signed. It’s time to take the next steps toward this dream! Over the next 6 weeks we will be exploring what this game could be!

Contract is signed. It’s time to take the next steps toward this dream! Over the next 6 weeks we will be exploring what this game could be!

aDrive

25,699 次观看 • 1 年前

This is the best way to understand how ML models actually work! Use Drawdata to draw a 2D dataset in Jupyter. Use it to actively pick data from the widget and update the model as the data is being drawn! Fully interactive, real-time, and open-source!

This is the best way to understand how ML models actually work! Use Drawdata to draw a 2D dataset in Jupyter. Use it to actively pick data from the widget and update the model as the data is being drawn! Fully interactive, real-time, and open-source!

Daily Dose of Data Science

52,070 次观看 • 8 个月前