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Fable 5 built this real-time ocean scene directly in the browser using Three.js, WebGPU and TSL, with no engine and no baked assets. The interesting part is not just that the water looks good. The whole system is being simulated: wave spectrum, GPU FFT, foam generation and refracted-ray caustics,... show more

Token Gremlin

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21,725 次观看 • 1 个月前 •via X (Twitter)

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A guy from China just built a system that reshapes thousands of glowing particles into a jellyfish, a dragon, a statue, and a samurai. Just by moving his hands in front of a camera. Just a webcam reading his hand position. Every particle recalculates in real time. 60 frames per second. Not pre-rendered. Not a recording. Live. Clench both fists and the entire thing collapses into nothing. The whole setup runs on a regular camera and a GPU particle system. No special hardware. This is where hand tracking, computer vision, and real-time graphics have gotten. And most people haven't noticed.

A guy from China just built a system that reshapes thousands of glowing particles into a jellyfish, a dragon, a statue, and a samurai. Just by moving his hands in front of a camera. Just a webcam reading his hand position. Every particle recalculates in real time. 60 frames per second. Not pre-rendered. Not a recording. Live. Clench both fists and the entire thing collapses into nothing. The whole setup runs on a regular camera and a GPU particle system. No special hardware. This is where hand tracking, computer vision, and real-time graphics have gotten. And most people haven't noticed.

Vaibhav Sisinty

18,319 次观看 • 1 个月前

AI in robotics gets all the attention right now, but sometimes the most interesting work is very practical. Viet built a small vision system that counts potatoes on a conveyor belt. No giant dataset. No huge model. Just a clear problem and a smart setup. He used Ultralytics’ ObjectCounter, trained a tiny YOLO11 nano model, and because there was no potato dataset, he annotated a single frame with SAM 2 and trained from that. One frame. Still works across the whole video. It is a good reminder that useful AI in industry often looks like this. Focused. Lightweight. Solves a real task. If you work in manufacturing or robotics, these small systems are usually the fastest wins. They save time, reduce errors, and do not need massive infrastructure. Nice work, Viet. His projects: —- Weekly robotics and AI insights. Subscribe free:

AI in robotics gets all the attention right now, but sometimes the most interesting work is very practical. Viet built a small vision system that counts potatoes on a conveyor belt. No giant dataset. No huge model. Just a clear problem and a smart setup. He used Ultralytics’ ObjectCounter, trained a tiny YOLO11 nano model, and because there was no potato dataset, he annotated a single frame with SAM 2 and trained from that. One frame. Still works across the whole video. It is a good reminder that useful AI in industry often looks like this. Focused. Lightweight. Solves a real task. If you work in manufacturing or robotics, these small systems are usually the fastest wins. They save time, reduce errors, and do not need massive infrastructure. Nice work, Viet. His projects: —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

1,676,696 次观看 • 9 个月前

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

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 次观看 • 2 个月前

AI IS NO LONGER JUST WRITING CODE IT iS STARTING TO MOVE THINGS IN THE REAL WORLD. Someone just built a pizza delivery system where the drone does the driving No delivery car No traffic No driver sitting behind the wheel Just: -> Order comes in -> Drone picks up the pizza -> Flies directly to the destination -> Delivers it -> Returns And this is where the AI story gets interesting For years, the AI boom was mostly digital: > Chatbots > Coding agents > Image generation > AI music > AI video But the next phase is different AI is getting a body The same technology stack that started with models and GPUs is now moving into the physical world NVIDIA built the compute layer Researchers built the models Companies like Zoox are building autonomous vehicles And now we're seeing AI powered machines actually move through the real world The crazy part? We designed entire cities around the assumption that humans have to physically drive everything AI doesn't have that limitation Why send a pizza through 5 km of traffic when a machine can simply fly over it? The AI boom isn't just about replacing human work It's about removing constraints humans had to design around The next big AI companies might not live inside your browser They might be flying above your house Bookmark this so you wont miss the next delivery

AI IS NO LONGER JUST WRITING CODE IT iS STARTING TO MOVE THINGS IN THE REAL WORLD. Someone just built a pizza delivery system where the drone does the driving No delivery car No traffic No driver sitting behind the wheel Just: -> Order comes in -> Drone picks up the pizza -> Flies directly to the destination -> Delivers it -> Returns And this is where the AI story gets interesting For years, the AI boom was mostly digital: > Chatbots > Coding agents > Image generation > AI music > AI video But the next phase is different AI is getting a body The same technology stack that started with models and GPUs is now moving into the physical world NVIDIA built the compute layer Researchers built the models Companies like Zoox are building autonomous vehicles And now we're seeing AI powered machines actually move through the real world The crazy part? We designed entire cities around the assumption that humans have to physically drive everything AI doesn't have that limitation Why send a pizza through 5 km of traffic when a machine can simply fly over it? The AI boom isn't just about replacing human work It's about removing constraints humans had to design around The next big AI companies might not live inside your browser They might be flying above your house Bookmark this so you wont miss the next delivery

0xSlyth

13,437 次观看 • 17 天前

Ok, that's amazing. 🦄 A side by side three.js comparison - with GitMCP and without. GitMCP's story originally started from a tweet by Three.js about their large, non-LLM-digestable, documentation file. Ido Salomon and I ended up creating a cool generic documentation MCP server, but we didn't forget threejs and mrdoob. So we put it to the test. Using GitMCP, I gave this prompt to Cursor + Claude 3.7: "Build a Three.js scene featuring a controllable realistic person navigating a textured dynamic urban environment with realistic lighting and subtle bloom effects. Ensure keyboard controls (WASD) for movement." This is the result. To the right is the one-shot result with our MCP server. To the left is the result without it, based just on Cursor's limited knowledge. The video is pretty conclusive. 🤯 It's really amazing since Cursor already knows a lot about three.js, but with our dedicated documentation MCP server it just outputs better results. And for all other libraries out there - that are not included in Cursor - this is a total game changer. A huge shout out to Cloudflare Developers and Anni Wang, who worked with us yesterday to quickly insert new capabilities in their AutoRAG feature (that enables indexing large amount of documentation) according to our specific needs, and to troubleshoot issues. It was very helpful. Knowledge is power, and that applies for every coding assitant. And not just for three.js! Check out GitMCP for any library you're using - link in the next comment.

Ok, that's amazing. 🦄 A side by side three.js comparison - with GitMCP and without. GitMCP's story originally started from a tweet by Three.js about their large, non-LLM-digestable, documentation file. Ido Salomon and I ended up creating a cool generic documentation MCP server, but we didn't forget threejs and mrdoob. So we put it to the test. Using GitMCP, I gave this prompt to Cursor + Claude 3.7: "Build a Three.js scene featuring a controllable realistic person navigating a textured dynamic urban environment with realistic lighting and subtle bloom effects. Ensure keyboard controls (WASD) for movement." This is the result. To the right is the one-shot result with our MCP server. To the left is the result without it, based just on Cursor's limited knowledge. The video is pretty conclusive. 🤯 It's really amazing since Cursor already knows a lot about three.js, but with our dedicated documentation MCP server it just outputs better results. And for all other libraries out there - that are not included in Cursor - this is a total game changer. A huge shout out to Cloudflare Developers and Anni Wang, who worked with us yesterday to quickly insert new capabilities in their AutoRAG feature (that enables indexing large amount of documentation) according to our specific needs, and to troubleshoot issues. It was very helpful. Knowledge is power, and that applies for every coding assitant. And not just for three.js! Check out GitMCP for any library you're using - link in the next comment.

Liad Yosef

41,745 次观看 • 1 年前

BREAKING: BRIAN ARMSTRONG JUST CONFIRMED THE REVOLUTION ON CNBC. “A new financial system is being built and it’s not built by the banks. It’s built on crypto.” His words. Not mine. What does it mean? - Instant global settlements - Stronger, permissionless credit - 24/7 access to capital anywhere on earth - Open markets that no one can shut down This isn’t about coins pumping. This is about power shifting back to the people. Block by block, crypto is dismantling the old plumbing of finance and replacing it with something unbreakable. Armstrong isn’t predicting the future. He’s building it. You’re not speculating on a trend. You’re front-running a revolution. The old system is dying. The new one is already running. Choose your side.

BREAKING: BRIAN ARMSTRONG JUST CONFIRMED THE REVOLUTION ON CNBC. “A new financial system is being built and it’s not built by the banks. It’s built on crypto.” His words. Not mine. What does it mean? - Instant global settlements - Stronger, permissionless credit - 24/7 access to capital anywhere on earth - Open markets that no one can shut down This isn’t about coins pumping. This is about power shifting back to the people. Block by block, crypto is dismantling the old plumbing of finance and replacing it with something unbreakable. Armstrong isn’t predicting the future. He’s building it. You’re not speculating on a trend. You’re front-running a revolution. The old system is dying. The new one is already running. Choose your side.

Merlijn The Trader

136,388 次观看 • 8 个月前

There's a moment in the Tokyo Sketch where Jin is just sitting, running his fingers over his phone. Not scrolling. Not looking for anything. No smile for the camera. No performance. Just... existing. And it hit me: we don't see that enough. Not from him, not from anyone. A person, fully relaxed, doing nothing, thinking nothing in particular. We all need moments like that. Where no one expects anything from us. Where we're allowed to just be. Maybe that's the real gift of watching him, not the big stages, but the small, quiet seconds in between. 🌙

There's a moment in the Tokyo Sketch where Jin is just sitting, running his fingers over his phone. Not scrolling. Not looking for anything. No smile for the camera. No performance. Just... existing. And it hit me: we don't see that enough. Not from him, not from anyone. A person, fully relaxed, doing nothing, thinking nothing in particular. We all need moments like that. Where no one expects anything from us. Where we're allowed to just be. Maybe that's the real gift of watching him, not the big stages, but the small, quiet seconds in between. 🌙

𝖫𝖾𝖭𝖺 🌙 | 𝖩𝗂𝗇

59,448 次观看 • 2 个月前

YOM 🤝 Onicorn We’ve partnered with Onicorn the exclusive decentralised platform connecting the best investors, KOLs and companies in Web3. Onicorn is a curated network where serious capital, top KOLs and real projects actually meet no noise, no tourists. They only work with the best, and we’re proud to be in that room. Because YOM is building something the next internet needs: a decentralised GPU edge network powering real-time cloud gaming and AI compute. Idle GPUs turned into a global engine — cheaper, faster, and closer to the player than the hyperscalers can manage. Two teams with the same standard: quality over noise. This is just the start.

YOM 🤝 Onicorn We’ve partnered with Onicorn the exclusive decentralised platform connecting the best investors, KOLs and companies in Web3. Onicorn is a curated network where serious capital, top KOLs and real projects actually meet no noise, no tourists. They only work with the best, and we’re proud to be in that room. Because YOM is building something the next internet needs: a decentralised GPU edge network powering real-time cloud gaming and AI compute. Idle GPUs turned into a global engine — cheaper, faster, and closer to the player than the hyperscalers can manage. Two teams with the same standard: quality over noise. This is just the start.

YOM

15,736 次观看 • 2 个月前

World Models are the path for some AI Models in the future. But how can we efficiently train these models to not only see the world the way humans do but to see the world in a new and unique way. By visualizing, what is normally sequenced audio patterns, we can derive much more insights. Here we see Paganini in a visual form that can than be described and transcribed into a World Model. We can observe connections in a manner that may not have been clear prior to the digitalization of music and sound in this way. The company with the most valuable potential in building a World Model is Tesla. Not that this type of visualization is being used, but that the mechanisms are in place, and the technology is in place for the company to thrive in this new form of AI.

World Models are the path for some AI Models in the future. But how can we efficiently train these models to not only see the world the way humans do but to see the world in a new and unique way. By visualizing, what is normally sequenced audio patterns, we can derive much more insights. Here we see Paganini in a visual form that can than be described and transcribed into a World Model. We can observe connections in a manner that may not have been clear prior to the digitalization of music and sound in this way. The company with the most valuable potential in building a World Model is Tesla. Not that this type of visualization is being used, but that the mechanisms are in place, and the technology is in place for the company to thrive in this new form of AI.

Brian Roemmele

57,454 次观看 • 9 个月前

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.

Dustin

22,390 次观看 • 1 个月前

Building a personal knowledge base for my agents is increasingly where I spend my time these days. Like Andrej Karpathy, I also use Obsidian for my MD vaults. What's different in my approach is that I curate research papers on a daily basis and have actually tuned a Skill for months to find high-signal, relevant papers. I was reviewing and curating papers manually for some time, but now it's all automated as it has gotten so good at capturing what I consider the best of the best. There are so many papers these days, so this is a big deal. You all get to benefit from that with the papers I feature in my timeline and on DAIR.AI. The papers are indexed using tobi lutke qmd cli tool (all of it in markdown files along with useful metadata). So good for semantic search and surfacing insights, unlike anything out there. I am a visual person, so I then started to experiment with how to leverage this personal knowledge base of research papers inside my new interactive artifact generator (mcp tools inside my agent orchestrator system). The result is what you see in the clip. 100s of papers with all sorts of insights visualized. I keep track of research papers daily, so believe me when I tell you that this system is absolutely insane at surfacing insights. This is the result of months of tinkering on how to index research and leverage agent automations for wikification and robust documentation. But this is just the beginning. The visual artifact (which is interactive too) can be changed dynamically as I please. I can prompt my agent to throw any data at it. I can add different views to the data. Different interactions. I feel like this is the most personalized research system I have ever built and used, and it's not even close. The knowledge that the agents are able to surface from this basic setup is already extremely useful as I experiment with new agentic engineering concepts. I feel like this knowledge layer and the higher-level ones I am working on will allow me to maximize other automation tools like autoresearch. The research is only as good as the research questions. And the research questions are only as good as the insights the agents have access to. Where I am spending time now is on how to make this more actionable. I am obsessed about the search problem here. The automations, autoresearch, ralph research loop (I built one months ago) are easier to build but are only as good as what you feed them. Work in progress. More updates soon. Back to building.

Building a personal knowledge base for my agents is increasingly where I spend my time these days. Like Andrej Karpathy, I also use Obsidian for my MD vaults. What's different in my approach is that I curate research papers on a daily basis and have actually tuned a Skill for months to find high-signal, relevant papers. I was reviewing and curating papers manually for some time, but now it's all automated as it has gotten so good at capturing what I consider the best of the best. There are so many papers these days, so this is a big deal. You all get to benefit from that with the papers I feature in my timeline and on DAIR.AI. The papers are indexed using tobi lutke qmd cli tool (all of it in markdown files along with useful metadata). So good for semantic search and surfacing insights, unlike anything out there. I am a visual person, so I then started to experiment with how to leverage this personal knowledge base of research papers inside my new interactive artifact generator (mcp tools inside my agent orchestrator system). The result is what you see in the clip. 100s of papers with all sorts of insights visualized. I keep track of research papers daily, so believe me when I tell you that this system is absolutely insane at surfacing insights. This is the result of months of tinkering on how to index research and leverage agent automations for wikification and robust documentation. But this is just the beginning. The visual artifact (which is interactive too) can be changed dynamically as I please. I can prompt my agent to throw any data at it. I can add different views to the data. Different interactions. I feel like this is the most personalized research system I have ever built and used, and it's not even close. The knowledge that the agents are able to surface from this basic setup is already extremely useful as I experiment with new agentic engineering concepts. I feel like this knowledge layer and the higher-level ones I am working on will allow me to maximize other automation tools like autoresearch. The research is only as good as the research questions. And the research questions are only as good as the insights the agents have access to. Where I am spending time now is on how to make this more actionable. I am obsessed about the search problem here. The automations, autoresearch, ralph research loop (I built one months ago) are easier to build but are only as good as what you feed them. Work in progress. More updates soon. Back to building.

elvis

466,109 次观看 • 4 个月前

This scene shows the arrest of a young woman from the city of Fardis in Iran, the city where I grew up. There is no information about her fate after she was taken into custody by the security forces of the ruling government in Iran. But our message is not only about this crime. It is addressed to you, the leaders and officials of the world. Remember this: when we were suffering under the violence of this government, you remained silent. Your silence was not neutrality, but a deliberate turning away from human suffering. With or without you, we will bring down this system built on violence, because the will of a people cannot be suppressed forever. But history will not forget that in the test of conscience, morality, and human responsibility, you failed. #IranMassacre #IranRevoIution2026 #IranProtests2026

This scene shows the arrest of a young woman from the city of Fardis in Iran, the city where I grew up. There is no information about her fate after she was taken into custody by the security forces of the ruling government in Iran. But our message is not only about this crime. It is addressed to you, the leaders and officials of the world. Remember this: when we were suffering under the violence of this government, you remained silent. Your silence was not neutrality, but a deliberate turning away from human suffering. With or without you, we will bring down this system built on violence, because the will of a people cannot be suppressed forever. But history will not forget that in the test of conscience, morality, and human responsibility, you failed. #IranMassacre #IranRevoIution2026 #IranProtests2026

Ahmad Batebi 🛡️ 🇮🇷 🇺🇸

25,360 次观看 • 6 个月前

If you think OpenAI Sora is a creative toy like DALLE, ... think again. Sora is a data-driven physics engine. It is a simulation of many worlds, real or fantastical. The simulator learns intricate rendering, "intuitive" physics, long-horizon reasoning, and semantic grounding, all by some denoising and gradient maths. I won't be surprised if Sora is trained on lots of synthetic data using Unreal Engine 5. It has to be! Let's breakdown the following video. Prompt: "Photorealistic closeup video of two pirate ships battling each other as they sail inside a cup of coffee." - The simulator instantiates two exquisite 3D assets: pirate ships with different decorations. Sora has to solve text-to-3D implicitly in its latent space. - The 3D objects are consistently animated as they sail and avoid each other's paths. - Fluid dynamics of the coffee, even the foams that form around the ships. Fluid simulation is an entire sub-field of computer graphics, which traditionally requires very complex algorithms and equations. - Photorealism, almost like rendering with raytracing. - The simulator takes into account the small size of the cup compared to oceans, and applies tilt-shift photography to give a "minuscule" vibe. - The semantics of the scene does not exist in the real world, but the engine still implements the correct physical rules that we expect. Next up: add more modalities and conditioning, then we have a full data-driven UE that will replace all the hand-engineered graphics pipelines.

If you think OpenAI Sora is a creative toy like DALLE, ... think again. Sora is a data-driven physics engine. It is a simulation of many worlds, real or fantastical. The simulator learns intricate rendering, "intuitive" physics, long-horizon reasoning, and semantic grounding, all by some denoising and gradient maths. I won't be surprised if Sora is trained on lots of synthetic data using Unreal Engine 5. It has to be! Let's breakdown the following video. Prompt: "Photorealistic closeup video of two pirate ships battling each other as they sail inside a cup of coffee." - The simulator instantiates two exquisite 3D assets: pirate ships with different decorations. Sora has to solve text-to-3D implicitly in its latent space. - The 3D objects are consistently animated as they sail and avoid each other's paths. - Fluid dynamics of the coffee, even the foams that form around the ships. Fluid simulation is an entire sub-field of computer graphics, which traditionally requires very complex algorithms and equations. - Photorealism, almost like rendering with raytracing. - The simulator takes into account the small size of the cup compared to oceans, and applies tilt-shift photography to give a "minuscule" vibe. - The semantics of the scene does not exist in the real world, but the engine still implements the correct physical rules that we expect. Next up: add more modalities and conditioning, then we have a full data-driven UE that will replace all the hand-engineered graphics pipelines.

Jim Fan

6,183,111 次观看 • 2 年前

#BREAKING 🔥‼️ The Syrian jihadist rebels have just seized Aleppo from Assad regime. They jailbreaked and released captured ISIS militants. They are chanting Allah Akbar together in Aleppo. Technically it’s a good thing that the regime is crumbling down, but there’s no need to cheer for literal ISIS-like Islamists. Replacing Assad with Salafi-Jihadi groups is replacing bad with bad, if not even worse. The Middle East doesn’t need more Islamism, but more secularism. Just pray for the Christian, Druze and Yazidi minority of Aleppo because if Jihadists chant Allah Akbar, this ain't a good sign in the middle east.

#BREAKING 🔥‼️ The Syrian jihadist rebels have just seized Aleppo from Assad regime. They jailbreaked and released captured ISIS militants. They are chanting Allah Akbar together in Aleppo. Technically it’s a good thing that the regime is crumbling down, but there’s no need to cheer for literal ISIS-like Islamists. Replacing Assad with Salafi-Jihadi groups is replacing bad with bad, if not even worse. The Middle East doesn’t need more Islamism, but more secularism. Just pray for the Christian, Druze and Yazidi minority of Aleppo because if Jihadists chant Allah Akbar, this ain't a good sign in the middle east.

Frankie™️🦅

73,688 次观看 • 1 年前

A guy from China is reshaping glowing particles into a jellyfish, a statue, a dragon, and a samurai just by moving his hands in front of a camera No controller, no mouse, no keyboard Just a camera reading his hand position and a particle system recalculating thousands of points in real time, morphing one shape straight into the next Clench both fists at the end, and everything collapses into nothing This is running live at 60fps, not pre-rendered The entire scene sits inside a wireframe box tracking every motion as raw geometry reshapes into whatever his hands tell it to become

A guy from China is reshaping glowing particles into a jellyfish, a statue, a dragon, and a samurai just by moving his hands in front of a camera No controller, no mouse, no keyboard Just a camera reading his hand position and a particle system recalculating thousands of points in real time, morphing one shape straight into the next Clench both fists at the end, and everything collapses into nothing This is running live at 60fps, not pre-rendered The entire scene sits inside a wireframe box tracking every motion as raw geometry reshapes into whatever his hands tell it to become

pulmencr

50,834 次观看 • 1 个月前

This video is not of a 3-ring circus! This is what the activists from the Gaza flotilla are doing on an IDF ship. While they’re already telling the world that they were ‘violently’ arrested by the IDF - you can see here exactly what their arrest looks like and how ‘vulnerable’ they are... By the way, would you expect the operators of a flotilla that is on its way to provide aid to "hungry and poor people who are going through genocide" to behave like this? But this is the truth... It's all a provocation. This is not an aid flotilla, this is a condom flotilla, and the people on it are not human rights activists. They’re paid clowns who are also useful idiots!

This video is not of a 3-ring circus! This is what the activists from the Gaza flotilla are doing on an IDF ship. While they’re already telling the world that they were ‘violently’ arrested by the IDF - you can see here exactly what their arrest looks like and how ‘vulnerable’ they are... By the way, would you expect the operators of a flotilla that is on its way to provide aid to "hungry and poor people who are going through genocide" to behave like this? But this is the truth... It's all a provocation. This is not an aid flotilla, this is a condom flotilla, and the people on it are not human rights activists. They’re paid clowns who are also useful idiots!

יוסף חדאד - Yoseph Haddad

27,572 次观看 • 4 个月前

The most interesting part of this robot is not the arm. It is the gripper. Instead of pushing the whole robot faster, this setup adds speed at the end effector. The gripper itself becomes a moving axis that can accelerate independently of the arm. That changes the physics of the system. • Faster cycle times without stressing the robot structure • Less inertia to fight against • Motion where it actually matters, at the tool center point It is a reminder that many performance limits in robotics are not solved by bigger motors, but by smarter mechanics. ——- Weekly robotics and AI insights. Subscribe free:

The most interesting part of this robot is not the arm. It is the gripper. Instead of pushing the whole robot faster, this setup adds speed at the end effector. The gripper itself becomes a moving axis that can accelerate independently of the arm. That changes the physics of the system. • Faster cycle times without stressing the robot structure • Less inertia to fight against • Motion where it actually matters, at the tool center point It is a reminder that many performance limits in robotics are not solved by bigger motors, but by smarter mechanics. ——- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

46,721 次观看 • 18 天前