正在加载视频...

视频加载失败

返回首页

Fei-Fei Li ( Fei-Fei Li ) beautifully explains Robotics. She defines robotics not by form, like humanoids or cars, but by function: they are any "embodied machines" that must perceive, understand, and act within a physical, 3D space. This core requirement is "spatial intelligence," the unifying principle of all...

rohanpaul_ai's profile picture

Rohan Paul

152,722 subscribers

51,174 次观看 • 4 个月前 •via X (Twitter)

科学技术
LIVE

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

📁 Fei-Fei Li founder of World Labs, says the next leap in AI is not language. Human intelligence does not just speak, it moves, perceives, and acts in the physical world. Spatial intelligence is the real core of intelligence. From text to space, from models to 3D and 4D worlds, from understanding words to interacting with reality. The next chapter is not read, it is inhabited.
1:41

📁 Fei-Fei Li founder of World Labs, says the next leap in AI is not language. Human intelligence does not just speak, it moves, perceives, and acts in the physical world. Spatial intelligence is the real core of intelligence. From text to space, from models to 3D and 4D worlds, from understanding words to interacting with reality. The next chapter is not read, it is inhabited.

Jon Hernandez

20,592 次观看 • 6 个月前

World Labs CEO Dr. Fei-Fei Li & SceniX Co-Founder Yunzhu Li on the data bottleneck in robotics and how world models help: "The lack of data in training, the lack of data in evaluation, this is very, very different from language models, where data is abundant on the internet." "And we know that in order for robotics to work, we have to somehow unlock the power of scaling law. But where does that come from?" "It's a profound problem that everybody's battling with in robotics." "We see a lot of unlock in being able to do this whole process through the modeling of the environments." "Being able to create these digital worlds... that's just going to unlock so much more potential for being able to replace all the costly and the unsafe data in the real environments with the data generated from the worlds for robots to be able to do scalable learning and evaluations." Fei-Fei Li Yunzhu Li martin_casado
1:49

World Labs CEO Dr. Fei-Fei Li & SceniX Co-Founder Yunzhu Li on the data bottleneck in robotics and how world models help: "The lack of data in training, the lack of data in evaluation, this is very, very different from language models, where data is abundant on the internet." "And we know that in order for robotics to work, we have to somehow unlock the power of scaling law. But where does that come from?" "It's a profound problem that everybody's battling with in robotics." "We see a lot of unlock in being able to do this whole process through the modeling of the environments." "Being able to create these digital worlds... that's just going to unlock so much more potential for being able to replace all the costly and the unsafe data in the real environments with the data generated from the worlds for robots to be able to do scalable learning and evaluations." Fei-Fei Li Yunzhu Li martin_casado

a16z

76,010 次观看 • 1 个月前

Fei-Fei Li on what simulation can do for robotics that real-world data can't: "You play out events that haven't happened, or cannot happen... And while you play it out, you learn how to act in it." "That's really important in robotics, because we cannot possibly have enough real-world data for that." "Here is a real life example: the industry of self-driving cars. Waymo has officially said they use billions of hours of simulation." "Cars are the simplest kind of robots. So clearly simulation plays a huge role in robotic learning." Fei-Fei Li Yunzhu Li World Labs martin_casado
1:30

Fei-Fei Li on what simulation can do for robotics that real-world data can't: "You play out events that haven't happened, or cannot happen... And while you play it out, you learn how to act in it." "That's really important in robotics, because we cannot possibly have enough real-world data for that." "Here is a real life example: the industry of self-driving cars. Waymo has officially said they use billions of hours of simulation." "Cars are the simplest kind of robots. So clearly simulation plays a huge role in robotic learning." Fei-Fei Li Yunzhu Li World Labs martin_casado

a16z

35,480 次观看 • 1 个月前

World Labs CEO Dr. Fei-Fei Li explains says "world model" has become an overloaded term & explains what each kind of world model does: "Right now there are three ways of calling world models when it comes to spatial intelligence." "One is what I call a renderer, when the model puts beautiful pixels on the screen." "Another kind of world model is what we call a planner. That is more for machines, more for robots." "The third kind, which I think is the linchpin of the three, is a simulator." "A simulator could become a renderer. The simulator could become a planner. But this layer is a huge critical path to unlock spatial intelligence. And that's what World Labs is working on." Fei-Fei Li at Bloomberg Tech live with Emily Chang
2:08

World Labs CEO Dr. Fei-Fei Li explains says "world model" has become an overloaded term & explains what each kind of world model does: "Right now there are three ways of calling world models when it comes to spatial intelligence." "One is what I call a renderer, when the model puts beautiful pixels on the screen." "Another kind of world model is what we call a planner. That is more for machines, more for robots." "The third kind, which I think is the linchpin of the three, is a simulator." "A simulator could become a renderer. The simulator could become a planner. But this layer is a huge critical path to unlock spatial intelligence. And that's what World Labs is working on." Fei-Fei Li at Bloomberg Tech live with Emily Chang

a16z

112,217 次观看 • 2 个月前

World Labs CEO Dr. Fei-Fei Li says AI must change how we teach and evaluate students: "AI must change learning. AI must change K-16 learning." "The most precious resource of our entire world is human capital." "When we have gotten the technology that can answer standardized tests... when AI can do better than an average human, it's not about humans are bad. It's about we need to change the education system." "We need to change how we evaluate. We need to change the way we empower teachers to educate the next generation of students where they can use these tools, be empowered, and do things that we can never imagine." "All of the kids today should not be scared of AI. They should feel the human agency to lead AI, to use AI in the right way, and to use AI to make the impact that they want to make for the world." Fei-Fei Li at Bloomberg Tech live with Emily Chang
1:35

World Labs CEO Dr. Fei-Fei Li says AI must change how we teach and evaluate students: "AI must change learning. AI must change K-16 learning." "The most precious resource of our entire world is human capital." "When we have gotten the technology that can answer standardized tests... when AI can do better than an average human, it's not about humans are bad. It's about we need to change the education system." "We need to change how we evaluate. We need to change the way we empower teachers to educate the next generation of students where they can use these tools, be empowered, and do things that we can never imagine." "All of the kids today should not be scared of AI. They should feel the human agency to lead AI, to use AI in the right way, and to use AI to make the impact that they want to make for the world." Fei-Fei Li at Bloomberg Tech live with Emily Chang

a16z

81,845 次观看 • 2 个月前

Dr. Fei-Fei Li just called out the biggest blind spot in the entire AI industry. We have been building half of human intelligence. And calling it the finish line. Li: “If you look at human intelligence, it pretty much boils down to two buckets.” The first bucket is language. Symbolic reasoning. Communication. The ability to think in words and abstractions. That’s what every major AI lab has spent the last decade building. The second bucket is the one the industry has almost entirely ignored. Li: “We call that in AI spatial intelligence.” How humans and animals perceive, navigate, and interact with the three-dimensional physical world. How we reach for objects. How we move through space. How we build and manipulate physical reality. From painting masterpieces to constructing the pyramids, non-verbal spatial intelligence is what actually shapes the world. Language describes reality. Spatial intelligence acts on it. And the gap between those two things is the gap between a chatbot and a robot. Li: “When this technology is ready, the robotic revolution is gonna start. We’re already seeing that trend.” Every robot is a moving agent. Every moving agent requires spatial intelligence to function in the real world. The humanoid robots being deployed in factories right now are hitting the ceiling of what language models alone can power. Spatial intelligence is the unlock. But Li didn’t stop at robotics. Li: “From a geopolitics point of view, this is part of the technology that goes straight into weapons.” Autonomous drone swarms. Battlefield navigation. Physical target acquisition without human oversight. Every military application of AI that operates in the real world runs on spatial intelligence. The nation that masters the transition from static text to dynamic three-dimensional perception doesn’t just win the software race. It commands the physical battlefield. The AI arms race just broke out of the data center. It’s operating in three dimensions now.
3:08

Dr. Fei-Fei Li just called out the biggest blind spot in the entire AI industry. We have been building half of human intelligence. And calling it the finish line. Li: “If you look at human intelligence, it pretty much boils down to two buckets.” The first bucket is language. Symbolic reasoning. Communication. The ability to think in words and abstractions. That’s what every major AI lab has spent the last decade building. The second bucket is the one the industry has almost entirely ignored. Li: “We call that in AI spatial intelligence.” How humans and animals perceive, navigate, and interact with the three-dimensional physical world. How we reach for objects. How we move through space. How we build and manipulate physical reality. From painting masterpieces to constructing the pyramids, non-verbal spatial intelligence is what actually shapes the world. Language describes reality. Spatial intelligence acts on it. And the gap between those two things is the gap between a chatbot and a robot. Li: “When this technology is ready, the robotic revolution is gonna start. We’re already seeing that trend.” Every robot is a moving agent. Every moving agent requires spatial intelligence to function in the real world. The humanoid robots being deployed in factories right now are hitting the ceiling of what language models alone can power. Spatial intelligence is the unlock. But Li didn’t stop at robotics. Li: “From a geopolitics point of view, this is part of the technology that goes straight into weapons.” Autonomous drone swarms. Battlefield navigation. Physical target acquisition without human oversight. Every military application of AI that operates in the real world runs on spatial intelligence. The nation that masters the transition from static text to dynamic three-dimensional perception doesn’t just win the software race. It commands the physical battlefield. The AI arms race just broke out of the data center. It’s operating in three dimensions now.

Dustin

122,781 次观看 • 6 个月前

Today at Stanford, Fei-Fei Li (Fei-Fei Li),Cofounder/CEO World Labs, gave one of the clearest explanations I’ve heard of what a World Model really is. She broke it down into three layers: 1️⃣ Rendering — What does the world look like? This is where most of today’s video generation models operate: generating increasingly realistic and beautiful pixels. The question is: Can AI generate what the world looks like? The primary consumer is humans. 2️⃣ Simulation — How does the world actually work? Fei-Fei gave a simple example: “How will this bottle move? If I pour the water out, how will the water flow?” This goes far beyond generating something that looks realistic. The model needs to understand physics, spatial relationships, cause and effect, and how the world changes over time. The consumers are both humans and machines. 3️⃣ Planning — What should happen next? This is where things get really interesting. AI doesn't just render the world or simulate what might happen. It uses its understanding of the world to decide: What should I do next? At this layer, the primary consumer is the machine itself. And this connects directly to two enormous opportunities: Autonomous driving and robotics. The progression is powerful: Rendering → Simulation → Planning The real promise of World Models isn't simply generating better videos. It's building AI that can understand the world, predict what happens next, and ultimately take intelligent action in the physical world.
3:54

Today at Stanford, Fei-Fei Li (Fei-Fei Li),Cofounder/CEO World Labs, gave one of the clearest explanations I’ve heard of what a World Model really is. She broke it down into three layers: 1️⃣ Rendering — What does the world look like? This is where most of today’s video generation models operate: generating increasingly realistic and beautiful pixels. The question is: Can AI generate what the world looks like? The primary consumer is humans. 2️⃣ Simulation — How does the world actually work? Fei-Fei gave a simple example: “How will this bottle move? If I pour the water out, how will the water flow?” This goes far beyond generating something that looks realistic. The model needs to understand physics, spatial relationships, cause and effect, and how the world changes over time. The consumers are both humans and machines. 3️⃣ Planning — What should happen next? This is where things get really interesting. AI doesn't just render the world or simulate what might happen. It uses its understanding of the world to decide: What should I do next? At this layer, the primary consumer is the machine itself. And this connects directly to two enormous opportunities: Autonomous driving and robotics. The progression is powerful: Rendering → Simulation → Planning The real promise of World Models isn't simply generating better videos. It's building AI that can understand the world, predict what happens next, and ultimately take intelligent action in the physical world.

PaulFang

11,155 次观看 • 22 天前

Modern AI is confined to the digital world. At Skild AI, we are building towards AGI for the real world, unconstrained by robot type or task — a single, omni-bodied brain. Today, we are sharing our journey, starting with early milestones, with more to come in the weeks ahead. Our Mission: Artificial General Intelligence grounded in the physical world. We believe AGI that can truly understand and reason in the real world can only be built through grounding in the physical world. Our Vision: Any robot, Any task, One brain. We tackle robotics in its full generality – building a continually improving, omni-bodied brain that can control any hardware for any task. Who are we? A passionate group of scientists & engineers driven by our shared vision. We have been researching AI and robotics for more than a decade. Our team includes pioneers of self-supervised learning, curiosity-driven exploration, end-to-end sim2real for visual locomotion, dexterous manipulation, learning from human videos, robot parkour, and many more. Many of these works have won awards at top-tier AI and Robotics conferences. Our team has also built production-ready systems at Anduril, Tesla, Nvidia, Meta, Kitty Hawk, Google, Everyday Robotics, and Amazon. Join us in our mission to build the robot brains of tomorrow.
2:48

Modern AI is confined to the digital world. At Skild AI, we are building towards AGI for the real world, unconstrained by robot type or task — a single, omni-bodied brain. Today, we are sharing our journey, starting with early milestones, with more to come in the weeks ahead. Our Mission: Artificial General Intelligence grounded in the physical world. We believe AGI that can truly understand and reason in the real world can only be built through grounding in the physical world. Our Vision: Any robot, Any task, One brain. We tackle robotics in its full generality – building a continually improving, omni-bodied brain that can control any hardware for any task. Who are we? A passionate group of scientists & engineers driven by our shared vision. We have been researching AI and robotics for more than a decade. Our team includes pioneers of self-supervised learning, curiosity-driven exploration, end-to-end sim2real for visual locomotion, dexterous manipulation, learning from human videos, robot parkour, and many more. Many of these works have won awards at top-tier AI and Robotics conferences. Our team has also built production-ready systems at Anduril, Tesla, Nvidia, Meta, Kitty Hawk, Google, Everyday Robotics, and Amazon. Join us in our mission to build the robot brains of tomorrow.

Skild AI

383,840 次观看 • 1 年前

Dr. Fei-Fei Li (Fei-Fei Li) is known as the “godmother of AI.” For the past two decades, she’s been at the center of AI’s most significant breakthroughs, including: - Spearheading ImageNet, the dataset that sparked the AI explosion we’re living through right now. - Leading work at Stanford Artificial Intelligence Laboratory (SAIL) - Serving as Chief Scientist of AI/ML at Google Cloud - Co-founding Stanford’s Institute for Human-Centered AI - Serving on the United Nations AI Scientific Advisory Board - Being named as Time's 100 most influential people in AI In this conversation, Fei-Fei shares the rarely told history of how we got to today—and what comes next. We discuss: 🔸 The backstory on ImageNet 🔸 Why robotics faces unique challenges compared with language models and what’s needed to overcome them 🔸 Why Fei-Fei believes AI won’t replace humans but will require us to take responsibility for ourselves 🔸 Why world models and spatial intelligence represent the next frontier in AI, beyond large language models 🔸 The surprising applications of Marble, from movie production to psychological research 🔸 How to participate in AI regardless of your role 🔸 Much more Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 Figma Make — A prompt-to-code tool for making ideas real: 🏆 Justworks — The all-in-one HR solution for managing your small business with confidence: 🏆 Sinch — Build messaging, email, and calling into your product:
1:40

Dr. Fei-Fei Li (Fei-Fei Li) is known as the “godmother of AI.” For the past two decades, she’s been at the center of AI’s most significant breakthroughs, including: - Spearheading ImageNet, the dataset that sparked the AI explosion we’re living through right now. - Leading work at Stanford Artificial Intelligence Laboratory (SAIL) - Serving as Chief Scientist of AI/ML at Google Cloud - Co-founding Stanford’s Institute for Human-Centered AI - Serving on the United Nations AI Scientific Advisory Board - Being named as Time's 100 most influential people in AI In this conversation, Fei-Fei shares the rarely told history of how we got to today—and what comes next. We discuss: 🔸 The backstory on ImageNet 🔸 Why robotics faces unique challenges compared with language models and what’s needed to overcome them 🔸 Why Fei-Fei believes AI won’t replace humans but will require us to take responsibility for ourselves 🔸 Why world models and spatial intelligence represent the next frontier in AI, beyond large language models 🔸 The surprising applications of Marble, from movie production to psychological research 🔸 How to participate in AI regardless of your role 🔸 Much more Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 Figma Make — A prompt-to-code tool for making ideas real: 🏆 Justworks — The all-in-one HR solution for managing your small business with confidence: 🏆 Sinch — Build messaging, email, and calling into your product:

Lenny Rachitsky

250,455 次观看 • 9 个月前

🤖 Three Japanese innovators just proved that the future of robotics can be printed — not assembled. 🇯🇵✨ I find this incredible. Japan has always led the world in robotics, but this breakthrough feels different — more creative, more human. A team of three brilliant minds has built a fully functional 3D-printed robotic system, rethinking everything from the gears to the frame. The result? Robots that are lighter, faster to produce, and easier to customize than ever before. What fascinates me is how this blends engineering and imagination — where design isn’t constrained by parts, but shaped by possibilities. This could change how we build robots, how we teach automation, and how quickly we bring new ideas to life. Would you trust a 3D-printed robot to work alongside you? #AI #Innovation #Technology #Robotics #3DPrinting #Automation #FutureOfWork #Engineering
0:59

🤖 Three Japanese innovators just proved that the future of robotics can be printed — not assembled. 🇯🇵✨ I find this incredible. Japan has always led the world in robotics, but this breakthrough feels different — more creative, more human. A team of three brilliant minds has built a fully functional 3D-printed robotic system, rethinking everything from the gears to the frame. The result? Robots that are lighter, faster to produce, and easier to customize than ever before. What fascinates me is how this blends engineering and imagination — where design isn’t constrained by parts, but shaped by possibilities. This could change how we build robots, how we teach automation, and how quickly we bring new ideas to life. Would you trust a 3D-printed robot to work alongside you? #AI #Innovation #Technology #Robotics #3DPrinting #Automation #FutureOfWork #Engineering

Pascal Bornet

518,119 次观看 • 8 个月前

America. Europe. Africa. Asia. Oceania. More than 250,000 real-world locations across 120+ countries have already been transformed into ultra high quality 3D Gaussian Splats by Over the Reality. From city centers and museums to beaches, mountains, and historical landmarks, every mapping created by our community contributes to a growing machine-readable representation of the physical world. This scene started as a simple Insta360 X5 recording and was transformed into a digital twin, where geometry, textures, and spatial structure are preserved and can be used by AI, Robotics, VPS, XR, and next-generation world models. This is what city-scale 3D mapping looks like. The link to become an Insta360 X5 mapper is in the first comment. 👇
1:22

America. Europe. Africa. Asia. Oceania. More than 250,000 real-world locations across 120+ countries have already been transformed into ultra high quality 3D Gaussian Splats by Over the Reality. From city centers and museums to beaches, mountains, and historical landmarks, every mapping created by our community contributes to a growing machine-readable representation of the physical world. This scene started as a simple Insta360 X5 recording and was transformed into a digital twin, where geometry, textures, and spatial structure are preserved and can be used by AI, Robotics, VPS, XR, and next-generation world models. This is what city-scale 3D mapping looks like. The link to become an Insta360 X5 mapper is in the first comment. 👇

Over the Reality 🌐

19,378 次观看 • 2 个月前

🚀 Announcing Echo — our new frontier model for 3D world generation. Echo turns a simple text prompt or image into a fully explorable, 3D-consistent world. Instead of disconnected views, the result is a single, coherent spatial representation you can move through freely. This is part of a bigger shift in AI: from generating pixels and tokens to generating spaces. Echo predicts a geometry-grounded 3D scene at metric scale, meaning every novel view, depth map, and interaction comes from the same underlying world — not independent hallucinations. Once generated, the world is interactive in real time. You control the camera, explore from any angle, and render instantly — even on low-end hardware, directly in the browser. High-quality 3D world exploration is no longer gated by expensive equipment. Under the hood, Echo infers a physically grounded 3D representation and converts it into a renderable format. For our web demo, we use 3D Gaussian Splatting (3DGS) for fast, GPU-friendly rendering — but the representation itself is flexible and can be easily adapted. Why this matters: consistent 3D worlds unlock real workflows — digital twins, 3D design, game environments, robotics simulation, and more. From a single photo or a line of text, Echo builds worlds that are reliable, editable, and spatially faithful. Echo also enables scene editing and restyling. Change materials, remove or add objects, explore design variations — all while preserving global 3D consistency. Editing no longer breaks the world. This is only the beginning. Echo is the foundation for future world models with dynamics, physical reasoning, and richer interaction — environments that don’t just look right, but behave right. Explore the generated worlds on our website and sign up for the closed beta. The era of spatial intelligence starts here. 🌍 #Echo #WorldModels #SpatialAI #3DFoundationModels Check it out:
1:07

🚀 Announcing Echo — our new frontier model for 3D world generation. Echo turns a simple text prompt or image into a fully explorable, 3D-consistent world. Instead of disconnected views, the result is a single, coherent spatial representation you can move through freely. This is part of a bigger shift in AI: from generating pixels and tokens to generating spaces. Echo predicts a geometry-grounded 3D scene at metric scale, meaning every novel view, depth map, and interaction comes from the same underlying world — not independent hallucinations. Once generated, the world is interactive in real time. You control the camera, explore from any angle, and render instantly — even on low-end hardware, directly in the browser. High-quality 3D world exploration is no longer gated by expensive equipment. Under the hood, Echo infers a physically grounded 3D representation and converts it into a renderable format. For our web demo, we use 3D Gaussian Splatting (3DGS) for fast, GPU-friendly rendering — but the representation itself is flexible and can be easily adapted. Why this matters: consistent 3D worlds unlock real workflows — digital twins, 3D design, game environments, robotics simulation, and more. From a single photo or a line of text, Echo builds worlds that are reliable, editable, and spatially faithful. Echo also enables scene editing and restyling. Change materials, remove or add objects, explore design variations — all while preserving global 3D consistency. Editing no longer breaks the world. This is only the beginning. Echo is the foundation for future world models with dynamics, physical reasoning, and richer interaction — environments that don’t just look right, but behave right. Explore the generated worlds on our website and sign up for the closed beta. The era of spatial intelligence starts here. 🌍 #Echo #WorldModels #SpatialAI #3DFoundationModels Check it out:

SpAItial AI

176,524 次观看 • 8 个月前

A few months ago we set out to understand exactly how our models can be used to accelerate progress in robotics and other AI systems that don’t just represent the world, but are actually able to interact with it. We’ve been collaborating with leading companies in the space and we’ve developed an initial approach that we're now opening up to accelerate development across the industry. Our fifth announcement is GWM Robotics. GWM Robotics is a learned simulator that generates synthetic data for scalable robot training and policy evaluation, removing the bottlenecks of physical hardware.
1:14

A few months ago we set out to understand exactly how our models can be used to accelerate progress in robotics and other AI systems that don’t just represent the world, but are actually able to interact with it. We’ve been collaborating with leading companies in the space and we’ve developed an initial approach that we're now opening up to accelerate development across the industry. Our fifth announcement is GWM Robotics. GWM Robotics is a learned simulator that generates synthetic data for scalable robot training and policy evaluation, removing the bottlenecks of physical hardware.

Runway

35,040 次观看 • 8 个月前

This simulated Earth matrix is layers upon infinite layers of microcsoms and macrocosms in the physical 3D plane. The Golden Ratio and Fibonacci sequence is seen all throughout nature in small scales like seashells, pinecones, the human ear and even as ultra small as human DNA itself and extending to much larger scales like The Earth/moon ratio seen in this video. Yes, this place was created by something but it does not prove the existence of the christian God from the Bible. It simply proves we are a part of a much larger, highly advanced well-oiled machine.
2:21

This simulated Earth matrix is layers upon infinite layers of microcsoms and macrocosms in the physical 3D plane. The Golden Ratio and Fibonacci sequence is seen all throughout nature in small scales like seashells, pinecones, the human ear and even as ultra small as human DNA itself and extending to much larger scales like The Earth/moon ratio seen in this video. Yes, this place was created by something but it does not prove the existence of the christian God from the Bible. It simply proves we are a part of a much larger, highly advanced well-oiled machine.

𝒦𝑒𝓁𝓁𝓎࿎☽

35,999 次观看 • 4 个月前

The mode of existence of the world can be understood as the set of its fundamental characteristics that make both its existence and its transformations possible. In other words, what basic properties must a world possess for its evolutionary existence to be possible at all? Among the key aspects, several can be identified: (a) physical space must be either finite or infinite; (b) if infinite, this infinity must be either spherical or linear; (c) physical reality must possess the capacity to generate vast, stable structures and highly complex phenomena — which, according to our observations, it indeed does; (d) this capacity, as an active self-organizing property, must either have a beginning or be beginningless — that is, it either existed eternally, or the world was originally maximally simple and static before this property spontaneously emerged. : The author proposes that the mode of existence of the world is defined by a set of fundamental characteristics that make both its persistence and its transformations possible. In other words, for any reality capable of evolutionary development to arise, certain basic properties must be present. Physical space must be either finite or infinite. If infinite, its geometry must be either spherical or linear. Physical reality must possess the inherent capacity to generate vast, stable structures and highly complex phenomena, as we observe in our own universe. Finally, this self-organizing property must either have existed eternally or have emerged spontaneously at a certain moment from an originally simple and static state. This framework invites us to consider the minimal conditions required for a universe like ours to evolve intelligence and complexity. It frames the question of cosmic origins not as a mystery of creation from nothing, but as an inquiry into the necessary and sufficient properties of matter and space that allow reality to unfold as it has.
0:57

The mode of existence of the world can be understood as the set of its fundamental characteristics that make both its existence and its transformations possible. In other words, what basic properties must a world possess for its evolutionary existence to be possible at all? Among the key aspects, several can be identified: (a) physical space must be either finite or infinite; (b) if infinite, this infinity must be either spherical or linear; (c) physical reality must possess the capacity to generate vast, stable structures and highly complex phenomena — which, according to our observations, it indeed does; (d) this capacity, as an active self-organizing property, must either have a beginning or be beginningless — that is, it either existed eternally, or the world was originally maximally simple and static before this property spontaneously emerged. : The author proposes that the mode of existence of the world is defined by a set of fundamental characteristics that make both its persistence and its transformations possible. In other words, for any reality capable of evolutionary development to arise, certain basic properties must be present. Physical space must be either finite or infinite. If infinite, its geometry must be either spherical or linear. Physical reality must possess the inherent capacity to generate vast, stable structures and highly complex phenomena, as we observe in our own universe. Finally, this self-organizing property must either have existed eternally or have emerged spontaneously at a certain moment from an originally simple and static state. This framework invites us to consider the minimal conditions required for a universe like ours to evolve intelligence and complexity. It frames the question of cosmic origins not as a mystery of creation from nothing, but as an inquiry into the necessary and sufficient properties of matter and space that allow reality to unfold as it has.

Zafar Mirzo | Quotes

1,851,902 次观看 • 6 个月前

A 10-minute walk. That's all it takes to transform a real-world neighborhood into a machine-readable digital twin. Captured with an Insta360 X5 and reconstructed by Over the Reality, this environment is no longer just a place on a map. It's spatial data that can power Visual AI, Robotics localization, VPS, XR experiences, and next-generation world models. Today, the OVER community has already created more than 270,000 machine-readable locations like this, forming one of the world's largest 3D datasets for Physical AI, an increasingly valuable asset as demand for high quality real-world data continues to grow.
1:30

A 10-minute walk. That's all it takes to transform a real-world neighborhood into a machine-readable digital twin. Captured with an Insta360 X5 and reconstructed by Over the Reality, this environment is no longer just a place on a map. It's spatial data that can power Visual AI, Robotics localization, VPS, XR experiences, and next-generation world models. Today, the OVER community has already created more than 270,000 machine-readable locations like this, forming one of the world's largest 3D datasets for Physical AI, an increasingly valuable asset as demand for high quality real-world data continues to grow.

Over the Reality 🌐

16,724 次观看 • 1 个月前

World Simulator, reimagined — now alive with humans, robots, and their vibrant society unfolding in 3D real-world geospatial scenes across the globe! 🚀 One day soon, humans and robots will co-exist in the same world. To prepare, we must address: 1️⃣ How can robots cooperate or compete intelligently? 2️⃣ How do humans build social bonds and communities? 3️⃣ How can both co-exist in an open, dynamic world? Announcing Virtual Community Project — a social-physical world simulator, where human characters and robotic agents can interact, grow, and co-evolve within open-world societies, stretching from London to New York, and beyond! Key features include: ✅ Unified multi-agent physics simulations for rich social + physical interactions of humans and robots ✅ Massive auto-generated 3D scenes grounded with the rea-world geospatial data ✅ Agent communities populated by robots and LLM-driven human characters with rich appearances, personalities, and social ties. 🌍 Enter our Virtual Community, an open world to study embodied AI at scale— one social-physical world model at a time! 🔗 Project: 💻 Code: Paper: 1/n
0:53

World Simulator, reimagined — now alive with humans, robots, and their vibrant society unfolding in 3D real-world geospatial scenes across the globe! 🚀 One day soon, humans and robots will co-exist in the same world. To prepare, we must address: 1️⃣ How can robots cooperate or compete intelligently? 2️⃣ How do humans build social bonds and communities? 3️⃣ How can both co-exist in an open, dynamic world? Announcing Virtual Community Project — a social-physical world simulator, where human characters and robotic agents can interact, grow, and co-evolve within open-world societies, stretching from London to New York, and beyond! Key features include: ✅ Unified multi-agent physics simulations for rich social + physical interactions of humans and robots ✅ Massive auto-generated 3D scenes grounded with the rea-world geospatial data ✅ Agent communities populated by robots and LLM-driven human characters with rich appearances, personalities, and social ties. 🌍 Enter our Virtual Community, an open world to study embodied AI at scale— one social-physical world model at a time! 🔗 Project: 💻 Code: Paper: 1/n

Chuang Gan

90,526 次观看 • 1 年前

A Few Thoughts on Robotics The criticism that robotics can only be used in a rather one-sided way is, at the same time, the solution to the problem. What do I mean by that? Since the Industrial Revolution, humanity has increasingly made production methods more efficient. Fordism introduced assembly line work, but this comes at the expense of monotonous, repetitive tasks. On the one hand, immense wealth has been created; on the other hand, countless people suffer from repetitive tasks, which are a direct consequence of that industrial revolution and the division of labor- in other words, assembly line work. The debate about whether AI and robotics could impact the labor market is answered in different ways. I have a clear opinion on this: Up to now, technology has merely been an augmentation, an improvement of human labor to make it more effective. Robotics and AI, however, represent a qualitative break with this situation. For the first time in human history, it won't be humans who become more efficient, but rather replaceable, insofar as human augmentation becomes *less* efficient than replacing human labor with robotics. In just a few years, a human using technology will simply be less efficient than a robot that doesn't know an eight-hour day, weekends, or holidays, but can perform monotonous tasks 24/7 on an assembly line without breaking down due to physical ailments or needing medical attention. Wear and tear simply means replacing specific parts of the robot. To return to the initial question: production doesn't require general-purpose robots capable of performing a wide variety of tasks, but rather specialized robots that excel at the specific tasks for which they are needed. Figure02 vividly illustrates why this is only now possible: even the simplest assembly line work still requires delicate manual dexterity because the production line is designed for human hands. This breakthrough has now arrived, but AGI (Automated Generating Intelligence) isn't necessary for robots to be used in production processes. It's sufficient that they can perform monotonous tasks. And that's why I believe 2026 will be the year of the robots. (Clip: Figure02 in production chain at BMW Car-production)
1:24

A Few Thoughts on Robotics The criticism that robotics can only be used in a rather one-sided way is, at the same time, the solution to the problem. What do I mean by that? Since the Industrial Revolution, humanity has increasingly made production methods more efficient. Fordism introduced assembly line work, but this comes at the expense of monotonous, repetitive tasks. On the one hand, immense wealth has been created; on the other hand, countless people suffer from repetitive tasks, which are a direct consequence of that industrial revolution and the division of labor- in other words, assembly line work. The debate about whether AI and robotics could impact the labor market is answered in different ways. I have a clear opinion on this: Up to now, technology has merely been an augmentation, an improvement of human labor to make it more effective. Robotics and AI, however, represent a qualitative break with this situation. For the first time in human history, it won't be humans who become more efficient, but rather replaceable, insofar as human augmentation becomes *less* efficient than replacing human labor with robotics. In just a few years, a human using technology will simply be less efficient than a robot that doesn't know an eight-hour day, weekends, or holidays, but can perform monotonous tasks 24/7 on an assembly line without breaking down due to physical ailments or needing medical attention. Wear and tear simply means replacing specific parts of the robot. To return to the initial question: production doesn't require general-purpose robots capable of performing a wide variety of tasks, but rather specialized robots that excel at the specific tasks for which they are needed. Figure02 vividly illustrates why this is only now possible: even the simplest assembly line work still requires delicate manual dexterity because the production line is designed for human hands. This breakthrough has now arrived, but AGI (Automated Generating Intelligence) isn't necessary for robots to be used in production processes. It's sufficient that they can perform monotonous tasks. And that's why I believe 2026 will be the year of the robots. (Clip: Figure02 in production chain at BMW Car-production)

Chubby♨️

15,228 次观看 • 9 个月前