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"Creativity requires controllability... This is why some of the current GenAI technology is deeply unsatisfying. Because it doesn’t give that controllability." —Dr. Fei-Fei Li, speaking at a16z speedrun last week

a16z speedrun 🧊

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33,489 次观看 • 1 年前 •via X (Twitter)

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9 条评论

a16z speedrun 🧊 的头像

a16z speedrun 🧊1 年前

More from speedrun in this week's newsletter:

StealthGPT 的头像

StealthGPT2 年前

The Rumor is true: StealthGPT is the only AI platform that beats Turnitin AI Detection

Lester 的头像

Lester1 年前

🗣️the biggest of facts!

Dante 🦔 的头像

Dante 🦔1 年前

@RKRigney Also explainability. How did it get there? It's always amazing to see other people's process of making their art. And it inspires us and influences our own processes.

floating point 的头像

floating point1 年前

Finally someone unconditionally said what we all felt! Love how FeiFei is always clear and bold! I’ll use this argument whenever our PM VP comes up with yet another Twitter inspired Sataya fueled LLM based “AI idea” :))

Jordan Mazer 的头像

Jordan Mazer1 年前

the AI:

Mini 的头像

Mini1 年前

Id argue creativity requires putting in the effort, which is why commissioning an artist does that not feel as satisying as making the art

Data & Analytics 的头像

Data & Analytics1 年前

@drfeifei @drfeifei, creativity often needs a balance – how can we make technology support innovation without stifling it? It's an important conversation for the future of GenAI. 💡 #InnovationInsights

Electe 的头像

Electe1 年前

@drfeifei @drfeifei, interesting perspective on creativity and technology. 🎨

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The moment is right to push forward into a new frontier for AI — one that is as fundamental as language, says Fei-Fei Li. That frontier is visual spatial intelligence. With Justin Johnson (Justin Johnson), her cofounder at World Labs, and a16z's martin_casado, Fei-Fei explains what unlocking this technology could mean, and why we’re in the midst of a “Cambrian explosion”:

The moment is right to push forward into a new frontier for AI — one that is as fundamental as language, says Fei-Fei Li. That frontier is visual spatial intelligence. With Justin Johnson (Justin Johnson), her cofounder at World Labs, and a16z's martin_casado, Fei-Fei explains what unlocking this technology could mean, and why we’re in the midst of a “Cambrian explosion”:

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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 robotics, allowing them to perform tasks and even collaborate with humans. Throughout all of human history, we have been confined to a single, shared reality: the "physical Earth 3D world." This singularity has been our only playground. However, new technologies that combine 3D generation and reconstruction are shattering this limitation. We can now create "infinite universes"—a multiverse of digital worlds for countless purposes, from training robots to enabling creativity, travel, and storytelling. This leap from one physical world to an infinite multiverse unlocks boundless possibilities for human imagination and interaction. Video from a16z

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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:

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:

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World Labs CEO Fei-Fei Li on the need for world models: "There's no language out there. You don't go out in nature and there's words written in the sky for you." "There is a 3D world out there that follows laws of physics, that has its own structures due to materials. To fundamentally back that information out and be able to represent it and be able to generate it is just fundamentally quite a different problem." "We will be borrowing useful ideas from language and LLMs, but this is fundamentally, philosophically a different problem."

World Labs CEO Fei-Fei Li on the need for world models: "There's no language out there. You don't go out in nature and there's words written in the sky for you." "There is a 3D world out there that follows laws of physics, that has its own structures due to materials. To fundamentally back that information out and be able to represent it and be able to generate it is just fundamentally quite a different problem." "We will be borrowing useful ideas from language and LLMs, but this is fundamentally, philosophically a different problem."

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📁 Fei-Fei Li, one of the most influential AI scientists in the world, argues that common sense is not as mysterious as we think. Much of it is already encoded in language, distilled through thousands of years of human communication. When an AI places the sun at the top of a drawing, it does not need deep physics, it is learning shared patterns. In her view, common sense can be learned, and in many ways an AI is not so different from a five year old child.

📁 Fei-Fei Li, one of the most influential AI scientists in the world, argues that common sense is not as mysterious as we think. Much of it is already encoded in language, distilled through thousands of years of human communication. When an AI places the sun at the top of a drawing, it does not need deep physics, it is learning shared patterns. In her view, common sense can be learned, and in many ways an AI is not so different from a five year old child.

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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.

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

11,309 次观看 • 27 天前