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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 🧊

36,148 subscribers

33,489 Aufrufe • vor 1 Jahr •via X (Twitter)

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9 Kommentare

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a16z speedrun 🧊vor 1 Jahr

More from speedrun in this week's newsletter:

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StealthGPTvor 2 Jahren

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

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Lestervor 1 Jahr

🗣️the biggest of facts!

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Dante 🦔vor 1 Jahr

@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.

Profilbild von floating point

floating pointvor 1 Jahr

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” :))

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Jordan Mazervor 1 Jahr

the AI:

Profilbild von Mini

Minivor 1 Jahr

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

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Data & Analyticsvor 1 Jahr

@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

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Electevor 1 Jahr

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

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📁 Fei Fei Li says that a key breakthrough in generative AI is the next token prediction objective, perfectly aligned with the task of producing language. She adds that vision and world modeling are harder because the real world is multimodal and demands observation, interpretation and reasoning. She notes that understanding and creating worlds is far more complex than generating text.

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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

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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World Labs co-founders Justin Johnson and Dr. Fei-Fei Li say Atlas unifies the two things computer vision has always kept apart: Justin: "Historically, reconstruction has been its own subfield in computer vision with its own specialized tasks and models. Generation is what all the text-to-video models are really good at." "Those are great for creative applications if I want to imagine something that's never been there before." "But now with Atlas, for the first time, we're putting these two different parts of visual intelligence together in one model. It can do both 3D reconstruction and generation together in one architecture." "We had to make it multimodal from the start. This thing natively works on text, images, videos, and camera poses as a native input to the model... It uses 3D as a native modality that it works on." Fei-Fei: "Computer vision has been around for more than half a century... Our field traditionally has multiple tracks. You go to a computer vision conference: you have the pixel generation track, you have some recognition track, and you have a 3D reconstruction track." "This is an elegant model that unifies the problem of reconstruction and generation by anchoring on viewpoints and viewpoint estimation. That's just incredibly powerful." Justin Johnson Fei-Fei Li

World Labs co-founders Justin Johnson and Dr. Fei-Fei Li say Atlas unifies the two things computer vision has always kept apart: Justin: "Historically, reconstruction has been its own subfield in computer vision with its own specialized tasks and models. Generation is what all the text-to-video models are really good at." "Those are great for creative applications if I want to imagine something that's never been there before." "But now with Atlas, for the first time, we're putting these two different parts of visual intelligence together in one model. It can do both 3D reconstruction and generation together in one architecture." "We had to make it multimodal from the start. This thing natively works on text, images, videos, and camera poses as a native input to the model... It uses 3D as a native modality that it works on." Fei-Fei: "Computer vision has been around for more than half a century... Our field traditionally has multiple tracks. You go to a computer vision conference: you have the pixel generation track, you have some recognition track, and you have a 3D reconstruction track." "This is an elegant model that unifies the problem of reconstruction and generation by anchoring on viewpoints and viewpoint estimation. That's just incredibly powerful." Justin Johnson Fei-Fei Li

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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250,455 Aufrufe • vor 10 Monaten

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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