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“Is AI overhyped or underhyped?” Fei-Fei Li: "Silicon Valley can mistake clear vision with short distance. In 2006 the first self-driving car drove 140 miles...it still took 20 years for Waymo to be barely on the road." "Clear vision is important, but the journey will be long."

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96,541 views • 7 months ago •via X (Twitter)

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Dr. Fei-Fei Li (Fei-Fei Li), the Godmother of AI, on the origin of computer vision and why spatial intelligence is the next frontier. At AI Startup School in San Francisco. 01:00 - Origins of ImageNet 02:15 - The Dream to Make Machines See 03:28 - A paradigm shift in AI 05:50 - AlexNet and Deep Learning 08:00 - Evolving Computer Vision 12:20 - Building World Labs 13:00 - The next frontier in AI 14:20 - Why Spatial Intelligence Is Harder Than Language 18:40 - Technical Barriers for Vision-Based AI 20:00 - AI is more than LLMs 25:50 - Fei Fei’s Journey 29:30 - Mentoring some of the legends of AI 33:00 - Audience Q&A

Dr. Fei-Fei Li (Fei-Fei Li), the Godmother of AI, on the origin of computer vision and why spatial intelligence is the next frontier. At AI Startup School in San Francisco. 01:00 - Origins of ImageNet 02:15 - The Dream to Make Machines See 03:28 - A paradigm shift in AI 05:50 - AlexNet and Deep Learning 08:00 - Evolving Computer Vision 12:20 - Building World Labs 13:00 - The next frontier in AI 14:20 - Why Spatial Intelligence Is Harder Than Language 18:40 - Technical Barriers for Vision-Based AI 20:00 - AI is more than LLMs 25:50 - Fei Fei’s Journey 29:30 - Mentoring some of the legends of AI 33:00 - Audience Q&A

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Fei-Fei Li says AI is not over-hyped; it is a civilizational technology that represents the new computing Wherever chips exist today, from light bulbs to self-driving cars, AI will inevitably follow "wherever there is compute, there will be AI"

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"Can AI ever be Newton? Can AI ever be Einstein? Can AI ever be Picasso?" Dr. Fei-Fei Li ( Fei-Fei Li ) gives a very simple explanations of how today's AI still has a long way to go. --- From 'FII Institute' YT channel (full link in comment).

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Fei-Fei Li: Open Source AI Needs To Be Protected⁣ ⁣ "I think open source should be protected. If there is efforts of open source both in public sector as like academia as well as private sector is so important. It's so important for the entrepreneurial ecosystem." — Fei-Fei Li

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“People are wildly overestimating what AI will do to society in the next two or three years, and wildly underestimating what it will do in ten or fifteen. It’s going to be slow, and then all of a sudden." Brian Chesky on whether AI is overhyped or underhyped:

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I loved getting to discuss the future of artificial intelligence—while sitting in a self-driving car!—with renowned computer scientist Fei-Fei Li. Her new book, The Worlds I See, is out tomorrow. I think you’ll want to read it.

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134,781 views • 2 years ago

The godmother of AI just delivered the reality check Silicon Valley refuses to hear. She has the standing to say it. Li: “Silicon Valley as a whole tends to mistake clear vision with short distance.” Seeing the destination clearly has nothing to do with how hard it is to reach. Self-driving cars were first demonstrated in 2006. Twenty years later Waymo is barely on the road. The vision was never the problem. The distance was. Clarity of destination gets mistaken for proximity to arrival. That’s the mistake the industry keeps making. And keeps making. Li: “I consider myself a scientist in my heart and I actually really don’t like hyping.” In an industry running at maximum temperature, Fei-Fei Li is one of the few people at the top willing to say that publicly. Not because the technology isn’t real. Because the gap between what’s visible and what’s required is being systematically underestimated. Large Language Models dominate the conversation. Text to text. Comparatively contained. The harder problem is spatial intelligence. AI that reasons about and acts within the physical three-dimensional world. Hardware. Physics. Data that doesn’t exist yet. Real-time adaptation to chaos. A robot that can clean a bathroom requires understanding every surface, every object, every force, every exception. That’s not a software update. That’s a civilizational research problem. Li: “I don’t call it hype. I call it a misleading sentiment. We don’t want to replace human creators.” The second place the industry gets it wrong is creativity. The narrative has hardened around replacement. AI takes the jobs. AI tells the stories. AI makes the art. Li considers that not just wrong but destructive. Wrong because AI doesn’t replicate creativity. Destructive because believing it can devalues the humans creating culture. Human creativity isn’t a process to be automated. It’s fundamental to what we are as a species. The goal is augmentation. Tools that make human creators faster and more capable. Not systems that generate output in the style of human work and call it creation. That distinction matters more than most people in the industry are willing to sit with. Precision of imagination is not proximity to reality. Li has spent her career in the gap between those two things. The map isn’t the territory. The journey is long. The hurdles are deep. And the scientist who built the foundation this era stands on is telling you the timeline everyone is selling is wrong. We’ve been almost there with self-driving for twenty years. The pattern doesn’t change just because the destination looks different.

The godmother of AI just delivered the reality check Silicon Valley refuses to hear. She has the standing to say it. Li: “Silicon Valley as a whole tends to mistake clear vision with short distance.” Seeing the destination clearly has nothing to do with how hard it is to reach. Self-driving cars were first demonstrated in 2006. Twenty years later Waymo is barely on the road. The vision was never the problem. The distance was. Clarity of destination gets mistaken for proximity to arrival. That’s the mistake the industry keeps making. And keeps making. Li: “I consider myself a scientist in my heart and I actually really don’t like hyping.” In an industry running at maximum temperature, Fei-Fei Li is one of the few people at the top willing to say that publicly. Not because the technology isn’t real. Because the gap between what’s visible and what’s required is being systematically underestimated. Large Language Models dominate the conversation. Text to text. Comparatively contained. The harder problem is spatial intelligence. AI that reasons about and acts within the physical three-dimensional world. Hardware. Physics. Data that doesn’t exist yet. Real-time adaptation to chaos. A robot that can clean a bathroom requires understanding every surface, every object, every force, every exception. That’s not a software update. That’s a civilizational research problem. Li: “I don’t call it hype. I call it a misleading sentiment. We don’t want to replace human creators.” The second place the industry gets it wrong is creativity. The narrative has hardened around replacement. AI takes the jobs. AI tells the stories. AI makes the art. Li considers that not just wrong but destructive. Wrong because AI doesn’t replicate creativity. Destructive because believing it can devalues the humans creating culture. Human creativity isn’t a process to be automated. It’s fundamental to what we are as a species. The goal is augmentation. Tools that make human creators faster and more capable. Not systems that generate output in the style of human work and call it creation. That distinction matters more than most people in the industry are willing to sit with. Precision of imagination is not proximity to reality. Li has spent her career in the gap between those two things. The map isn’t the territory. The journey is long. The hurdles are deep. And the scientist who built the foundation this era stands on is telling you the timeline everyone is selling is wrong. We’ve been almost there with self-driving for twenty years. The pattern doesn’t change just because the destination looks different.

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Elon Musk in new interview: "10 years from now, probably 90% of all distance driven will be driven by the AI in a self-driving car. It will be quite a niche thing in 10 years to actually be driving your own car." AI already drives for 90%+ of the miles I travel.

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📁 Fei-Fei Li, computer vision pioneer and Stanford professor, says the next frontier of AI is spatial intelligence. The ability to perceive, reason and act in the physical world. Not just see and talk. But do. Just as vision triggered the Cambrian explosion of life, spatial intelligence could trigger the next explosion of AI.

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Stanford Deep Learning for Computer Vision taught by Professor Fei-Fei Li (Fei-Fei Li) and Assistant Professor Ehsan Adeli. Such an enjoyable YT series. (link in comment)

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Brian Chesky's vision for an AI-first world is miles ahead of the Silicon Valley narrative. Haven't seen it this clearly since Steve Jobs.

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Fei-Fei Li says some parts of today's AI are already superhuman — languages, speed, broad knowledge But the creative leap, like combining creativity and abstraction, is still missing Even with all the star-motion data, today's or tomorrow’s AI wouldn't deduce Newton's laws

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Fei-Fei Li (Fei-Fei Li) on limitations of LLMs. "There's no language out there in nature. You don't go out in nature and there's words written in the sky for you.. There is a 3D world that follows laws of physics." Language is purely generated signal.

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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”:

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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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