Fei-Fei Li

AI’s next frontier is Spatial Intelligence, a technology that will turn seeing into reasoning, perception into action, and imagination into creation. But what is it? Why does it matter? How do we build it? And how can we use it? Today, I want to share with you my thoughts on building and using world models to unlock spatial intelligence in this essay below. 1/n

@_k_art_ik_ @adityaag Yeah, I’m pretty happy with this one line too ;)

“A good idea is not as good as a crazy idea”- @drfeifei One line takeaway from the fireside today @adityaag

Today, we’re launching a new way to create with AI. With OpenArt Worlds, you can generate a fully navigable 3D environment from a single prompt or image, step inside it, and capture shots exactly the way you envision them. No more starting over. No more inconsistent scenes. You build the world once - and create inside it. • Move through your scene freely • Find your angles • Add characters and elements • Capture production-ready shots

Try It Here 🌎 storage.googleapis.com/forge-dev-publ…

Exploring cozy worlds 🍀 24 million splats Take a walk through it right in your browser ↓

Our imaginations are unbounded, so should the worlds we create be…🌐😍

70 hackers joined us in SF for the first-ever World Labs Hackathon. In just 3.5 hours, 32 teams used Marble for projects ranging from robotics sims and agents to AR/VR interfaces, games, art experiences, and real estate tools. Check out what they built ↓

We don't expect LLMs to multiply numbers or sort lists directly within their output token stream. Instead, we ask them emit code and execute it in a separate runtime. Why predict the opposite outcome for simulating interactive worlds? worldlabs.ai/blog/3d-as-code

Text became the universal interface for software. 3D is becoming the universal interface for space. It’s the medium that lets humans and AI generate, edit, simulate, and share worlds together. worldlabs.ai/blog/3d-as-code

Love this essay from World Labs’ team! Just like codes, 3D is a universal interface for machines and people.🤩

@GregMadison @theworldlabs 🤩🌐

@danliu So guilty😆

It’s wild when you consider that @drfeifei created imagenet which lead to alexnet which led to gpu-based ai that gave us llms and $5 trillion nvda.. Simply put, she’s responsible for Sam and Dario not willing to hold hands.

@theworldlabs 😍

We’re building foundational world models to power the next era of 3D. From robotics to gaming, spatial intelligence unlocks entirely new worlds. Powered by inference at scale – shoutout to Baseten.

@levelsio @theworldlabs 🌎🤩

✨ Built my own Guassian Splat viewer for my app 🏡 Interior AI It takes splats generated from your interior with the @theworldlabs API so you can walk around them in 3d space It's starting to look much more real than when I added splats 6 months ago, great work 🌐 World Labs!

@tamrrat Oh I so love this demo using @theworldlabs ' Marble API! 😍

turn any google street view url into a 3D gaussian splat!

‼️VLMs/MLLMs do NOT yet understand the physical world from videos‼️ In our recent work, we found that even the most advanced AI models still lag behind humans in one key aspect: reasoning about the kinematic properties of objects from videos. Takeaways: 1. ChatGPT 5.1 leads overall among 21 advanced VLMs, followed by Gemini 2.5 Pro/Flash. 2. Grok 4.1 delivers impressive performance at the lowest API cost. 3. Qwen3-VL is the top-performing open-source model. Read here: quantiphy.stanford.edu 🧵1/N

Check out this absolutely insane 40million splat scene of Coit Tower ... (great demo of sparkjs 2.0 handling massive scale)

@theworldlabs The most anticipated upgrade of the open source @sparkjsdev library is now in developer preview mode!🚀

Stream infinite worlds on the web. Spark 2.0 is now in developer preview.

@aakashgupta 🙏

A 15-year-old girl immigrates to New Jersey from China. Doesn’t speak English. Her parents, both educated engineers back in Chengdu, are now working as cashiers and restaurant cooks. She gets a job washing dishes at a Chinese restaurant to help the family survive. She gets into Princeton on a full scholarship. Her reaction is so disbelieving she asks two different advisors to verify the acceptance letter is real. Then her mom gets sick, so the family opens a dry cleaning shop in Parsippany. Every weekend for seven years, Fei-Fei Li leaves Princeton’s physics department to run the register, handle inspections, talk to customers, manage billing. Monday through Friday: quantum mechanics problem sets. Saturday and Sunday: sorting other people’s laundry. She later called herself the “CEO” of the dry cleaning business. She kept running it remotely through half of her PhD at Caltech. In 2007, she proposed building an image dataset so massive her own mentor told her she’d taken the idea “way too far.” Pre-ImageNet, the entire AI field was working with datasets containing a few hundred images. She built one with 15 million. Most researchers at the time believed algorithms were the bottleneck. She bet on data when nobody else would. By 2012, a team ran a neural network on that dataset and halved the existing error rate overnight. AlexNet on ImageNet became the moment the deep learning era started. Every computer vision product shipping today traces its lineage back to that dataset. Fast forward to 2024. She starts World Labs. Four months in, $230 million raise, $1 billion valuation. Today, $1 billion more at roughly $5 billion. The bet investors are making: that the woman who gave AI its eyes with 2D image recognition is about to give it spatial awareness of the 3D physical world. Her new model, Marble, generates persistent 3D environments from text or images. Unlike video generators that fake depth frame by frame, Marble creates actual geometric space where objects stay where you left them. The investor list tells you everything. AMD and NVIDIA both wrote checks. When the two biggest competing chipmakers both fund the same startup, they’re telling you this workload is coming whether their competitor funds it or not. Autodesk put in $200 million and signed on as strategic advisor, which means they see spatial AI integrating directly into CAD and design workflows within 18 months. From dry cleaner to ImageNet to a $5 billion spatial intelligence company. Fei-Fei Li has now placed two bets that the rest of the field thought were too early and too big. The first one created modern computer vision. The second one is trying to give machines the ability to understand physics. If she’s right again, this is the last major unlock before embodied AI actually works.

@hudsonmp10 Yes!

@drfeifei @drfeifei will u be there?

Happy Building! 🤩