Hub

Robot policies work in the lab. The real world is where they break. To close that gap, we are open-sourcing the most diverse egocentric dataset with the help of @LeRobotHF. Coming to 🤗 @huggingface on Thursday November 12th.

Something is coming... 👀

We let our contributors describe Hub instead 🎥 No script, just people in Brazil talking about recording their everyday life. The detail that matters is the habit. They record their daily tasks every day, because it fits a life they already live. Supply is the hard side of any physical data network. Incentive-driven collection churns when the incentive ends. A habit compounds into collection capacity that keeps growing. That retention lets Hub keep adding new environments and tasks without starting from zero.

Your job pays you once. Now it can pay you twice. Commercial tasks are live on Hub. Until today, you earned by recording tasks at home. Now you can record your actual job: the shop, the salon, the farm, the workshop, the factory and more. Same hours you already work. The difference is they count now, at a higher rate than household tasks. What do you do at work that a robot could never do?

🧺 A robot can be taught to fold one towel. It cannot be taught to fold laundry. No two piles land the same way. There is no motion to memorize. That gap is the whole game in robotics, and it only closes with footage of real hands working in real homes. If you record with us, you are already closing it. So tell us: what has Hub taught you about robotics and where AI is heading?

🇧🇷 One of our contributors just aired on Brazil's biggest television network. A news segment. No ad spend. Her, recording her own day with Hub, getting paid for it. For the first time in history, anyone with a phone can help teach machines how the physical world works. Thousands of people already are. This is what it looks like before everyone else catches on.

Hub creators have now recorded over 2,000,000 clips of everyday human tasks. At home: folding laundry, weeding a garden, taking care of animals. On the job: mechanics, agriculture, construction, and many more. This side is scaling fast, and will soon cover any kind of work a human can do. Real people, in the wild. First person, across the Americas. This is the physical world getting written down for the first time, and it is the one thing robots cannot learn from the internet. What could you teach a robot that nobody else can?

AI has seen a dog get fed more times than anyone could count. It still couldn't feed one itself. Recognizing a task and knowing how to physically do it are not the same kind of intelligence. Most AI training data teaches the first. Almost none of it teaches the second. What that second kind actually requires is specific: the half-second a hand waits before releasing food, timed to the exact moment a dog's mouth is ready, not a second before. The angle of a crouch that keeps balance on uneven tile. The grip that's firm enough to hold, loose enough to let go cleanly. It only exists in the motion itself. Hub pays real people to record exactly this, first person, inside their own homes, at a scale no single lab could stage on its own. One woman, one dog, one ordinary Tuesday, is a single recording. Multiply it by everyone else doing the same ordinary things in their own homes, and it stops being a data point. It becomes the dataset embodied AI has been missing.

Founding Engineer, France. The systems this person builds ship data to frontier AI labs. Remote, open now ⬇️

🇧🇷 Hub is hiring a Field Operator in São Paulo Full ownership of the ground there: closing businesses, installing kits, training crews, keeping the recordings flowing. We hire on drive, not resume, this can be someone's first real job. Know someone built for this? Refer them and share this post. If we hire your referral, you get $500. Apply on our profile.

The actual race in robotics isn't the hardware 1X raised $100M, Tesla is scaling Optimus, Boston Dynamics has been at it for decades. They all hit the same wall. Real-world training data that doesn't exist at the scale they need. A robot trained on simulation fails in a real environment. It needs to learn from real people. Thousands of hours. Hundreds of countries. That's the race @hubxyz is in.

AI learned to talk from the internet It'll learn to act from us Backed by Y Combinator

🇦🇷 It's a Tuesday night in Buenos Aires Third floor. A woman folds laundry. Her hands move the way yours do, without thinking. Smoothing the towel flat. Finding the corners. She isn't filming her face. She's filming her hands. Two floors down, someone fills the sink until it steams. One plate at a time. Down the hall, a bed gets made. On a sill above, a watering can tips and the soil goes dark. Your body knows every one of these motions. A machine knows none of them. That's why the lights are on. Every movement so worn-in you forgot you learned it. Robots can't do it. Can't find it online. Nobody ever thought to record it. Hub does. $4/hour. For a lot of people behind this glass, that's more than a day's wage. Paid for things they'd be doing anyway. São Paulo. Bogotá. Buenos Aires. One building of unremarkable evenings. In the cities the industry keeps forgetting to look at. The other side of AI isn't a lab. It's the life behind the windows. The door downstairs is open. Someone's already walking in.

No cold emails. No push campaign Just contributors posting their links because the money showed up. $120. $32.55. $18.40 All from completing tasks on HubApp and inviting their friends. The earnings did the rest. Join them: platform.hub.xyz

🫵 There's a version of this where you're the person who opened the AI economy for your city Still time to be that person. LATAM only: airtable.com/appPdUpo3OtpDF7…