Hub (@hubxyz) provides real-world training data to frontier AI labs and robotics.
Human labor is half of global GDP. Almost none of it has ever been recorded.
Hub opens access to it through a global network of contributors capturing hard-to-access data.
Congrats on the launch, @xarmin and @tim404x!
https://t.co/ndxHExv6DC
๐ฝ๏ธ The dishwasher automated the easy part.
Scraping the plate, sorting, the pan that doesn't fit, the glass you check against the light: in almost every home, that's still done by hand.
For robotics, that's the hard part. Wet, reflective, deformable, and different in every home.
Hub captures it first person, in real homes and workplaces, verified and already allocated to labs training on it.
The next stage of automation is being decided at the sink.
We let our contributors describe Hub instead ๐ฅ
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?
๐ง๐ท 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.
๐งบ 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?