Aug 26, 2026 07:22 AM
The company is Figure in San Jose California. They are trying to build the world's largest physical robotics dataset.
https://www.figure.ai/news/introducing-index
They say,
It looks like you put on one of their camera headsets when you are performing one of the tasks that they are interested in: Household chores and various practical tasks, not watching TV, eating or having sex.
Take washing dishes. Every kitchen is laid out differently, and everybody washes different dishes in different order. That kind of variation doesn't bother humans but they can completely confuse and stump a robot. The answer is a large and diverse enough training dataset that the AI can generalize the insignificant differences while still noting differences that really make a difference.
https://www.figure.ai/news/introducing-index
They say,
Quote:The data needed to scale a truly general purpose robot doesn't exist on the internet - it has to come from the real world: a global sampling of physics captured across every environment on earth.
For the last 4 months, we’ve been building a Figure-exclusive pipeline to scale data collection at higher throughputs, with broad diversity and strict quality standards...
Our AI stack, Helix, gets more capable the same way every learned system does: with data. That's not a new idea in machine learning, it's the central finding of the last decade of AI research, and one worth restating plainly for robotics...
Index is our answer to the data problem: the largest useful robot training dataset in the world. Four months ago, we launched an app in stealth to test the idea: could we collect the physical data Helix needs directly from humans, at scale? Today we’re rebranding this as Index and launching on Google Play and the App Store...
The data inherits its diversity directly from the people generating it. Every new Creator brings an unseen environment, unfamiliar objects, and their own idiosyncratic way of completing a task, the kind of long-tail variation that's nearly impossible to define upfront...
To date, Creators have earned $15M. We're collecting across the full diversity of human tasks: cooking, cleaning, laundry, and other household chores at home, as well as inside businesses such as logistics centers, restaurants, factories, and offices. We’ve seen tasks as obscure as cleaning kitty litter, changing oil, busing restaurant tables, and we welcome the diversity
It looks like you put on one of their camera headsets when you are performing one of the tasks that they are interested in: Household chores and various practical tasks, not watching TV, eating or having sex.
Take washing dishes. Every kitchen is laid out differently, and everybody washes different dishes in different order. That kind of variation doesn't bother humans but they can completely confuse and stump a robot. The answer is a large and diverse enough training dataset that the AI can generalize the insignificant differences while still noting differences that really make a difference.