Figure has publicly launched the Index platform, which has been operating secretly for four months, paying global users to collect first-person real-world operation videos to train its humanoid robot vision-language-action model Helix.

Figure claims that Index has accumulated 264,000 downloads, covering 108 countries, with over 44,000 active contributors weekly, and has uploaded 16 million video segments; the platform currently receives about 30 minutes of video per second, which the company estimates equates to approximately 4.9 years of human activity recorded daily. These figures are disclosed by Figure and have not been independently audited.

Users can record tasks such as cooking, laundry, cleaning, moving, and organizing to earn rewards. Figure states that it has paid contributors $15 million and plans to invest over $1 billion in data and computing power over the next 12 months, aiming to scale data operations by 100 times.

The core of Index is not an ordinary video library, but rather converting human first-person actions into training data for robots. Figure claims that every 1,000 hours of collected video averages 373 tasks, 1,146 manipulated objects, and 116 environments; the data is then filtered, anti-fraud checked, deduplicated, rebalanced, and hierarchically annotated.

Figure previously demonstrated in Project Go-Big that Helix can learn end-to-end control solely from human videos and transfer to humanoid robots with zero-shot learning; the company claims this is the first time a humanoid robot has learned low-level SE(2) speed control directly from human videos, using images and language. This conclusion is part of the company's technical statement, and external parties have not yet obtained complete training data, evaluation protocols, or independent reproduction conditions.

Helix 02 has been used to control the full-body movements, operations, and balance of Figure 03. Figure disclosed that the model completed approximately 4 minutes of dishwasher loading and unloading tasks under conditions without resets or human intervention, involving 61 continuous movement-operation actions while maintaining task status and implicit error recovery.

Figure has been advancing data, models, and manufacturing in parallel. The BotQ factory has increased the production speed of Figure 03 from one unit per day to one unit per hour in less than 120 days, delivering over 350 units; the first line's designed annual capacity is 12,000 units, and the company aims to produce a total of 100,000 units within four years.

In terms of market mechanisms, Index uses cash incentives to transform ordinary users' homes and workplaces into data supply sources, with funds flowing to video contributors, annotation reviews, cloud storage, training computing power, and data governance; Figure aims to convert diverse human operation data into Helix capabilities and robotic deployment advantages. Beneficiaries include companies with data collection channels, GPU computing power, edge-side sensors, and robotic deployment scenarios; humanoid robot teams relying on a small amount of remote operation data, single-scene demonstrations, or expensive custom integrations will face pressure from data scale disparities.

Source: Public Information