Editor-Curated Robotics Industry Briefing - RobotToday

Mifengpai Unveils Data Crowdsourcing Initiative for Robot Training Through Daily Activities

On September 23, Mifengpai launched a global initiative to crowdsource data for robot training, showcasing over 50,000 real environments and 5,000 tasks. The event highlighted the need for extensive data on everyday actions, which are crucial for training robots but have not been systematically recorded. Mifengpai's approach combines hardware, an app, and a data engine to facilitate this data collection. This initiative is significant as it addresses the challenge of gathering large-scale data necessary for developing embodied artificial general intelligence (AGI). Mifengpai's infrastructure, including the MEgo collection devices and a user-friendly app, aims to democratize data collection by allowing ordinary users to contribute through standardized tasks. The company has already seen substantial engagement, with 20,000 registered users and over 13,000 data collection tasks submitted in just one month. Looking ahead, Mifengpai has introduced a subsidy plan worth 100 million yuan to support task and equipment subsidies, along with a scene data alliance involving over 50 companies across various sectors. This collaborative effort is expected to enhance the quality and quantity of data available for robot training, ultimately improving robotic capabilities in everyday tasks.

leaderobot.com By Leaderobot Sep 25, 2026 Data Crowdsourcing Robot Training AI Technology Human-Robot Interaction

Figure AI Launches Index to Crowdsourced Human Video for Helix AI Training

Figure AI has officially launched Index, a platform designed to crowdsource real-world human video to train its Helix AI architecture. This initiative, part of Project Go-Big, aims to overcome traditional data bottlenecks in robotics by gathering physical interaction data from smartphone users worldwide. The company has already paid out $15 million to contributors and plans to invest over $1 billion in data acquisition and compute resources over the next year. The significance of Index lies in its ability to provide diverse physical interaction data necessary for zero-shot generalization, a challenge that has long hindered robotics development. Unlike conventional methods that rely on slow and labor-intensive processes, Index allows users to record everyday tasks or hire gig workers to capture first-person footage, thus streamlining the data collection process. This innovative approach addresses the critical shortage of embodied interaction data in the robotics field. Looking ahead, Figure AI's launch of Index represents a pivotal shift in its commercial strategy, as the company moves towards scaling hardware production and deploying units in real-world settings. With the recent achievement of its 1,000th Figure 03 build and ongoing pilots with BMW and Catalyst Brands, the focus now shifts to enhancing onboard intelligence and reasoning capabilities, which are seen as the primary challenges moving forward.