Roundtable: How Embodied Data Shapes the Future of the Industry? | GAIR 2025
Analysis
This article from Lei Feng Net discusses a roundtable at the GAIR 2025 conference focused on embodied data in robotics. Key topics include data quality, collection methods (including in-the-wild and data factories), and the relationship between data providers and model/application companies. The discussion highlights the importance of data for training models, the need for cost-effective data collection, and the evolving dynamics between data providers and model developers. The article emphasizes the early stage of the data collection industry and the need for collaboration and knowledge sharing between different stakeholders.
Key Takeaways
- •Data quality is crucial for training effective models in robotics.
- •Data collection methods are evolving, with options like data factories and in-the-wild approaches.
- •Cost-effectiveness and adaptability to different hardware and scenarios are important for data collection.
- •Collaboration and knowledge sharing between data providers and model developers are essential for industry growth.
“Key quotes include: "Ultimately, the model performance and the benefit the robot receives during training reflect the quality of the data." and "The future data collection methods may move towards diversification." The article also highlights the importance of considering the cost of data collection and the adaptation of various data collection methods to different scenarios and hardware.”