Nexdata Unveils Premium Data Services for Embodied AI

Nexdata has built dedicated “data collection centers” at multiple locations to support the practical application of embodied AI. By providing ready-made datasets immediately and customizing them to meet customer requirements, Nexdata solves the biggest challenge in physical AI development: the lack of training data.

AI is evolving from “computation” to “body.” Embodied AI, an intelligence that perceives, learns, and makes decisions while interacting with its environment in real time, is attracting attention as the next generation of intelligence in a wide range of fields, including home, medical care, manufacturing, and mobility. However, the biggest obstacle hindering its development is “data.”

Three data challenges hindering the practical application of embodied AI

Rising costs of data collection

There are four main approaches to collecting data for embodied AI: collecting data from real environments using remotely operated robots, generating synthetic data through simulation, motion capture, and using image and video data from the web. However, none of these approaches achieves the ideal balance, and companies are faced with a dilemma between quality, cost, and scalability. These fundamental challenges are hindering the speed of embodied AI development.

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Lack of data standards

In the field of embodied AI, common data formats and annotation standards have yet to be established. Data formats vary depending on the task, device, and environment. As a result, sharing and reusing data with other companies and projects is extremely difficult. Furthermore, variables such as lighting conditions, object shape, and cultural background limit the generalization performance of models.

Lack of dynamic interaction data

The essence of embodied AI lies in dynamic scenes where humans and the environment interact in real time. However, such natural behavior changes instantaneously and cannot be recorded without high-precision sensors and strict synchronization technology. In particular, rare and important events such as falls, emergency avoidance, and obstacle detection are nearly impossible to collect in the real world. Even in simulation, achieving both realism and reproducibility remains a major challenge.

Nexdata’s Solution

To solve this problem, Nexdata has built a data infrastructure dedicated to embodied AI and has begun providing full-scale data services. We provide comprehensive support, from providing ready-made datasets to multi-modal data collection and annotation services.

SOURCE: PRTimes