What does Nexdata's Physical AI Data Factory do?

We operate over 8,000 sqm of facilities with more than 400 robots to collect and provide high-quality real-world data for environment recognition, decision-making, and motion control required for robot development.

Why is large-scale data needed for Physical AI?

To improve control accuracy in real environments, it is necessary to teach AI diverse physical phenomena and human action patterns that cannot be replicated in simulations.

What types of datasets do you provide?

We provide three types of datasets: 3D environmental data, first-person perspective (Ego-centric) task execution videos, and precise control data including trajectories and force feedback.

AI News NQ Analysis

Nexdata Expands Physical AI Data Collection Factory with Total Investment of 2.5 Billion JPY, Offering Datasets for Foundation Models and Ego-centric Data Collection

NQ Score 82/100

N1 Content Completeness 9

AI Summary (NQ-processed)

Nexdata invested over 2.5 billion yen to build an 8,000 sq meter physical AI data collection factory. Operating over 400 robots, it provides crucial real-world datasets for robotics development.

AI Analysis

Frequently Asked Questions

Q: What does Nexdata's Physical AI Data Factory do?: A: We operate over 8,000 sqm of facilities with more than 400 robots to collect and provide high-quality real-world data for environment recognition, decision-making, and motion control required for robot development.
Q: Why is large-scale data needed for Physical AI?: A: To improve control accuracy in real environments, it is necessary to teach AI diverse physical phenomena and human action patterns that cannot be replicated in simulations.
Q: What types of datasets do you provide?: A: We provide three types of datasets: 3D environmental data, first-person perspective (Ego-centric) task execution videos, and precise control data including trajectories and force feedback.