Data is the source of intelligence for foundation models. The scaling of language models has shown that model capability depends heavily on both data scale and data quality. But robotics data is far ...

After helping build some of the world's most widely used open AI datasets at Hugging Face, Guilherme Penedo and Hynek ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Until now, researchers and startups building humanoid robots faced a critical challenge: no publicly available, large-scale, annotated motion dataset designed specifically for robotics. At GTC 2026, ...

The next frontier, however, is the integration of artificial intelligence into physical intelligent systems capable of ...

If physical AI is going to match the accomplishments of LLMs, there's a data problem that needs to be solved.

Physical AI raised $10B+ in 2025, but robots still train on under 5,000 hours of real-world data. Who's funding the race to ...

We offer fully enriched datasets along with a process of creating unique data from scratch with our scalable process. At this point, it’s practically Hollywood for AI.” — Inna Nomerovska, CMO at ...

Connecting the dots: AI has mostly been confined to the virtual world, but it is now learning from the physical mechanics of everyday life, driven by a global surge in data collection and annotation.

X Square Robots' system combines foundation models, robotics hardware, a data pipeline system, and real-world deployments.

A robot on a factory floor can carry parts, scan shelves, and move around people with growing skill. What it still struggles ...

SAN JOSE, CA, UNITED STATES, March 16, 2026 /EINPresswire.com/ — Until now, researchers and startups building humanoid robots faced a critical challenge: no ...