Data is the source of intelligence for foundation models. The scaling of language models has shown that model capability ...

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

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.

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, ...

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

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

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 ...

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, ...

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 ...

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

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