Emerging from stealth to scale world-ready data for robotics, world models, and embodied AI SAN JOSE, Calif., March 17, 2026 /PRNewswire/ - Physicl today emerged from stealth at NVIDIA GTC, ...

Georgia Tech researchers Vidya Muthukumar and Eva Dyer are leading a multi-institutional project to develop a theory for data augmentation, aiming to improve the generalization and fairness of AI ...

The rapid development of artificial intelligence (AI) technology has become a cornerstone of multidisciplinary research worldwide, establishing a new paradigm of "AI for Science." AI is progressively ...

Currently, deep learning is the most important technique for solving many complex machine vision problems. State-of-the-art deep learning models typically contain a very large number of parameters ...

The task of point cloud classification suffers from the problem of insufficient data, and data augmentation is an effective method to alleviate this problem. However, the effect of conventional ...

A conditional generative adversarial network architecture was implemented to generate synthetic data. Use cases were myelodysplastic syndromes (MDS) and AML: 7,133 patients were included. A fully ...

Facing strict privacy laws, telcos use AI-generated synthetic data as a compliant workaround to train ML models without exposing sensitive customer information.

A new technical paper titled “An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design” was published by researchers at the University of Texas at Austin, Nvidia ...

Ambuj Tewari receives funding from NSF and NIH. You’ve just finished a strenuous hike to the top of a mountain. You’re exhausted but elated. The view of the city below is gorgeous, and you want to ...