Synthetic data augmentation is a way to overcome data scarcity in practical machine learning applications by creating artificial samples from scratch.

Common Data Augmentation Techniques Several tried-and-true methods have been employed across various computer vision applications. Below are some of the most effective: ...

The introduction of synthetic data into the finance sector marks the beginning of a new era of data-driven innovation.

In the past year, Georgia Tech researchers Vidya Muthukumar and Eva Dyer have made a powerful impression on the National Science Foundation (NSF), forging partnerships between their labs and the ...

This may involve reskilling existing staff, hiring data scientists and AI specialists, and providing opportunities for continuous learning,” Zamanian writes. Many managed service providers use AI to ...

While advances in AI have been slow to reach commercial P&C insurance, new trends in data augmentation could help pick up the pace.

In business, data accessibility has fundamentally changed how companies operate. However, being "data-driven" is no longer an aspiration; it’s a competitive necessity.

A new forecast by Gartner suggests that decision support by artificial intelligence will give businesses a big boost in the next six years. It'll become the most valuable use of AI for businesses.