Guest blog by Anthony Collins, Technical Director Data and Digital Competency Centre; Nathaniel Henman, Data Scientist; John ...

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Data is real. We enjoy the use of real world substantiated ...

These people do not exist. These faces were artificially generated using a form of deep learning known as generative adversarial networks (GANs). Synthetic data like this is becoming increasingly ...

As AI becomes more common and decisions more data-driven, a new(ish) form of information is on the rise: synthetic data. And some proponents say it promises more privacy and other vital benefits. Data ...

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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Andy Brinkmeyer shares how engineering ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...

As AI companies start running out of training data, many are looking into so-called “synthetic data” — but it remains unclear whether such a thing will ever work. But while companies like Anthropic, ...