Companies can’t avoid working with data, but management of that data can pose serious challenges. Customer and other personal data keep escaping, courtesy of breaches that surged 78% last year in the ...

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 Department of Homeland Security and Chief Data Officers Council put out calls recently for products and insight on synthetic data generation. Government agencies are on the hunt for vendors and ...

As AI demand outpaces the availability of high-quality training data, synthetic data offers a path forward. We unpack how synthetic datasets help teams overcome data scarcity to build production-ready ...

Synthetic data are artificially generated by algorithms to mimic the statistical properties of actual data, without containing any information from real-world sources. While concrete numbers are hard ...

In a recent study published in the journal Nature Medicine, researchers used diffusion models for data augmentation to increase the robustness and fairness of medical machine learning (ML) models in ...

Artificial intelligence systems are only as powerful as the data they are trained on. High-quality labeled datasets determine whether a model performs with precision or fails in production.

Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...

Artificial intelligence (AI) is transforming our world, but within this broad domain, two distinct technologies often confuse people: machine learning (ML) and generative AI. While both are ...

Perhaps in the earlier days of AI/ML, you were a little curious about what the limiting factors would be in these new technologies. One potential one was cost, but we’ve seen the value of compute ...