Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...

Security professionals can recognize the presence of drift (or its potential) in several ways. Accuracy, precision, and ...

In a recent paper, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and co-author William Gilpin show that a deceptively ...

Enterprises face challenges in preparing data for generative AI due to data quality and accessibility issues. Gartner ...

Synthesizing tables—creating artificial datasets that closely resemble real ones—plays a crucial role in supervised machine learning (ML), with a wide range of practical applications. These include ...

We used Tonic Fabricate to generate a fully synthetic email corpus, then RL fine-tuned an open-source model against it. The ...

Protein engineering is a field primed for artificial intelligence research. Each protein is made up of amino acids; to ...

A new suite of tools and services address need for high-quality domain-specific datasets and human feedback pipelines ...

AI is not overhyped. The potential requires equal attention to the less glamorous but more important role of data management.

NIIMBL’s 2025 National Meeting emphasized the need for system interoperability through standardization of means for data ...