Nuance and Judgement are Needed for an AI Resilient Enterprise. While multi-modal AI can ingest vast amounts of data, it ...

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...

Advances in high-throughput omic technologies allow for assaying a growing compendium of molecular layers, ranging from genome and epigenome profiling and transcriptomics to proteomics and ...

VentureBeat and other experts have argued that open-source large language models (LLMs) may have a more powerful impact on generative AI in the enterprise. More powerful, that is, than closed models, ...

A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable) principles for scientific data is transforming the state-of-practice for data management and stewardship, ...

The world is changing rapidly, and if businesses want to keep up, there is no alternative but to change with it. Customer behavior, market conditions, and the technological landscape are in a constant ...

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 ...

The OMOP Oncology Module provides a platform for standardization of cancer data enabling the conduct of observational cancer studies and identifying patient cohorts in a distributed research network.

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...