Enterprise AI depends on data pipelines. Learn why data quality, schema drift and monitoring decide success before models go ...

Enterprises racing to deploy generative AI often focus on models. In practice, outcomes depend on how well organizations ...

The AI data industry will continue to reinvent itself, and the companies that take the lead will do so by building a ...

As AI adoption accelerates, organizations will increasingly measure AI success not by model size, but by the economics of ...

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 ...

Once, the world’s richest men competed over yachts, jets and private islands. Now, the size-measuring contest of choice is clusters. Just 18 months ago, OpenAI trained GPT-4, its then state-of-the-art ...

Most services agreements for vendor-provided technology services contain standard provisions allowing vendors to use customer data and data ...

As institutions become more data-rich and data-reliant, their capacity for analytics is not necessarily keeping up. In an Educause QuickPoll of higher education IT leadership focused on data strategy ...

Data modeling is an important part of business intelligence that requires the support of skilled professionals. Learn more about what they do. Databases are central to the operations of many ...