The limitation for many companies investing in AI is not the sophistication of the models being deployed, but the lack of AI-ready data.

In a recent Views & Comments column published in Engineering, researchers Jinghai Li and Li Guo from the Chinese Academy of Sciences offer profound insights into the future development of data science ...

Enterprise technology vendors are racing to make AI work against the structured and relational data inside databases, data ...

Public health departments depend on accurate and timely data to guide their efforts to control the spread of disease. Full integration of information technology is the norm for other essential data ...

Enterprise data systems now sit beside ranking, inference and decision pipelines that influence what users see, interact with, and act on. At scale, these systems often remain operational while ...

AI innovations have long promised productivity at scale, powered by breakthroughs in underlying technologies such as large language models (LLMs), aiding state-of-the-art applications to reason with ...

Agencies across the government, including in the White House, are planning for, procuring, building, or attempting to scale impact and improve performance through integrating data and using data ...

As user acquisition costs continue to climb and the complexity of global game operations intensifies, many studios are discovering the limitations of their traditional analytics tools. The modern ...