AI initiatives don’t stall because models aren’t good enough, but because data architecture lags the requirements of agentic systems.

Data modeling, at its core, is the process of transforming raw data into meaningful insights. It involves creating representations of a database’s structure and organization. These models are often ...

Amazon Web Services's AI Shanghai Lablet division has created a new predictive model -- an open-source benchmarking tool called 4DBInfer used to graph predictive modeling on RDBs, a relational ...

Data modeling tools play an important role in business, representing how data flows through an organization. It’s important for businesses to understand what the best data modeling tools are across ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When Snowflake announced its $250 million acquisition of Crunchy Data two weeks ago at its ...

Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know. One of my first projects as a software developer was ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

SAN FRANCISCO--(BUSINESS WIRE)--Cyber risk analytics leader CyberCube has launched the world’s first set of detailed Exposure Databases to enable (re)insurers and brokers to perform a wide array of ...

This article was written by Bloomberg Intelligence senior industry analyst Mandeep Singh and associate analyst Robert Biggar. It appeared first on the Bloomberg Terminal. AI’s shift to inference at ...

Patrick Walsh is the cofounder and CEO of IronCore Labs, the data security encryption platform for software companies and AI. The proliferation of generally intelligent AI models is turning machine ...