Most enterprise data lives outside databases. Here's why that's holding AI back — and how connecting context can change it.

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Information, without order, is chaotic. Attempting to work ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data ...

Enterprises face key challenges in harnessing unstructured data so they can make the most of their investments in AI, but several vendors are addressing these challenges.

Large language models (LLMs) such as OpenAI’s GPT-4 are the building blocks for an increasing number of AI applications. But some enterprises have been reluctant to adopt them, owing to their ...

What’s the best way to store, search, and analyze content not based on their technical characteristics but on their meaning? The volume of data being created today is truly staggering. IDC projects ...

In this TechRepublic exclusive, a COO states that successful AI initiatives must have the right unstructured data at the right time. Then, she details the proper unstructured data preparation for AI.

It's not just a mess -- it's a security risk, a compliance hazard, and a missed opportunity. That was the message from data evangelist Karen Lopez during the June 27 session of the "How To Take ...

We talk to Nasuni founder and chief technology officer (CTO) Andres Rodriguez about the characteristics needed from storage to make optimal use of unstructured data in the enterprise, as well as the ...