When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Christine Benz: Hi, I’m Christine Benz for Morningstar. I’ve noticed that many investors do a good job of selecting investments, but they struggle putting the pieces together into a portfolio that ...

The Model Context Protocol (MCP) is an open standard (open-sourced by Anthropic) that defines a unified way to connect AI assistants (LLMs) with external data sources and tools. Think of MCP as a ...

For years, businesses, governments, and researchers have struggled with a persistent problem: How to extract usable data from Portable Document Format (PDF) files. These digital documents serve as ...

One decision many enterprises have to make when implementing AI use cases revolves around connecting their data sources to the models they’re using. Different frameworks like LangChain exist to ...

Using data in journalism is not new. But over the past decades, it has come a long way. In the 1960s, Philip Meyer began experimenting with the use of computers to process data for various projects at ...

Data modeling and data analysis are two fundamental ideas in the contemporary field of data science that frequently overlap but are very different from one another. Although both are crucial in ...

Alex Merced is the co-author of O'Reilly's "Apache Iceberg: The Definitive Guide" and a developer advocate for Dremio Structuring data thoughtfully is critical for both operational efficiency and ...

In our previous articles, we’ve talked about the exciting possibilities of search funds, a form of Entrepreneurship Through Acquisition (ETA). Let’s take a step back—what exactly is ETA? ETA is a ...

Generative AI’s reliance on extensive data has led to the use of synthetic data, which Rice University research shows can cause a feedback loop that degrades model quality over time. This process, ...