What is data modeling, and why does it break down? Fundamentally, data modeling involves arranging data in a structured way to improve accessibility and use for a range of applications and analyses.

Tencent initially ran the database on hosts packed with fast SSDs to handle the needs of different data models, such as I/O-intensive key-value and time-series models.

SurrealDB allows developers to model data using multiple different data models at once, and to deploy databases across both cloud and on-premises environments.

The process of de-identifying test databases can be approached in a variety of ways, and we’re often asked how our approach differs as compared to others. In this article, we’ll explore how our ...

A novel approach from the Allen Institute for AI enables data to be removed from an artificial intelligence model even after it has already been used for training.

In practice, generative AI tools use different strategies for different types of data when building large data models—the complex neural networks that organize vast amounts of information.

Researchers find large language models process diverse types of data, like different languages, audio inputs, images, etc., similarly to how humans reason about complex problems. Like humans, LLMs ...

The platform provides a framework for security and compliance and enables developers to test different large language models ...

Microsoft Research has had 7,000 downloads of its Comega programming technology, which is intended to bridge the gap between relational, object, and XML data models. Comega, or Cω, is described ...