The core of the Python data model architecture is special methods (also known as "magic methods"). These methods, which start ...

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

AI is reshaping brand engagement, but its effectiveness relies on high-quality, curated data, a significant challenge for ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

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 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 ...

Tamed DB sprawl and saved cloudy resources with 'X-Stor' Exclusive Chinese web giant Tencent has revealed it created a NoSQL database that it believes can handle multiple data models more elegantly ...

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...

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 by ...

A study using multiple agronomic models to examine two long-term agricultural research stations in North America shows that ...