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.

Predictive modeling is a statistical analysis of data used to generate future scenarios for organizations and companies. It can be used in any industry, enterprise, or endeavor in which data is ...

Among Oslo’s pieces: a modeling-specific language—code-named M—in which to write domain specific languages (DSLs); a way to build visual DSLs (code-named Quadrant); and a repository that ...

Previous models have been stuck at 65% accuracy for decades, but now a standard BERT based (LLM) model is able to do this in a reasonable time (milliseconds) with an 85% - 90% accuracy.

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis ...

Zyphra Technologies is announcing the release of Zyda, a massive dataset designed to train language models.It consists of 1.3 trillion tokens and is a filtered and deduplicated mashup of existing ...

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 ...

Chances are, unless you're already deep into AI programming, you've never heard of Model Context Protocol (MCP). But, trust me, you will. MCP is rapidly emerging as a foundational standard for the ...