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, ...

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, ...

With so much attention devoted to the purported wonders of predictive cognitive computing models (typically characterized by classic machine learning and deep learning), it’s easy to lose sight of the ...

Data modeling tools are like blueprints for organizing information in a way that makes sense to computers. They help people make sense of complex data by visually representing how different pieces of ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

SqlDBM, a leading collaborative, cloud-based data modeling platform for the enterprise, is unveiling Tx, a transformational workflow solution that empowers teams to facilitate both relational and ...

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.

SqlDBM, the leading cloud-native data modeling platform for the enterprise, today announces the release of its Model Context Protocol (MCP) Server live at Databricks Data + AI Summit 2025. This ...

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...