What Data Leaders Must Fix Before AI Can Scale In 2026

In 2026, data leaders must focus on enhancing data foundations rather than feature expansion. That means prioritizing data ...

Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...
Regtechtimes on MSN

Data residency as the operating layer for global AI adoption

In regulated healthcare, the hardest part of scaling AI is often not the model, it is the data boundary. The data privacy management software market is projected to grow from $5.37 billion in 2025 to ...

CloudOffix Partners with Enterprise Process Modelling to Accelerate Meaningful Digital Transformation

CloudOffix and Enterprise Process Modelling Join Forces to Bridge Strategy, Execution, and Experience in Digital ...
The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...