AI’s biggest constraint isn’t algorithms anymore. It’s data…specifically, high-quality, forward-looking data. It is the “Rare ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

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 and ...

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

Geospatial Information Systems (GIS) have transformed the way we capture, store, and analyse spatial data by integrating methods from computer science, statistics and geography. Central to GIS is the ...

A new crowd-trained way to develop LLMs over the internet could shake up the AI industry with a giant 100 billion-parameter model later this year. Flower AI and Vana, two startups pursuing ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

Outside of tightly controlled environments, most robotic systems still struggle with reliability, generalization and cost. The gap between what we can demonstrate and what we can operate at scale ...

How to Improve Cancer Patients ENrollment in Clinical Trials From rEal-Life Databases Using the Observational Medical Outcomes Partnership Oncology Extension: Results of the PENELOPE Initiative in ...