Redgate Software, the end-to-end Database DevOps solution provider, is launching Redgate Data Modeler, a new SaaS-based data modeling tool that enables teams to collaboratively design, document, and ...

It seems like everyone wants to get an AI tool developed and deployed for their organization quickly—like yesterday. Several customers I’m working with are rapidly designing, building and testing ...

Abstract: Data augmentation plays a crucial role in data-driven geoscience research by minimizing sampling costs and improving the generalization and predictive accuracy of models utilized in mineral ...

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.

Figure 1. Average result across 8 benchmarks for different methods. High performance at the same selection ratio indicates high efficacy, while achieving similar performance with a smaller selection ...

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, ...

My name is Bill Burkett, and I am a data modeler. I don’t call myself that often and sometimes have misgivings about doing so. I often get the feeling that being a “data modeler,” when considered in ...

A team has developed a new method that facilitates and improves predictions of tabular data, especially for small data sets with fewer than 10,000 data points. The new AI model TabPFN is trained on ...

Abstract: Utilizing fake data (simulated based on mechanism models or generated through data-driven models) for data enhancement is a popular approach to solve the problem of fault diagnosis with ...