A new computational model of the brain based closely on its biology and physiology not only learned a simple visual category learning task exactly as well as lab animals, but even enabled the ...

Abstract: Reconstruction of complete seismic data is a crucial step in seismic data processing, which has seen the application of various convolutional neural networks (CNNs). These CNNs typically ...

First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The ...

These are not “nice-to-haves”; they are prerequisites for distributed cognition, operating at machine speed. As Tatipamula and Cerf point out, the network can no longer simply host intelligence. It ...

What will shape enterprise data in 2026? We look at insights from Bloomberg’s Enterprise Data & Tech Summit in London on ...

Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...

As enterprises modernize, the question is no longer whether to use SAP or non-SAP tools, but how to make them work together ...

This study found that certain characteristics in linked electronic health record data across episodes of care can help identify patients with Alzheimer disease and related dementias at high risk of 30 ...

Learn about model risk, its causes, management strategies, and real-world examples from financial industry pitfalls. Unlock ...

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

Garbage in, garbage out. That is a motto insurers are focused on as AI adoption accelerates. No matter how sophisticated an ...

Abstract: Due to the greatly improved capabilities of devices, massive data, and increasing concern about data privacy, Federated Learning (FL) has been increasingly considered for applications to ...