Tech Xplore on MSN

Deep AI training gets more stable by predicting its own errors

Artificial intelligence now plays Go, paints pictures, and even converses like a human. However, there remains a decisive difference: AI requires far more electricity than the human brain to operate.
Art of the Problem on MSN

How neural networks actually learn, from brain cells to deep learning

This video explores how neural networks evolved from early ideas about the brain into the foundation of modern deep learning. From Rosenblatt’s perceptron to GPUs and backpropagation, it traces the ...
Gizmodo

Machine Learning vs. Deep Learning: What’s the Difference?

Artificial intelligence is everywhere these days, but the fundamentals of how this influential new technology work can be difficult to wrap your head around. Two of the most important fields in AI ...
eWeek

Deep Learning vs Generative AI: Understanding the Key Differences

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
Ars Technica

How a stubborn computer scientist accidentally launched the deep learning boom

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...
Technology Networks

Machine Learning Applications in Proteomics

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
EurekAlert!

Transfer learning-enhanced physics-informed neural network (TLE-PINN): A breakthrough in melt pool prediction for laser melting

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...