We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Extreme Learning Machines (ELMs) represent a class of feedforward neural networks distinguished by their rapid learning speed and analytical determination of output weights. Unlike conventional neural ...

Using lab-grown brain tissue, researchers uncovered complex patterns of neural signaling that differ subtly between healthy ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

In the Neural Engineering Center, part of our work focuses on neural and brain machine interfaces. One of the key elements of the ability to analyze neural systems and to enhance or replace neuronal ...

You know that expression When you have a hammer, everything looks like a nail? Well, in machine learning, it seems like we really have discovered a magical hammer for which everything is, in fact, a ...

In the machine learning world, the sizes of artificial neural networks — and their outsize successes — are creating conceptual conundrums. When a network named AlexNet won an annual image recognition ...

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

When Google Translate was released, in 2006, I was an eighth grader stumbling through introductory Spanish, and my teacher had little reason to worry about her students using it to cheat. It’s almost ...