The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Neuromorphic computing systems, encompassing both digital and analog neural accelerators, promise to revolutionize AI ...

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

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 ...

The project's solution is an imaging system combining a metalens array, an RGB CMOS sensor and a computing layer chip.