Can a neural network be constructed entirely from DNA and yet learn in the same way as its silicon-based brethren? Recent ...

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech ...

What is an artificial neural network? Artificial neural networks are one of the main tools used in machine learning.

Deep learning has advanced rapidly, driving breakthroughs in image recognition, natural language processing, and autonomous ...

Known as deep learning, or neural networks, this technology has been around since the 1940s, but because of today’s exponential proliferation of data — images, videos, voice searches, browsing ...

The 2012 breakthrough—the deep learning revolution—was the discovery that we can get dramatically better performance out of neural networks with not just a few layers but with many.

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.

Born in the 1950s, the concept of an artificial neural network has progressed considerably. Today, known as “deep learning”, its uses have expanded to many areas, including finance.

Artificial Neural Networks: Learning by Doing Designed to mimic the brain itself, artificial neural networks use mathematical equations to identify and predict patterns in datasets and images.

During learning, the new patterns of neural population activity that develop are constrained by the existing network structure so that certain patterns can be generated more readily than others.