Geoffrey Hinton, professor at the University of Toronto and engineering fellow at Google Brain, recently published a paper on the Forward-Forward algorithm (FF), a technique for training neural ...

Recently, Shaila Niazi, a third-year doctoral student in Çamsari’s lab, achieved a significant breakthrough in that effort, becoming the first to use probabilistic hardware to train a deep generative ...

A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI.

If successful, DeepMind's goal to bridge deep learning and classical computer science could revolutionize AI and software as we know them.

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks.

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

On the 10th anniversary of key research that led to deep learning breakthroughs, AI luminaries say the 'revolution' will continue.

Artificial intelligence (AI) has come a long way since its inception, and backpropagation is one of the most fundamental algorithms that has contributed to the development of machine learning. It is a ...

Hinton’s backpropagation algorithm allowed LeCun to train models deep enough to perform well on real-world tasks like handwriting recognition.