Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases. Written by eWEEK content and product ...

In addition to pure deep neural networks (DNNs), sometimes people use hybrid vision models, which combine deep learning with classical machine learning algorithms that perform specific sub-tasks.

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 networ ...

The strategic advantage of QML continues to expand its presence in industries that deal with complex, high-dimensional data.

In this review, to improve the efficiency of deep learning research, we focus on three aspects: quantized/binarized models, optimized architectures, and resource-constrained systems. Recent advances ...

At around that time, Andrew Ng, worked out that by using GPUs in a neural network could increase the speed of deep learning algorithms 1,000 fold. Describing the latest in neural networks, Marc Warner ...

Deep Learning and Neural Networks While classic machine-learning algorithms solve many problems that rule-based programs have struggled with, they are poor at dealing with soft data such as images ...

If you've been following developments over the last few years, you may have noticed that deep learning and neural networks have grown wildly. Neural network architecture is able to make predictive ...