In principle it's possible to create a neural network classifier for MNIST data using just a single linear layer that accepts 784 input values and emits 10 logits or pseudo-probabilities. But this ...

Neural networks are more powerful than these alternatives, in both the mathematical sense and ordinary language sense, but neural networks are more complex than the alternatives. Let me reiterate that ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light ...

Recurrent neural networks, or RNNs, are a style of neural network that involve data moving backward among layers. This style of neural network is also known as a cyclical graph .

Convolutional neural networks (CNNs): These machine learning systems are commonly used for machine vision, object detection, image classification and certain types of forecasting.

The race is on to create one neural network that can process multiple kinds of data -- a more-general artificial intelligence that doesn't discriminate about types of data but instead can crunch ...

The Large Hadron Collider is one of the biggest experiments in history, but it’s also one of the hardest to interpret. Unlike seeing an image of a star in a telescope, saying anything at all about the ...

As a result, researchers are increasingly turning to synthetic data to supplement or even replace natural data for training neural networks. “Machine learning has long been struggling with the data ...