What if in our attempt to build artificial intelligence we don’t simulate neurons in code and mimic neural networks in Python, but instead build actual physical neurons connected by physical synapses ...

The data science doctor continues his exploration of techniques used to reduce the likelihood of model overfitting, caused by training a neural network for too many iterations. Regularization is a ...

Neural network dropout is a technique that can be used during training. It is designed to reduce the likelihood of model overfitting. You can think of a neural network as a complex math equation that ...

While power tools and libraries, such as Apache Spark and Intel’s Trusted Analytics Platform, make it possible to quickly design, implement, train, and test neural network applications, it is the ...

At the MIT EmTech Digital conference, startup Nervana announced plans to design and build a custom ASIC processor for neural networks and machine learning applications that the company’s CEO, Naveen ...

Artificial Intelligence—or, if you prefer, Machine Learning—is today’s hot buzzword. Unlike many buzzwords have come before it, though, this stuff isn’t vaporware dreams—it’s real, it’s here already, ...

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When we design a skyscraper we expect it will perform to specification: that the tower will support so much weight and be able to withstand an earthquake of a certain strength. But with one of the ...