A Pioneering Scientist Explains ‘Deep Learning’ – AI Trends

Buzzwords like “deep learning” and “neural networks” are everywhere, but so much of the popular understanding is misguided, says Terrence Sejnowski, a computational neuroscientist at the Salk Institute for Biological Studies. Terrence Sejnowski Sejnowski, a pioneer in the study of learning algorithms, is the author of The…

Artificial Intelligence Has a Strange New Muse: Our Sense of Smell

Today’s artificial intelligence systems, including the artificial neural networks broadly inspired by … weakens the connections between its artificial neurons to more accurately determine … insight could be useful for artificial intelligence, too. The cocktail party problem … VISIT THE SOURCE ARTICLE Author:

CNN Tensor Shape Explained – Convolutional Neural Networks and Feature Maps

Convolutional neural networks are artificial neural nets used for image recognition in deep learning. Let’s look at the typical tensor input shape for a CNN. We’ll also introduce input channels, output channels, and feature maps. Check out the corresponding blog and other resources for this…

Mist and Juniper Networks Partner to Automate Network Operations and Deliver Untapped Insight to Mobile Users Using Artificial Intelligence

… in self-learning networks powered by Artificial Intelligence (AI), today announced collaboration efforts … . The joint solution uses advanced artificial intelligence to remediate issues in the … and Mist solution combines network intelligence with artificial intelligence and deep-learning insights to … VISIT THE SOURCE…

Why Initialize a Neural Network with Random Weights?

The weights of artificial neural networks must be initialized to small random numbers. This is because this is an expectation of the stochastic optimization algorithm used to train the model, called stochastic gradient descent. To understand this approach to problem solving, you must first understand…

How to Configure the Number of Layers and Nodes in a Neural Network

Artificial neural networks have two main hyperparameters that control the architecture or topology of the network: the number of layers and the number of nodes in each hidden layer. You must specify values for these parameters when configuring your network. The most reliable way to…

This artificial intelligence model mimics human brain

… the hardware implementation of large-scale artificial neural networks. The graphene-based neural … even a rudimentary level of intelligence in wearable electronics and sensors … configurations to optimise these new “artificial synapses”. Despite the challenges, Dr … VISIT THE SOURCE ARTICLE Author:

Tensorflow.js – Introducing client-side neural networks

In this video, we’re going to introduce the concept of client-side artificial neural networks, which will lead us to deploying and running models, along with our full deep learning applications, in the browser. To implement this cool capability, we’ll be using Tensorflow.js (TFJS), Tensorflow’s Javascript…

Bias in an Artificial Neural Network explained | How bias impacts training

In this video, we’ll be discussing the bias present within artificial neural networks, so let’s get to it. When reading up on artificial neural networks, you may have come across the term “bias.” It’s sometimes just referred to as bias. Other times you may see…

Dissecting artificial intelligence to better understand the human brain

… science world, multiple forms of artificial intelligence are emerging – different networks … are now state-of-the-art in many artificial intelligence applications, such as computer vision … understanding of both cognition and artificial intelligence. “It’s a … VISIT THE SOURCE ARTICLE Author: