All About Circuits

Latest Deep Learning Articles and Videos

Categories

FPGA Roundup: New Contenders Hone in on Memory, Size, Power, and Even AI

FPGA Roundup: New Contenders Hone in on Memory, Size, Power, and Even AI

Three newly-released FPGAs can tell us a lot about the direction of these devices in the industry.


News Jul 02, 2020 by Dr. Steve Arar
Intel’s AI Portfolio Shows How Designs Must Gear Up for Real-Time Processing

Intel’s AI Portfolio Shows How Designs Must Gear Up for Real-Time Processing

With processing demands on data centers higher than ever before, designers should be aware of how hardware- (and software-) based AI may have increasing prominence in their designs.


News Jun 22, 2020 by Adrian Gibbons
Researchers Enhance Natural Movement in Robotics Using AI

Researchers Enhance Natural Movement in Robotics Using AI

Those using robotic prosthetics could soon move more naturally following the development and integration of AI-backed technologies by U.S. researchers.


News Jun 04, 2020 by Luke James
COVID-19 Puts Spotlight on Open-Source RISC-V Cores, IP

COVID-19 Puts Spotlight on Open-Source RISC-V Cores, IP

Remote work during this pandemic has shed light anew on the virtues of RISC-V, which has just gotten more accessible.


MATLAB and Simulink Get a Major Deep Learning Facelift

MATLAB and Simulink Get a Major Deep Learning Facelift

MathWorks has revamped MATLAB and Simulink with a host of deep learning development tools—and they say these updates will be a major boon for automotive and wireless designers.


News May 09, 2020 by Robin Mitchell
Printed Circuit Boards Receive an AI Boost Through Fraunhofer’s Modular Platform

Printed Circuit Boards Receive an AI Boost Through Fraunhofer’s Modular Platform

The AI platform from the Fraunhofer Institute for Applied Information Technology (FIT) is comprised of modules for artificial intelligence, machine learning, and deep learning.


News May 06, 2020 by Luke James
How to Build a Variational Autoencoder with TensorFlow

How to Build a Variational Autoencoder with TensorFlow

Learn the key parts of an autoencoder, how a variational autoencoder improves on it, and how to build and train a variational autoencoder using TensorFlow.


Google Proposes AI as Solution for Speedier AI Chip Design

Google Proposes AI as Solution for Speedier AI Chip Design

One of the trickiest aspects of chip design is figuring out how to pack more circuitry into a smaller footprint while maintaining power, speed, and energy efficiency.


News Apr 06, 2020 by Luke James
FPGAs Are More Accessible to Non-FPGA Specialists Than Ever Before

FPGAs Are More Accessible to Non-FPGA Specialists Than Ever Before

FPGAs pose a major drawback: they require the expertise of highly specialized (and scarce) engineers trained to work with FPGAs. Three companies have set out to change that.


News Mar 26, 2020 by Gary Elinoff
AI Devices Are Helping Us Stay One Step Ahead of COVID-19

AI Devices Are Helping Us Stay One Step Ahead of COVID-19

A number of companies are pumping out new edge AI technology—none of which explicitly state pandemic prediction or healthcare assistance as a use case. But with the overwhelming number of COVID-19 cases, might this new technology be used to that end?


News Mar 25, 2020 by Gary Elinoff
Osaka University Develops an FPGA Computing Device for Maximal Optimization of AI Tasks

Osaka University Develops an FPGA Computing Device for Maximal Optimization of AI Tasks

Osaka University researchers have built a new device that can be customized by the user for maximum efficiency in AI applications.


News Mar 13, 2020 by Luke James
Arm Adds Machine Learning and Neural Processing IP to Its AI Platform

Arm Adds Machine Learning and Neural Processing IP to Its AI Platform

Arm’s Cortex-M55 and its Ethos-U55 NPU are designed to deliver a combined 480 x leap in machine learning performance.


News Feb 11, 2020 by Gary Elinoff
Understanding Local Minima in Neural-Network Training

Understanding Local Minima in Neural-Network Training

This article discusses a complication that can prevent your Perceptron from achieving adequate classification accuracy.


Incorporating Bias Nodes Into Your Neural Network

Incorporating Bias Nodes Into Your Neural Network

This article shows you how to add bias values to a multilayer Perceptron implemented in a high-level programming language such as Python.


How to Increase the Accuracy of a Hidden Layer Neural Network

How to Increase the Accuracy of a Hidden Layer Neural Network

In this article, we’ll perform some classification experiments and gather data on the relationship between hidden-layer dimensionality and network performance.


How Many Hidden Layers and Hidden Nodes Does a Neural Network Need?

How Many Hidden Layers and Hidden Nodes Does a Neural Network Need?

This article provides guidelines for configuring the hidden portion of a multilayer Perceptron.


Training Datasets for Neural Networks: How to Train and Validate a Python Neural Network

Training Datasets for Neural Networks: How to Train and Validate a Python Neural Network

In this article, we’ll use Excel-generated samples to train a multilayer Perceptron, and then we’ll see how the network performs with validation samples.


Signal Processing Using Neural Networks: Validation in Neural Network Design

Signal Processing Using Neural Networks: Validation in Neural Network Design

This article explains why validation is particularly important when we’re processing data using a neural network.


How to Create a Multilayer Perceptron Neural Network in Python

How to Create a Multilayer Perceptron Neural Network in Python

This article takes you step by step through a Python program that will allow us to train a neural network and perform advanced classification.


Neural Network Architecture for a Python Implementation

Neural Network Architecture for a Python Implementation

This article discusses the Perceptron configuration that we will use for our experiments with neural-network training and classification, and we’ll also look at the related topic of bias nodes.