Purchasing Artificial Intelligence

Artificial intelligence (AI) and its offshoot, machine learning, have been attracting a lot of interest across manufacturing verticals with the promise of converting in-depth data analysis into improved production operations. The technology is also being applied directly to production in tangible ways, as can be seen in Frito-Lay’s use of machine learning in its quality and weighing process.

But just how do you get your hands on this technology to begin using it? One answer to that question is Newark’s online AI resource site. This segment of the Newark site covers topics ranging from basic explanations of AI, to the different types of AI applications, to descriptions of specific AI products.

To help visitors to the site avoid getting bogged down in the AI-related possibilities, the Newark AI site features the company’s AI Configurator—an interactive tool that allows engineers to determine the most appropriate products for their AI projects. According to Newark, the AI Configurator identifies the various development boards, sensors, and software from a wide range of vendors that best meet the needs of the application. Users select the application that most closely resembles their requirements from a list that includes predictive maintenance, voice recognition, object or human recognition, motion recognition and machine learning.This enables users to select the most suitable products with confidence and obtain optimum results faster, speeding up development without the need for unnecessary and often time-consuming research.”

Two new AI products recently added to this site include:

• The SmartEdge Agile device—a meta-sensor, coupled with the Brainium Internet of Things (IoT) platform and designed to provide AI and security for edge computing. The SmartEdge Agile meta-sensor is CE and FCC certified and both hardware and software can be used for IoT projects.
• The Ultra 96 Arm-based Xilinx Zynq UltraScale MPSoc development board based on the Linaro 96 board specification to simplify machine learning. The 96 boards’ specifications are open and define a standard board layout for development platforms used in software applications, hardware devices and kernels.