Issue link: https://resources.mouser.com/i/1437726
30 REIMAGINING WHAT'S NEXT Intel Software toolS for aI applIcatIonS h ardly a decade ago, the notion of practical Artificial Intelligence (AI) was seen as a pipe dream by many technical professionals not working directly on such technology. Still, the idea of humanity creating artificial life is as old as antiquity. The Greeks had a legend of an artificial bronze creature named Talos that protected the island of Crete by hurling massive boulders at would-be invaders. The 1950s saw an explosion in science fiction literature and movies, many of which featured robots or similar automatons that manifested some level of human-like intelligence. And while we are still far from a true generic AI, we are approaching fairly reliable mastery of mimicking human behavior in a few narrow use cases such as machine vision. Silicon is to AI as carbon is to you and me. Intel is one of the companies that are synonymous with silicon as they were the first to launch a commercially available microprocessor, the Intel 4004, in 1971. They are now taking their fifty-plus years of computer architecture and electronic design expertise and applying it to the frontier land that is AI. Undoubtedly, they hope that AI will represent as big of a revolution in computing as semiconductors and the Internet once were. Thus, Intel knows that their success and the success of AI technology are beholden to product developers' success and system integrators that choose to leverage Intel hardware. As such, Intel has invested heavily in producing developer tools to make creating AI-based applications as straightforward and cost-effective as possible. Some of the more popular use cases involving AI technologies include object detection, image/video classification, recommendation engines, anomaly detection, text classification, text matching, and natural language processing. AI is an umbrella term for a branch of computer science that covers a wide range of approaches to mimicking animals and ultimately human-like thinking. Machine Learning (ML) and Deep Learning (DL) are two specific implementations that give technology the learning and problem-solving abilities found in biological life. DL is Michael Parks, PE for Mouser Electronics Intel one API And ArtIfIcIAl IntellIgence APPlIcAtIons Intel one API And ArtIfIcIAl IntellIgence APPlIcAtIons