You can’t escape the drumbeat around artificial intelligence. Everywhere you turn, there’s a TV ad pushing the latest AI software. It seems like every vendor is pushing the latest tool kit. Every day, there’s an article on a new use case for ChatGPT, Bard, etc. The world seems to be screaming: You need AI now!
Artificial intelligence is indeed becoming a crucial technology in automation and industry. But for those new to AI technologies, it’s not always clear where to begin. How is AI be applied to automation applications? Where can it have the most value? How do you measure success?
Machine learning techniques have been slashing costs and improving results in test and measurement operations for more than a decade, and the hopes of tapping into process data to glean actionable insights is the underpinning principle of Industry 4.0.
Introducing AI into manufacturing is a challenge. Integrating physical and chemical parameters, the sheer volume of data and the inherent responsibility associated with decision-making underscore the complexities. Because of these difficulties, many ambitious AI solutions often never pass the initial creation and testing stages.
Jim begins the episode with an insight into the ongoing process of creating AI policies and guidelines, addressing how they influence AI’s safe and responsible deployment. The discussion elaborates on various governments’ approaches to AI policy, highlighting the global impact of these decisions.
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