With the digital transformation of various industries, large multinational companies have begun to use artificial intelligence (AI) to maintain competitiveness in the current digital environment. Regardless of size, AI is equally important to all enterprises, so small and medium-sized enterprises should also catch up. Start thinking about how to make the best use of AI.
According to reports, with the rise of the Industrial Internet of Things (IIoT), many companies found in the process of collecting data generated by production systems that data analysis alone cannot effectively process these huge amounts of data and provide insights to drive production operations. progress. And this is where AI and machine learning can make a difference.
Companies must recognize that AI and machine learning will play an increasingly important role. In 2017, companies spent $12 billion on AI and machine learning, and IDC predicts that it will grow to $57.6 billion by 2021. While machine learning is used to screen big data to find patterns and insights, it is AI that enables companies to use these insights to create value, such as managing the entire supply chain when automatically changing production line schedules. Change to avoid job conflicts and interruptions.
With the rise of the on-demand economy and the increasingly complex global supply chain, AI helps companies stay ahead in highly competitive markets. In order to effectively use AI, enterprises must first update and strengthen the infrastructure, including upgrading the network to facilitate the rapid and reliable transmission of data to the edge system for processing; secondly, the sensor and data analysis tools for collecting data must be deployed; The insights to optimize business processes allow companies to truly benefit from using AI.
Basically, AI can be divided into Big AI and Little AI. Big AI is used to solve large and complex problems across multiple enterprises, usually using big data in the cloud. Little AI is a real-time edge analysis tool, focusing on solving Micro-problems such as optimizing a single production line with minimal human intervention can be deployed in high-availability systems, using AI-driven automation, where SMEs can begin to use AI, and in-situ deployment of automated production systems is Little AI The main application scenario.
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