Читать книгу Industrial Internet of Things (IIoT). Intelligent Analytics for Predictive Maintenance онлайн

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Through AI solutions, it is possible to eliminate boring tasks that may be necessary, but with machine learning, it performs basic tasks, considered human-computer interaction technologies, or even related to the more robust use found in conversational interfaces that use machine learning to understand and meet customer needs [23–25].

Even through AI solutions, it is possible to concentrate diffuse problems where data inform all levels of the operation of a modern company, i.e., it has a lot of material to interpret, so it is necessary to consume this amount of information at scale. Since the extent of the data available today has gone beyond what humans are capable of synthesizing, making it a perfect job for machine learning. Through the data, the information is extracted from various sources of public and private data, still comparing them and making changes when necessary [25].

Through AI solutions, it is possible to distribute data, given that modern cybersecurity leads to the need to compare terabytes of internal data with a quantity of external data. With machine learning, it can automate the process of detecting attacks as cybersecurity problems change and increase, vital for dealing with distributed data problems, assessing that humans are unable to involve their actions around a distribution so wide of information. AI solves dynamic data, which is a valued characteristic, given the major obstacle related to addressing individual employee characteristics, or dynamic problems of human behavior. Through AI, it is possible to use determining complex patterns to help organizations move more quickly and respond better to the changing needs of each employee [26].