How are the emerging artificial intelligence and machine learning technologies leading the advancement of industry 4.0

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Introduction

Artificial intelligence and machine learning have been at the center of major innovations that we have seen in the last few years. Ranging from advanced quantum computing systems to smart medical devices, artificial and machine learning deserve a notable mention. The advancement in smart personal assistants can also be attributed to the advances in machine learning-related technologies. The above-mentioned technologies have brought so many advancements in hardware and software that the service industries related to such areas have generated revenues worth 150 billion dollars in the year 2019. In this article, we take a closer look at emerging artificial and machine learning technologies that are slated to lead the advancement of industry 4.0.

Artificial Intelligence and machine learning at the center stage of hyper-automation

A market research report by Gartner predicts that one of the most dominant information technology trends of 2020 has been hyper automation. Hyper automation believes in the theory that a large number of business processes and operations in an organization can be highly automated. Two important concepts that are becoming popular as a result of this Gartner forecast include digital automation and intelligent automation.

Needless to mention, Artificial Intelligence and python machine learning language are two important resources that are actively pursued by major digital firms. This is because they are not only the drivers of hyper-automation but also a gateway of advancement for the software industry. With the help of deep learning technologies and artificial neural networks, various models are being conceived which are automating business operations. Advanced algorithms and AI models are used to mine large data sets for structured information and business forecasting. This is helping the businesses to choose the right path of investment amid a changing and dynamic market.

A rush for AI product engineering is driving the digital market

According to a Gartner report, only 50% of the products that are conceived through traditional models make it to the production stage. The report also forecast that if these models are powered by artificial intelligence, the number would be increased by 75%. This means that research in AI product engineering would give rise to systems that can be readily commercialized. The distinguishing factor between an AI system and a traditional system is the ability of the former to adapt to various instructions and get modified in the long run. Hence, the systems which are considered with the help of artificial intelligence are scalable and highly reliable. Not only do these products give full returns for investment but also lead to long-term profits. Another advantage of using such products is that they motivate the industry to invest in innovative AI product engineering giving rise to robust research platforms.

AI for cybersecurity

The entire infrastructure of Artificial Intelligence and machine learning in the environs of a smart city is dependent upon the levels of cybersecurity. Various types of corporate systems are still reluctant to fully adopt digital systems due to prevalent cybersecurity threats like ransomware, malware, and trojans. However, various types of artificial intelligence and machine learning systems can be used to identify and mitigate various kinds of cybersecurity threats. With the help of artificial intelligence, different kinds of cybersecurity tools can serve as investigation probes in communication channels. This can not only detect any suspicious digital activity but can also neutralize an impending threat. With the help of AI and ML algorithms,  potential data breaches can be avoided. According to IHS Markit, artificial intelligence systems and devices can be actively incorporated into smart homes to make them immune from cybersecurity threats.

The ethical angle

Various questions around the ethical angle of artificial intelligence have been a cause of concern in recent times. The intentional use of artificial intelligence for causing damage to various financial systems has made policymakers rethink various policy issues and regulations. Artificial intelligence has also been used by hackers to cause damage to critical infrastructure and defense establishments. This has raised questions around the areas of national security. Other kinds of data breaches and privacy issues are also being investigated.

All this calls for a strong policy framework regarding the gradual adoption of artificial intelligence systems in our smart surroundings. The creation of a white paper on AI ethics can distinguish between the pros and cons of this technology and clear the way for its full-fledged adoption in the age of industry 4.0.

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