Artificial intelligence and machine learning have been at the center of significant innovations that we have seen in the last few years. Artificial and machine learning deserve notable mention, from advanced quantum computing systems to intelligent medical devices. The advancement in smart personal assistants can also be attributed to the advances in machine learning-related technologies. The technologies mentioned above have brought so many improvements in hardware and software that the service industries related to such areas generated revenues worth 150 billion dollars in 2019. In this article, we take a closer look at emerging artificial and machine learning technologies that are slate 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 hyper-automation is one of the most dominant information technology trends of 2020. Hyper automation believes that many business processes and operations in an organization can be highly automat. Two crucial concepts becoming popular due to this Gartner forecast include digital and intelligent automation.
Needless to mention, Artificial Intelligence and Python machine learning language are two significant resources that major digital firms actively pursue. This is because they are the drivers of hyper-automation and a gateway of advancement for the software industry. With the help of deep learning technologies and artificial neural networks, various models are being conceiv that automate business operations. Advanc algorithms and AI models are use to mine large data sets for structur information and business forecasting. This helps businesses choose the right investment path 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 conceived through traditional models make it to the production stage. The report also forecasts that if these models are power by artificial intelligence, the number would be increas by 75%. Research in AI product engineering would give rise to systems that can be readily commercializ. The distinguishing factor between an AI system and a traditional system is the ability of the former to adapt to various instructions and get modifi in the long run. Hence, the methods considered with the help of artificial intelligence are scalable and highly reliable. Not only do these products give full returns for investors, but they 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 an intelligent city depends upon the levels of cybersecurity. Various corporate systems still need to fully adopt digital strategies due to prevalent cybersecurity threats like ransomware, malware, and trojans. However, multiple 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 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 avoide. According to IHS Markit, artificial intelligence systems and devices can be actively incorporat into intelligent 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 to cause damage to different financial systems has made policymakers rethink various policy issues and regulations. Hackers have also used artificial intelligence to cause harm to critical infrastructure and defense establishments. This has raised questions about the areas of national security. Other kinds of data breaches and privacy issues are also being investigat.
All this calls for a robust policy framework regarding the gradual adoption of artificial intelligence systems in our intelligent surroundings. Creating 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.