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In the times of AI and ML

There are at least two clear trends that show a demand-supply mismatch in tech jobs, in cutting-edge IT fields such as artificial intelligence and machine learning. One is through industry predictions that estimate growth in the AI market from $21.46 billion to $190.61 billion between 2018 and 2025. Year on year growth is projected to be an impressive 36.62% during the same period. The second trend is more subtle. Big Indian IT firms in the U.S. are reportedly ‘hoarding’ employees in these two fields as they foresee a shortage in skilled experts. They also fear a corresponding rise in the cost of hiring employees for tech contracts they have bagged for the future.

Using AI and ML

Unlike the exaggerated robots of the 2001 Steven Spielberg movie of the same name, artificial intelligence (AI), in reality, is tamer. AI is understood to mean ways of making computers, computer-controlled robots or programmes think intelligently mimick the manner in which humans think intelligently. A computer programme with AI can solve generic problems it is programmed to, instead of just specific ones. They can accommodate new modifications to input without breaking structure. Traditional programmers would have to sort, sift and debug thousands of lines of code to make modifications.

AI finds applications in strategy games such as chess or poker where advance moves are determined by heuristic logic, natural language processing, virtual assistant technology, image and speech recognition and automated robotics. General AI systems which can solve any given problem are rare. Insurance and banking organisations regularly use AI to monitor fraud. Marketers use AI every time you shop online to gather your browsing habits and predict what you are most likely to buy. They will then advertise those products through pop-ups and logos. Self-driving cars, auto-pilot modes and smart homes using sensors all rely on AI and affect daily lives of consumers.

There is also a difference between AI and machine learning (ML), although a number of articles on the web club them together or use them interchangeably. “ML is the study of computer algorithms that improve automatically through experience” according to Tom Mitchell of Carnegie Mellon University. It is simply one of the ways we use to achieve AI or something closer.

Acquire skills

Nearly all forms of enterprise software, factory automation, transport and other industries are increasingly using AI-based interfaces in their daily operation. In fact, by 2030, AI may end up offering $ 15.7 trillion to the global economy.

Mathematical and programming skills are central to acquiring competency in this field. However, for seasoned tech professionals, it is important to develop excellent communication skills. An understanding of how business works and the common processes used in day-to-day operations will help you better utilise your core competencies to improve organisational workflows. For complete beginners, programming using C++ is a mandatory requirement. Also necessary is an understanding of how algorithms are created and executed.

Typically, knowledge and expertise in Bayesian networks, neural networks, cognitive science theory, engineering, physics, robotics, undergraduate algebra, calculus, statistics and probability are essential to hone your talents in ML. Computer science graduates need only supplement their knowledge of math and computing with a specialised course in AI and ML.

Opportunities galore

Analysis of professional networking site Linkedin.com has shown that India is the third best-placed economy after the US and China to crack AI jobs and careers with high penetration of AI awareness. AI is a big part of investments into startups at an estimated by private players alone in 2016.

Among the more exciting opportunities one can expect in 2019 is the rising application of AI in healthcare to detect and diagnose health issues in individuals. Smart infrastructure to help balance rapid growth in urban centers in India is also an option being explored by the government. B. Tech programmes now mandatorily have AI, IoT, ML and some other essential components of emerging technology. However, constant changes in this dynamic field have made it mandatory for professionals to keep upskilling through noted institutions to remain relevant and job-worthy.

The author is CEO and founder, Intellipaat

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Printable version | Feb 23, 2021 3:20:36 AM | https://www.thehindu.com/education/in-the-times-of-ai-and-ml/article26341502.ece

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