What is Artificial Intelligence? – Scope for Engineering Students

Among the students considering an engineering degree, Artificial Intelligence is a great shift as a stream. Those who are Electronics and Communications Engineering degree holders, a large percentage of them are inclined towards pursuing a career in AI. So, what exactly is AI, and why has there been such an uproar about it? Are there sufficient career options? Will it sustain its demand in the future? How did it all start? Here's an article just for you. Consider it a brief starter and a compressive guide to help you understand the basics of Artificial Intelligence.

What is Artificial Intelligence (AI)?

Definition:

Techopedia defines AI as: "AI is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans."

Comparison with Human Intelligence:

The above definition means that computers or machines can act or behave "intelligently" just like human beings. The question is: Computers are already intelligent; they can compute and calculate much faster than any average human brain. So, are all computing machines that make calculations or numerical data processing faster part of AI? The answer is, "NO." In the above example, the machines are merely performing routine activities at a much greater speed based on "instructions" fed to them. These activities do not require any amount of "perception," or "learning," or "decision-making" and hence cannot be termed as Artificial Intelligence. When machines try to "learn" from the environment, "decide" their course of action, and then "behave" in a way that can exploit the probabilities of attaining the goals, it is known as Artificial Intelligence. In a way, AI tries to mimic human Intelligence by emulating cognitive functions. Why is it called "Artificial" and not "natural" Intelligence, or are the two the same? No, they are not. AI is merely trying to emulate natural responses such as understanding human speech and responding to it with certain limitations. In addition to that, "Artificial" Intelligence lacks emotionality and consciousness compared to "natural" Intelligence.

Cognitive features of AI:

All AI programs are cumulative of three cognitive functions: Learning, Analysis, and Correction

Learning:

This process involves the data accumulation aspect. The large data acquired is then converted into actionable information by using "rules" or algorithms. These algorithms are nothing but built-in instructions for the machine to complete a certain task with the data given.

Analysis:

The Analysis or the Reasoning aspect deals with the part where the machine can "choose" the right or suitable algorithm in a certain situation to produce a certain result.

Correction:

This is the best part of AI because the programming is such that it can self-correct the algorithms and fine-tune it with each application to ensure the best results possible.

Brief History of AI:

The famous novel of 1818, Frankenstein, written by Mary Shelley, is about a monstrous creature who could behave like humans created through scientific experiments. However, the subject's actual evolution, whereby an unnatural or artificial machine could behave like a human by displaying Intelligence elements, began with Alan Turing. Alan Turing is well-thought-out to be the father of Artificial Intelligence. Turing's Theory of Computation suggests that a computer can simulate any deduction through shuffling symbols like "0" and "1". The 2014 movie, The Imitation Game, is a must-watch for those who wish to see how "machines can think" became a concept with Turing's code-breaking of the Enigma, a German communication system during the Second World War. In 1956, in a Dartmouth College workshop, a famous American computer and cognitive scientist coined the term "Artificial Intelligence," and it became a separate field. Since the 1980s, Artificial Intelligence has become a billion dollar industry with the production of "expert systems."

What is the AI Effect?

To understand the AI Effect, let's look at Larry Tesler's Theorem: "AI is whatever hasn't been done yet." The concept of referring to something or some phenomenon as AI is quite dynamic according to the AI effect. Once a problem is solved, or a program is designed, and the solution or "intelligence" is applied to multiple systems, it stops being intelligent anymore. It just becomes a program that requires no more "intelligence," just a collection of codes. When a machine plays chess, the first solution that went into designing the system was AI. Still, the minute it became a program, it is not considered to be Intelligence any longer. This concept gives "problem-solving" a huge credit and its repetition, none at all. Once AI solves a problem, it is not a part of AI anymore. Pamela McCorduck, the famous American author of AI books, refers to the AI effect as an "Odd Paradox." She says, "practical AI successes, computational programs that achieved intelligent behaviour, were soon assimilated into whatever application domain they were found to be useful in, and became silent partners alongside other problem-solving approaches, which left AI researchers to deal only with the "failures," the tough nuts that couldn't yet be cracked."

AI in BML Munjal University:

At BMU, we strongly believe in leading students through this change in industrial requirements and transition in science and technology. We create industry-ready professionals geared up to delve into the real-world challenges through our curriculum and pedagogy. We have integrated learning with the process of theory as well as practice. Our courses are designed in a way that helps to keep students abreast of the latest developments in the fields of education, science, technology, and management. Our B.Tech specialisation in Electronics and Communication Engineering includes advanced subjects on Artificial Intelligence, Data Science, Machine Learning. Through this course, we target to prepare the students to become the researchers and industry experts of tomorrow specializing in Artificial Intelligence. We endeavour our best to build in a spirit of inquiry, problem-solving, creativity, and innovation in the minds of our young enthusiasts.

Why is AI in Demand?

We now know what Artificial Intelligence is and where it came from. But why is there a demand now, and experts see a skyrocketing demand in the future? To answer this, let us see how Artificial Intelligence works. The learning process of Artificial Intelligence works just like humans. Machine Learning is, therefore, often used interchangeably with AI. But Machine Learning is the process of "teaching" the AI system and the system learning by mimicking humans. In most cases, the system can perform better than humans, faster, more efficiently, and less susceptible to errors. This is why AI is bringing storms in industries where human effort can be replaced by machines. And that is, in turn, causing a shift in technology, the labor market, the job market, and newer applications. Let us

Scope of AI:

There is a vast field in which Artificial Intelligence can be and is being applied. From robotics, medicine, engineering, military, space science, marketing, social media, communications, AI is altering how things have been working and empowering technology. It is no wonder that the billion-dollar turnover companies are shifting to AI and are continuously looking out for engineers who can work and develop the technology to benefit their operations. Facebook, Amazon, Intel, Samsung, Accenture, Uber, Google, Microsoft, and such giants. This is not to exclude thousands of start-ups operating in the AI field and bringing out numerous applications using this technology. Nearly 31% of all organizations use AI in their processes and operations, whether recruitment or communications. We should not forget to mention the banking financial sector is the primary user of AI for risk detection and fraud analysis. The AI applications are not restricted to industry operations alone. If we look around us - mail filtering, spam detection, customized advertisements, social media, self-driving cars, smartwatches, Alexa responding to our queries "intelligently," phones using face passwords, maps throwing up the best-available driving routes are all using Artificial Intelligence. So, where do we get ongoing? Well, AI and analytics make a great team. With the help of relevant data, analytics is designed to analyze the ever-increasing amount of data that organizations can access. More and more establishments realize the importance of analytics in their organizations to achieve competitive advantage and effectiveness. To do this better and achieve the business objectives in highly effective manners, organizations are executing AI and analytics in their dull jobs. This blend of power helps process data quicker and easier to extract insights on an instantaneous basis. A clear consideration of analytics is what paves the way for AI adoption. Because it is only an establishment's strong analytic capabilities that will help it leverage AI more effectively. Therefore, a career in AI is becoming increasingly more desirable. More and more productions worldwide are going to be AI dependent in the coming days. The global spending on Artificial Intelligence is expected to go up to more than seven billion dollars per year by 2022, unthinkable even in the last year.

Career opportunities in Artificial Intelligence (AI)

If you have been reading this article, AI as a subject certainly interests you. There is a possibility, and rightly so, you will eventually choose AI as a career option. And by all means, you should. Between 2015 and 2018, there is almost 100% growth in the segment, including jobs with Machine Learning, neural network tags, and deep learning. AI is at the top in terms of the list of skills with the growing demand for jobs. There is a lot of work available on how AI will replace human jobs and, therefore, lose jobs rather than create opportunities. According to McKinsey Global Institute's data, by the year 2030, at least 73 million jobs will be automated by AI. While it is true that certain repetitive, hazardous, unproductive, time-consuming jobs can be replaced by AI, the companies will be under immense pressure to hire more and more AI professionals who can work with the technology to make it more effective and applicable to their businesses. There is a vast shortage in the current years, and that gap may go up in the coming years unless more engineers step up and are garnered towards the field. It is the best moment to make the most of this opportunity and launch oneself into an interesting and rewarding career. Let us look at some of the jobs that have been created in the field of AI and ML:

• Machine learning Engineer
• AI Expert
• Data Mining Engineer
• Business Intelligence Developer
• Data Scientist
• AI Research Scholar

Artificial Intelligence systems work with algorithms fed into them by Machine Learning engineers. An ML Engineer can earn an average of $ 114,121 per year in the US and Rs 8,00,000 in India (According to Glassdoor). On the other hand, data plays a huge role in AI. An enormous amount of data goes into building each algorithm and each AI system. A data scientist works towards crunching this data and analyzing them, which goes into building the system. A data engineer is closely associated with AI and can earn somewhere around $113000 per year in the US.

Conclusion:

The above examples clearly show where the demand stands today for AI professionals. And with each passing day, this is going up, as are the applications of AI. Let's consider the contribution of AI in healthcare alone. We have virtual health assistants, chatbots, and IBM Watson, which can recognize natural speech and respond accordingly by mining patient data. These are certain areas in which AI is turning out to be a boon for the human race. No wonder there is so much investment in such technologies, which justifies AI's trajectory in the future. We can only hope that AI continues to grow and develop so that it can be used to positively impact our lives.