It is certain that artificial intelligence will be the future branch of engineering and it will drive technological innovation in the academic world. Leading colleges and universities of the world would provide courses in artificial intelligence at the undergraduate and postgraduate level. In addition to this, new research institutions would be established that would exclusively specialise in artificial intelligence. The story would not be different in India. A large number of engineering colleges would provide short term and long term courses related to artificial intelligence as well as research areas related to the subject. The top engineering colleges in Ghaziabad, Noida, Gurgaon and other areas around the capital would turn into AI factories with the motive of training students in artificial intelligence and related skills. That said, it becomes pertinent to look at the basics of artificial intelligence in deeper detail.
The AI evolution
AI as a concept started evolving as early as the 1940s. It was during this time that the term artificial neurons was coined by McCullough and Pitts. Ten years later, the computer was fabricated based on artificial neural networks. For the next 30 years, artificial intelligence witnessed little development and more stagnancy. It was during the 1980s that the progress of artificial intelligence picked up pace which continues till date. In fact, the 21st century has been primarily dominated by various applications of artificial intelligence.
The AI ecosystem
The ecosystem of artificial intelligence is powered by intelligent machines, systems and processes. Machine learning, natural language processing, deep learning as well as data analytics form critical components of this ecosystem. This ecosystem provides the interface where human machine interaction takes place in a seamless manner. One of the best examples of an ecosystem powered by artificial intelligence is that of a smart city. In the environs of a smart city, different devices, processes and systems communicate with each other at various levels. The communication between different devices and systems is popularly known as the internet of things. In addition to this, data processing and data analytics are also critical components of this ecosystem.
AI engineering
AI engineering is a specialised discipline that is built exclusively with subjects like machine learning, deep learning, reinforcement learning, internet-of-things, cloud computing data structures and soft computing. We can say that AI engineering deals with those prospects of computer science that have a wide range of applications. The most important applications of artificial intelligence are in the domains of e-commerce and business analytics. For instance, predictive analytics, prescriptive analytics, diagnostic analytics, customer recommendation, customer personalization as well as customer targeting are all outcomes of systems powered by artificial intelligence.
AI skill set
The skill set of artificial intelligence is as vast as the scope of this subject. The programming languages that most of the developers use include Python, JavaScript, HTML5, numpy and the like. The person who wishes to pursue a career in artificial intelligence should be proficient in software development. He should have a firm understanding of the development of software life cycle, testing as well as maintenance. He should also be proficient in mathematical skills as they form a vital component of algorithms through which we can conceive intelligent systems. Some of the basic mathematical skills relate to the disciplines of algebra, probability, and statistics. K nearest neighbor classification techniques, Naive Bayes, and support vector machines are also equally important. AI models can be easily fabricated if we have a firm understanding of Markov models, Naive Bayes, and gaussian mixture models.
Applications: Business AI
The applications of artificial intelligence in business operations are vast and numerous. In fact, business intelligence is a direct consequence of the application of artificial intelligence in business development. It is important to understand business intelligence with the help of some examples. The customer data collection, it’s processing, and analytics can be attributed to artificial intelligence. This analytics becomes extremely crucial for taking important business decisions. In addition to this, we can use analytics to predict the growth of our business in a dynamic market. Customer recommendation systems, as well as customer relationship management systems, can be effectively maintained with the help of artificial intelligence.
The way ahead
Artificial intelligence is not restricted to technical skills alone. It also requires soft skills so that the most technical information can be conveyed in a simplified format. This can help in drafting future road maps for the optimization of business operations.
In the future, the scope of artificial intelligence will increase and this technology will traverse newer and wider realms.