How Artificial Intelligence became a hot topic of the 21st century

Artificial Intelligence

Welcome to the age of Artificial Intelligence, where the world is lit not by switches but by our wishes and commands.

The field of Artificial Intelligence (Artificial Intelligence) has shown an upward trend of growth in the 21st century. The evolution in Artificial Intelligence has advanced the development of human society in our own time, with dramatic revolutions shaped by both theories and techniques.

However, the multidisciplinary and fast growing features make Artificial Intelligence a field in which it is difficult to be well understood. In this paper, we study the evolution of Artificial Intelligence at the beginning of the 21st century using publication metadata extracted from 9 top-tier journals and 12 top-tier conferences of this discipline.

We find that the area is in the sustainable development and its impact continues to grow. From the perspective of reference behavior, the decrease in self-references indicates that the Artificial Intelligence is becoming more and more open-minded. The influential papers/researchers/institutions we identified outline landmarks in the development of this field.

Last but not least, we explore the inner structure in terms of topics’ evolution over time. We have quantified the temporal trends at the topic level and discovered the inner connection among these topics. These findings provide deep insights into the current scientific innovations, as well as shedding light on funding policies.

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In this new age of technology, everyone wants to incorporate artificial intelligence (AI), machine learning (ML) and deep learning (DL) in day-to-day life to achieve ease of working. Most of the times, these are interchangeably used but it is important to understand that artificial intelligence is the hood under which all these other terms are. These technologies have wide range of applications in various sectors such as banking, finance, manufacturing, healthcare, education, business, information technology, retail etc.

Artificial intelligence is a part of computer science which teaches machines to think and work like humans.

There are three different types of AI:

• Artificial Narrow Intelligence (ANI),
• Artificial General Intelligence (AGI) and
• Artificial Super Intelligence (ASI).

Examples of artificial intelligence are manufacturing robots, self-driving cars, smart assistants, proactive healthcare management, disease mapping, automated financial investing, virtual travel booking agent, social media monitoring and so on.

Now, moving on to machine learning, this is a division of artificial intelligence. Machine learning offers various algorithms which use statistical methods and concepts to learn from the historic data which is available and change the understanding of the algorithm subsequently. There are different machine learning algorithms such are decision trees, random forests, K-means clustering, support vector machines, linear or logistic regression etc. All these algorithms build models using sample data and use this model to make certain decisions or predictions as per the need.

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There are three types of ML:

• Supervised Learning,
• Unsupervised Learning and
• Reinforcement Learning.

Machine learning applications include email filtering, churning of a customer or loan defaulter, predicting outcomes of games, scores of students, prices of houses or cars and so on.
And finally, we have Deep learning. This is a subset of artificial intelligence as well. Deep learning mimics the functions of a human brain by using neural networks. Deep learning is essentially a machine learning algorithm which uses multiple deep neural networks to evaluate the available data and produce results accordingly.

Deep learning is used for:

• Different object detection,
• speech recognition,
• languages translation,
• caption generation,
• news aggregation and etc.

Deep learning models require humongous amount of data along with high computational power. With increase in data, there is increase in the depth of neural networks and this results in DEEP networks being formed. Advantage of deep networks over machine learning is that as the model trains on the sample data, it begins to learn to extract and engineer its own functions which we manually must engineer in case of traditional machine learning algorithms.

In upcoming blogs, we will dive deep into different algorithxsms, their uses and applications, required hyper-parameters and so on. Stay tuned!

METHODOLOGY

In this section, we first introduce publication dataset used in analyzing the corpus of AI. Next, we describe several measures quantifying the importance of authors and publications in this area. Finally, we emphasize on profiling the inner structure of the field based on the topic evolution.

The law of reciprocation: Artificial Intelligence

Before the advent of the 21st century, humans began to industrialize things since the invention of the steam engine. Such an endeavor of the industrial revolution introduced the concept of factories with which came the menial factory jobs and the huge machines, which were operated by humans. This called for the factories to be more automated than they already are. Automation is achieved when a particular machine or a set of machines can carry out a function in a self-sustained manner without human intervention.

Humans and Machines: They go hand in hand; how?

Humans and machines have a long history that dates back to the invention of the first wheel cart and the first fire lighting device or mechanism. Humans have for a long time sought the invention of an automaton – the machine that can mimic humans. And the most characteristically unique feature possessed by humans is intelligence. 

Hence when computers came into play after the second world war – thanks to Alan Turing – humans finally got the perfect thing which ran upon data structures and algorithms and hence had the ability to mimic the human brain. What we possess is natural intelligence – provided to us directly by mother nature. And so, we try and create a model of it – and since we made it – call it artificial intelligence.

The artificial glamour of intelligence: Why AI is truly remarkable

Just like humans can practically do any human job, so can an AI. This includes making art or writing beautiful lines of poetry or simply working an office job. In the 21st century, we live in an age of development and data. Companies are hiring people to make AIs and develop them to fit customers’ needs. Since AI finds its application in almost every field – like a human – most people working with high-end systems and technologies have begun to learn AI and it grows like wildfire with time.