A Step : Towards Artificial Intelligence

We’re in a world where everyone is trying to save their time and energy. The invention of machines and the ongoing tech advancement has very much satisfied this quest. The capability of machines for multitasking, has elevated the efficiency and the speed, which in turn reduces the time of performance. This multitasking feature also led us towards the concept of Artificial Intelligence (AI). As the name suggests, Artificial Intelligence points to the creation of computers as intelligent as human beings.

According to the father of Artificial Intelligence John McCarthy, AI is defined as : “The science and engineering of making intelligent machines, especially intelligent computer programs

Artificial Intelligence is the ability of a machine or a computer, to perform functions coherently as humans do. It is a way to make machines learn to work, think, or react in a way similar to humans.

While development of computers or machines, a common question emerged in everyone’s mind, “ Is machine able to think and work like humans? ”. At this point, the idea generated, to create the intelligent machines that could be replaced by humans, when needed.


As the entire world is moving towards automation and increased efficiency, AI is, and will play an important role towards the future in the technologies.

Nowadays, Artificial Intelligence is used in almost all industries, be it medical, engineering, or education, at a very large scale. Following are some fields where AI is used on its boom:

  • Gaming

The gaming industry are one of the earliest users of AI. There are many games which are using bots, such as, PUBG, Chess, Poker, Tic-Tac-Toe, etc. In all such games we’re playing games against AI – powered bots.

  • Smart Speakers

We all know about the Amazon Echo series, how it works and recognizes the words and commands that are given to it, and behaves accordingly. It can also be used to send and receive messages, setting reminders, getting latest news and notifications, etc. Smart Speakers can be best considered as an example for use of AI in real life.

  • Online Advertisements

Online ad industry also has a broad use of Artificial Intelligence to track the user statistics for a particular website or products and also provides ads based on those statistics. If we assume the online ads without AI, the users would get ads which will have no connection to their previous searches. So, we can say that AI is effective in determining user’s interests and providing the ads accordingly.

  • Smartphones

If we look at the stats, more than 4 out of 10 people in the world are equipped with a smartphone. So, for the higher sales, the companies would focus  on providing smart features including AI for better functioning. These features can include smart voice assistant, like Google Assistant, Alexa, Siri, etc. or the inbuilt AI camera. The cameras in these smartphones are expert enough to capture portraits, scenes very well.

There are many such areas where AI is being used at its peak. Our lives are largely affected by the technologies, especially, AI. So, if we assume that technology doesn’t affects our lives, that’ll be wrong assumption, for sure.    


Artificial Intelligence is impacting the future of industries and also the human beings. It is the main reason for the emergence of technologies like, big data, deep learning, machine learning, IoT, etc. There is no industry or field left, where AI has not setup its roots. It is covering the entire market slowly and quickly.  

As AI is focused on making the machines learn things and think just like humans. This will lead to the replacement of humans with machines in industry. Saving the time on one hand and increasing the efficiency on the other. But we should focus on the idea that AI is not to replace us. It will improve our abilities, and will make us better for what we are doing.

So far we’ve also got the concept of NLP (Natural Language Processing), which is nothing but the branch of Artificial Intelligence, that includes how machines are capable of understanding human language. Its common examples, as we’ve already discussed are Google Assistant, Alexa, Siri. NLP just understands the commands like, “Hey Google, turn on the flashlight” and turns these into numbers understood by the machines.

Here, we can say that through AI we’re all able to make machines understand our language.This in turn will save our time in programming, for even  small commands, that needs to be put up.


We all are very well aware of the fact of, AI becoming popular in industries and businesses. But there are many real-world challenges being faced by the creators, to make AI operate smoothly. Following are some of the most common challenges faced, of which we all must be aware of :

  • Lack of Data

The AI algorithms learn from the data that is already available, provided the quality of data should be good. If the data is up to the mark, better will be the final algorithm. This generally requires a large amount of data which may not be available at times. In order to overcome this problem, some of the companies are focused in creating AI models which could give their best results in spite of the lack of data.

  • Bias

The nature of an AI machine relies on the amount of data given to process, and get themselves trained. But sometimes they become biased too, based on some specifications in data ( like religion, gender, community or race) they are fed with . In such cases, companies find it difficult to tackle the situation. The only solution could be, to create some more algorithms that can’t differentiate people and work efficiently.

  • Case – Specific Learning

AI algorithms are trained only for a particular situation. They can’t be transferred from one situation to another. Like ,humans deal with different situations depending on any previous situation, machines are not able to face  situations, other than what they are commanded for. For this, we’ll have to create another algorithm with different data set, related to the current situation. We can perform this algorithm slightly similar, to the one’s we’ve formed earlier, but having additional steps and conditions.

One thing we all need to remember is that any problem or situation cannot be solved or handled in a short span of time. So, the companies dealing with the problems or situations, need to have better knowledge of Artificial Intelligence. So that they could form the algorithms in minimum amount of time. Hence if any new problem arises in front of them, they could easily tackle that.

  • Knowledge Deficiency

Although, AI is the hot topic in the tech industry, but there are only a few people, who are aware about, how AI works actually and what is it. The small business owners don’t know that how can they replace the traditional systems with Artificial Intelligence. The conceptualization of AI is confined to the technology experts, college students, research scholars and few more other than these.

In order to make more people aware about this, these skilled people should come out to increase the knowledge regarding AI, which will help to increase company’s productivity effortlessly and within a time limit.


Artificial Intelligence has been broadened very rapidly, it’s necessary to have information about the tools available for AI. There are a number of tools available for AI. Some of them are listed below:

  • Caffe

It was created by Yangqin Jia as his Ph.D. research at UC Berkeley. It has a structure having BSD-authorized C++ library with Python interface. Caffe is coded with easily readable source code and is having good quality. It is now an open-source tool that can be used by anyone.

  • Keras

It is also an open-source neural network for those who prefer to work in Python environment. If we want to perform some tasks quickly and easily, then we should go for it. It works on neural networks that uses TensorFlow and similar methods as its backend.

  • Scikit-Learn

It is an open-source Machine Learning framework beneficial for data mining, data visualization or data analysis. It enlarges the libraries of Python, i.e., NumPy, SciPy, Matplotlib. It doesn’t have multiple versions and is not suitable for large amount of data.

  • Theano

It is a Python library that makes mathematical expressions easy to define, optimize, manipulate, and evaluate using computer’s algebra system. While dealing with deep learning, there are a number of numerical tasks to be performed. In that case, using Theano is the best choice.

There are many other tools and frameworks as :

  • TensorFlow
  • MxNet
  • PyTorch
  • CNTK
  • AutoML
  • Google ML Kit
  • Azure Machine Learning
  • IBM Watson


Artificial Intelligence has always been a topic of discussion and interest as well,   and it’ll always be until the machines are  going to work, react, think, create and behave like humans. The world has already done so much researches and experiments to do the same.While  many of them are on the way to reach their goal. We can clearly see that AI has almost covered the needs of humans, and has been so much helpful in saving the manpower and time. But along with the advantages it provides, it’s also required to focus on the consequences to be faced. Overall, every technology has its own merits and demerits based on the requirements of the current generation.

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