The What, How, and Why of Artificial Intelligence and Machine Learning

The What, How, and Why of Artificial Intelligence and Machine Learning

We all are well aware of Virtual Personal Assistants, Smart Cars, and Video Games but do we all know how all these technologies came into existence. Artificial Intelligence made it all possible. Artificial Intelligence majorly focus on areas of computer science where it lays more emphasis on creating intelligent machines that work and reacts the same like humans do. The computers made with Artificial Intelligence are capable of Learning, Planning, Problem Solving, Speech recognition etc.

Machine Learning is an application of Artificial Intelligence that serves the systems with an ability and capability to automatically learn and improve from experience. Machine Learning majorly focuses on the development of computer programs that extensively accesses the data and uses it for them.

Machine learning allows the software applications in becoming more accurate so as to correctly predict the outcomes. Machine Learning focuses majorly on building the algorithms to receive input data further using the statistical analysis so as to predict an output value within an acceptable range.

The process of machine learning begins with observations or data so as to look into the patterns in the data and make decisions in future.


Artificial Intelligence called to be a part of Computer Science focuses majorly on intelligent machines creation that has got the capability of reacting with the humans. Machines are able to gain new experiences, can easily adjust with the new inputs and perform human like tasks. All this is made possible due to Artificial Intelligence.


When Philosophers were trying to make sense of human thinking in respect to the system, they turned out to invent the concept Artificial Intelligence in the year 1956. Philosophy is called to play a significant role in the introduction and growth of Artificial Intelligence. AI is applicable in various areas like:

Expert System is the area where the computers are created and programmed in a way that enables them to take decisions in real life situation.

Robotics, quite popular as computer programmed without the ability of seeing, hearing and reacting to the sensory stimuli including light, heat, sound, temperature and pressure.

Natural Language where the chatbots are developed in a way that they can easily identify natural human language if there is a direct communication with a customer.

Gaming Systems makes the manipulation of strategic games possible.

Neural System reproduces various types of physical connections that occur in the human brains. All this is being done by simulating intelligence.

Also See: The ABCs of AI Marketing: What, Why, and How?


  • AI helps in creating employment opportunities by eliminating the old jobs and bringing in new job opportunities.
  • It has lead to an improvement in the healthcare facilities, and enables easy tracking of your health in real time.
  • It also helps in protecting the environment by reducing the energy use.
  • It provides complete security to us on various online platforms and also in the real world.
  • It reduces of possibilities of accidents taking place by increasing the safety. It also helps in decreasing the traffic.


Machine learning is a part of Artificial Intelligence. It helps in accurate application of the Artificial Intelligence. All this makes the system capable enough to automatically learn and improve just from the experience without the need of getting programmed. Machine learning constantly strives to develop the computer programs in a way that they are able to access data and can use it to learn for their own use.


The process of machine learning involves two techniques which are Supervised and Unsupervised Learning. Supervised Model has an objective of predicting the future outputs for which it uses the known input and output to train a model. On the other hand, Unsupervised Learning focuses more on identifying hidden patters or the intrinsic structures in the input data.

Supervised Machine Learning develops a model which is predictive models and is being prepared for both input and output data. To develop predictive models, Supervised Learning uses classification and regression techniques.

Unsupervised Learning uses only group and data which are based on input data. The most common technique of unsupervised learning is Clustering.


Machine Learning is useful in many aspects in our day to day life which are as follows:

  • Machine Learning helps in securing the data from all types of malware
  • It also provides personal security and can also speed up the events by ensuring complete safety.
  • Machine Learning gives more information about different patterns of human health by providing them complete healthcare
  • Most popular use of machine learning is the online search which is being done by Google and various other competitors enabling them to improve the understandings of search engine.
  • It also helps in giving information and accurate update son financial trading. MI is also used by various trading firms for predictions.

The best examples of Artificial Intelligence and Machine Learning are as follows:

  • The Virtual Personal Assistants like Siri, Google Now, Cortana are all intelligent digital devices. They are helpful in finding the information when you ask for it with the help of your voice and that is when they respond well to your question with an accurate answer.
  • Security Surveillance is very common. But do you think it is under human’s capability to keep monitoring multiple cameras at once? No right. Artificial Intelligence and Machine Learning makes it all possible.
  • Netflix is also another common output which is predictive technology and recommends the users based on their choices, interests and behaviour.
  • Video Games are the best example of AI and ML. The creation of video game characters learns your behaviour and responds further reacting in unpredictable ways.
  • Online Customer Support is an example too for AI and ML. While the customers are browsing the website, they get to chat with the computer support representative but its not the live person you are talking to, at times its a rudimentary AI and it extracts knowledge from the website and present it will before the customers.
  • In 2015, Gmail introduced Smart reply which indicates its capability of responding to emails on your behalf. The machine learning tools automatically suggests varied responses.
  • Google Maps helps in analysing the speed of the traffic with the help of location data. Using that data Google suggests with the fastest routes to reduce travelling time.
  • Paypal a popular online payment platform also uses machine learning algorithms to fight against all fraud. Using the deep learning techniques Paypal undergoes the analysis of various quantities of customer data and leads to evaluation of the risks accordingly.
  • Uber is another best example as it using machine learning algorithms to identify arrival times, pick up locations and drop locations.
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