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Artificial intelligence - What is and Why we need ?

By Ranju RNov. 19, 2018, 3 p.m. Application development company
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Learn about the Turing Test, a way to test machines' intelligence, and the first successful attempt by Eugene Goostman, a program that convinced 33% of judges it was a human, in a 2014 test at the University of Reading.

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In 1950 Alan Turing introduced a way to test the intelligence of the machines, the Turing test, it tests the capability of a computer to think like a human being. On June-7 of 2014 a computer program called Eugene Goostman, which simulates a 13-year-old Ukrainian boy convinced 33% of judges that they are in conversation with a human in a test conducted at the University of Reading, the first time in the 65 years history of the Turing test. 

Artificial intelligence(AI) makes a computer learn from experience and perform human-like tasks. It can learn and unlearn based on new inputs and predict the future by processing large amounts of data and mapping it to a pattern. In simple terms, AI makes a computer intelligent. Using AI computers can give a result that is not fed explicitly but based on the large dataset given or from the experience gained over time. 

Some activities that a computer with AI can perform are:

  1. Speech recognition

  2. Learning

  3. Planning

  4. Problem-solving

AI Specifications


The core part of AI is the algorithm. These are programming commands that inform a regular non-intelligent computer on how to solve problems with AI. These are rules that teach computers how to figure things out on their own.

Machine learning

Machine learning is a subset of AI, by this, we can train a computer with an existing dataset and can perform a task without any help of explicit instruction. The computer can identify patterns using various algorithms and can predict futuristic outputs. A good example of machine learning can be an AI paraphrasing tool. It efficiently understands the meaning and context of the given input, and then predicts a better output, while retaining the original meaning.

Neural network

A neural network is a series of algorithms that can capture the relationship between the data, just like how the human brain works. Neural networks refer to systems of neurons that can adapt to changing input. It can generate the best possible result based on the training.

Deep learning

Deep learning is a trending term in recent days and it is closely related to Big data analysis. As the term suggests it is one of the learning algorithms that is used to extract higher-level details from raw data that is unstructured or unlabeled. It is the same as that of a machine learning algorithm but with numerous layers of this algorithm. By deep-learning, we will be able to develop self-driving cars - that can identify between a poll and human standing in a road.

Natural language processing

NLP is a branch of AI that supports machines to understand human language. By using this a human can interact with a machine using their communication language. Alexa, Siri, Google Home, etc are some examples that make use of this feature.

Reinforcement learning

Reinforcement learning is the training of the models(mathematical model to identify patterns) to make some decisions. In this learning, the system will achieve a goal from a complex environment by trial and error method. It is something like a game-like situation in which the AI gets a reward if it does the right thing, otherwise some penalties, the goal is to maximize the total reward.

Supervised learning

Supervised learning is the process of algorithm learning from the labeled training data. The training dataset consists of a pair, an input value, and an attached output value. The system will analyze the input-output relation and identify patterns and inferences. Later this learning will be used for the prediction for a new input value.

Unsupervised learning

In unsupervised learning, there will be input values but there won’t be any attached output values. Here the goal is to analyze the data and identify the structure and distribution of it to know more about the data. 

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Why is it important now!

Today the amount of data that is generated is very high, it overruns the human ability to analyze, interpret and make decisions based on that data. AI can get into this picture and can analyze and understand the data, thereby the future of all complex decision making.

Data security

Malware is one of the problems when we interact with the internet. In a single day, 1000’s of new malware are created. The good part is that the new malware has only 2-10% of variation from the previous malware file. Using AI we can predict the new malware with ease and secure our network or system.


Machine learning algorithms can process more information and spot more patterns than humans. The various test results can be analyzed based on the previous data, we can identify the health issues with the help of AI. The studies reveal that breast cancer from mammograms can be identified with the help of AI, and it is found that the correct ratio is higher than the prediction by the real doctors.

Marketing Personalization

Using AI we can personalize the buying experience of the customers in the retail online industry. It can analyze the buying patterns of various customers and can streamline the experience of a particular customer. Maybe the retail store can provide a particular offer to selected customers, or recommend the appropriate item for that customer.

Fraud Detection

Machine learning can better identify fraud transactions in the online industry. PayPal, an online payment service provider heavily uses AI to identify fraud traction to ensure security for its customers. 


Machine learning algorithms can analyze the user's activity and can compare it with the millions of other users to identify what might the user like to buy or watch. They have already been used on Amazon or Netflix.

Online Search

Google the giant search engine uses the AI capabilities to streamline the search results that provide to the users based on the search query. Whenever a user interacts with a search query, it trains itself to give the optimal result for the next user. Also when we start typing something it fills itself using the capability of machine learning and the prediction algorithms.

Natural Language Processing

Using the NLP module of AI, the machine can understand the human language, thus the manual customer care operations can be reduced on a large scale. The machine itself can understand and analyze the query and can respond to the end customers just like a human. This is very much scalable(as it does not mostly depend on the human) and can provide 24/7 help and support for the user.

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Smart Cars

Smart cars or auto-driving cars are one of the innovative products of Artificial Intelligence. Self-driving cars are in their primitive state, but a lot of vendors are now creating smart cars that can drive with little human intervention.

The computational power of machines has come a long way from the days of Alan Turing to the present and AI is augmenting our existing technologies in ways more than imagined, from smart bots to writing assistants AI is changing our industries and operations at an exceptional pace or rather revolutionizing them.

 Artificial Intelligence is a revolutionary wave sweeping across industries, click here and ride this wave. 

SayOne Tech 

SayOne Tech, a technology company with offices in India and the USA, has proven expertise and experience in employing emerging technologies to deliver world-class, secure, scalable, and reliable solutions. The tech company strongly believes in empowering their clients to adapt to constantly changing business environments quickly and achieve their goals. The core values that SayOne is c passionate about are integrity, commitment, and transparency.  

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