The crux of modern computer science is Artificial Intelligence.   The idea of Artificial Intelligence refers to civilizations that existed centuries ago.

Moving from the stage of hypothesis, in 1950 Alan Turing, a British academician published his seminal paper ‘Computing Machinery and Intelligence’.  He brought forth a test, to check if machinery can exhibit intelligent behaviour in equal terms with human intelligence.   This test was later known as the ‘Turing test’.

The word ‘Artificial Intelligence’ was embraced for the first time in 1956 by American Computer scientist John McCarthy and co-equals at the Dartmouth Conference.  To give credibility to the decision, AI qualified for research at the grounds of MIT Laboratory, Massachusetts, USA. 

At regular intervals the idea was tested at places like General Motors in assembly lines.  But global attention came when the IBM Deep blue computer defeated chess maestro Garry Kasporov in 1997.   From there AI had no looking back.  

Suggest further reading on the subject:‘What are the major domains of Artificial Intelligence’

On the basis of AI capabilities

Artificial Intelligence has progressed in stages from its point of evolution. For better understanding let’s categorize it on the basis of its capabilities into three major categories

1. Artificial Narrow Intelligence (ANI):
   ANI model is widely used in diversified fields. You are probably using multiple tools powered by these types as AIs. It is structured for performing a single task and therefore, called a ‘Weak’ AI. Though having only, a single task capability yet, it is utilized in diversified fields like chess, weather forecasting etc. It displays real time data, yet confined within the parameters set. Therefore, the desired outcome is not conclusive. The classic example is ‘Self-driven cars’ using the same designated route from the set framework. E-commerce site, giving us suggestions using the base of our previous search or selection.
2. Artificial General Intelligence (AGI):
   The AGI model places emphasis for machines to perform like humans. Machines need the flexibility and synergy to exhibit human traits. This feat is possible only through an intellectual and emotional collaboration, a unique skill of human behaviour. Research is undergoing in all AI laboratories to find a mechanism to develop AGI in order to get results using analytical, cognizant, emotional and conscious sciences. For this model to materialize, it needs an enormous amount of funding, time and manpower. While we don’t have a functioning AGI yet, most studies and projections say that it is inevitable. If you were born in generation X you’d probably see it in your lifetime.
3. Artificial Super Intelligence (AGI):
   To summarize, it narrows the gap between the AGI and ASI models. In AGI models, machines are equally positioned with humans, whereas in ASI models machines need to surpass human intellect. ASI is anticipated to outperform humans in thought process exhibiting intelligence at all fields from creativity to problem solving techniques. Though at the nascent stage of development, if this concept materializes, as Elon Musk predicted, it might cause the extinction of the human race.

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