Evolution of Artificial Intelligence -1

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Early technologies were based on Mechanical and Electrical innovations. Computers were in massive sizes and limited storage power. Data storage relied on Punch cards and magnetic tapes.Computational jobs were time consuming requiring human intervention. Several major industries like Healthcare, Manufacturing operated differently without AI. Finance transactions were recorded on paper ledgers and investments decisions were taken by human analysts and fraud detections were less sophisticated leading to high risks. Understanding these facts highlights shifting of  continuous process of shifting from manual to strong AI driven systems in use today.                     

AI (Artificial Intelligence) stated simply is trying computers to think and act like humans. It forms the basis of all computer learning and future of all  complex decisions making. It is a simulation of human intelligence in machines designed to think and act like humans. It can be categorised into 3 parts-

1. Narrow AI - To perform narrow task like face recognition, internet searches etc.

2. General AI-  Any individual's task which a human can do.

3. Super intelligent AI- Above all in human intelligence can do. 

AI is not a single tool rather collection of models, algorithms and systems used to solve complex problems, automate tasks and support better - decision making. At the core, it is machine learning which enables programs to improve over time without being explicitly programmed. It works as -

1. Huge data sets in the system - customer purchase histories, images.

2. Algorithms  that data repeatedly learning which inputs lead to best outcomes. 

3. Loops of feedback that constantly refine the model accuracy to identify and learning from its                  mistakes and improve upon with each pass.

By this process, AI develops insights, make predictions, take actions based on data without any human help. The functioning of AI vary depending upon the purpose and technology used. It involves creating  systems needed for to take decisions or predictions rather than following coded instructions. Its programming involves developing tools, software or programs from data sets enabling them to predict results, limited decisions in order to manage the challenges effectively.

AI programming involves using one or more programming languages, frameworks and codes to develop  AI applications from automotive repetitive tasks to enhancing decision-making processes. It is reshaping how software is developed, maintained and utilized across various industries. Top AI  programming languages used are Python, R, LISP, Prolog and Java. Before selecting langauges, one should consider multiple factors e.g. develop preferences, and specific project requirements and the availability of frameworks. 

I shall be discussing about the tools for AI application in various segments in my next post.  

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