Decoded: Difference Between Machine Learning & Artificial Intelligence

The buzzwords that are talked about in one breathe and even used interchangeably. While many of us think that Machine Learning (ML) and Artificial  Intelligence (AI) are same, that is not the case.

The two together make the base of Big Data, and hence, will be the wave makers in the world of futuristic technology.

Here let’s clear the air as to how ML and AI even if interconnected are completely different in their definition.

AI is a broader technology that is driving today’s “smart” world, on the other hand, ML is the current application which is driving the world of AI. So, in simple terms the best of AI is achieved using data that is read by ML.

Artificial Intelligence

AI in simple terms is the science where in machines exhibit human intelligence. A term coined in 1956, AI has come a long way in evolution. Then it was building computers with human intelligence, now it is powering bigger things, robots, homes, and even space projects. Moreover, this trend has been seen in movies since then, too. From Star Wars to Terminator and to Matrix, all showcasing AI in different forms. While the larger works are called General AI, the more personalised search, face recognition on Facebook and image classification on Pinterest are Applied AI.

Machine Learning

Machine Learning comes in to being when we talk about Applied AI. It is an approach to achieve this form of AI. Why? Because ML is the basic practice of reading algorithms, learning from it and making predictions based on the readings. These algorithms form the core of Applied AI. Thus, ML brings down the efforts of human coding of software, rather instructions are set to accomplish a particular task and the machine is trained to use large amounts of data and algorithms. This gives the ability to the machine to learn and perform the task to perfection.

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