Understanding Artificial Intelligence (AI) & Machine Learning (ML)

Artificial Intelligence and Machine Learning are the hottest buzzwords today and are often used interchangeably. They are not similar anyway, but the perception that they are might confuse the one with another. While the topics like Big Data and Analytics crop up, these two terms mostly come into the scenario and are used. It would be worth to understand the difference between AI and ML and how these are slamming the technological world with its powerful potential.

Let’s understand and discover the technological potential of Artificial Intelligence and Machine Learning and what differentiates one with other further in this blog.

What is Artificial Intelligence?

Artificial Intelligence, in general, is the capability of a machine to imitate human behavior intellectually. The machines could demonstrate certain aspects like reasoning, self-correction, and learning just like a human brain does. If you want an example – Sophia, the AI robot is the prototypical instance of this.

AI is often categorized into two groups – Applied and General AI. Applied AI a.k.a Vertical or Narrow AI is a smart structure that addresses a specific requirement, like trading stocks, or tailored ads. To understand, consider an example of LinkedIn Message. It predicts possible replies to a message as and on the basis of conversation, it will learn itself and will give the most probable suggestions in future. It shows that we have already started using applied AI in our everyday lives. Nguyen explained that the predicted responses are formulated by machine learning models which are trained on a large amount of message data – these modes find the most common responses to messages whose linguistic characteristics (i.e. a sequence of phrases or words) are comparatively similar to an input message!

General AI is broader type and it requires a fully developed machine to understand, infer and respond to different tasks and functions, just like humans do. In short, it comes with the capabilities that can handle any task that a human is capable of. This technology is more akin to droids portrayed in sci-fi movies.

Future of AI-

AI is certainly no longer a future technology, it has already found a traction in the enterprise. Be it to unify huge amount of data, or reducing attritions with its algorithms, AI is something that will benefit every other industry like – Medical, Information Technology, Retail, Finance, Transportation & Logistics, Media & Entertainment, Education, etc.

Machine Learning- A Subset of AI

AI is a concept that represents several things, including machine learning. Machine learning is counted as AI, but not all AI can be machine learning. For an example, symbolic logics like expert systems, rules engines and knowledge graphs – all comprise AI, but cannot be categorized with machine learning.

In the simpler terms, Machine Learning is an application of artificial intelligence that empowers systems to automatically learn and improve from experience without even requiring to be programmed explicitly. It also enables to develop computer programs that can access data and further use it learn by themselves. With this machine learning reaches to a point where it can solely interact with individuals and make decisions without any human assistance. The common example of this is voice recognition systems such as Siri from Apple and Cortana from Microsoft. These both use machine learning algorithms and deep neural networks to mimic human interactions. These apps will develop themselves automatically further by understanding the nuances and semantics of language without any human intervention or assistance.

Applications of Machine Learning

The applications of ML are countless from the business perspective. It could help organizations to analyze complex data and automatically diversifies it with tremendous accuracy. It gives organizations the insights through which they can make informed decisions to boost their operations for a better outcome. However, to achieve this kind of excellence, ML algorithms need to be taught and trained thoroughly by the experts.

Despite differences, machine learning and artificial intelligence are closely interlinked with each other. However, artificial intelligence is a broader term for all kind of tasks that a machine could carry out itself while machine learning is a specific subset of algorithms for AI. These two always interests tech experts and surprise the world with its incomparable innovations.


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