Is AI really worth the hype?

Updated: 1 day ago

#ArtificialIntelligence #emergingtechnologies #AI #ML #NLP



You would have heard the buzz words like AI, ML, NLP et al. in several technology platforms and social media. Although pretty much everyone knows what their full forms are, are these technologies really as useful and relevant as they are portrayed to be?


To understand it, let us first delve into AI and its buddies through a simple analogy. AI is a garden in which you will have several kinds of trees and plants which could potentially give fruits, flowers, vegetables et al. Does it imply that there could be "weeds" in this garden as well? Of course! However, unlike the natural garden where weeds and plants exists (most of the times) by nature, weeds in AI garden will exist only by pure intent.


AI, by now, has exponentially matured to such an extent that almost every technology / software / program in our current digital world has some form of AI incorporated into it. And why so? "cebause" AI simulates / replaces "human intelligence" to accomplish certain tasks with same or better outcome. AI has several branches under it namely Machine Learning, Robotics, Expert Systems, Natural Language Processing (NLP), Neural Networks, Planning / Optimization, Perception AI (speech and vision). Let us have a brief of each of these categories for better understanding:


  1. Perception AI: The sensory information which exists in real world (and usually captured and understood / interpreted by humans through sensory organs) is captured and interpreted, acquired, selected, and then organized into required categories through an algorithm / program.

  2. Machine Learning (ML): This further breaks down to deep learning. Its algorithm / program has an ability to understand the underlying data / information from business systems or any other data rich systems. This "understanding" can either be used to perform a particular task (based on the gathered intelligence) or can simply be applied to improvise the tasks in itself through a continuous learning model

  3. Natural Language Processing (NLP): It is an algorithm which understands and interprets languages, speeches (including accents). This is pretty much similar to a human reading a book or listening to someone and comprehending it.

  4. Robotics: Robotics has several sub components under it. In a nutshell, robotics deals with development of tools to perform certain tasks based on pre-fed instructions. Advanced level of robotics (enabled with high-end and complex AI algorithms) allows the "robots" to learn and improvise from previously conducted tasks, surrounding environment and data / information thereby achieving maturity and proficiency through experience, like humans.

  5. Expert Systems: These systems are built with complicated algorithms to enable the computer systems to take "intelligence decisions" like humans do.

  6. Neural Networks: This branch of AI is a reflection of human brains to such an extent that the nodes / neurons are built to take effective decisions in similar pattern like humans brain cells do.

Naturally, businesses have been tremendously revamped and disrupted post the advent of these technologies. Although the 21st century has seen exponential growth and relevance in AI and similar emerging technologies, it looks like AI flight has just taken-off from runway and "sky is the limit". Right from the automated homes to driverless cars, we will experience AI (or already experiencing it) in some form or the other.


The bigger question is the ability to regulate and control it. While the emerging technologies are progressing at a swift pace, the regulation and controlling bit needs

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