You surely haven’t missed the headlines about artificial intelligence and how robots are going to take away all our jobs one day.
Administrators, production line workers, customers, service representatives, cars and perhaps even the surgeons are all set to be the victims of the fast progressing and rapidly escalating Artificial Age.

Artificial Intelligence and Machine Learning are real, and no doubt, the next big thing. 

The Amazon Echo, unveiled first in November 2014, an artificially intelligent Bluetooth speaker, which can answer trivia questions, tells you the weather, adds items to a shopping list, and much more.
The Echo is based on Amazon’s cloud-based voice service, Alexa, which can hear, comprehend and resolve any question or command.
In the future, we will perhaps see robot butlers, police that patrol 24*7, robotic friends and, following the words of Tesla boss Elon Musk, an eventual Terminator-style apocalypse where the machines will become self-aware and decide to devour the humans.

Tesla’s new stint with Artificial Intelligence will deal with incorporating the algorithms for the company’s Autopilot software which currently gives Tesla vehicles limited levels of automatic driving capability.

Simply stated, Artificial Intelligence is a computer system designed to learn, make decisions and carry out tasks that would normally require human intervention.

This phrase is the mantra of the current era, being used by technologists, academicians, journalists and venture capitalists alike.

But this is not the typical case of the public not understanding the scientists- here the scientists are often as bewildered as the public.

With the intersection of smart technology and analytics, companies are beginning to realize the long-awaited benefits of Artificial Intelligence.
This year AI has assumed a strong overhold in the top 1000 organisations declared by Fortune.

An overwhelming 97.2% of executives report that their organizations are investing in creating or launching big data and AI initiatives.

The idea that our era is somehow seeing the emergence of an intelligence in Silicon that threatens our own entertains us, enthralling and frightening us in equal measure.

“When we search on Google, it’s an AI deciding what we should see. When a dating site matches two separate people together there’s a matching algorithm that is breeding humans”- said Sam Altman,  co-chairman of OpenAI, a research organization headed by Elon Musk, dedicated to ensuring that AI is developed in a safe, manageable way so as to minimize an existential risk robots may pose to humanity.

The most famous “back-propagation” algorithm was discovered by David Rumelhart in the early 1980s, which is considered to be the core of the AI revolution. One of its applications was to optimize the thrusts of the Apollo spaceships as they headed towards the moon.

Since then there has been no looking back and the road for Artificial Intelligence has been uphill ever since. And why should they?

Research and systems-building in areas such as document retrieval, text classification, fraud detection, recommendation systems, personalized search, social network analysis, planning, diagnostics and A/B Testing, using AI and Machine Learning have been a major success.

Forward-looking companies such as Amazon had already started using ML throughout their businesses, solving mission-critical back-end problems in fraud detection and supply chain prediction, and building innovative consumer-facing services such as recommendation systems.

As datasets and computing resources grew rapidly, it became evidently clear that ML soon would overpower not only Amazon but any big-scale company where decisions had to be made based on Data Sciences.

At a time when giants like Amazon, Microsoft, Walmart and Alibaba are all pinning their hopes on India’s e-commerce opportunity in companies like Flipkart and Paytm.
Google has made ”tremendous progress in retail in India”. 
India is a multi-lingual country its retail sector constantly needs real-time translation from English to Hindi or some other language which is preferred.
For this, a number of organizations have leveraged the use of Google Cloud for speech API, natural language processing, speech to text, not to mention the ability of AI to help shoppers discover associated products whether it is size, colour, shape or even brand.

 Use of AI-powered chatbots has been a stupendous success for the Indian Retail market, an example of which is Policybazaar, since they are always available, deliver smart and flexible analytics through conversations on mobile devices using standard messaging tools and voice-activated interfaces.
Google’s use of AI is not limited to the retail sector.

Google is leveraging TensorFlow machine learning capability to help diagnose and hopefully eliminate different forms of cancer.
Another example is of high school students in California, who using Tensor Flow created a device that can put on trees and they can help predict wildfires, by taking in data and then applying Machine Learning models.

Project Oasis is a self-sustaining plant ecosystem that reflects outside weather patterns by creating clouds, rain, and lights inside a box. By using cloud analytics as well as ML, it can predict weather patterns.

AI and ML have spread its wings to the Human Resource Management sector too, drastically changing how recruitment could work for every company. However, the biggest valuable contribution of AI is undoubtedly that done in the healthcare sector.

Prevention of medical errors by offering both clinical decision support during critical medical events as well as documenting those electronically in real time are some of the applications. Utilizing data gathered from patients to clinically innovate to improve patient outcomes to an even greater extent, is another.
Complicated activities include making medical diagnoses, predicting when machines will fail or gauging the market value of certain assets, involve thousands of data sets and non-linear relationships.
In these cases, it’s difficult to use the data we have to best effect- to ‘optimise’ our predictions.
In other cases, including recognizing objects in images and translating languages, we can’t even develop rules to describe the features we’re looking for.

The solution provided to complex predictions-data optimization and feature specification-is transferred from the programmer to the program, by Artificial Intelligence.


But just as AI systems can dazzle us with their game-playing or sensorimotor skills, the same AI can turn out to be ruthlessly flawed, having conceptual mistakes humans cannot even predict.

In the medical system, Artificial intelligence would measure variables and outcomes in various places and times, conducted statistical analyses and made use of the results in other places and times. However, this could turn out to be a problem, not to do with data analysis per se, but with what is called ‘provenance’.

Provenance is, broadly speaking, where data arises, what inferences are drawn from the data, and how relevant are those inferences to the present situation.

 For example the use of AI in amniocentesis.

 Here the probability of Down Syndrome in a foetus is predicted using an ultrasound and genetic modification, but in most cases, the data may not be required and the prediction may turn out to be incorrect.

The two major drawbacks of Artificial Intelligence continues to be the fact that it cannot go beyond the periphery of the data the ‘robot’ is fed. Knowledge cannot be integrated or accumulated by the system on its own.
Thus, if provided with inaccurate or incorrect data sets, the machines will reflect the same with serious repercussions in the field it is being used for.

The second drawback is the fear of machines replacing humans in their workspace, although some experts argue that human touch, emotional intelligence are mandatory requirements, which machines can’t provide.
For example, one can see the misuse of data fed into the Artificial Intelligence-based application Strava, which, though normally plots a jogging route map for joggers, also leaked the locations of the military personnel posted secret places.

The awful lot of hype around AI, largely stemming from people’s perception based on Hollywood movies, which have successfully planted the fear of apocalypse, war or financial crash in every human ’s heart.
The reality is, however, that AI, like every new creation in the 21st century, can both very amazing or dangerous, based on how it is used or misused.