How is adoption of machine learning becoming the new-normal?

How is adoption of machine learning becoming the new-normal?

How is adoption of machine learning becoming the new-normal? - by Mr.Dinesh Kumawat, Co-Founder at Analytics Steps

In today’s world (AI) is present all around us, there is a high chance that you are using AI right now. Popular usage of AI is Machine Learning (ML), in which computer software learns and acts like human brains (through cognition) by absorbing data and information in the form of real-world interactions and observations.

As per a report published by the Brookings Institute, the ongoing coronavirus recession is highly likely to bring focus to automation. Why? This is because companies would like to reduce the necessity of employees through automation. Generally, companies are forced to shut down factories if an employee falls ill, however, the same will not apply in the case of AI. In the coming years, a completely automated supply chain from the warehouse to your home can well become a reality.

As history showcases, times of crisis provide clear passage to rapid changes. For instance, the Internet developed across the world post the world wars, and more recently, post-2008 financial crisis, the role of cloud computing became prominent across the world.

The Covid-19 crisis has brought AI & ML to a similar stage. Though the implication of increased usage of AI is being debated, there are several domains where Machine Learning has already become the new normal and is growing rapidly every passing day.

Here are a few domains where Machine Learning is emerging as a part of the new normal:

Boosting E-Commerce sales: Computers can use Machine Learning algorithms which helps them to recognize images with an accuracy of 98% which is similar to that of a human being.

There are several ways through which Machine Learning can be applied in businesses, especially in the e-commerce industry. Your smartphone can virtually turn into a shopping mall using this technology. You can just click a photograph in your vicinity, and the same can come in web results – all without typing a single word.

In the present times, algorithms even determine the advertisements which you will see on your screen based on your interests and buying pattern online. Due to the pandemic, many more people are shopping online thus providing a further boost to the e-commerce industry, and if experts are to be believed, the trend will remain the same even post the pandemic.

Performing daily life activities through voice commands: Speech recognition is also rapidly becoming a part of our day-to-day lives. Now instead of using remotes, you can ask Alexa to turn off the lights or play songs on television just by using your voice. Combine this with the internet and you can do the same sitting on the other end of the planet.

Though the technology of speech recognition has remained around us for a very long time, yet, it has not become a part of the mainstream model of communication till now due to accuracy issues. Computer scientist Andrew Ng has predicted that if speech recognition becomes 99 percent accurate from the current 95 percent, it will become the primary mode of our interaction with computers. The way in which speech recognition software like Siri or Cortana is evolving, (speech becoming the primary mode of communication with AI) is going to become a reality very soon.

Managing Financial Services & securing data: In today’s date, Machine Learning plays an important role in various financial services including risk management, managing assets, or calculating credit scores.

It provides insights and makes predictions when a large amount of data is fed into the system. In general, traders use mathematical models to monitor business news and learn about possible factors which can have a positive or negative impact on market price. However, unlike humans, Machine Learning uses algorithmic trading that can analyze and process a large amount of information within a short period. Also, algorithm trading does not account for emotional factors thus providing clear and better results.

Another important usage of Machine learning is to flag out online fraud especially in banking institutions or companies providing financial services. In today’s world, fraud is considered a high threat to valuable data. Earlier, fraud detection was based on a set of rules which can be bypassed by online hackers. However, with the advent of machine learning, any unique activities or anomalies are investigated by security teams.

As more and more businesses move online, Machine Learning will play an even more important role in micro-managing financial services.

Improving the Healthcare sector: Machine Learning in the healthcare sector is growing at a very steady pace. It performs several important tasks, for example – it helps to analyze genetic mutations and prevent diseases, it helps to improve operations and lower costs and meet growing medical demands, main data integrity amongst many others.

Machine Learning is also being used by radiologists in medical imaging such as Magnetic Resonance Imaging (MRIs), Positron Emission Tomography (PET), and Ultrasound (US) where it can predict and find images even when the disease is in its nascent stage.

Alongside this, many medical institutes maintain data in a hand-written format which can be very cumbersome to organize and can even lead to occasional errors during interpretation. Machine Learning streamlines all these challenges and keeps the data in a very organized manner to assist the administration.

Application of Machine Learning in sports: The domain of sports has just begun to explore new possibilities through the application of machine learning. From improving player performance to boosting ticket sales, it can play an important role.

Machine Learning can help to develop insights about a player or a team, weather conditions, etc. thus improving the chances of a win. The data about fans is also gathered through different platforms and analyzed to retain them or sell them merchandise. Overall, it is going to provide the traditional sports sector with a completely new dimension. 

With the coronavirus pandemic spreading across the world, AI & ML are becoming popular across several domains. This Google trends chart rightly depicts the rising popularity of AI in healthcare.

https://trends.google.com/trends/explore?date=today%205-y&q=ai%20in%20healthcare

So the question that emerges here is whether machine learning is going to become the new normal or whether it is going to fade away? In my opinion, the answer is yes; it is definitely going to stay.

Machine Learning is going to evolve further and tap into other industries as well because the possibilities associated with it are limitless.

The above article is originally penned down by Mr. Dinesh Chandra Kumawat Co-Founder at Analytics Steps (alumnus of IIT Roorkee).

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