How Machine Learning Is Changing The World?

How Machine Learning Is Changing The World?

Machine Learning has provided a scope of possibilities that contain alternatives, a choice understanding of the world. Right after the microchip, Machine Learning has held the helm of being the biggest innovation. And, those who had been sceptical about Machine Learning are soon realizing that they are integrally a part of our reality. Neural Networks, for instance, is one such technology that is breaking thresholds of AI and its understanding. The presence of ML tools is equipping people to be more productive and healthier. The experts are also busy labelling it as a newer rendition of the industrial revolution, a kind of diagnostic to its former counterpart. Here AI will be harnessing the mental and cognitive abilities rather than reinforcing physical and mechanical strength. So, this piece will cover a few aspects of how our modernity is impacted via Machine Learning and how it’s also changing our respective purview of the world.

Still oblivious to the applications of Machine Learning?

While it is culturally quite easy to fixate the idea of Artificial Intelligence, some of us are still alien to the idea of Machine Learning. AI often directs our imaginations towards the sci-fi intervention of the media, but in actuality, the portrayals are far from being sinister. These are the tools that are shaping our daily lives while we still stay oblivious to their existence. Since AI has already been mentioned, it is to be noted that ML is what drives AI – a program that can teach and improve themselves over time. Essentially, Machine Learning is automating the extraction of big data and analyzing the same to make predictions – if incorrect, then they learn from that to reinforce a better strategy for the next one. For instance, Monolithic web platforms like Netflix, Google, Amazon are using the same to deliver semantic results that analyze a user’s preference, purchase history and predict what they want tentatively. 

Now, if you were to quantify data on a global scale, researchers will tell you that the individual data disposal is massive. It almost exacts at 1.2 trillion searches annually with over 40,000 searches being processed every second. So, in a day that comes to around 3.5 billion searches equating to us spending an equivalent of 1 billion years online. And, this is also where Machine Learning comes in since that huge data dump is not computable without it. But, ML is far more complex than what we know. It is also being adopted and integrated into almost every industry, affecting every aspect of our lives. It is essentially automating the formerly manual labour. So, the applications are also improving our sense of connectivity, streamlining a future that can accommodate AI and IoT (Internet of Things).

How is ML affecting our work life?

While skepticism has often led to some believe that ML’s implications on professions, workforce, and industries are catastrophic, the miraculous aspects of it have been extensively discussed as well. Machine Learning can potentially replace a huge portion of skilled labor through automation, but the intensity of its application will largely vary depending on the kind of work they are handling along with the difficulties associated with that specific workforce. As of now, ML allows automation of singular tasks and some jobs require simultaneous intervention which ML is not capable of handling. But let’s have a quick overview of its implications in some of the well-known industries.

Education

Teachers are a requirement and no amount of computable intervention can compensate for the functions dominated by them. But with machine learning, automation of specific processes can take place. For instance, a computer can chart out a study plan specific to one’s needs. Test results can be analyzed faster with automated grading. Even a student’s academic history and attendance can be used to assist them in having a better approach. Although these applications don’t compromise teacher-student dynamic, it sure eases the process of learning.

Law

Like the field of education, legal agencies are also turning to ML for processing huge chunks of data associated with legal precedents. For instance, J.P. Morgan is using software named COIN which can review previous cases and documents in and under a few seconds which otherwise would take 360,000 hours of manual labour. Although the interventions are still in requirement of the human touch, ML can surely expedite trials and speed up the entire process.

Labor

From driverless trucks to self-help kiosks, the automation is what we have seen from ML integration in industries. But there is also a variable to which someone is willing to deal with machines since humans can quickly come up with solutions or improvise, unlike the machines.

Health

ML is taking a huge leap in the constructs of medical facilities where programs are being able to cross-reference and analyze across databases to come up with a faster diagnosis of a disease. This can dynamically improve the rate at which treatments are improvised. For instance, hospitals are equipped with AI to detect tumours more precisely. ML is also helping researchers to finally find a cure for cancer.

How is ML affecting domestic life?

Just as the industries, domestic life is also being enhanced with IoT and Machine Learning. For instance, AlterEgo which is a headset that can respond to our brainwaves, helping us control appliances that are around our house. Although it is still in its developmental stages, the implications of a wearable gadget like that can help us visualize the next decade or so.

Is ML consolidating our future?

Shortly, we can have a tentative expectation of automation of almost everything. From your home to your transport, everything can be automated with just a push of a button. ML is helping us aim for a more comfortable future, one that harbours convenience and innovation. The scary assumptions of it may still haunt us, thanks to sci-fi media, the reality of ML or AI is still far from being scary. It is a reality we all would want to live in.

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One thought on “How Machine Learning Is Changing The World?

  1. Nice article! Thanks.
    I like ML and a couple of days ago I open for myself Self-Organizing Maps (SOM). SOM was introduced by Finnish professor Teuvo Kohonen in the 1980s is sometimes called a Kohonen map. An original, SOM-based representation of financial markets was created.
    The MST produced out of SOM’s winning nodes allowed highlighting the relations between enterprises and inspecting the emergence of critical patterns.
    A representation of the global financial situation was built too; it can assist policymakers in realizing efficient interventions during the periods of high instability.

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