Nowadays, the term ‘machine learning’ has become kind of a buzzword. You find it online and in tech circle conversations frequently! However, the mass is yet to get a clear perception of the term. It is also used in alliance and interchangeably with the term AI or artificial intelligence. While many think of it as a technology of the future, the reality is AI is already here and it is evolving at a fast pace.
So, what actually is machine learning?
Machine learning is a part of AI in which a computer application is programmed to learn from patterns and experiences without much manual intervention. Gaining expertise in machine learning has become a prerequisite for new age job seekers as more and more companies are inducting machine learning algorithm into their existing modules to make their organizations more agile. It can also enhance performance level by making logical deductions from various events. It involves analysis of big data.
Online technology behemoths like Google, Amazon use it to offer semantic results which are based on algorithms analyzing browsing pattern, buying history of visitors. This helps the brands assume and predict what the customers may like in the future too.
The number of people searching the web for information keeps growing with time. By 2018, the number of people using the web to look for information has crossed past the 4 billion mark. In each second, approximately 40000 online searches are processed. This amounts to a whopping 3.5 billion searches per day! This gargantuan amount of data cannot be processed and analyzed without the aid of machine learning. With time, it is being deployed into all industries. In near future, it is slated to alter the ways we interact, seek information and avail services.
How machine learning impacts life
The effects of machine learning on diverse professions and industries are evident, from the manufacturing sector to the language translation industry. However, opinions are divided. Machine learning does have the potential to computerize a big portion of skilled labor. However, the impact on workforce depends also on the level of hardships and complexities involved in the job. In some industries deploying it is simple while in others, more time is required before it can be used in lieu of manual methods.
Education sector - Teachers are expected to wear many hats- including those of analyst, counselor, mentor, and of course educator. It is too early to find a computer program or robot that can do all these efficiently! However, through machine learning some of the teaching related tasks can definitely be automated. Analysis of progress of students, recording attendance and academic history and determining individual study plans are being done. It is yet too early to opt for a teacher-less classroom but basic and repetitive tasks associated with teaching can be automated through AI.
Legal sector -The law firms are turning to machine learning with time, worldwide. Needless to say, such entities need to deal with massive amount of data for their operations, on a daily basis! J.P. Morgan makes use of a software program called COIN for reviewing previous cases and documents fast. For these firms, saving time is also important and AI tech helps them do that. However, machine learning or AI is not yet advanced enough to replace human lawyers.
Manual labor - This is one area where machine learning is slowly replacing human workers. In assembly lines, AI enabled robots can perform the work done by several workers faster and more accurately. In such work, not much complexity or analysis is involved. It also reduces risk of injury and accidents to a large extent. Of course, such operations are monitored remotely by humans.
Healthcare sector - Machine learning is being deployed in a big way in health sector. It is useful in carrying out better and faster patient diagnosis and treatment. Even in this sector, AI tech is used to deal with large amount of data and analyze those which can be very helpful and time saving for the doctors. They can use data to figure out best possible way to treat complex cases and use AI algorithms to diagnose specific diseases.
Transport sector -Autonomous driving technology is at nascent stage but major car companies are experimenting with it. China for example has made some progress in operating driverless public buses. Google is not only making self-driving car but it has joined hands with Rolls Royce to make the first ever self-driving ship. Even some aviation companies are going to launch pilotless commercial aircrafts in near future.
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