Machine Learning: The powerful technology that can change the world
What is Machine Learning?

A software application that is designed in a way that it constantly captures data and uses the data to improve itself in order of responses is called Machine Learning. As the name suggest, in this case the machine (or the application) has been designed in a way that it can self-learn and improve. While regular computer programs generally give outputs based on how they are programmed, for machine learning the output constantly keeps improving itself based on how the user has responded to the previous outputs.

The term machine learning was coined in 1959 by Arthur Samuel, known to be pioneer in the field of computer gaming and Artificial Intelligence. He was working in IBM when he coined the term after creating programs that played checkers.

Why is ML Important?

Even though the term and concept of machine learning had been around since 1959, it is only recently that machine learning had been put to use in its full potential. The reason being the availability of Big Data. Since machine learning as technology helps analyse large chunks of data, easing the tasks of data scientists it is being seen as the next big thing currently. In fact, machine learning has changed the way Data extraction and interpretation works. The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. This has resulted into the concept of machine learning gaining fresh momentum.

What are the different types of ML?
Generally machine learning is divided into 2 types – Supervised Learning and Unsupervised Learning

Supervised learning is where there is a skill trainer who constantly work to train the machine. In this process, we teach or train the machine using data which is well labelled. The machine has been given a set of data which is the ‘correct answer’. After that, everytime the machine is provided a new set of data, the machine analyses it against the training data provided earlier and tries to produce a correct outcome following the logic.

Unsupervised learning is where the machine has not been given any data that is properly labelled. Here the task of machine is to group unsorted information according to similarities, patterns and differences without any prior training of data. It goes unsaid that compared to supervised learning, this process is computationally more complex and the output data at times is comparatively less accurate.

What are the various real life examples of ML ?

Ever saw how Facebook can suggest you the names of people to tag when you upload a group photo? The ability of facial recognition in an image is a real life example of machine learning. ML has also been used in Facebook and Youtube’s recommendation engine where they suggest you content or show you advertisements based on your interest area. ML is now also used in medical field for easier and faster diagnosis of disease or suggesting better medical course of action.

What is the difference between AI and ML?

Artificial Intelligence is a broader field and machine learning is only a subset of it. Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”. This includes a lot of computation beyond machine learning including machine learning, language processing, fuzzy logic, robotics and others.

Amazon Alexa, Google Home, Apple Siri: Are they AI or Machine Learnings?

As mentioned, Artificial Intelligence is a larger concept and ML is only a part of it. Devices like Amazon Alexa, Google Home, Apple Siri etc. use both rely on natural language generation and processing and ML, forms of artificial intelligence, in order to effectively operate and perform better over time.

What is the future of ML?

Google says” Machine Learning is the future” so there can be no doubt about the fact that ML will be the way forward in technology. Since people have started realising the importance of data and since in all aspects of life – from banking to stock markets to IOT devices – we have started collecting huge amount of data, the implementation of machine learning to analyze and deduce meaningful results from these data will grow. In fact, many experts believe that Machine Learning is fast changing the face of medicine, healthcare, manufacturing, banking, and several other sectors by helping people to make necessary decisions. ML algorithms are trained over instances or examples through which they learn from past experiences and analyze the historical data. As the time passes and as the volume of data increases, these machines will perform even better.

This also means that our dependence on these will increase, which is a matter of concern for many social experts and psychologists. The fact that machines are training themselves and constantly becoming smarter can result into an apocalypse that is often seen in Hollywood science fiction movies, as many experts believe. With newer unseen accidents happening regularly with various fields of Artificial Intelligence including Robots at Facebook centre developing their own communication language, this fear of ‘robot apocalypse’ do not look very far-fetched anymore.

ML also bring a lot of concern about data privacy and how these data is used to trigger responses in common man. With all social media platforms, IOT devices, service providers constantly collecting data about us, a very little is being kept secret anymore. This data is now fed into a machine learning algorithm to trigger a desirable result. So we are shown Ads that will make us click them, we are shown content that will evoke certain emotion, and allegedly we are shown content that will influence our polarization towards a certain political party or religious community.

As the line between man and machines narrow, many experts have given a call for ethical development in the field of ML. That said, it is one of the most powerful technological invention ever and the possibilities are immense. How mankind uses it will decide the future.