Machine learning is an application of artificial intelligence that allows systems to learn and improve automatically from experience without being explicitly programmed. In this article, I’ll walk you through some examples of how Google uses machine learning.
How Machine Learning Helps An Organization?
Machine learning focuses on the development of computer programs that can access data and use it to learn on their own. The learning process begins with observations or data, such as examples, direct experience, or instructions, in order to look for patterns in the data and make better decisions in the future based on the examples we provide.
The main goal of using machine learning by organizations is to enable computers to learn automatically without human intervention or assistance, and to adjust actions accordingly.
Below are the 10 organizations today using Machine Learning in most of their daily tasks:
So How Google Uses Machine Learning?
In modern times, Google is everywhere. So much so that you are probably reading this article using Google search. And although machine learning has long been a part of Google, now it seems Machine Learning is everywhere.
From Google Search, Google Photos to even applications like Google Translate, everything uses machine learning. In fact, Google and its parent company Alphabet are heavily invested in machine learning research in almost every area imaginable such as ethical principles, quantum computing, health, robotics, perception, etc.
Use Cases of How Google Uses Machine Learning
Now let’s have a look at some examples of how Google uses Machine Learning in its applications.
If we want to translate a text from English to German, but you don’t know German? Well, Google Translate is the tool for you. While not exactly 100% accurate, it is still a great tool for converting text, images, or even video in real-time from one language to another.
And in case you are wondering how that translates more or less precisely, of course, Google Translate uses machine learning. Google uses statistical machine translation, a fancy way of saying that it analyzes millions of documents already translated from one language to another, then searches for common patterns and basic vocabulary of the language.
And then, in the end, Google’s translate algorithm chooses the most accurate translation possible based on educated guesses that usually turn out to be correct.
Most of the time we use Google Photos a lot if you are also an Android user. Google Photos allows you to save all your photos in one location even if they were taken from multiple devices and also offers many other cool effects using machine learning.
For example, Google Photos also automatically creates albums of photos taken during a specific period without any intervention on your part. And that’s not all, he can also select the best photos. And if you haven’t sorted all of your photos into albums, you can also search for them by entering names.
Suppose you want to find a photo with your dog, type in Dog and you will get all the dog pictures. This is done with the help of image recognition, in which deep learning is used to sort millions of images on the internet in order to classify them more precisely. So, using Deep Learning, images classified as Dog in your Google Photos are displayed.
Do you want some help organizing your calendar? Want to know the best Italian restaurants near you? Do you want to book cinema tickets on the go? Well, fear not !!! The Google Assistant is here to make your life easier.
It is basically a personal assistant created using a combination of Google Knowledge Graph, image recognition and a popular field of machine learning known as natural language processing. Google Assistant is designed as a chatbot by Google that can be connected to your phones, TVs, speakers, etc. with the possibility of having a conversation with you.
Here, the Google Knowledge Graph provides information gathered from various sources, while natural language processing allows the Google Assistant to interact with you and formulate its answers based on your questions.
If you visited this article from Google search it also uses machine learning and when you start typing in the search box it automatically anticipates what you are looking for. It then provides suggested search terms for the same.
These suggestions are presented because of recommendations from previous research, a trend everyone is looking for, or your current location. The best invention for students ever is Google search and no one will deny it.
Google search and Google Maps also use machine learning and help users with their daily tasks. Google knows it all and when you start typing in the search box, it automatically anticipates what you’re looking for and comes up with suggested search terms.
These suggestions can be based on the research you have done in the past, what is popular now, or where you are at the time.
So these were some use cases of how Google uses machine learning in its daily tasks to serve its services to the whole world. I hope you liked this article on how Google uses Machine Learning. Feel free to ask your valuable questions in the comments section below.