How Google Uses the Artificial Intelligence In Its Services
Artificial Intelligence has occupied the most of sectors of IT industry and growing rapidly day by day.
Google is one of the Company who using AI in their services for better performance.
Lets see How Google uses AI in its different services ?
Google Search Engine:-
RankBrain is a component of Google’s core algorithm which uses machine learning (the ability of machines to teach themselves from data inputs) to determine the most relevant results to search engine queries.
The machine learning aspect of RankBrain is what sets it apart from other updates. To “teach” the RankBrain algorithm to produce useful search results, Google first “feeds” it data from a variety of sources. The algorithm then takes it from there, calculating and teaching itself over time to match a variety of signals to a variety of results and to order search engine rankings based on these calculations.
The world is migrating. Leave the rest of the world, at least 24 languages are spoken in India itself, with over 13 different scripts and 720 dialects. Well, if we talk about the world there are roughly 6,500 spoken languages in the world today. Can’t thank Google enough cause we’ve all used Google Translate at some point (I hope, you travel a lot too). The best is that it’s free, fast, and is generally accurate. Its translation of words, sentences, and paragraphs have helped many to decode and understand.
It is true that it is not 100% accurate when it comes to larger blocks of text or for some language, but it can provide people with a general meaning to make the understanding less complex. All this is possible because of Statistical Machine Translation (SMT).
Google Photos also automatically creates albums of photos taken during a specific period without any input from you. And that’s not all, it can also select the “best photos”. And in case you haven’t sorted all your pictures into albums, you can also search for them by typing in names. Suppose you want to find a picture with your dog, type in “Dog” and you will get all the dog pictures!
This is done using Image Recognition, wherein Deep Learning is used to sort millions of images on the internet in order to classify them more accurately. So using Deep Learning, the images that are classified as “Dog” in your Google Photos are displayed.
It is basically a personal assistant that is enabled using a combination of Google Knowledge Graph, Image Recognition, and Natural Language Processing.
The Google Assistant is envisioned as a chat-bot by Google which can be connected to your phones, TVs, speakers, etc. with the ability to actually have 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 according to your questions.
With the help of machine learning, Google keeps track of the users’ search history. With the help of that history, it recommends the advertisement to the user as now its aware of its target market. It’s heavily based on the search history data and machine learning helps Google to achieve this.
It created a win-win situation. With Google AdSense, the website owners earn money from their online content and AdSense works by matching text and display ads to the site based on the content and the visitors.
With machine learning, Google Ads has helped the advertisers to pay to display brief advertisements. With that service offerings, product listings, video content have also came into the picture. Then, the mobile application installs within the Google ad network to the web users was also common.
AI reduces energy used for cooling Google Data Centers by 40%. By applying DeepMind’s machine learning to its own data centers, Google managed to reduce the amount of energy it use for cooling by up to 40 percent. In any large scale energy-consuming environment, this would be a huge improvement. Given how sophisticated Google’s data centers are already, it’s a phenomenal step forward.
Google’s machine learning system was able to consistently achieve a 40 percent reduction in the amount of energy used for cooling.
That’s all for now. Thank You For Reading :)