How MNCs Using Machine Learning And Artificial Intelligence…
Have you ever wonder how Netflix, YouTube, or search engines like Google or social media like Facebook, Twitter give the best results to their customers or how Tesla is working on Autonomous cars. If yes then this blog is for you. I am going to talk about the core concepts which powers many of the services that we use today. Yes, the process called machine learning is behind all the services that we use today. Be its product recommendation, voice assistance, email Spam and Malware filtering, customer support, fraud detection, and many more. So let first discuss what machine learning is.
What is Artificial Intelligence?
Artificial Inteligence(AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and perform some task on their own according to conditions. As human beings thinks and takes action according to different condition then AI refers to giving same power to machine.
What is Machine Learning?
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
How Google uses Machine Learning?
Google is the master of all. It takes advantage ofmachine learning algorithm and provides customers with a valuable and personalized experience. Machine learning is already embedded in its services like Gmail, Google Search and Google Maps.
1. Google Translate
Want to translate a text from English to Hindi but don’t know Hindi? Well, Google Translate is the tool for you! While it’s not exactly 100% accurate, it is still a great tool to convert text, images, or even real-time video from one language to another. And in case you wonder how it translates more or less accurately, well Google Translate uses Machine Learning of course!
It uses Statistical machine translation (SMT) which is a fancy way of saying that it analyses millions of documents that are already translated from one language to another (English to Hindi in this case) and then looks for the common patterns and basic vocabulary of the language. After that, it picks the most accurate translation possible based on educated guesses that mostly turn out to be correct. For Example: Let’s see how Google Translate translates “Machine Learning is cool” into Hindi!!!
2. RankBrain
Suppose you want to know who is the CEO of Google? And then you want to know who is his wife? But how do you search this on Google? You cannot exactly write the name of Sundar Pichai or his wife since you don’t know it! In this case, you can simply search “CEO of google wife” on Google and you will get the required results. This is achieved using RankBrain in Google Search.
RankBrain is basically a deep neural network that is helpful in providing the required search results. It is one of the factors in the Google Search algorithm that determines which search pages are displayed. In case there are any unique words or phrases on Google Search (like “CEO of google wife” in our case!) then RankBrain makes intelligent guesses to find which search results fit the situation and filter them accordingly. In fact, RankBrain is currently so important that Google says it is its third most important page ranking factor for the results of a search query.
3. Google Photos
In case you are a millennial, I am sure you are a selfie addict! And of course, you use Google Photos a lot if you are an Android user as well. And it’s no shock that you do! Google Photos allows you to back up all your photos in a single location even if they were shot from multiple devices and it also offers lots of other cool effects using Machine Learning.
For Example, 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.
4. Google Assistant
Want a little help in organizing your calendar? Want to know the best Italian restaurants near your home? Want to book movie tickets on the go? Well, never fear!!! Google Assistant is here to make your life easier! 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 chatbot 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.
How Tesla is using Machine Learning
As we all know Tesla is the pioneer in the field of manufacturing electric cars. Tesla led by Elon Musk is a household name in the automotive industry. The only goal was to prove that electric cars could be better over traditional fuel-powered cars.
According to Tesla, they have gathered data from over 100 million miles with their software. Then they compile these data to generate road maps for driverless cars. Tesla crowdsources its data from all of its vehicles as well as their drivers, with sensors that can pick up information about a driver’s hand placement on the instruments and how they are operating them. All these data help them to modify its system in every aspect. According to the researchers at McKinsey and Co, it is estimated that the value gathered data will be worth $750 billion in the year 2030. Tesla uses this data to generate dense maps which shows the increase in the traffic to the risks which will cause the drive to take action.
Tesla uses Machine learning in the cloud which is responsible to educate the entire fleet at an individual level. They use some edge cutting which decides what action needs to be taken. The cars are also able to form networks with other Tesla vehicles nearby to share some information. Tesla has used existing customer databases for its data analytics using it to understand customer requirements and regularly updating their systems accordingly. Elon Musk has claimed 2020 to be the year for Tesla to release its full self-driving system built on Autopilot.
How Netflix is using Machine Learning
Netflix is a streaming service that offers a wide variety of award-winning TV shows, movies, anime, documentaries, and more — on thousands of internet-connected devices.
Netflix has a huge collection of content and day by day it is increasing rapidly so users might not able to find relevant content of their interest. That’s why Netflix uses a recommendation system to recommend movies and shows to its users. This is one of the best features of Netflix. Netflix uses what history of its users to recommend which shows and movies the user would be interested in watching. It allows users to consume data in the best way. Also, it increases the viewership, also the minimum threshold that the company decides for success, and also the monthly subscription. Netflix also uses its user’s data in the production of any movies and shows based on location. By using the data it helps to decide what kind of story is best to produce, the actors and directors which are best for that story what should be the budget of the project.