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 Machine Learning?
Definition of machine learning by Arthur Samuel:
Machine Learning is the subfield of computer science that gives “computers the ability to learn without being explicitly programmed.” ~ Arthur Samuel
Let’s try to understand this definition in simple words. According to this definition, we are not going to give sets of rules to the machines instead we will give enough data so that machines can learn by own.
In simple words, machine learning is the process that powers machines to learn and predict like humans. The process is very simple, find the pattern in historical data and apply that pattern.
Now let us see how various companies are using Machine Learning.
How Tesla is using Machine Learning
“We develop and deploy autonomy at scale. We believe that an approach based on advanced AI for vision and planning, supported by efficient use of inference hardware is the only way to achieve a general solution to full self-driving.” — Tesla on its official site
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.
How Twitter is using Machine Learning
Twitter is a social networking platform that allows its users to send and read micro-blogs of up to 280-characters known as “tweets” with their followers. It is important for news reporting, event promotion, marketing, and business. Twitter uses artificial intelligence to improve user experience.
Twitter uses artificial intelligence to recommend relevant tweets to its users. Twitter’s artificial intelligence algorithm scans thousands of tweets per second and ranks them for every user’s feed. Twitter also uses AI to filter inappropriate content from the platform. Twitter also uses artificial intelligence to rank tweets. Twitter’s ranking algorithm has lots of data that it has processed through deep learning model and has learned what would be the relevant tweets for any particular user. All the tweets are scored based on the ranking mode whether the user would like it or not. The ranking model ranks the tweets based on the content or it has an image or videos and how many likes or retweets it has received. Twitter uses IBM Watson and NLP skills to track and remove abusive tweets. Twitter is continuously redefining its algorithm to meet the requirements of the platform. Twitter is using the various tools powered by artificial intelligence to improve the user experience and its services.