“I think people who are naysayers and try to drum up these doomsday scenarios- I don’t understand it, it’s really negative, and in some ways, I think it’s pretty irresponsible.”

 – Mark Zuckerberg, Facebook CEO.

If you are also a frequent user of social media or networking site Facebook, then you must have come across various different things like friend suggestions of the same school you have studied, shopping advertisements of the thing you were looking for, etc. Do you think Facebook has become an inner-knower as it knows everything that is going on inside you! No no! Don’t worry. Facebook doesn’t know you internally. This is only because of the use of Machine Learning on Facebook.

Facebook is utilizing machine learning for classification, ranking, and content understanding services. These include, but are not limited to, things like your news feed, serving ads, search, classifying objects, identifying people’s faces in posts, and language translation from one country’s language to another’s.

Facebook is currently having one of the best machine learning algorithms in place; much stronger and sturdier driven to provide the best user experience to its millions and millions of users. They use it almost everywhere on their platform, whether be it news feed section, or trying to find more friends and browsing images and much more.

Facebook uses a DL application called DeepFace to teach it to recognize people in photos. It says that it’s the most advanced image recognition tool which is more successful than humans in recognizing whether two different images are of the same person or not. If you have “tag suggestions” or “face recognition” turned on in Facebook this means that you have given permission for facial recognition. With this permission, the Machine Learning algorithm analyzes the pixels of the face in the picture and creates a template which is a string of numbers. But, this template is unique for every face and is used to detect that face with another face suggests a tag for you.

Facebook uses a tool it developed itself called DeepText to extract meaning from words we post by learning to analyze them contextually. Facebook then generates leads with this tool by conversions they are having. It offers user-related shopping links to connect chats and posts to potential interests. DeepText helps in understanding stuff like grammar, idioms, slang, context, etc.

For example: If in a post there is a term “I love Apple,” then does the user mean the fruit or the company? It’s most certainly the company (except for Android users!), but it really depends on the context and this has to be learned through DeepText. DeepText uses Deep Learning because of these challenges, and often in several languages, and therefore treats named data far more effectively than conventional models of Natural Language Processing.

Did you searched about machine learning and then saw their ads regarding machine learning courses on your Facebook page? It is because of the usage of Machine Learning algorithms. These algorithms analyze your age, gender, location, page likes, interests, and even your mobile data to cluster us together and then show you ads specifically targeted towards these clusters.

To determine which ads to show to which people, Facebook uses deep neural networks-the building stones of deep learning. This has always been the pillar of its business, but it aims to retain a strategic advantage over other high-tech rivals such as Google who are vying for the dominance of the same market by tasking computers themselves to figure out as much as they can about us, and to cluster us together in the most informative ways when serving us ads.

These are people all over the world that use Facebook, but many of them also don’t know English. The first click on the “See Translation” button for some text sends a translation request to the server, and then that translation is cached by the server for other users. This is done by the Facebook translator by reviewing millions of documents already translated from one language to another and then scanning for the language’s typical trends and basic vocabulary. After that, based on educated guesses that often turn out to be false, it chooses the most precise translation possible.

Different posts show up in your personal Facebook News Feed is according to a ranking system. The rank is decided on three factors: Your friends, family, public figures, or businesses that you interact with a lot are given top priority. The more you visit a friend’s profile or even the pages that you visit on Facebook, the more their news or posts appear at the top of your feed.

Facebook is a supporter of open source and makes most of the work of its AI labs. Facebook Artificial Intelligence Research (FAIR) is freely available for anyone to use or modify however they like. It has even open sourced design of its Graphics Processor Unit (GPU) driven AI hardware – super-fast computers optimized for carrying out Deep Learning tasks. The majority of Facebook’s Deep Learning is built on the Torch platform. It is a development environment that is focused on the development of deep learning technologies and machine learning neural networks.

Suicide is the second leading cause of death for teenagers around the world. Thanks to Facebook, it helps in the prevention of suicides with the use of AI. AI may signal posts to individuals who may be in need and/or motivated by suicidal impulses maybe. To further identify users who may be at risk, the AI uses machine learning to flag key phrases in posts and distressing remarks from friends or family members. It is very difficult to examine human complexities as a whole, but Artificial Intelligence can follow the meaning and understand what a suicidal trend is and what it is not.

Social media issues are always related to security and privacy. In addition to this, Facebook is using machine learning to detect content falling into several categories like- nudity, graphic violence, terrorism, hate speech, spam, fake account, and suicide prevention. Machine Learning is helping Facebook to identify fake accounts created for malicious purposes and shuts them down instantly.

Facebook distinguishes fake accounts in two ways:

First, there are “user-misclassified accounts,” personal profiles that are supposed to be websites for businesses or pets. These are pretty easy to work with, only translating them to websites. In the other hand, “violating accounts” is more serious. There are personal accounts that indulge in scamming and spamming or otherwise abuse the terms of service of the website. Without throwing the too large net and snagging actual accounts as well, offending accounts must be deleted as soon as possible.

AI and Social media are already here! The use of machine learning imitates human intelligence with the use of algorithms and historical data. Artificial intelligence answers the following questions first, and then various machine learning algorithms are implemented to implement the personalized artificial intelligence hacks.

• How much time do they spend online?
• Which is the favorite platform?
• Why do they use social media, and for what?
• Where do they use social media?

For thousands of people, the point is to answer these questions and merge them with historical records. The effect would be that you will have an immense amount of useful data that can be conveniently analyzed with the use of AI software for your company.

Regarding the question “Is AI taking over the social media companies?” the answer is no, at least not now. Artificial intelligence is everywhere, and any time we open our device or communicate with an App, it operates quietly in the background. It receives information and learns about it. It’s been a long way from the basic theory of truth. As of today, though, this technology also needs upgrades.

Machine learning and AI are intelligent tools that will empower businesses. In less than a second, it can calculate thousands of questions, a job that a person would possibly take hours. Nonetheless, people should be aware of how much information these businesses are gathering about-person.

Companies collect knowledge from all over the world, and any particular consumer in real life will have an incredibly significant effect on the material that a person will partake in and see in the future.

The above-mentioned use cases of machine learning on Facebook are just the beginning. There are many use cases of how Facebook is revolutionizing its business with the use of Artificial Intelligence. Deep Learning is the area of artificial intelligence where the real magic is happening right now. Traditionally, computers, while being very fast, have not been very smart as they didn’t have the ability to learn from their mistakes and have to be given precise instructions in order to carry out any task.

The takeaway is that if Facebook can implement Machine Learning to help humanity, then you can do it too. Spark the zeal inside you and start understanding Machine Learning.

Sairam Uppugudla: Entrepreneur, CEO, Data Scientist, or Data Enthusiast are the major features that describe Sairam Uppugudla the best. I am a tech-expert with 7+ years of experience in multiple technologies like Data Science, Python, Data Analysis, Big Data, Machine Learning Training, NLP, etc. With 360 degrees of expertise in various technologies, I’ve been known for the practical real-time projects. I love enjoying and exploring all about data. I am running an Edutech company under the name Codegnan. As an entrepreneur, my mission is to develop a culture of technology in the young and innovative minds who are our future.