If you recall the early days of Facebook photo tagging, you've witnessed firsthand how far the company's artificial intelligence features and capabilities have advanced. In the terrible old days, the social network was prone to propose inappropriate tags for individuals in photos—or worse, mistake a chair or futon for your closest buddy.
Facebook's picture recognition capabilities have advanced dramatically due to artificial intelligence and machine learning. The technology automatically analyses what happens in photographs that lack human descriptions or tags, enabling users to search for photos using keywords even if they are not annotated. As with other big technology companies, Facebook is investing heavily in AI research and development. Facebook employs hundreds of employees working on artificial intelligence, and according to, CEO Mark Zuckerberg has "tripled his company's investment in processing power for AI and machine learning research" in recent years.
Facebook now utilizes artificial intelligence to help people find the correct content across text, images, and videos and impact how its advertising product functions. This is crucial for advertisers attempting to reach Facebook's almost two billion users. Some of the major ways in which Facebook is deploying AI-
The majority of data posted on Facebook is still text-based. While video may have a higher data capacity in gigabytes, text may still be just as rich in terms of insights. While a picture may be worth a thousand words, if all you want to do is answer a fundamental question, 1,000 words are sometimes unnecessary. Each piece of data that is not required to answer your query is noise, and more critically, a waste of storage and analysis resources.
Facebook employs a technology called DeepText that is created to extract meaning from the words we publish by learning to evaluate them contextually. Neural networks assess the relationship between words to determine how their meaning changes due to their proximity to other words. Due to the nature of semi-supervised learning, the algorithms do not require reference data – such as a dictionary – to explain the meaning of each word. Rather than that, it teaches itself by the way words are employed.
Facebook trains it to recognize people in images using a deep learning program called DeepFace. It claims that its most advanced picture recognition engine is more accurate than humans at determining if two separate photographs are of the same person – with a 97 percent success rate compared to 96 percent for people.
It's safe to assume that the application of this technology has generated controversy. Privacy advocates argued it went too far since it would allow Facebook – based on a high-resolution image of a crowd – to assign identities to many of the faces, obviously impeding our ability to move freely in public. Previously, the social media giant used a less advanced version of the facial recognition program that did not use Deep Learning. Since the technology initially made news, Facebook has been relatively silent about its development and may be presumed to be awaiting the result of current privacy lawsuits before disclosing anything about their plans to roll it out.
Facebook decides which advertisements to present to people using deep neural networks — the cornerstones of deep learning. This has always been the foundation of its business, but by assigning machines to learn as much as possible about us and to cluster us in the most insightful ways possible when serving us ads, it hopes to maintain a competitive edge against other high-tech competitors such as Google that are vying for market supremacy.
Facebook has even chosen to delegate the duty of determining which procedures may be enhanced using AI and Deep Learning to robots. A system named- Flow has been built that utilizes Deep Learning analysis to perform simulations of 300,000 machine learning models each month, allowing engineers to validate concepts and identify efficiency possibilities.
Artificial intelligence has already significantly influenced how Facebook operates and how each Facebook user interacts with the network. Its News Feed is regulated by artificial intelligence and may grow even more reliant on the technology shortly. Machine learning algorithms at the firm are becoming increasingly adept at comprehending text and pictures. And the advertisements you view may be strongly influenced by the preferences and insights revealed by AI to the company's data scientists.
The platform's application of AI across all aspects is anticipated to accelerate. In 2016, Facebook launched FBLearner Flow, an internal platform for sharing machine learning expertise and code. At a high level, FBLearner Flow enables the transfer of algorithms and models from one element of a business's operations to another, accelerating the growth of machine learning. This—along with the company's tremendous advancements in artificial intelligence—has some significant ramifications for marketers.
Pay close attention to how Facebook's News Feed evolves over the next couple of years.
Marketers rely on the News Feed to reach customers with everything from advertisements to organic content. If artificial intelligence begins to determine entirely what consumers want to see, marketers may lose insight into how those judgments are made.
The aim is that super-effective AI would make it even easier to target the right audiences with sponsored advertisements. However, this may not apply to organic content if the material shared by your brand does not outperform that picked by algorithms. On Facebook, marketers may need to rely far more on sponsored targeting than on organic shared engagement.
Evaluate the value of your Facebook content
Consumers and Facebook now have more significant influence over platform content than at any point in history. Facebook's AI advancements expedite changes on a large scale, possibly giving consumers a greater capacity to filter out undesirable communications. Posts and updates of mediocre quality will not suffice. Brands must be ruthlessly honest about the value they generate through their content. Assume that it is insufficient at the moment and devise a plan to rectify the situation.
Investigate AI solutions that can assist you in determining your return on investment
Depending on the changes made by Facebook and other internet companies as a result of artificial intelligence, you may have to fight fire with fire. Keep an eye on artificial intelligence (AI) technologies that evaluate campaigns and propose lucrative actions. These may give critical advice on producing a sufficient return on investment on Facebook and other social media platforms. It pays to begin by demoing products that pique your interest.
Zuckerberg has committed to employing artificial intelligence to address some of the company's and customers' most pressing issues, particularly in seven key categories: Discriminatory Speech Terrorism, Nakedness, Graphic Brutality, Junk mails, Imitation Accounts, Automatic Image Recognition, Machine Translation, Talking Pictures, and Chatbots are examples of how AI is used.
In a word, artificial intelligence is here to stay and will undoubtedly have a significant influence on how Facebook serves both users and marketers. Although Facebook has always been coy regarding future breakthroughs, the company is constantly leveraging technology to deliver new features and services each year. With so many AI-based projects in place, Facebook can overcome new obstacles and forging new routes. After all, the invention is a never-ending process.