HackMDRole of AI and Machine Learning in Instagram's New features and Algorithms
Who could say in 2010 that Instagram, the popular photo-sharing app, would attract over 2 billion, monthly active users?
With number of users this big, comes an insanely enormous amount of data that can’t be processed using traditional methods.
Comes in artificial intelligence and machine learning, for help.
This blog will dive into how AI and machine learning would shape new features of Instagram, how algorithms will be trained, whether you should buy Instagram followers, and more.
Keep reading.
How Instagram uses AI to moderate content?
Instagram removes content (posts, Reels, Stories, comments) that violates its community guidelines.
There are pieces of content that although doesn’t violate community guidelines, are considered to be offensive, inappropriate, or disrespectful.
Instagram reduces its reach to the Explore page instead of scrapping off completely from the platform.
Community guidelines regulate what is allowed on the app and what doesn’t, helping make Instagram a safer place for everyone around the globe.
Instagram uses a combination of artificial intelligence and human reviewers to take decisions about whether content if it goes against community guidelines or not.
New Instagrammers buy Instagram auto views to support their content marketing efforts while adhering to the platform’s community guidelines, obviously.
It’s a nice tactic to gain traction on Instagram and build clout at a much faster pace compared to organic marketing methods.
What machine learning algorithm does Instagram use?
Instagram uses the K-Nearest Neighbor or KNN algorithm - one of the simplest machine learning algorithms that finds out the most frequent occurrences in a user’s activity on the platform or averages of an element in a layered data set.
Utilizing the KNN algorithm, Instagram can predict what type of content a user might be interested in and suggest relevant posts around that interest.
Two basic ML principles regulate these post-picking decisions; Embeddings-based similarity, and Co-occurrence based similarity.
Both these techniques work to decide the order words are used in the text and gauge how relevant they are. Instagram uses the same techniques to dive into how similar two accounts are on the app.
This is the key to finding the right account and content, and suggesting them to the right audience who might be interested in.
There are several marketing techniques to use the Instagram algorithms to your advantage. One of those is to buy Instagram likes and train the algorithms to push your content to others and grow your account.
How does AI decide about content?
Artificial intelligence teams at Instagram start by creating AI models that can recognize what’s inside a post and then decide about the action to be taken.
One AI model can be built to see if an Insta post has graphic or nudity elements, for example - there may be thousands of others.
If it finds a nudity element, it may decide to remove that content completely or may keep it off the Explore page if it’s inappropriate and doesn’t contain nudity - limiting its reach on the app.
Sometimes, AI can not decide about a post and it may forward it to our review team which will review the content and makes a decision about it.
AI technology learns from each decision and learns from it. With thousands of decisions taken every day, the technology learns and gets better over time.
To win the Instagram game as a new brand or influencer, a smart way is to model the successful accounts in your niche.
You can start with modeling their profile pictures with the help of Instagram profile viewer, and their bio, and then creating content taking inspiration from what they do on their profiles.
The next section will dive into the types of ML algorithms that help regulate content on Instagram and other social media.
How AI and ML Enhance User Experience on Instagram
One of the most common misconceptions about Instagram is that it has one single algorithm is used to enhance the user experience on the app. This can’t be more wrong.
In reality Instagram relies on various machine learning algorithms, qualifiers, and procedures to figure out what’s best for an individual user - enhancing the user experience overall.
An average user is not well-versed with the technical process behind algorithms, while a technical brain is.
Instagram machine learning algorithms dive into insights based on users’ activities and engagement with the content.
Development teams at Instagram are working continuously, tweaking little changes to these algorithms and suggesting the most relevant posts and ideas a user might love.
Instgarma has a separate algorithm that decides which content to show on a user’s home feed.
Similarly, there are custom machine learning algorithms for Explore page feed, Stories feed, and Reels feed page, etc.
All these different algorithms help to create a tailor-made feed suggestions for an individual user.
Avoiding Spam and Showing Relevant Content
Instagram uses DeepText - an AI algorithm of Facebook based on Deep Learning algorithm. This algorithm is a text-understanding engine that helps provide users with a spam-free user experience.
DeepText can also understand intentions and emotions behind text to differentiate between comments generated by humans and bots.
It processes several thousands of text pieces and comments every second, improving upon its accuracy very fast.
This amazing artificial intelligence technology automates the process of removing spam comments.
A lot of public celebrities and popular influencers benefit from this algorithm by avoiding bot-generated comments on their posts, especially when they go live in Live Rooms.
Instagram coding teams are working on developing a high-accuracy multi-language model of this AI engine to show the most relevant content to the users using the app from different global geographics.
Many brands and content creators Instagram followers to boost the organic growth of their Insta profiles.
What are the four 4 types of machine learning algorithms?
To help you better understand artificial intelligence and machine learning algorithms used by Instagram, here are a brief overview of the four ML algorithms.
1: Supervised Learning
In this ML model, data is fed to the machines through labeled datasets. Machines utilize this training data and are able to predict the output in the future.
Moreover the test datasets are provided to check if a machine can give an accurate output against the input.
More common applications of supervised learning are image classification and segmentation, disease identification and medical diagnosis, fraud detection, spam detection, and speech recognition.
2: Unsupervised Learning
Unlike supervised learning, no labeled data is provided to machines to train them. They analyze an unclassified data and categorize that based on the features, differences, and similarities.
The common applications of unsupervised learning are network analysis, plagiarism and copyright check, recommendations on e-commerce websites, and detect fraud in bank transactions.
3: Semi-supervised Learning
This method of training the AI machines came up with the idea of incorporating the pros and cons of supervised and un-supervised ML models.
Machines are trained using labeled and unlabeled data at the same time, making this method of AI learning very cost-effective.
4: Reinforcement Learning
In this technique, machines learn on their own using trial and error method. No labeled data is fed to machines.
Machines use their own experiences based on feedback-data to produce results against particular inputs.
Reinforcement learning is further categorised into two types; positive reinforcement learning and negative reinforcement learning.
Features Of Artificial Intelligence
Here are the underlying features of artificial intelligence that makes it unique and amazing tool to power big data processing.
Eliminate dull and boring tasks
AI reduces the burden of doing boring tasks from our shoulders. We all have faced this situation in our professional lives that we do don’t enjoy and feel really boring, but we had to get it done any way.
The beautifu thing about AI is that it can perform all those boring and tedious tasks all day long without experiencing the boredom.
Data ingestion
Artificial intelligent systems can hold and process magnanimous amount of data that goes beyond our imagination.
Even a small company of 100 employees produce huge piles of data. Imagine the huge chunks Facebook or Google might be producing.
Imitates human cognition
This is one of the most valuable assets attributed to the AI systems - to imitate and behave like a human brain does.
This is the reason they are called artifiially “intelligent”.
Futuristic
AI systems are trained to only respond to the current scenario they are in, they also keep in mind what could happen in the future, as well.
Prevent natural disasters
Artifiial intelligense is being utilized to help businesses, social media growth, and more; it’s now our job to take the things further and use it to help prevent or contain the losses after natural disasters.
Scientists are working to develop a neural network based on the data of more than 100,000 past earthquakes, volcanoes, and other disasters. This would help a lot in reducing the damage to the life and resources.
Facial Recognition and Chatbots
AI systems can recognize the faces nad help lock the machines or block unauthorized access.
Chatbots are AI-based chat systems that help solve problems through texting with the users. Possibilities are endless, and it’s a matter of time that we see an increasing application of AI in our lives and the things in our surroundings.
AI Helps Eliminate Cyberbullying
In a survey conducted in 2017 by Ditch The Label, 45% of young people aged between 12 and 25 reported having faced some form of cyberbullying on Instagram.
To counter this grave problem, DeepText’s immense understanding of textual context was used.
There is a serious challenge that faces DeepText, though. This algorithm has to accurately distinguish which text is categorically spam, and which isn’t, to maintain freedom of expression on the platform.
Developers are also feeding the AI a wide number of contextual text to help it learn the words that describe human sentiments, specifically offensive or derogatory remarks.
Back in 2019, Instagram also vowed to analyze the images, and not just text, to identify the posts categorized as cyberbullying.
