The five most underrated uses for AI

As internet speeds improve and technological innovation advances, AI is becoming an increasingly important concept to help developers deal with large amounts of data. 

AI is a catch-all term for multiple advanced technologies, including machine learning (ML), neural networks, natural language processing, and voice recognition. 

An extremely wide range of programs and devices are now able to gather and process data – from cars, to smartphones, to home appliances. AI programs can process information far quicker than humans, and in most cases with a higher level of accuracy. 

It’s no surprise that AI is being included in an increasing variation of applications, but it may come as a surprise just how widely AI is used. Here are some everyday uses for AI that you might not have considered. 

You might not have stopped to consider it, but your social media pages are individually curated just for you, through the power of AI. AI affects almost every aspect of your social media use, on sites such as Facebook, Instagram, Twitter and Snapchat. The feeds that you are presented with are usually taken from pages that you have ‘liked’, but AI decides which posts, people and pages you are most likely to want to see. 

Many small businesses complain that after Facebook changed their algorithm, they are only able to reach a small fraction of their customers. The advertisers you do regularly see have paid a hefty price to allow AI to show ads to customers who may be interested based on their online behavior.

It’s not just your newsfeed. Twitter uses neural networks to crop images to maximise their aesthetic output. For this, machine learning studies eye-tracking that records the area people look at first in a photo. This means AI can even understand which parts of images are most appealing.

AI tracks your usage patterns on social media, web searches, and other online behaviors, and uses the data to personalise your social media experience.

AI technology largely powers your email spam filter. Simple rules-based filters are no longer effective against spam, as spammers are quick to modify their message so it passes the filter. Instead, AI spam filters continuously learn from signals, such as the words in the message and message metadata. The AI filter can provide personalised results according to your own definition of spam. Using machine learning algorithms, Gmail filters 99.9% of spam.