Smart machines and applications are steadily becoming a daily phenomenon, helping us make faster, more accurate decisions. And with more than 75% of businesses investing in Big Data, the role of AI and machine learning is set to increase dramatically over the next five years.
Here are ten real-world examples of machine learning and AI you’re probably using right now.
Machine Learning Examples
1. Siri and Cortana
Voice recognition systems such as Siri and Cortana use machine learning and other technologies to imitate human interaction. As they progress, these apps will learn to ‘understand’ the nuances and semantics of our language.
For those who are more visual, here are the 10 machine learning examples as an infographic:
Remember when Facebook used to prompt you to tag your friends? Nowadays, the social network’s algorithms recognise familiar faces from your contact list, using some seriously impressive technology. ‘We closely approach human performance,’ says Yaniv Taigman, part of Facebook’s AI department.
3. Google Maps
4. Google Search
The world’s biggest search engine offers recommendations and suggestions based on previous user searches. In 2012, Google introduced Knowledge Graph – an algorithm used to decipher the semantic content of a search query. Knowledge graph allows users to view related information without navigating away from the first page.
As you can tell, Google has a thing for AI. In 2015, they introduced a smart reply function allowing your inbox to respond to emails on your behalf. The machine learning tool automatically suggests three different responses.
10 per cent of mobile inbox users’ emails were sent using smart reply in 2016.
The online payment platform uses machine learning algorithms to combat fraud. By implementing deep learning techniques, PayPal analyses vast quantities of customer data and evaluates risk accordingly.
Machine learning is integral to Netflix’s video recommendation engine. The company has valued the ROI of these algorithms at £1 billion a year due to their impact on customer retention.
Machine learning is crucial to the Uber model. The tech giant uses machine learning algorithms to determine arrival times, pick-up locations and UberEATS’ meal deliveries.
Lyst is an ecommerce fashion site working with a new breed of model – the machine learning model. To match customer searches with relevant recommendations, Lyst uses meta-data tags to make visual comparisons between items of clothing. Their algorithms read these tags and decide on the best matches.
You know that cheesy pop song you listened to that triggered numerous other cheesy pop recommendations? That’s machine learning at work. Much like Netflix, Spotify uses machine learning to establish your likes and dislikes and provide you with a list of related tracks.
Is your business next?
As existing business processes continue to evolve, more and more companies are warming to the idea of an automated future. Industries lacking competition will benefit from the innovation and commercial advantages machine learning will bring.
While most organisations are in the early stages of adoption, FS&I services, healthcare and retail are already introducing examples of machine learning platforms across their respective fields:
The NHS is trialing an AI-powered chatbot on the 111 non-emergency helpline.
- The Royal Bank of Scotland launched a language processing AI to answer RBS, Natwest and Ulster Bank customer questions.
- Online shopping delivery service, Ocado, is working on a machine learning project to replace barcode scanning.
Gartner predicts smart machines will enter mainstream adoption by 2021. As this trend continues, further everyday examples of machine learning and AI will arise. Not only will this provide businesses with a competitive edge, it’ll completely redefine the way we think about work.