Alongside topics like virtual reality (VR), augmented reality (AR), blockchain and cryptocurrency, and self-driving cars, machine learning has also been heralded as a big step forward for technology. It seems as though companies all over the place are talking about it, saying that they too will be embracing machine learning and using it in the products and services that they offer us.
The technology looks poised to change the world around us but just what exactly is machine learning? And will the tech actually impact our day to day lives or is it just exaggerated hype?
What is Machine Learning?
In technological terms, machine learning is a sector of artificial intelligence in which huge amounts of data are fed to computers. These computers are then able to “learn” by using this data, extrapolating things without having been explicitly programmed to do so. For example, while programmers may have previously needed to tell a computer to do something, machine learning allows them to infer and take action based on these inferrals.
The technology has huge potential, allowing researchers and businesses to access hidden insights. Human researchers are limited to their own knowledge and experiences when making suggestions about data but a computer can pull from a variety of sources, potentially coming up with ideas that no one had thought of.
How Machine Learning is Used in the World Around Us
Machine learning has quickly been adopted by businesses and it has already been embraced in many of the apps and services that we use on a daily basis. WordStream notes that image-based social media platform Pinterest uses machine learning in order to improve content discovery. Twitter also uses machine learning to offer curated timelines, showing users relevant tweets based on how they have been interacting with the platform already. Users won’t have to filter through streams of content they don’t want to see as content will be picked per their needs and interests, as identified through machine learning.
There are higher level tech applications for machine learning too. On the data security side of things, Imperva uses machine learning technology to study user access behaviour, identify unusual activity, and only alert a user to the truly dangerous activity. It allows businesses to uncover “risky users” who pose a threat, by looking at behaviour and actions, alerting teams to risks. Meanwhile, Chinese search engine Baidu is investing in AI and machine learning for its voice search features. It allows it to better identify voice search inputs and generate synthetic voices, which is incredibly important given the forthcoming growth in voice search queries.
The machine learning applications detailed above are just the beginning of this boom. According to a report by MarketsandMarkets, the machine learning market is set to be worth $8.81 billion by 2022 as improvements in data generation and increased demand lead to a rise in adoption. This means that we can expect more and more uses of machine learning in the future, with companies finding new ways to make the tech benefit their users.