The role of machine learning in industry

Machine learning is a subset of artificial intelligence (AI) where computers independently learn to do something

they were not explicitly programmed to do. They do this by learning from experience — leveraging algorithms and

discovering patterns and insights from data. This means machines don’t need to be programmed to perform exact

tasks on a repetitive basis, they can independently identify and correct any errors in a process.

Machine learning is rapidly being adopted across several industries — according to Research and Markets, the machine

learning market is predicted to grow to $8.81 billion by 2022, at a compound annual growth rate of 44.1 per cent. One

of the main reasons for its growing use is that businesses are collecting Big Data, from which they need to obtain valuable

insights. Machine learning is an efficient way of making sense of this data, for example the data sensors collect on the

condition of machines the factory floor.

As the market develops and grows, new types of machine learning will emerge and allow new applications to be explored.

However, many examples of current machine learning applications fall into two categories; supervised learning and unsupervised

learning.

It’s no longer just humans that can think for themselves — machines, such as Google’s Duplex, are now able to pass the

Turing test. Manufacturers can make use of machine learning to improve maintenance processes and enable them to make

real-time, intelligent decisions based on data.

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