Machine learning, like the Internet of Things, is one of those terms you’ve probably heard of but are perhaps unsure about what it is.
Simply put, machine learning (ML) is a branch of artificial intelligence (AI) that gives computers the ability to gather, analyse and interpret data without human input.
ML isn’t a particularly new technology, but it’s not being used to its full advantage by businesses – there are many ways companies from all industries can benefit and thrive using this tech.
Here in Sapere’s Software Surgery, we take you through the basics of ML…
What is it?
Machine learning is an element of AI and computer science which focuses on the use of data and algorithms to mimic the way that humans learn in order to improve its accuracy.
It does this through probability; by applying clever algorithms to lots of good quality data, ML can make predictions on the likely outcome of a scenario that the human brain couldn’t compute.
Using more data than humans can comprehend allows ML to analyse trends and patterns, learning from them to refine itself continually without the need for human input.
Why is it useful?
Every business uses data to a greater or lesser extent. Decisions made on this data can increasingly make the difference between keeping up with your competition or falling further behind.
ML uses this data to its advantage, using it in such a way as to spot complex patterns that humans can miss and capitalising on the findings.
It also frees those same humans from the drudge work of sifting through reams of data, so they can be more useful employed elsewhere.
I still don’t quite get it. Can you give me an example?
Say you work in the construction industry, one of the most hands-on industries you can find. ML still has scope to save time and cut costs. From identifying site risks through photographs to improving design quality, the potential is there – it just needs to be taken up.
Or take your Siri or Alexa – that’s also based on ML translating speech into text.
As Alexa hears more of your voice and your requests, she uses that data to continually improve. And every time she makes a mistake in interpreting your request, that data is used to make her smarter the next time around.
What’s the future of ML?
If lockdown has had any advantage, it’s in the rapid digitalisation of industries that were previously reluctant or resistant.
And as more and more businesses expand their digital horizons, the application of ML will increase accordingly.
Universities have already started degree courses in ML to produce the data scientists the country needs to exploit these technologies.
Because the more data businesses digitally collect, the more opportunity there is to do something clever with it – even in the most unexpected of industries.
A great example of this is Google, which has been using AI and satellite data to prevent illegal fishing.
Every day of the year, 22 million data points are created to show where ships are in the world’s waterways. Google engineers have discovered that, by applying ML to the data, they can identify why a vessel was at sea. This ultimately led to the creation of Global Fishing Watch, which can identify where fishing is happening and, therefore, also when it is happening illegally.
Machine learning has great potential to speed up processes and make the most of all the data we’re surrounded by.
And as for the most common question, no: machine learning robots are not going to take over the world. Not yet anyway…