Why you need to get on top of machine learning Posted on : Dec 08 - 2017

There’s a significant level of hype around machine learning – generated by tech vendors, the media, and even CIOs themselves. But putting the hoopla aside, machine learning technologies actually have real substance and as a CIO, it’s worthwhile getting on top of the trends in this area.

So what’s all the fuss about?

Machine learning is here and we use it every day without considering that it’s actually what is powering many of the services that we use. A great example is Google Maps, which most people would be using daily or weekly.

Initially, Google used machine learning to review images and to protect the privacy of users. However, the company soon realised the technology could be used to automatically provide up-to-date information to Google Maps – and read street numbers and names, and even business names from images.

Some of us also use machine language for speech recognition – like the technology used in Apple’s Siri personal assistant.

In the financial services sector, several innovative banks have applied technologies as (nuance) to integrate voice into their digital channels. This is not new technology but note that Google, Hitachi, Samsung and others are all looking at artificial intelligence (AI) and voice integration. In essence, what all the fuss is about is that we now have a more advanced ability to apply machine learning to automate what were previously quite manual tasks.

Machine learning for the IT team

We have all heard about IBM applying Watson to learn about treating cancer, but I’m also aware of real examples of this technology being applied to deep learning on the operation of production IT systems.

By looking for trends and reviewing all those logs and alerts, then we can see that machine learning has a significant leg-up on human beings ability to absorb all the details and synthesize this same data into an insight.

The opportunity for the CIO is to get in front of this change and start to evaluate how this could be applied in your own organisation. One of the key things that you can bring to the discussion is that the understanding that machine learning is just data analysis, with along with neural networks and AI, has been around for many years. View More