By Thomas Macaulay
Nov. 9, 2016
Businesses are often data-rich but information-poor. Machine learning (ML) is changing that. The use of artificial intelligence (AI) to let computers learn independently through algorithms without being explicitly programmed can help companies process vast quantities of complex data to improve analytics, predictive accuracy and decision-making.
Machine learning is already being used in everything from fraud detection to self-driving cars, and in sectors from marketing to government. CIO UK looks at how eight leading CIOs are using machine learning in their businesses.
"We are currently working on machine learning to pick up early signals of ill health. For instance, feedback loops on the early signs of sepsis, which flag before any detectable signs to the clinician. My current role is to ensure that this is implemented in line with national recording guidance which does not cover machine learning. This is currently in pilot phase in the A&E in Salford."
Rachel Dunscombe, Salford Royal NHS Foundation Trust
"We're running a pilot with Microsoft's backing, plugging building management systems into their machine learning product, to see if we can predict maintenance cycles and energy use. I see that as a really interesting area of development, and it also ties into our IoT work."
Chris Weston, Bellrock
"We could use machine learning where we currently have manual intervention in aspects of our workflows, and we could even get to the stage where we use a lot of machine learning in our underwriting algorithms," says Rob Harding, Capital One Europe CIO. The company has already implemented some aspects of machine learning into its data science team, but Harding believes there is much more to be explored in the area.
Rob Harding, Capital One Europe
"At Ovo we have 20 percent of our base on smart meters already, transmitting consumption data to us up to every 10 seconds. We have developed a smart IoT device that connects to the meter via ZigBee and gives us data in real time. We store everything in NoSQL and time series databases and analyse it using machine learning."
Mariano Albera, Ovo Energy
"We've deployed some AI/ML capability within our sentiment dashboard application, which uses machine learning services in the cloud combined with in-house data to build a picture for the licensee. The BI/analytics initiative we've started centres on SQL Server 2016, which brings high-end analytics and machine learning capability through Cortana and PowerBI."
Mike McMinn, Marston's
"Today, every plant around the world brings forecasting, inventory, and production information together in their ERP to help managers meet a demand cycle. With machine learning and AI, we will be connecting the machines in the plant to that ERP, and our ability to determine how, when and where to produce parts to meet a demand forecast will improve dramatically."
Jim Fowler, GE