MACHINE LEARNING
We live in an age of data , with digital information now being seen as more valuable than oil . Fittingly , then , this overtaker of oil also holds the keys to helping us reduce our reliance on it .
Despite being an issue that has almost all the world ’ s leaders ’ attention , stopping climate change seemingly still has no definitive answer . But in the current craze for AI , industry experts are pointing at how a subset of the technology , machine learning ( ML ), can help us get a handle on it .
By applying ML to work on the terabytes of data collected from the grid of a country , we can optimise the outputs of systems that are in charge of energy , and balance those that are intensive users of it .
Analysing this data effectively is still a massive challenge , as is implementing a system to power it . The impetus for doing so is , however , apparent . So what do business leaders need to know to get the wheels in motion on the train to a more sustainable tomorrow ?
Leveraging ML for energy ML is a subset of AI that allows computers to learn without explicit programming . It works by feeding algorithms massive amounts of data to enable them to identify patterns and make predictions .
Machine learning applications are widespread and constantly evolving , impacting fields like healthcare ( analysing medical images for disease detection ), finance ( identifying fraudulent activity ), aimagazine . com 99