The march of the machines is upon society: the vast power of machine learning has been freed from the confines of IT laboratories and is disrupting businesses across the world, delivering deep insight, accurate predictions and detailed learnings that have the potential to make huge transformation.
In my series, I've looked at the different ways in which data can be deployed to help people make decisions. Over time, more of the decision-making process has shifted from people manually collating data from different sources in their heads to using data sets that can be automatically joined together.
Events If you missed out on early bird tickets for MCubed, our machine learning and AI extravaganza, don't despair - you can still save a bundle of cash on our optional workshop sessions. We'll admit it - we were late posting details of a brace of our workshops.
You've probably encountered the term "machine learning" more than a few times lately. Often used interchangeably with artificial intelligence, machine learning is in fact a subset of AI, both of which can trace their roots to MIT in the late 1950s. Machine learning is something you probably encounter every day, whether you know it or not.
Google has been pretty far ahead of the curve when it comes to its artificial intelligence research. The world was shocked when its AI beat a top human player at the game of Go. More recently the company taught AI to use imagination and make predictions. The latest trick in Google's machine-learning research?
AI is helping identify problems and solve them faster and better, finding applications across industries.
Engineering news The smart materials of the future are likely to be discovered not in the lab, but on a supercomputer. Materials science has exploded in recent years - offering tantalising potential solutions to engineering challenges ranging from higher-capacity batteries to safer medical devices.
