Fairness, trust and transparency are qualities we usually associate with organisations or individuals. Today, these attributes might also apply to algorithms. As machine learning systems become more complex and pervasive, Cambridge researchers believe it’s time for new thinking about new technology.
Today we begin a month-long focus on research related to artificial intelligence. Here, four researchers reflect on the power of a technology to impact nearly every aspect of modern life – and why we need to be ready.
The Government have announced £5.4 million in funding to launch the Centre for Digital Built Britain at the University of Cambridge, which will help people make better use of cities by championing the digital revolution in the built environment. The Centre is part of a landmark government-led investment in growing the UK’s construction sector.
A group of researchers from the UK and the US have used machine learning techniques to successfully predict earthquakes. Although their work was performed in a laboratory setting, the experiment closely mimics real-life conditions, and the results could be used to predict the timing of a real earthquake.
A new app gives UK residents the chance to get involved in an ambitious, ground-breaking science experiment that could save lives.
Electron ‘spin’ could hold the key to managing the world’s growing data demands without consuming huge amounts of energy. Now, researchers have shown that energy-efficient superconductors can power devices designed to achieve this. What once seemed an impossible marriage of superconductivity and spin may be about to transform high performance computing.
India’s booming business centres and gleaming shopping malls mask a grimmer reality. While one section of the population gets richer, another section gets poorer. In the countryside, farmers and others ‘left behind’ by the economic surge find themselves in increasingly desperate circumstances. In many cases their plight, exacerbated by crippling debt, has led to suicide.
Algorithm matches genetic variation to disease symptoms and could improve diagnosis of rare diseases19 Apr 2017
A faster and more accurate method of identifying which of an individual’s genes are associated with particular symptoms has been developed by a team of researchers from the UK and Saudi Arabia. This new approach could enable scientists to take advantage of recent developments in genome sequencing to improve diagnosis and potential treatment options.
‘Big data’ study finds that children from families with limited education have strongest long-term response to teacher encouragement, and are more likely to progress to university as a result.