Thinking and learning about artificial intelligence are the mental equivalent of a fission chain reaction. The questions get really big, really quickly. The most familiar concerns revolve around short-term impacts: the opportunities for economic productivity, health care, manufacturing, education, solving global challenges such as climate change and, on the flip

Artificial intelligence (AI) represents a new generation of digital software for a number of reasons. Its ultimate power is still untested and theoretical, and an industry that is likely to keep blooming over the next few decades, disrupting industries, taking over jobs, and hopefully freeing humanity from a lot of daily,

As Miguel de Cervantes rightly said, “Diligence is the mother of good fortune.” For developers working on machine learning and AI projects, this diligence needs to be focused acutely on the quality of the data used to train models. Models that are trained on data of low quality, with poor

Machine-learning algorithms are transforming the search for extraterrestrial intelligence, finding candidate signals faster and better than ever before, but the development of artificial general intelligence could complicate contact. Turn a radio telescope to the stars in the sky, and it’s instantly deafened. From pulsars to radio galaxies, and ionospheric disturbances in the atmosphere to

‘Civilization’ has always been a precarious affair. Werner Herzog described it as a layer of thin ice over a sea of darkness and chaos. It is also a concept that has been widely abused, being used as a hypocritical justification for such uncivilised acts as enslavement, wars, and colonisation. In