First it was checkers (draughts to you and me), then chess, then Jeopardy!, then Go and now poker. One after another, these games, all of which require significant amounts of intelligence and expertise if they are to be played well, have fallen to the technology we call artificial intelligence (AI). And as each of these milestones is passed, speculation about the prospect of "superintelligence" (the attainment by machines of human-level capabilities) reaches a new high before the media caravan moves on to its next obsession du jour. Never mind that most leaders in the field regard the prospect of being supplanted by super-machines as exceedingly distant (one has famously observed that he is more concerned about the dangers of overpopulation on Mars): the solipsism of human nature means that even the most distant or implausible threat to our uniqueness as a species bothers us. The public obsession with the existential risks of artificial superintelligence is, however, useful to the tech industry because it distracts attention from the type of AI that is now part of its core business. This is "weak AI" and is a combination of big data and machine-learning – algorithms that ingest huge volumes of data and extract patterns and actionable predictions from them.