Markov chain Monte Carlo (MCMC) is a popular tool for Bayesian inference.However, MCMC cannot be practically applied to large data sets because of theprohibitive cost of evaluating every likelihood term at every iteration. Here we present Firefly Monte Carlo (FlyMC) MCMC algorithm with auxiliary variables that only queries the likelihoods of a subset of the data at each iteration yet simulates from the exact posterior distribution. FlyMC is compatible with modern MCMC algorithms, and only requires a lower bound on the per-datum likelihood factors. In experiments, we find that FlyMC generates samples from the posterior more than an order of magnitude faster than regular MCMC, allowing MCMC methods to tackle larger datasets than were previously considered feasible.

Switching from a nine-to-five to a nine-to-three workday could be the way forward in an increasingly hi-tech world, researchers say. A University of Otago report, released on Monday, found that while the impact of increased use of artificial intelligence (AI) on jobs was hard to predict, a shorter work week could help businesses and workers adapt. Report co-author Professor James Maclaurin said using AI alongside human workers could increase efficiency, productivity and potentially incomes. Avoiding AI, on the other hand, pushed workers into low-paid work while technology took on high value tasks. READ MORE: * Flexible work: The rise – and pros and cons – of shunning the'office' * Independent watchdog needed to probe Government's use of AI: law, computer science experts * The tech sector won't wait for us to catch up * While artificial intelligence is tipped to be'as significant as electricity', it's not coming for your job, yet "The key question is whether New Zealand will successfully deploy AI, ultimately increasing our GDP [gross domestic product], or [whether] more and more of the profits from the AI revolution flow to large, data-rich international companies such as Google and Facebook."

From virtual assistants to driverless cars, technology imitating human intelligence is on the rise. But at what ethical cost and how do boards future-proof their organisations in the face of rapid change? Earlier this year, a Japanese insurance company made headlines for doing something that company executives and directors around the world have been anticipating - and fearing - for years. Fukoku Mutual Life Insurance made 34 of its staff redundant and replaced them with artificial intelligence (AI) system IBM Watson. Japanese newspaper The Mainichi reported the company will be using Watson to determine payout amounts and check customer cases against their insurance contracts. Other Japanese insurance companies have announced they are looking at or are already using AI for similar purposes and The Japan Times reported in April that the country's Ministry of Economy, Trade and Industry was planning to trial AI to help government workers write draft answers for questions put to Cabinet ministers.