DeepMind experiment shows AI must grow smarter, not just bigger

DeepMind says that teaching machines to realistically mimic human language is more complex than simply throwing increasing amounts of computing power at the problem, despite that being the predominant strategy in the field. In recent years, most progress in building artificial intelligences (AIs) has come from increasing their size and training them with ever more data on the biggest computer available. But this makes the AIs expensive, unwieldy and hungry for resources. A recent system created by Microsoft and Nvidia required more than a month of supercomputer access and almost 4500 high-power graphics cards to train, at a cost of millions of dollars. In a bid to find alternatives, AI firm DeepMind has created a model that can look up information in a vast database, in a similar way that a human would use a search engine.