AIs use hide-and-seek to learn to tackle real-world problems

Pitting two artificial intelligences against each other in games such as DeepMind's Go has led to some of the biggest breakthroughs in AI in recent years, as the machines learn skills through trial and error that eventually lead to them beating humans. But can the same technique produce a more useful AI capable of operating in the real word? OpenAI, a San Francisco-based AI research group, published research on Tuesday showing what it claimed was a method for training increasingly powerful smart systems that could prepare them for tackling more ordinary human problems. Set in increasingly realistic environments, the technique points to a way for the AI to "evolve" in a simulated world until it is ready to be used, it said. The researchers used several intelligent "agents" in a game of hide-and-seek played in a simulated physical environment.