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US military trains financial force on search for ‘common sense’ AI Posted on : Jun 16 - 2018

Defence research group Darpa seeks breakthrough in quest for truly intelligent machines

The US defence department is preparing to take on one of the biggest challenges in artificial intelligence: how to endow computers with common sense.

The effort could lead to military systems with greater awareness of the world around them and the ability to adapt in the way humans do, said Dave Gunning, a programme manager at Darpa, the US defence research group best known for funding early work on the internet and autonomous vehicles.

One result would be systems that “don’t drive off a cliff and have the sense to come in out of the rain”, he said. It could also lead to flexible machines that communicate more naturally with people and can adapt to unexpected events.

The pursuit of machines with common sense highlights design weaknesses in today’s AI that could severely limit the usefulness of the technology. “This is the elephant in the room, the 800lb gorilla. If we don’t make progress on this we’ll never get beyond the brittle [AI] systems we currently have,” said Mr Gunning.

Programming computers to have the sort of intuitive understanding of the world that comes as second nature to humans was a central hope when the field of AI was founded more than half a century ago. It was abandoned early on but has seen a recent revival of interest in academic circles. Paul Allen, Microsoft co-founder, doubled investment into his own AI research institute earlier this year to push the idea.

“This is one of the oldest, if not the oldest, dream of AI researchers,” said Joshua Tenenbaum, a professor of cognitive science and computing at Massachusetts Institute of Technology. “We think of this as at the heart of what it means to be intelligent.”

Many of the recent breakthroughs in AI have come from systems that crunch vast amounts of data in search of patterns, enabling them to do things such as identify images or make predictions. But with no real understanding of the world, these so-called deep-learning systems are unable to take on problems outside the narrow areas they were designed for.

“They don’t generalise well across different topics and aren’t robust in unforeseen situations,” said Yejin Choi, an associate professor at the University of Washington who is among the AI researchers working on common sense. View More