These talents are readily apparent in the new wave of autonomous vehicles, warehouse robotics, smartphones and digital assistants such as Amazon's Alexa.

But these machines struggle with other basic tasks. Though Alexa does a pretty good job of recognising what you say, it cannot respond to anything more than basic commands and questions. When confronted with heavy traffic or unexpected situations, driverless cars just sit there.

AI "recognises objects, but can't explain what it sees. It can't read a textbook and understand the questions in the back of the book," said Oren Etzioni, a former University of Washington professor who oversees the Allen Institute for Artificial Intelligence. "It is devoid of common sense."

Success may require years or even decades of work — if it comes at all. Others have tried to digitise common sense, and the task has always proved too large.

In the mid-1980s, Doug Lenat, a former Stanford University professor, with backing from the government and several of the country's largest tech companies, started a project called Cyc. He and his team of researchers worked to codify all the simple truths that we learn as children, from "you can't be in two places at the same time" to "when drinking from a cup, hold the open end up."

Thirty years later, Lenat and his team are still at work on this "common sense engine"— with no end in sight.

Allen helped fund Cyc, and he believes it is time to take a fresh approach, he said, because modern technologies make it easier to build this kind of system.

Lenat welcomed the new project. But he also warned of challenges: Cyc has burned through hundreds of millions of dollars in funding, running into countless problems that were not evident when the project began. He called them "buzz saws."

The New York Times