Computational models based on baby brainpower could give enable AI to overcome limitations such as handling nuances and uncertainty, said researchers.

"Children are the greatest learning machines in the universe. Imagine if computers could learn as much and as quickly as they do," said study co-author Alison Gopnik developmental psychologist at University of California Berkeley, who authored "The Scientist in the Crib" and "The Philosophical Baby."

In a wide range of experiments involving lollipops, flashing and spinning toys, and music makers, among other props, researchers are finding that children - at younger ages - are testing hypotheses, detecting statistical patterns and drawing conclusions while constantly adapting to changes.

"Young children are capable of solving problems that still pose a challenge for computers, such as learning languages and figuring out causal relationships," said study co-author Tom Griffiths, director of Berkeley's Computational Cognitive Science Lab, according to a university statement.

"We are hoping to make computers smarter by making them a little more like children. Your computer could be able to discover causal relationships, ranging from simple cases such as recognizing that you work more slowly when you haven't had coffee, to complex ones such as identifying which genes cause greater susceptibility to diseases," said Griffiths.