While the most advanced computers today can perform the most complicated tasks and calculations than average humans but computers still fall short in learning ability. However scientists are looking to remedy this by learning from "the greatest learning machines in the universe": human babies.

Scientists at the University of California, Berkeley are tapping into the cognitive ability of babies to program computers to think more like humans. If computers can replicate the learning abilities of toddlers, artificial intelligence could improve by leaps and bounds.

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

Babies can quickly adapt to new stimuli and can soak up information like sponges. Children possess a capacity to navigate a world that is new to them and can test hypotheses and draw conclusions about important things like lollipops and flashing toys. A healthy newborn baby has a brain that contains 100 billion neurons which grows into a vast network of synapses or connections by the age of 2 or 3.

Gopnik and her colleagues at UC Berkeley are tracking the cognitive steps children use to solve problems and then using them as computational models. If computers could learn like children it could lead to AI with better human interaction skills. Such programs like robotic answering services, computerized tutoring programs and even robots that can identify genes will sound less machine-like.

"Young children are capable of solving problems that still pose a challenge for computers, such as learning languages and figuring out causal relationships," Tom Griffiths, director of UC Berkeley's Computational Cognitive Science Lab, said in a 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."

This line of research could lead to an artificial intelligence that would be able to adapt easily to outside influences. Gopnik, Griffiths and other UC Berkeley psychologists, computer scientists and philosophers plan to create a center at Berkeley's Institute of Human Development to continue their research.