Toddler smarter than smartest AI

This article at io9 discusses research at UC Berkeley that is looking at how toddlers learn for ideas to improve computer AI.

In a wide range of experiments involving lollipops, flashing and spinning toys, and music makers, among other props, UC Berkeley researchers are finding that children – at younger and 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 Tom Griffiths, director of UC Berkeley’s Computational Cognitive Science Lab. “We are hoping to make computers smarter by making them a little more like children.”

hmmmm…teaching computers to “play”? They might be onto something 😉

The healthy newborn brain contains a lifetime’s supply of some 100 billion neurons which, as the baby matures, grow a vast network of synapses or neural connections – about 15,000 by the age of 2 or 3 – that enable children to learn languages, become socialized and figure out how to survive and thrive in their environment.

Adults, meanwhile, stop using their powers of imagination and hypothetical reasoning as they focus on what is most relevant to their goals, Gopnik said. The combination of goal-minded adults and open-minded children is ideal for teaching computers new tricks.

“We need both blue-sky speculation and hard-nosed planning,”

The reserchers have found toddlers learning and exploration is remarkably sophisticated. A key being the ability to play pretend – immersion into hypothetical and creative environments – are an important tool in forming causal models and exploring relationships. IT would be interesting to look at teens and adults that spend considerable time inn “game worlds” and see if there is a way to recapture any of that “golden age of pretending” to rekindle some of that ability to form neural networks to “rewire” patterns in adults, whose neural nets can get a bit inflexible.

So to understand how to make computers more creative, adults may benefit from more imaginative activities? Could exploring game play by humans and computers help both?

About Paul Vebber

"If you read about something, you have learned about it. If you can teach something, you have mastered it. Designing a useful game about something however, requires developing a deep understanding of how it relates to other things."
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