Hybrid AI: A new way to make machine minds that really think like us

ARTIFICIAL intelligence has come a long way. In recent years, smart machines inspired by the human brain have demonstrated superhuman abilities in games like chess and Go, proved uncannily adept at mimicking some of our language skills and mastered protein folding, a task too fiendishly difficult even for us. But with various other aspects of what we might reasonably call human intelligence – reasoning, understanding causality, applying knowledge flexibly, to name a few – AIs still struggle. They are also woefully inefficient learners, requiring reams of data where humans need only a few examples. Some researchers think all we need to bridge the chasm is ever larger AIs, while others want to turn back to nature's blueprint.