The big picture: For the past 5 years, Elon Musk and others have warned of a future disaster resulting from unchecked superintelligent AI. But today, much of the field is caught in a rather more elementary tug-of-war over which avenue will imbue AI even with the capacity for basic understanding. Since the field took shape in the 1950s, artificial intelligence has advanced in fits and starts, with various tribes claiming the vanguard at different points. The current period began in the early 2010s, when a trio of researchers in Canada brought AI out of a decadeslong funk by reviving deep learning, aided by new and powerful hardware. Now, some of those same pioneers are warning against leaning too heavily on their contributions, and researchers with one foot in adjacent fields are sounding an increasingly insistent alarm about AI's trajectory.

Axios Sign up for a daily newsletter defining what matters in business and markets Email A reality check for AI hubris Illustration: Sarah Grillo/Axios For the better part of a decade, artificial intelligence has been propelled by a rocket fuel in seemingly endless supply. Deep learning, a method that allows machines to identify hidden patterns in data, has powered commercial applications like autonomous vehicles and voice assistants, and it's potentially worth trillions of dollars a year. The other side: The rosy portrait of unstoppable progress belies a fear among some AI luminaries that things are not on the right path. In a new sort of resource curse, they say that deep learning has sucked energy away from other strains of inquiry without which AI may never approach even a child's intellectual capabilities. The big picture: For the past 5 years, Elon Musk and others have warned of a future disaster resulting from unchecked superintelligent AI. But today, much of the field is caught in a rather more elementary tug-of-war over which avenue will imbue AI even with the capacity for basic understanding.