This discrepancy between the relative ease of teaching a machine abstract thinking and the difficulty of teaching it basic sensory, social, and motor skills is what's known as Moravec's paradox. Named after an observation the roboticist Hans Moravec made back in the late 1980s, the paradox states that what's hard for humans (math, logic, scientific reasoning) is easy for machines, and what's hard for machines (tying shoelaces, reading emotions, having a conversation) is easy for humans. In her latest book, Robots and the People Who Love Them: Holding On to Our Humanity in an Age of Social Robots, science writer Eve Herold argues that thanks to new approaches in machine learning and continued advances in AI, we're finally starting to unravel this paradox. As a result, a new era of personal and social robots is about to unfold, she says--one that will force us to reimagine the nature of everything from friendship and love to work, health care, and home life. To give readers a sense of what this brave new world of social robots will look like, Herold points us toward Pepper, a doe-eyed humanoid robot that's made by the Japanese company SoftBank.