Machines lack the creativity for novel ideas and have no feelings and no fond memories of their youth. But recent technological advances are narrowing the gap between human brains and circuitry. At Stanford University, bioengineers are replicating the complicated parallel processing of neural networks on microchips. Another development--a robot named Darwin VII--has a camera and a set of metal jaws so that it can interact with its environment and learn, the way juvenile animals do. Researchers at the Neurosciences Institute in La Jolla, Calif., modeled Darwin's brain on rat and ape brains. The developments raise a natural question: If computer processing eventually apes nature's neural networks, will cold silicon ever be truly able to think? And how will we judge whether it does? More than 50 years ago British mathematician and philosopher Alan Turing invented an ingenious strategy to address this question, and the pursuit of this strategy has taught science a great deal about designing artificial intelligence, a field now known as AI. At the same time, it has shed some light on human cognition. So what, exactly, is this elusive capacity we call "thinking"? People often use the word to describe processes that involve consciousness, understanding and creativity. In contrast, current computers merely follow the instructions provided by their programming. In 1950, an era when silicon microchips did not yet exist, Turing realized that as computers got smarter, this question about artificial intelligence would eventually arise. [For more on Turing's life and work, see box on opposite page.] In what is arguably the most famous philosophy paper ever written, "Computing Machinery and Intelligence," Turing simply replaced the question "Can machines think?" with "Can a machine--a computer--pass the imitation game?" That is, can a computer converse so naturally that it could fool a person into thinking that it was a human being?