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Each year, we choose the 35 innovators under the age of 35 whose new technologies seem most gloriously creative and most likely to expand human life. (Here are the 2006 winners.) In editing this year’s TR35–and rereading the profiles of last year’s winners, whom we introduced in the October 2005 issue–I’ve noticed a few things about successful innovation.

(1) Successful innovators are famously untroubled by the prospect of failure. Bryan Cantrill, an engineer at Sun Microsystems who invented software that allows systems engineers to track bugs in real time (and whom we named one of 2005’s TR35), says, “People who have innovated once, and who say they are not frightened that they won’t be able to repeat their success, are probably lying. The challenge is not to be crippled by fear, but allow it to drive you forward.” More profoundly, (2) many innovators appreciate failure. Yael Maguire, the chief technology officer of ThingMagic and another of last year’s TR35, who has designed machines that read radio frequency identification chips, says, “If you’re not working on technologies that are going to fail, you’re not pushing the boundaries enough. Even if a technology failed … you’ll be able to put it in your back pocket and use it for some other purpose.”

(3) Innovators commonly recognize that “problems and questions are the limiting resource in innovation,” says Ed Boyden, a Stanford University neurobiologist and one of 2006’s TR35. He means that difficult questions are thrilling: “If we take a really hard question, like ‘What is consciousness?’ or ‘How do we store memories?’, it’s not even clear how we should even approach the problem.” In attempting to answer such questions, Boyden used genetic engineering to create a precise, reliable neural switching system; scientists could use it to study how brains function, and it might one day provide treatments for Parkinson’s disease, blindness, and depression.

Boyden illustrates another theme: how (4) innovators find inspiration in disparate disciplines. The brain is “the ultimate computer,” says Boyden, who has applied lessons to human neurobiology that he gleaned from his earlier work in computer science and electrical engineering.

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