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We’re not prepared for the end of Moore’s Law


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Gordon Moore, overlooking the trend of his Law.

Gordon Moore's prediction that the number of components on an integrated circuit would double every year has defined the trajectory of technology and, in many ways, of progress itself.

Credit: MS TECH

Gordon Moore's 1965 forecast that the number of components on an integrated circuit would double every year until it reached an astonishing 65,000 by 1975 is the greatest technological prediction of the last half-century. When it proved correct in 1975, he revised what has become known as Moore's Law to a doubling of transistors on a chip every two years.

Since then, his prediction has defined the trajectory of technology and, in many ways, of progress itself.

Moore's argument was an economic one. Integrated circuits, with multiple transistors and other electronic devices interconnected with aluminum metal lines on a tiny square of silicon wafer, had been invented a few years earlier by Robert Noyce at Fairchild Semiconductor. Moore, the company's R&D director, realized, as he wrote in 1965, that with these new integrated circuits, "the cost per component is nearly inversely proportional to the number of components." It was a beautiful bargain—in theory, the more transistors you added, the cheaper each one got. Moore also saw that there was plenty of room for engineering advances to increase the number of transistors you could affordably and reliably put on a chip.

Soon these cheaper, more powerful chips would become what economists like to call a general purpose technology—one so fundamental that it spawns all sorts of other innovations and advances in multiple industries. A few years ago, leading economists credited the information technology made possible by integrated circuits with a third of US productivity growth since 1974. Almost every technology we care about, from smartphones to cheap laptops to GPS, is a direct reflection of Moore's prediction. It has also fueled today's breakthroughs in artificial intelligence and genetic medicine, by giving machine-learning techniques the ability to chew through massive amounts of data to find answers.

But how did a simple prediction, based on extrapolating from a graph of the number of transistors by year—a graph that at the time had only a few data points—come to define a half-century of progress? In part, at least, because the semiconductor industry decided it would.

 

From Wired
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