You could argue that this has become a self-fulfilling prophecy. Once Moore’s prediction came to pass, it was simply a matter of working hard to ensure it continued to do so. The industry has a continued stake in trying to reach the next milestone predicted by Moore’s Law, because if any company ever fell behind this curve, it would be out of business.
But while Moore provided a name to something, the phenomenon he named didn’t actually create it. If you generalise Moore’s Law from chips to simply thinking about information technology and processing power in general, Moore’s Law becomes the latest in a long line of technical rules of thumb that explain extremely regular changes in technology over the last few centuries.
Chris Magee, a professor at MIT in the Engineering Systems Division, has measured these changes. Together with his postdoctoral fellow, Heebyung Koh, he compiled a vast data set of all the different instances of information transformation that have occurred throughout history. By lining up one technology after another – from calculations done by hand in 1892 that clocked in at a little under one calculation a minute to today’s machines – a pattern emerged. Despite the differences among all of these technologies, human brains, punch cards, vacuum tubes, integrated circuits, the overall increase in humanity’s ability to perform calculations has progressed quite smoothly and extremely quickly. Put together, there has been a roughly exponential increase in our information transformation abilities over time.
But how does this happen? How can all of these combined technologies yield such a smooth and regular curve? When someone develops a new innovation, it is often largely untested. As its developers improve and refine it, they begin to realise the potential of this new innovation. Its capabilities begin to grow exponentially, but then a limit is reached. And when that limit is reached there is the opportunity to bring in a new technology, even if it’s still tentative, untested and buggy. Combine all these successions of technologies together and what you get is a smooth curve of progresss.
Giant’s shoulders
So technological knowledge exhibits rapid growth just like scientific knowledge. But the relationship between the progression of technological facts and that of science is tightly intertwined.
Take the periodic table of chemical elements. We know that the number of known elements has steadily increased over time. However, while the number appears to have grown relatively smoothly over the centuries, if you look at the data more closely, a different picture emerges. As science historian Derek de Solla Price found, the periodic table has grown by a series of logistic curves. He argued that each of these was due to a successive technological advance or approach. For example, from the beginnings of the scientific revolution in the late 17th Century until the late 19th Century, more than sixty elements were discovered, using various chemical techniques, including electrical shocks, to separate compounds into their constituent parts.
However, these approaches soon reached their limits, and the discoveries slowed. But, following a Moore’s Law-like trajectory, a new technology arose. The particle accelerator was created, and its atom-smashing ability enabled further discoveries. As particle accelerators of increasing energies have been developed, we have discovered heavier and larger chemical elements. In a very real way, these advances have allowed for new facts.
Technological growth facilitates changes in facts, sometimes rapidly, in many areas: sequencing new genomes (nearly two hundred distinct species were sequenced as of late 2011); finding new asteroids (often done using sophisticated computer algorithms that can detect objects moving in space); even proving new mathematical theorems through increasing computer power.
