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and immediately know what it would do, then it would be an easy matter to check that the program did not contain any bugs.

Notions like the difficulty of finding bugs have no obvious connection to traditional ideas in science. And perhaps as a result of this, even after computers had been in use for several decades, essentially none of this type of intuition from practical computing had found its way into basic science. But in 1981 it so happened that I had for some years been deeply involved in both practical computing and basic science, and I was therefore in an almost unique position to apply ideas derived from practical computing to basic science.

Yet despite this, my discoveries about cellular automata still involved a substantial element of luck. For as I mentioned on page 19, my very first experiments on cellular automata showed only very simple behavior, and it was only because doing further experiments was technically very easy for me that I persisted.

And even after I had seen the first signs of complexity in cellular automata, it was several more years before I discovered the full range of examples given in this chapter, and realized just how easily complexity could be generated in systems like cellular automata.

Part of the reason that this took so long is that it involved experiments with progressively more sophisticated computer technology. But the more important reason is that it required the development of new intuition. And at almost every stage, intuition from traditional science took me in the wrong direction. But I found that intuition from practical computing did better. And even though it was sometimes misleading, it was in the end fairly important in putting me on the right track.

Thus there are two quite different reasons why it would have been difficult for the results in this chapter to be discovered much before computer technology reached the point it did in the 1980s. First, the necessary computer experiments could not be done with sufficient ease that they were likely to be tried. And second, the kinds of intuition about computation that were needed could not readily have been developed without extensive exposure to practical computing.

and immediately know what it would do, then it would be an easy matter to check that the program did not contain any bugs.

Notions like the difficulty of finding bugs have no obvious connection to traditional ideas in science. And perhaps as a result of this, even after computers had been in use for several decades, essentially none of this type of intuition from practical computing had found its way into basic science. But in 1981 it so happened that I had for some years been deeply involved in both practical computing and basic science, and I was therefore in an almost unique position to apply ideas derived from practical computing to basic science.

Yet despite this, my discoveries about cellular automata still involved a substantial element of luck. For as I mentioned on page 19, my very first experiments on cellular automata showed only very simple behavior, and it was only because doing further experiments was technically very easy for me that I persisted.

And even after I had seen the first signs of complexity in cellular automata, it was several more years before I discovered the full range of examples given in this chapter, and realized just how easily complexity could be generated in systems like cellular automata.

Part of the reason that this took so long is that it involved experiments with progressively more sophisticated computer technology. But the more important reason is that it required the development of new intuition. And at almost every stage, intuition from traditional science took me in the wrong direction. But I found that intuition from practical computing did better. And even though it was sometimes misleading, it was in the end fairly important in putting me on the right track.

Thus there are two quite different reasons why it would have been difficult for the results in this chapter to be discovered much before computer technology reached the point it did in the 1980s. First, the necessary computer experiments could not be done with sufficient ease that they were likely to be tried. And second, the kinds of intuition about computation that were needed could not readily have been developed without extensive exposure to practical computing.


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From Stephen Wolfram: A New Kind of Science [citation]