A New Kind of Science
Copyright 2002
By Stephen Wolfram
A New Kind of Science, raised expectations that some great new understanding was about to be shared with the world, but now here it is, and many are disappointed. It's an impressive work, with roughly a thousand high quality images, but the author's incredible ego, and overly wordy style get in the way of readability. Written during ten years in isolation and without feedback from the scientific community, the book suffers from lack of acknowledgement of the work of others, and questionable accuracy in some areas.

Researchers need enormous computer power to forecast changes in the Earth's climate, but they can predict the speed of a ball rolling down a ramp with pencil and paper. Stephen Wolfram claimed in his 2002 best seller, A New Kind of Science, that there is a clear dividing line between complex problems that require computer crunching and those for which equations alone will do. He argued that many important problems are more like the climate than the ball. But according to the 20 February PRL, his definition of complexity is imperfect because many of the problems he classified as complex are easily solved, as long as you can accept approximate answers. The results suggest that the traditional approach of physics--the equivalent of pencil and paper--is more widely applicable than Wolfram's analysis implies.

In May 2002, after spending a decade living as a recluse, the legendary Stephen Wolfram stepped into the public arena with the publication of a book promising to revolutionize the way we do science. For hundreds of years, scientists have successfully used mathematical equations that show how various entities are related. For example, Newton’s equation (his second law of motion) F=ma shows us how force (F) is related to mass (m) and acceleration (a). The problem with this approach is that equations fail to adequately describe complex phenomena all around us, such as the turbulence of boiling water or the changing weather. Whereas equations cannot capture such complexity, Wolfram believes that simple computational rules can. Therefore, to model nature’s complex phenomena, Wolfram proposes that scientists give up their unwieldy equations and instead employ the types of computational rules used in cellular automata (CA) and related computer programs. These programs repeatedly execute a set of rules that are simple enough for a child to follow. Yet, despite their ultimate simplicity, these programs can generate immense complexity.