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[Computers] are developing so rapidly that even computer scientists cannot keep up with them. It must be bewildering to most mathematicians and engineers... In spite of the diversity of the applications, the methods of attacking the difficult problems with computers show a great unity, and the name of Computer Sciences is being attached to the discipline as it emerges. It must be understood, however, that this is still a young field whose structure is still nebulous. The student will find a great many more problems than answers.
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Exponential Growth in Computation How about computation? In 1971, Intel put out its first computer chip, the Intel 4004. It had 2,300 transistors on it, at $1 each. Intel no longer actually tells you how many transistors are on their chips, but the recent Core i9 had 7 billion transistors at less than a millionth of a penny each. This represents a 27-billion-fold increase in price performance in forty-five years.
The university is being called upon to educate previously unimagined numbers of students; to respond to the expanding claims of national service; to merge its activities with industry as never before. Characteristic of this transformation is the growth of the knowledge industry, which is coming to permeate government and business, and to draw into it more and more people raised to higher and higher levels of skill. The production, distribution and consumption of knowledge is said to account for 29 percent of gross national product, and knowledge production is growing at about twice the rate of the rest of the economy. What the railroads did for the second half of the last century, and the automobile for the first half of this century, may be done for the second half of this century by the knowledge industry; and that is, to serve as the focal point for national growth.
Faster-than-exponential growth also occurs in computing power, as measured by the evolution of the number of MIPS per $1,000 of computer from 1900 to 1997. Thus the so-called Moore's law is incorrect, since it implies only an exponential growth. This faster than exponential acceleration has been argued to lead to a transition to a new era, around 2030, corresponding to the epoch when we will have the technological means to create superhuman intelligence.
Today, multiple major waves seem to be arriving simultaneously — technologies like the cloud, AI, AR/ VR, not to mention more esoteric projects like supersonic planes and hyperloops. What’s more, rather than being concentrated narrowly in a personal computer industry that was essentially a niche market, today’s new technologies impact nearly every part of the economy, creating many new opportunities. This trend holds tremendous promise. Precision medicine will use computing power to revolutionize health care. Smart grids use software to dramatically improve power efficiency and enable the spread of renewable energy sources like solar roofs. And computational biology might allow us to improve life itself. Blitzscaling can help these advances spread and magnify their sorely needed impact.
A study of the high-speed computer market with the intention of specifying a new computer brings forth a number of interesting observations... [An] striking feature of the market is that we seem to be close to satisfying the need for present-day uses of computers, but are standing on the threshold of a vast new area of applications. This new area can be characterized by the phrase computers which interact with the outside world. This concept is called "Integrated Data Processing", "Real-Time. Operation", "Process Control", "In-Line Operation", etc, Its characteristic feature is the ability of the computer to accept and send information directly to other devices. The use of computers in this fashion is being developed in the aircraft and missile industries . It is important to note that both scientific and commercial applications are going in this direction.
Computing spread out much, much faster than educating unsophisticated people can happen. In the last 25 years or so, we actually got something like a pop culture, similar to what happened when television came on the scene and some of its inventors thought it would be a way of getting Shakespeare to the masses. But they forgot that you have to be more sophisticated and have more perspective to understand Shakespeare. What television was able to do was to capture people as they were. So I think the lack of a real computer science today, and the lack of real software engineering today, is partly due to this pop culture.
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