Programmers waste enormous amounts of time thinking about, or worrying about, the speed of noncritical parts of their programs, and these attempts at efficiency actually have a strong negative impact when debugging and maintenance are considered. We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil. Yet we should not pass up our opportunities in that critical 3%.

I remember that mathematicians were telling me in the 1960s that they would recognize computer science as a mature discipline when it had 1,000 deep algorithms. I think we've probably reached 500.

By understanding a machine-oriented language, the programmer will tend to use a much more efficient method; it is much closer to reality.

When certain concepts of TeX are introduced informally, general rules will be stated; afterwards you will find that the rules aren't strictly true. In general, the later chapters contain more reliable information than the earlier ones do. The author feels that this technique of deliberate lying will actually make it easier for you to learn the ideas. Once you understand a simple but false rule, it will not be hard to supplement that rule with its exceptions.

The whole thing that makes a mathematician’s life worthwhile is that he gets the grudging admiration of three or four colleagues.

There's ways to amuse yourself while doing things and thats how I look at efficency.

The most important thing in the kitchen is the waste paper basket and it needs to be centrally located.