By National Research Council, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on the Fundamentals of Computer Science: Challenges and Opportunities
Computing device technology: Reflections at the box, Reflections from the sector presents a concise characterization of key rules that lie on the middle of laptop technological know-how (CS) study. The booklet deals an outline of CS study spotting the richness and variety of the sector. It brings jointly dozen essays on varied features of CS study, their motivation and effects. via describing in obtainable shape machine science’s highbrow personality, and through conveying a feeling of its vibrancy via a suite of examples, the publication goals to arrange readers for what the long run may perhaps carry and aid to motivate CS researchers in its construction.
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Additional info for Computer Science: Reflections On The Field, Reflections From Field
The flow of control proceeds simply as follows: based on its current state, and the symbol it is currently reading, the machine may write a new symbol on the current page (erasing the existing one), move to the next or preceding page, and change its state. Subject to these rules, the Turing machine processes the input it is given and may eventually choose to halt, at which point the notebook contains its output. Why should we accept this model? First, it accords well with common sense. It seems to be the way that symbolic computation, as performed slowly and painfully by humans, proceeds.
The problems of image understanding, language understanding, locomotion, game playing, and problem solving each provide enormous challenges for the computer scientist. A second class of intelligence-related research is to understand how the human mind works by trying to solve problems the way humans do. It turns out, for example, that the simple “if A then B” logic harking back to Aristotle does not capture nearly enough of the way people think and make inferences about their environment. A third class of intelligence-related research is enabling computers to interact with the world by enabling them to sense the environment, move within it, and manipulate objects.
Hardware designers seek to make processors that execute instructions faster, memory that provides more information, and input/output devices that communicate more effectively. Furthermore, we can and do focus on making these primitive elements faster without worrying about what the software running on the hardware is actually doing. But how do we know this all works? Why is relatively simple hardware sufficient for most computing? Which instructions do I need in my instruction set architecture?