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[[Ankur Gupta]] | [[Ankur Gupta]] | ||
==Short Definition== | |||
* Data compression | |||
* Useful only if dispensed in a reasonable time | |||
==Summary Points== | |||
The quantitative measure of wisdom is the compression ratio achieved; the speed of query access is the “in-time" component. | |||
The world is drowning in data, and we are faced with the challenge of understanding it quickly and well. The idea of well-understood varies based on the data we have, but '''the universal goal is to distill the huge amount of information into its most essential components. This filtration process was considered a practical definition of wisdom by a number of thinkers in the Victorian Age.''' In their view, wisdom serves as a verifiable process of cognitive thought with respect to the real world. This pragmatic definition corresponds strongly with the nature of information from a computer scientist’s perspective, and in particular, to the task of compression. In an increasingly technical world, it is of critical importance to update our notions of wisdom to incorporate a new information-processing aspect to wisdom. It is no longer sufficient to consider a model where wisdom is dispensed by a human expert to a single individual. ''Computers can retain huge amounts of information and process it to find the answer to any question contained therein'' -- why disallow the concept of wisdom in this case? Careful organization of the data may address both the speed issue and the quality of the result; '''the organization requiring the least amount of memory capacity may be termed as wisdom'''. In this project, we draw a parallel between the definition of wisdom and compression, which is often achieved by reorganizing data to reduce redundancy. | The world is drowning in data, and we are faced with the challenge of understanding it quickly and well. The idea of well-understood varies based on the data we have, but '''the universal goal is to distill the huge amount of information into its most essential components. This filtration process was considered a practical definition of wisdom by a number of thinkers in the Victorian Age.''' In their view, wisdom serves as a verifiable process of cognitive thought with respect to the real world. This pragmatic definition corresponds strongly with the nature of information from a computer scientist’s perspective, and in particular, to the task of compression. In an increasingly technical world, it is of critical importance to update our notions of wisdom to incorporate a new information-processing aspect to wisdom. It is no longer sufficient to consider a model where wisdom is dispensed by a human expert to a single individual. ''Computers can retain huge amounts of information and process it to find the answer to any question contained therein'' -- why disallow the concept of wisdom in this case? Careful organization of the data may address both the speed issue and the quality of the result; '''the organization requiring the least amount of memory capacity may be termed as wisdom'''. In this project, we draw a parallel between the definition of wisdom and compression, which is often achieved by reorganizing data to reduce redundancy. |