I believe you're referring to binary Huffman codes? However, this is only one form of compression. Consider that a Pseudo-random number generator with only 3 variable integers (a multiplier, a modulus and a seed). These 3 integers can generate a unique sequence of pseudo-random bits of information. The trick is to reverse the sequence to only 3 bits. The method described here doesn't use PRNG, but instead uses a system of linear equations and solves for the variables as the data symbols.
I think you can represent large amounts of data in less and less information, given large enough computing power and large enough mutual client/server databases.
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I believe you're referring to binary Huffman codes? However, this is only one form of compression. Consider that a Pseudo-random number generator with only 3 variable integers (a multiplier, a modulus and a seed). These 3 integers can generate a unique sequence of pseudo-random bits of information. The trick is to reverse the sequence to only 3 bits. The method described here doesn't use PRNG, but instead uses a system of linear equations and solves for the variables as the data symbols.
I think you can represent large amounts of data in less and less information, given large enough computing power and large enough mutual client/server databases.