First you would have to translate all those things to binary. That would take quite a few rules. However, you are looking at the problem backwards. The problem is not DEscription but PREscritpion. You may be able to easily turn Shakespeare's works to binary code (in essence it has been done, you can easily download them from several sites), but you cannot create them. Which is what the problem of life and evolution is - to create that complex, tremendously large 4 bit code which is the basis of life.
BTW - there has been a lot of talk about Kolmogorov complexity in this thread in the abstract. However I have not seen examples of its use in the specific (althout I may have missed it). What is the complexity of the human DNA code compared to Hamlet, to a sedimentary rock 1 foot square, to a drop of water, to a snowflake. While it is nice to discuss abstract ideas, it seems to me that if one is speaking about supposed models of reality, one needs to give specific examples and test the theory to the reality.
You have it precisely backwards. There is only one rule. Eight bits make an ASCII character.
The rule I gave does create the works of Shakespeare inter alia.
I don't know why this point is so often overlooked, gore3000. Thanks for mentioning it.
Whatever the ascii length of a (or all) Shakespeare work(s) - create a program which randomly generates bit strings of that length. Eventually the program will generate a matching bit stream.
That is no doubt true but IMHO, it does not necessarily tell us much about the genetic code. First of all, the amount of time in the geological record is finite, so one question is what is the probability of yielding a particular bit string given a certain rate of production and window of opportunity.
Secondly, the theory of evolution suggests that the content of the bit string becomes more complex over time – a stair stepping effect. So the window of opportunity questions are more narrowly construed, step by step.
Thirdly, and most importantly, the steps of increasing complexity are functional - they have information content. That also must be explained.
That’s why I’m raising the question of how we can evaluate the genetic code of living creatures. From what I have read, the issue comes down to entropy v complexity. But as with the multi-verse models, the question of motive is also in the mix (emphasis mine):
At this website the reader is advised to use the difference to argue against creationists:
This article highlights some of the main concepts of Algorithmic Information Theory. Knowledge of this subject can be useful when arguing with Creationists whose use of concepts from both Classical and Algorithmic Information Theory tends to be sloppy. This article is only a survey of the major ideas. For the mathematical proofs, see the cited material.
"Highly ordered" is paradoxically opposite from "complex" in algorithmic-based information theory. The emergent property of "instructions," "organization," and the "message" of "messenger biomolecules" is simply not addressed in Maxwell-Boltzmann-Gibbs equations of heat equilibration and energy flux between compartments. Surprisingly, the essence of genetic "prescriptive information" and "instructions" is not addressed by current "information theory" either. Shannon information theory concerns itself primarily with data transmission, reception, and noise-reduction processing without regard for the essence of the "message" itself.
The Foundation questions whether "order," physical "complexity," or "shared entropy" are synonymous with "prescriptive information," "instructions," or "organization." Christoph Adami emphasizes that information is always "about something, and cannot be defined without reference to what it is information about." It is "correlation entropy" that is "shared" or "mutual." Thus, says Adami, "Entropy can never be a measure of complexity. Measuring correlations within a sequence, like Kolmogorov and Chaitin (and Lempel-Ziv, and many others) is not going to reveal how that sequence is correlated to the environment within which it is to be interpreted. Information is entropy "shared with the world," and the amount of information a sequence shares with its world represents its complexity." (Personal communication; see also PNAS, April 25, 2000, 97, #9, 4463-4468).
Differences of perspective among information theorists are often definitional. "Complexity" and "shared entropy" (shared uncertainty between sender and receiver) has unfortunately often been used synonymously with "prescriptive information (instruction)." But is it? Mere complexity and shared entropy seem to lack the specification and orchestrational functionality inherent in the genetic "instruction" system of translation.
The confusion between algorithmic instruction and Maxwell-Boltzmann-Gibbs entropy may have been introduced through the thought experiment imagining Maxwell's Demon - a being exercising intelligent choice over the opening and closing of a trap door between compartments. Statistical mechanics has no empirical justification for the introduction of purposeful control over the trap door.
Solar energy itself has never been observed to produce prescriptive information (instruction/organization). Photons are used by existing instructional mechanisms which capture, transduce, store, and utilize energy for work. Fiber optics is used by human intelligence to transmit meaningful prescriptive information (instruction) and message. But raw energy itself must not be confused with functional prescriptive information/instructions. The latter is a form of algorithmic programming. Successions of certain decision-node switch settings determine whether a genetic "program" will "work" to accomplish its task.