I define “raw information”, as used in other parts of the model, more precisely, in ways that are supposed to map onto Shannon-information or Kolmogorov information. I used the phrase “tech level” because my initial expectation is that power is proportional to the log of raw information. Some of my data concerning the rate of progress instead uses something with a meaning more like “perceived social change” or “useful information”, which I called “tech level”, and seems to be the log of raw information.
It may be that “useful information” really is Shannon information, and “raw information” is uncompressed, redundant information; and that this accounts for observations that “useful information” appears to be the log of “raw information”. For instance, we have an exponential increase in the number of genes sequenced; but probably a much-less-than-linear increase in the number of types of genes known. We have an exponential increase in journal articles published; but the amount of independent, surprising information in each article may be going down.
A (thermal, say) random number generator is easy to build and a good source of both Shannon and algorithmic (Kolmogorov) information. Having lots of information in these senses is not helpful for winning battles.
probably a much-less-than-linear increase in the number of types of genes known
I should clarify: We still have an exponential increase in the number of protein families known; but a less-than-linear increase in the number of protein domains known. Proteins are composed of modules called “domains”; a protein contains from 1 to dozens of domains. Most “new” genes code for proteins that recombine previously-known domains in different orders.
A digression: Almost all of the information content of an organism resides in the amino-acid sequence of these domains; and a lower bound of about 64% of domains (and 84% of those found in eukaryotes) evolved before eukaryotes (which include all multicellular organisms) split from prokaryotes about 2 billion years ago. (One source: Michael Levitt, PNAS July 7 2009, “Nature of the protein universe”.) So it’s accurate to say that most of evolution occurred in the first billion years; the development of more-complex organisms seems to have nearly frozen evolution of the basic components. We would likely be more complex today if those ancient prokaryotes had been able to hold off evolving into eukaryotes for another billion years, so that they could develop more protein domains first. There’s a lesson for aspiring singularians in there somewhere.
(Similarly, most evolution within eukaryotes seems to have occurred during a period of about 50 million years, just before the Cambrian explosion, half a billion years ago. Evolution has been slowing down in information-theoretic terms, while speeding up in terms of intelligence produced.)
I define “raw information”, as used in other parts of the model, more precisely, in ways that are supposed to map onto Shannon-information or Kolmogorov information. I used the phrase “tech level” because my initial expectation is that power is proportional to the log of raw information. Some of my data concerning the rate of progress instead uses something with a meaning more like “perceived social change” or “useful information”, which I called “tech level”, and seems to be the log of raw information.
It may be that “useful information” really is Shannon information, and “raw information” is uncompressed, redundant information; and that this accounts for observations that “useful information” appears to be the log of “raw information”. For instance, we have an exponential increase in the number of genes sequenced; but probably a much-less-than-linear increase in the number of types of genes known. We have an exponential increase in journal articles published; but the amount of independent, surprising information in each article may be going down.
A (thermal, say) random number generator is easy to build and a good source of both Shannon and algorithmic (Kolmogorov) information. Having lots of information in these senses is not helpful for winning battles.
True. However, I’m considering information that’s not at all random, so I don’t think that’s a problem.
I should clarify: We still have an exponential increase in the number of protein families known; but a less-than-linear increase in the number of protein domains known. Proteins are composed of modules called “domains”; a protein contains from 1 to dozens of domains. Most “new” genes code for proteins that recombine previously-known domains in different orders.
A digression: Almost all of the information content of an organism resides in the amino-acid sequence of these domains; and a lower bound of about 64% of domains (and 84% of those found in eukaryotes) evolved before eukaryotes (which include all multicellular organisms) split from prokaryotes about 2 billion years ago. (One source: Michael Levitt, PNAS July 7 2009, “Nature of the protein universe”.) So it’s accurate to say that most of evolution occurred in the first billion years; the development of more-complex organisms seems to have nearly frozen evolution of the basic components. We would likely be more complex today if those ancient prokaryotes had been able to hold off evolving into eukaryotes for another billion years, so that they could develop more protein domains first. There’s a lesson for aspiring singularians in there somewhere.
(Similarly, most evolution within eukaryotes seems to have occurred during a period of about 50 million years, just before the Cambrian explosion, half a billion years ago. Evolution has been slowing down in information-theoretic terms, while speeding up in terms of intelligence produced.)