Compressibility and Shannon’s entropy provide a baseline measure of the intrinsic information content of data. But the health of that data must also relate to how robust it is; how well encoded it is to withstand noise and corruption. And when an organism’s data contains mutual, survival related information about the organism and its environment, t

it was the very inaccessibility of this information—untranslatable, mysterious—that intrigued people thousands of years later.

The phase transition proposed from non-alive to alive has to be more intricate and only truly visible when you investigate the hierarchy of information flow:

clever illustration, a group game of twenty questions that he called “negative twenty questions.” In this variant of the usual play, the guesser asking yes/no questions believes the group being interrogated has a single item in mind that they’ve all agreed on in the guesser’s absence. In actuality, each person can start with whatever they want in m

knowledge of one thing reduces uncertainty about another thing.

For the dataome humans generate the one thing that we have yet to see machines or artificial algorithms produce: original information, real innovation, and open-ended novelty. Ideas seemingly plucked from the ether.

we’re missing what’s right in front of us. Evolution has been tinkering with ways to better propagate information on Earth since the get-go four billion years in the past.

when humans talk about meaning we’re usually referring to things that speak to our personal experiences, our aesthetic senses, and our intellects, or to our emotional inner lives and our ability to enhance our sense of satisfaction and happiness.

In the history of information theory, and science in general, one of the most influential research papers of the twentieth century is Claude Shannon’s “A Mathematical Theory of Communication,”