Some ~72 years ago in 1951, Claude Shannon released his Paper, "Prediction and Entropy of Printed English", an extremely fascinating read now.

It begins with a game. Claude pulls a book down from the shelf, concealing the title in the process. After selecting a passage at random, he challenges his wife, Mary to guess its contents letter by letter. The space between words will count as a twenty-seventh symbol in the set. If Mary fails to guess a letter correctly, Claude promises to supply the right one so that the game can continue.

In some cases, a corrected mistake allows her to fill in the remainder of the word; elsewhere a few letters unlock a phrase. All in all, she guesses 89 of 129 possible letters correctly—69 percent accuracy.

Discovery 1: It illustrated, in the first place, that a proficient speaker of a language possesses an “enormous” but implicit knowledge of the statistics of that language. Shannon would have us see that we make similar calculations regularly in everyday life—such as when we “fill in missing or incorrect letters in proof-reading” or “complete an unfinished phrase in conversation.” As we speak, read, and write, we are regularly engaged in predication games.

Discovery 2: Perhaps the most striking of all, Claude argues that that a complete text and the subsequent “reduced text” consisting of letters and dashes “actually…contain the same information” under certain conditions. How?? (Surely, the first line contains more information!).The answer depends on the peculiar notion about information that Shannon had hatched in his 1948 paper “A Mathematical Theory of Communication” (hereafter “MTC”), the founding charter of information theory.

He argues that transfer of a message's components, rather than its "meaning", should be the focus for the engineer. You ought to be agnostic about a message’s “meaning” (or “semantic aspects”). The message could be nonsense, and the engineer’s problem—to transfer its components faithfully—would be the same.

a highly predictable message contains less information than an unpredictable one. More information is at stake in (“villapleach, vollapluck”) than in (“Twinkle, twinkle”).

Does "Flinkle, fli- - - -" really contain less information than "Flinkle, flinkle" ?

Shannon concludes then that the complete text and the "reduced text" are equivalent in information content under certain conditions because predictable letters become redundant in information transfer.

Fueled by this, Claude then proposes an illuminating thought experiment: Imagine that Mary has a truly identical twin (call her “Martha”). If we supply Martha with the “reduced text,” she should be able to recreate the entirety of Chandler’s passage, since she possesses the same statistical knowledge of English as Mary. Martha would make Mary’s guesses in reverse.

Of course, Shannon admitted, there are no “mathematically identical twins” to be found, but and here's the reveal, “we do have mathematically identical computing machines.”

Those machines could be given a model for making informed predictions about letters, words, maybe larger phrases and messages. In one fell swoop, Shannon had demonstrated that language use has a statistical side, that languages are, in turn, predictable, and that computers too can play the prediction game.