The unbearable slowness of being: Why do we live at 10 bits/s?

So, in the context of random word lookup with filter for things, we have a latency of a few seconds and a total selection of 20 bits.

Meanwhile the machinery in understanding that it is a game, processing the audio input of the question, producing the output of the answer is all taken for granted.

> That is one of the primary problems of society's obsessions with classical notions of gender.

What you go on to discuss is sex, and sexual dimorphism, which is a remarkably robust way of classification. The "classical" notions of gender (tbh, "classical" doesn't make much sense here) as sex based is fairly reasonable all things considered. Consider the arguments presented in this essay [0]. That, however, doesn't really mean much for how we should treaty people in public who desire to express their gender in different ways, which is, of course, respecting of their dignity and desires, in most cases.

[0]: https://philosophersmag.com/unexceptional-sex/

> If the questions are properly designed, each will reveal 1 bit of information about the mystery thing. If the guesser wins routinely, this suggests that the thinker can access about 2^20 ≈ 1 million possible items in the few seconds allotted. So the speed of thinking – with no constraints imposed – corresponds to 20 bits of information over a few seconds: a rate of 10 bits per second or less.

This is an extrinsic definition of "information" which is task relative, and has little to do with any intrinsic processing rate (if such a thing can even be defined for the imagination).

The question of why does biological hardware capable of very high "intrinsic rates" deliver problem solving at "very low extrinsic rates" seems quite trivial. Its even a non-sequitur to compare them: properties of the parts are not properties of wholes. "Why does a gas move at 1 m/s, when its molecules move at 1000s m/s..."

All the 'intrinsic processing' of intelligence is concerned with deploying a very large array of cognitive skills (imagination, coordination, planning, etc.) that are fully general. Any given task has requires all of those top be in operation, and so we expect a much slower rate of 'extrinsic information processing'.

Consider how foolish the paper is to compare the intrinsic processing of a wifi network with the extrinsic task-specific processing of a human: it is likewise the case that if we set a computer the challenge of coordinating the solution of a task (eg., involving several LLMs) across a network, it's task-specific performance would drop off a cliff -- having a much slower 'solution rate' than 10bit/second.

These 'task-specific bits' represent a vast amount of processing work to solve a problem. And are at least as much to do with the problem, than the system solving it.

It seems to me all this paper does is define tasks in a highly abstract way that imposes a uniform cost to process '1 bit of task information'. Do the same for computers, and you'd likewise find tiny bitrates. The rate at which a problem is solved is 'one part of that problem per second' for a suitable definiton of 'part'

It’s an experimental result by Shannon: https://archive.org/details/bstj30-1-50/page/n5/mode/1up

In short, you show someone an English text cut off at an arbitrary point and ask them to predict which letter comes next. Based on how successful they are, you can calculate the information content of the text. The result from this experiment was approximately one bit per letter.

Representing it is not the concern of the experiment. I don’t think anyone has a scheme that can do this. But it’s straightforward enough in theory. You create a compressor which contains a simulated human English speaker. At each point, ask the simulation to rank all the letters that might come next, in order. Emit the rank of the actual next letter into your compressed data. To decompress, run the same procedure, but apply the ranks you read from the data stream to the simulation’s predictions. If your simulation is deterministic, this will produce output matching the compressor’s input.

From the paper:

Take for example a human typist working from a hand-written manuscript. An advanced typist produces 120 words per minute. If each word is taken as 5 characters, this typing speed corresponds to 10 keystrokes a second. How many bits of information does that represent? One is tempted to count the keys on the keyboard and take the logarithm to get the entropy per character, but that is a huge overestimate. Imagine that after reading the start of this paragraph you are asked what will be the next let…

English contains orderly internal structures that make the character stream highly predictable. In fact, the entropy of English is only ∼ 1 bit per character [1]. Expert typists rely on all this redundancy: if forced to type a random character sequence, their speed drops precipitously.

[1] Shannon CE. Prediction and Entropy of Printed English. Bell System Technical Journal. 1951;30(1):50-64.