Thanks to @General_Effort@lemmy.world for the links!
Here’s a link to Caltech’s press release: https://www.caltech.edu/about/news/thinking-slowly-the-paradoxical-slowness-of-human-behavior
Here’s a link to the actual paper (paywall): https://www.cell.com/neuron/abstract/S0896-6273(24)00808-0
Here’s a link to a preprint: https://arxiv.org/abs/2408.10234
We don’t think in “bits” at all because our brain functions nothing like a computer. This entire premise is stupid.
Bit in this context refers to the [Shannon](https://en.wikipedia.org/wiki/Shannon_(unit\)) from information theory. 1 bit of information (that is, 1 shannon) is the amount of information you receive from observing an event with a 50% chance of occurring. 10 bits would be equivalent to the amount of information learned from observing an event with about a 0.1% chance of occurring. So 10 bits in this context is actually not that small of a number.
The paper gives specific numbers for specific contexts, too. It’s a helpful illustration for these concepts:
A 3x3 Rubik’s cube has 2^65 possible permutations, so the configuration of a Rubik’s cube is about 65 bits of information. The world record for blind solving, where the solver examines the cube, puts on a blindfold, and solves it blindfolded, had someone examining the cube for 5.5 seconds, so the 65 bits were acquired at a rate of 11.8 bits/s.
Another memory contest has people memorizing strings of binary digits for 5 minutes and trying to recall them. The world record is 1467 digits, exactly 1467 bits, and dividing by 5 minutes or 300 seconds, for a rate of 4.9 bits/s.
The paper doesn’t talk about how the human brain is more optimized for some tasks over others, and I definitely believe that the human brain’s capacity for visual processing, probably assisted through the preprocessing that happens subconsciously, or the direct perception of visual information, is much more efficient and capable than plain memorization. So I’m still skeptical of the blanket 10-bit rate for all types of thinking, but I can see how they got the number.
Their model seems to be heavily focused on visual observation and conscious problem solving, which ignores all the other things the brain is doing at the same time: keeping the body alive, processing emotions, maintaining homeostasis for several systems, etc.
These all require interpreting and sending information from/to other organs, and most of it is subconscious.
It’s a fair metric IMO.
We typically judge super computers in FLOPS, floating-point-operations/sec.
We don’t take into account any of the compute power required to keep it powered, keep it cool, operate peripherals, etc., even if that is happening in the background. Heck, FLOPs doesn’t even really measure memory, storage, power, number of cores, clock speed, architecture, or any other useful attributes of a computer.
This is just one metric.
10 shannons, that is, 10 bits, each with 50% probability would be equivalent to the amount of information gained from observing an event with 1/1024 chance of occurring, not 1/10. Thats because this unit gets combined multiplicatively. The wikipedia article mentions that if there are 8 possible events with equal probability, the information content would be 3 shannons.
Right, 1/1024 is 0.0009765625 or about 0.1%.
Also supposing it did, I’m quite sure that everyone’s brain would function at different rates. And how do you even measure those people that don’t have an internal monologue? Seems like there is a lot missing here.
It’s an average. The difference between two humans will be much less than the difference between humans and machines.
Because it’s a Techspot article, of course they deliberately confuse you as to what “bit” means to get views. https://en.wikipedia.org/wiki/Entropy_(information_theory) seems like a good introduction to what “bit” actually means.
That is a fair criticism.
ITT: A bunch of people who have never heard of information theory suddenly have very strong feelings about it.
If they had heard of it, we’d probably get statements like: “It’s just statistics.” or “It’s not information. It’s just a probability.”
Some parts of the paper are available here: https://www.sciencedirect.com/science/article/abs/pii/S0896627324008080?via%3Dihub
It doesn’t look like these “bits” are binary, but “pieces of information” (which I find a bit misleading):
“Quick, think of a thing… Now I’ll guess that thing by asking you yes/no questions.” The game “Twenty Questions” has been popular for centuries as a thinking challenge. 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 million possible items in the few seconds allotted. Therefore, the speed of thinking—with no constraints imposed—corresponds to 20 bits of information over a few seconds: a rate of 10 bits/s or less.
The authors do draw a distinction between the sensory processing and cognition/decision-making, at least:
To reiterate: human behaviors, including motor function, perception, and cognition, operate at a speed limit of 10 bit/s. At the same time, single neurons can transmit information at that same rate or faster. Furthermore, some portions of our brain, such as the peripheral sensory regions, clearly process information dramatically faster.
But our brains are not digital, so they cannot be measured in binary bits.
There is no other definition of bit that is valid in a scientific context. Bit literally means “binary digit”.
Information theory, using bits, is applied to the workings of the brain all the time.
How do you know there is no other definition of bit that is valid in a scientific context? Are you saying a word can’t have a different meaning in a different field of science?
Because actual neuroscientists understand and use information theory.
Actual neuroscientists define their terms in their papers. Like the one you refuse to read because you’ve already decided it’s wrong.
Actual neuroscientists do not create false definitions for well defined terms. And they absolutely do not need to define basic, unambiguous terminology to be able to use it.
Please define ‘bit’ in neuroscientific terms.
All information can be stored in a digital form, and all information can be measured in base 2 units (of bits).
But it isn’t stored that way and it isn’t processed that way. The preprint appears to give an equation (beyond my ability to understand) which explains how they came up with it.
Your initial claim was that they couldn’t be measured that way. You’re right that they aren’t stored as bits, but it’s irrelevant to whether you can measure them using bits as the unit of information size.
Think of it like this: in the 1980s there were breathless articles about CD ROM technology, and how, in the future, “the entire encyclopedia Britannica could be stored on one disc”. How was that possible to know? Encyclopedias were not digitally stored! You can’t measure them in bits!
It’s possible because you could define a hypothetical analog to digital encoder, and then quantify how many bits coming off that encoder would be needed to store the entire corpus.
This is the same thing. You can ADC anything, and the spec on your ADC defines the bitrate you need to store the stream coming off… in bits (per second)
As has been shown elsewhere in this thread by Aatube a couple of times, they are not defining ‘bit’ the way you are defining it, but still in a valid way.
Indeed not. So using language specific to binary systems - e.g. bits per second - is not appropriate in this context.
So ten concepts per second? Ten ideas per second? This sounds a little more reasonable. I guess you have to read the word “bit” like you’re British, and it just means “part.” Of course this is still miserably badly defined.
Here’s a link to Caltech’s press release: https://www.caltech.edu/about/news/thinking-slowly-the-paradoxical-slowness-of-human-behavior
Here’s a link to the actual paper (paywall): https://www.cell.com/neuron/abstract/S0896-6273(24)00808-0
Here’s a link to a preprint: https://arxiv.org/abs/2408.10234
Thank you! I’ll add these to the body.
Edit: Never mind, it doesn’t seem to want to let me save. Oh well.
Edit 2: Weird, it did when I tried it again, so thanks!
“They also explain why we can only think one thought at a time”
I know a lot of people who would disagree with that
They would be incorrect, as this neuroscientist explains: https://drsarahmckay.com/the-myth-of-multi-tasking/
deleted by creator
i can agree at some extent why it could be at 10bits/sec.
the brain is known to do some shortcuts when parsing/speed reading but slows down when we try to extract details from written works. it is also more tiring to scrutinize details than to just read articles.
i was surprised that they got the speed measured.
The Caltech release says they derived it from “a vast amount of scientific literature” including studies of how people read and write. I think the key is going to be how they derived that number from existing studies.
In fact, the 10 bits per second are needed only in worst-case situations, and most of the time our environment changes at a much more leisurely pace."
Bruh some tech pro is going to read this and interpret this in a terrible fashion but then again humans already change our environment.
what
So the article is going with humans only think as fast because evolution determines this speed was sufficient. So if i was highly misguided individual wanting to up the average human speed we need to create an environment where there is a need to process data faster. Sounds like a horror cyber punk but in reality human progress is super fast now relative to 10k years ago. So the change may happen naturally.
Oh, you have the full text of the paper?? Please share it! We’d like to read it for ourselves.
Yet, it takes an enormous amount of processing power to produce a comment such as this one. How much would it take to reason why the experiment was structured as it was?
Information theory is all about cutting through the waste of a given computation to compare apples to apples.
I’ll replicate an example I posted elsewhere:
Let’s say I make a machine that sums two numbers between 0-127, and returns the output. Let’s say this machine also only understands spoken French. According to information theory, this machine receives 14 bits of information (two 7-bit numbers with equal probability for all values) and returns 8 bits of information. The fact that it understands spoken French is irrelevant to the computation and is ignored.
That’s the same line of reasoning here, and the article makes this clear by indicating that brains take in billions of bits of sensory data. But they’re not looking at overall processing power, they’re looking at cognition, or active thought. Performing a given computational task is about 10 bits/s, which is completely separate from the billions of bits per second of background processing we do.
A lion sucks if measured as a bird.
I could believe that we take 10 decisions based on pre-learned information per second, but we must be able to ingest new information at a much quicker rate.
I mean: look at an image for a second. Can you only remember 10 things about it?
It’s hard to speculate on such a short and undoubtedly watered down, press summary. You’d have to read the paper to get the full nuance.
I mean: look at an image for a second. Can you only remember 10 things about it?
The paper actually talks about the winners of memory championships (memorizing random strings of numbers or the precise order of a random arrangement of a 52-card deck). The winners tend to have to study the information for an amount of time roughly equivalent to 10 bits per second.
It even talks about the guy who was given a 45 minute helicopter ride over Rome and asked to draw the buildings from memory. He made certain mistakes, showing that he essentially memorized the positions and architectural styles of 1000 buildings chosen out of 1000 possibilities, for an effective bit rate of 4 bits/s.
That experience suggests that we may compress our knowledge by taking shortcuts, some of which are inaccurate. It’s much easier to memorize details in a picture where everything looks normal, than it is to memorize details about a random assortment of shapes and colors.
So even if I can name 10 things about a picture, it might be that those 10 things aren’t sufficiently independent from one another to represent 10 bits of entropy.
I didn’t see any point in linking to the paper since you have to pay to access it, but here you go if you want to do that:
Send the DOI to a science nexus search bot on Telegram and you’ll get the paper.
10 bits means 2^(10) = 1024 different things can be encoded.
Yes thank you. I know how binary works!
I was responding to “Look at an image for a second. Can you only remember 10 things about it?” I didn’t think that was a fair characterization. I see you probably specifically meant 10 yes/no questions about an image, but I don’t think yes/no questions are a fair proxy for “things”.
In any case you can read the preprint here https://arxiv.org/abs/2408.10234v2 and they make it immediately clear that 10 bits/s is an order-of-magnitude estimate, and also specifically list (for example) object recognition at 30-50 bits/s.
Sure, that’s what I meant with the nuance missing from the press release.
It depends what/how is being encoded in those 10 bits.
A decision tree was just one example.
Thanks for the link.
Crazy how a biological analog lump is capable of even a fraction of what a brain can do.
Caltech article: https://www.caltech.edu/about/news/thinking-slowly-the-paradoxical-slowness-of-human-behavior
The full text of the paper costs $35 to read once.
“Look, I made a really exciting controversial discovery! It’s really emotional and intriguing! You’re missing out! Only smart rich people can read it! Put your money in the basket please :)” Our education system is dead the the populace is too stupid to care.
The educational system isn’t setting the prices. The publishers are separate private enterprises which are mostly profit-driven.
In the last 20 years, “open access” journals have been created where the author (author’s grant money, mostly from the government) pays the charges instead of the readers. That has led to a whole slew of other problems including predatory and phony journals springing up.
author’s grant money, mostly from the government, paid for by tax dollars, by US citizens, as part of taxes attributed to education and healthcare. yaaaaaaaawn.
