The actual paper [1] says that functional MRI (which is measuring which parts of the brain are active by sensing blood flow) indicates that different brain hardware is used for non-language and language functions. This has been suspected for years, but now there's an experimental result.
What this tells us for AI is that we need something else besides LLMs. It's not clear what that something else is. But, as the paper mentions, the low-end mammals and the corvids lack language but have some substantial problem-solving capability. That's seen down at squirrel and crow size, where the brains are tiny. So if someone figures out to do this, it will probably take less hardware than an LLM.
This is the next big piece we need for AI. No idea how to do this, but it's the right question to work on.
[1] https://www.nature.com/articles/s41586-024-07522-w.epdf?shar...
When the first chess engines came out they only employed one of these: calculation. It wasn't until relatively recently that we had computer programs that could perform all of them. But it turns out that if you scale that up with enough compute you can achieve superhuman results with calculation alone.
It's not clear to me that LLMs sufficiently scaled won't achieve superhuman performance on general cognitive tasks even if there are things humans do which they can't.
The other thing I'd point out is that all language is essentially synthetic training data. Humans invented language as a way to transfer their internal thought processes to other humans. It makes sense that the process of thinking and the process of translating those thoughts into and out of language would be distinct.
After all, that's what Artificial General Intelligence would at least in part be about: finding and proving new math theorems, creating new poetry, making new scientific discoveries, etc.
There is even a new challenge that's been proposed: https://arcprize.org/blog/launch
> It makes sense that the process of thinking and the process of translating those thoughts into and out of language would be distinct
Yes, indeed. And LLMs seem to be very good at _simulating_ the translation of thought into language. They don't actually do it, at least not like humans do.
If "general cognitive tasks" means "I give you a prompt in some form, and you give me an incredible response of some form " (forms may differ or be the same) then it is hard to disagree with you.
But if by "general cognitive task" you mean "all the cognitive things that human do", then it is really hard to see why you would have any confidence that LLMs have any hope of achieving superhuman performance at these things.
To some extent this is true.
To calculate A + B you could for example generate A, B for trillions of combinations and encode that within the network. And it would calculate this faster than any human could.
But that's not intelligence. And Apple's research showed that LLMs are simply inferring relationships based on the tokens it has access to. Which you can throw off by adding useless information or trying to abstract A + B.
Solving puzzles is a specific cognitive task, not a general one.
Language is a continuum, not a puzzle. The problem with LLMs is that testing has been reduced to performance on language puzzles, mostly with hard edges - like bar exams, or letter counting - and they're a small subset of general language use.
When it comes to general intelligence, I think we are trying to run before we can walk. We can't even make a computer with a basic, animal level understanding of the world. Yet we are trying to take a tool that was developed on top of system that already had an understanding of the world and use it to work backwards to give computers an understanding of the world.
I'm pretty skeptical that we're going to succeed at this. I think you have to be able to teach a computer to climb a tree or hunt (subhuman AGI) before you can create superhuman AGI.
https://arstechnica.com/ai/2024/10/llms-cant-perform-genuine...
or do you maybe think no logical reasoning is needed to do everything a human can do? Tho humans seem to be able to do logical reasoning
Then LLMs came along, and ML folks got rather too excited that they contain implicit knowledge (which, of course, is required to deal with ambiguity). Then the new aspiration as "all in one" and "bigger is better", not analyzing what components are needed and how to orchestrate their interplay.
From an engineering (rather than science) point of view, the "end-to-end black box" approach is perhaps misguided, because the result will be a non-transparent system by definition. Individual sub-models should be connected in a way that retains control (e.g. in dialog agents, SRI's Open Agent Architecture was a random example of such "glue" to tie components together, to name but one).
Regarding the science, I do believe language adds to the power of thinking; while (other) animals can of course solve simple problems without language, language permits us to define layers of abstractions (by defining and sharing new concepts) that goes beyond simple, non-linguistic thoughts. Programming languages (created by us humans somewhat in the image of human language) and the language of mathematics are two examples where we push this even further (beyond the definition of new named concepts, to also define new "DSL" syntax) - but all of these could not come into beying without human language: all formal specs and all axioms are ultimately and can only be formulated in human language. So without language, we would likely be stuck at a very simple point of development, individually and collectively.
EDIT: 2 typos fixed
Based on my experience with toddlers, a rather smart dog, and my own thought processes, I disagree that language is a fundamental component of abstraction. Of sharing abstractions, sure, but not developing them.
When I'm designing a software system I will have a mental conception of the system as layered abstractions before I have a name for any component. I invent names for these components in order to define them in the code or communicate them to other engineers, but the intuition for the abstraction comes first. This is why "naming things" is one of the hard problems in computer science—because the name comes second as a usually-inadequate attempt to capture the abstraction in language.
In my personal learning journey I have been exploring the space of intuitive learning which is dominant in physical skills. Singing requires extremely precise control of actions we can't fully articulate or even rationalise. Teaching those skills requires metaphors and visualising and a whole lot of feedback + trial & error.
I believe that this kind of learning is fundamentally non verbal and we can achieve abstraction of these skills without language. Walking is the most universal of these skills and we learn it before we can speak but if you study it (or better try to program a robot to walk with as many degrees of freedom as the human musculoskeletal system) you will discover that almost all of us don't understand what all the things that go into the "simple" task of walking!
My understanding is that people who are gifted at sports or other physical skills like musical instruments have developed the ability to discover and embed these non verbal abstractions quickly. When I practise the piano and am working on something fast, playing semiquavers at anything above 120bpm is not really conscious anymore in the sense of "press this key then that key"
The concept of arpeggio is verbal but the action is non verbal. In human thought where does verbal and non-verbal start and end? Its probably a continuum
A black box that works in human language and can be investigated with perturbations, embedding visualizations and probes. It explains itself as much ore more than we can.
Not to over-hype LLMs, but I don't see why this results says this. AI doesn't need to do things the same way as evolved intelligence has.
Open AI O1 seems to be trained on mostly synthetic data, but it makes intuitive sense that LLMs work so well because we had the data lying around already.
Similar reason we look for markers of Earth-based life on alien planets: it's the only example we've got of it existing.
An Ab Initio AGI would maybe be free of our legacy, but LLMs certainly are not.
I would expect a ship-like intelligence a la the Culture novels to have non-English based cognition. As far as we can tell, our own language generation is post-hoc explanation for thought more so than the embodiment of thought.
for more, see "Assembly Theory"
LLMs basically become practical when you simply scale compute up, and maybe both regions are "general compute", but language ends up on the "GPU" out of pure necessity.
So to me, these are entirely distinct questions: is the language region able to do general cognitive operations? What happens when you need to spell out "ubiquitous" or declense a foreign word in a language with declension (which you don't have memory patterns for)?
I agree it seems obvious that for better efficiency (size of training data, parameter count, compute ability), human brains use different approach than LLMs today (in a sibling comment, I bring up an example of my kids at 2yo having a better grasp of language rules than ChatGPT with 100x more training data).
But let's dive deeper in understanding what each of these regions can do before we decide to compare to or apply stuff from AI/CS.
No this is not true. For two reasons.
1. We call these things LLMs and we train it with language but we can also train it with images.
2. We also know LLMs develop a sort of understanding that goes beyond language EVEN when the medium used for training is exclusively language.
The naming of LLMs is throwing you off. You can call it a Large Language Model but this does not mean that everything about LLMs are exclusively tied only to language.
Additionally we don't even know if the LLM is even remotely similar to the way human brains process language.
No such conclusion can be drawn from this experiment.
A crow has a small brain, but also has very small neurons, so ends up having 1.5B neurons, similar to a dog or some monkeys.
The absence of both of these things is an incredible crippler for technological development. It doesn't matter how intelligent you are, you're never going to achieve much technologically without these.
I don't think brain size correlations is as straightforward as 'bigger = better' every time but we simply don't know how intelligent most of these species are. Land and Water are completely different beasts.
And it turns out that human brain volume and intelligence are moderately-highly correlated [1][2]!
[1]: https://pmc.ncbi.nlm.nih.gov/articles/PMC7440690/ [2]: https://www.sciencedirect.com/science/article/abs/pii/S01602...
https://www.scientificamerican.com/article/gut-second-brain/
There are 100 million in my gut, but it doesn't solve any problems that aren't about poop, as far as I know.
https://en.wikipedia.org/wiki/List_of_animals_by_number_of_n...
If the suspiciously round number is accurate, this puts the human gut somewhere between a golden hamster and ansell's mole-rat, and about level with a short-palated fruit bat.
On the other hand, further understanding how to engage complex cognitive processes in nonverbal individuals is extremely useful and difficult to accomplish.
All intelligence is the mitigation of uncertainty (the potential distributed problem.) if it does not mitigate uncertainty it is not intelligence, it is something else.
Intelligence is a technology. For all life intelligence and the infrastructure of performing work efficiently (that whole entropy thing again) is a technology. Life is an arms race to maintain continuity (identity, and the very capacity of existential being.)
The modern problem is achieving reliable behavioral intelligence (constrained to a specific problem domain.) AGI is a phantasm. What manifestation of intelligence appears whole and complete and is always right? These are the sorts of lies you tell yourself, the ones that get you into trouble. They distract from tangible real world problems, perhaps causing some of them. True intelligence is a well calibrated “scalar” domain specific problem (uncertainty) reducer. There are few pressing idempotent obstructions in the real world.
Intelligence is the mitigation of uncertainty.
Uncertainty is the domain of negative potential (what,where,why,how?)
Mitigation is the determinant resolve of any constructive or destructive interference affecting (terminal resolve within) the problem domain.
Examples of this may be piled together mountains high, and you may call that functional AGI, though you would be self deceiving. At some point “good enough” may be declared for anything so passing as yourselves.
Basically we need Multimodal LLM's (terrible naming as it's not an LLM then but still).
There's been progress. Look at this 2020 work on neural net controlled drone acrobatics.[1] That's going in the right direction.
I’d be extremely surprised if AI recapitulates the same developmental path as humans did; evolution vs. next-token prediction on an existing corpus are completely different objective functions and loss landscapes.
I then looked it up and they had each copy/pasted the same Stack overflow answer.
Furthermore, the answer was extremely wrong, the language I used was superficially similar to the source material, but the programming concepts were entirely different.
What this tells me is there is clearly no “reasoning” happening whatsoever with either model, despite marketing claiming as such.
Stepping back a level, it may only actually tell us that MRIs measure blood flow.
> Recent work has revealed that the neural activity patterns correlated with sensation, cognition, and action often are not stable and instead undergo large scale changes over days and weeks—a phenomenon called representational drift.
[...]
So, I'm not sure how conclusive this fmri activation study is either.
Though, is there a proto language that's not even necessary for the given measured aspects of condition?
Which artificial network architecture best approximates which functionally specialized biological neutral networks?
OpenCogPrime:KnowledgeRepresentation > Four Types of Knowledge: https://wiki.opencog.org/w/OpenCogPrime:KnowledgeRepresentat... :
> Sensory, Procedural, Episodic, Declarative
From https://news.ycombinator.com/item?id=40105068#40107537 re: cognitive hierarchy and specialization :
> But FWIU none of these models of cognitive hierarchy or instruction are informed by newer developments in topological study of neural connectivity;
ultimately, there's no reason that a general algorithm couldn't do the job of a specific one, just less efficiently.
An easy conclusion to jump to but I believe we need to be more careful. Nothing in these findings proves conclusively that non-verbal reasoning mechanism equivalent to humans couldn't evolve in some part of a sufficiently large ANN trained on text and math. Even though verbal and non-verbal reasoning occurs in two distinct parts of the brain, it doesn't mean they're not related.
You mean besides a few layers of LLMs near input and output that deal with tokens? We have the rest of the layers.
1. Syntax
2. Semantics
3. Pragmatics
4. Semiotics
These are the layers you need to solve.
Saussure already pointed out these issues over a century ago, and Linguists turned ML Researchers like Stuart Russell and Paul Smolensky tried in vain to resolve this.
It basically took 60 years just to crack syntax at scale, and the other layers are still fairly far away.
Furthermore, Syntax is not a solved problem yet in most languages.
Try communicating with GPT-4o in colloquial Bhojpuri, Koshur, or Dogri, let alone much less represented languages and dialects.
Higher order faculties aside, animals seem like us, just simpler.
The higher functioning ones appear to have this missing thing too. We can see it in action. Perhaps all of them do and it is just harder for us when the animal thinks very differently or maybe does not think as much, feeling more, for example.
----
Now, about that thing... and the controversy:
Given an organism, or machine for this discussion, is of sufficiently robust design and complexity that it can precisely differentiate itself from everything else, it is a being.
This thing we are missing is an emergent property, or artifact that can or maybe always does present when a state of being also presents.
We have not created a machine of this degree yet.
Mother nature has.
The reason for emergence is a being can differentiate sensory input as being from within, such as pain, or touch, and from without, such as light or motion.
Another way to express this is closed loop vs open loop.
A being is a closed loop system. It can experience cause and effect. It can be the cause. It can be the effect.
A lot comes from this closed loop.
There can be the concept of the self and it has real meaning due to the being knowing what is of itself or something, everything else.
This may be what forms consciousness. Consciousness may require a closed loop, and organism of sufficient complexity to be able to perceive itself.
That is the gist of it.
These systems we make are fantastic pieces. They can pattern match and identify relationships between the data given in amazing ways.
But they are open loop. They are not beings. They cannot determine what is part of them, what they even are,or anything really.
I am both consistently amazed and dismayed at what we can get LLM systems to do.
They are tantalizingly close!
We found a piece of how all this works and we are exploiting the cral out of it. Ok fine. Humans are really good at that.
But it will all taper off. There are real limits because we will eventually find the end goal will be to map out the whole problem space.
Who has tried computing that? It is basically all possible human thought. Not going to happen.
More is needed.
And that "more" can arrive at thoughts without having first seen a few bazillion to choose from.
An example was the problem of memory shared between systems. ML people started doing LLM’s with RAG. I looked into neuroscience which suggested we need a hippocampus model. I found several papers with hippocampus-like models. Combining LLM’s, vision, etc with hippocampus-like model might get better results. Rinse repeat for these other brain areas wherever we can understand them.
I also agree on testing the architectures with small, animal brains. Many do impressive behaviors that we should be able to recreate in simulators or with robotics. Some are useful, too, like how geese are good at security. Maybe embed a trained, goose brain into a camera system.
I am not convinced it follows. Sure LLMs don’t seem complete however there’s a lot of unspoken inference going on in LLMs that don’t map into a language directly already - the inner layers of the deep neural net that operates on abstract neurons.
Perhaps, but the relative success of trained LLMs acting with apparent generalised understanding may indicate that it is simply the interface that is really an LLM post training;
That the deeper into the network you go (the further from the linguistic context), the less things become about words and linguist structure specifically and the more it becomes about things and relations in general.
(This also means that multiple interfaces can be integrated, sometimes making translation possible, e.g.: image <=> tree<string>)
We have, it's called DreamCoder. There's a paper and everything.
Everything needed for AGI exists today, people simply have (incorrect) legacy beliefs about cognition that are holding them back (e.g. "humans are rational").
Despite being an LLM skeptic of sorts, I don’t think that necessarily follows. The LLM matrix multiplication machinery may well be implementing an equivalent of the human non-language cognitive processing as a side effect of the training. Meaning, what is separated in the human brain may be mixed together in an LLM.
You would think the whole "split-brain" thing would have been the first clue; apparently not.
We need to add the 5 senses, of which we have now image, audio and video understanding in LLMs. And for agentic behavior they need environments and social exposure.
Humans not taking this approach doesn’t mean that AI cannot.
And yeah it seems that core primitives of intelligence exist very low in our brains. And with people like Michael Levin, there may even be a root beside nervous systems.
Spoiler alert: brains require a lot of blood, constantly, just to not die. Looking at blood flow on an MRI to determine neural circuitry has to deal with the double whammy of both an extremely crude tool and a correlation/causation fallacy.
This article and the study are arguably useless.
I used to rationalize to myself along similar lines for a long time, then I realized that I'm just not as smart as I thought I was.
I'm brilliant - I've read volumes of encyclopedias, my hobbies include comparative theology, etymology, quantum mechanics and predicting the future with high accuracy (I only mention stuff I'm certain of tho ;) but so much so it disturbs my friends and family.
The highest I scored was in the 160s as a teenager but I truly believe they were over compensating for my age - only as an adult have I learned most children are stupid and they maybe in fact didn't over compensate. I am different than anyone else I've ever personally met - I fundamentally see the world different.
All of that is true but that's a rather flawed way of assessing intelligence - fr. I'm being serious. The things we know can free us as much as they can trap us - knowledge alone doesn't make a man successful, wealthy, happy or even healthy - I'm living evidence of this. That doesn't cut it as a metric for prediction of much. There are other qualities that are far more valuable in the societal sense.
Every Boss I've ever worked for has been dumber than me - each one I've learned invaluable stuff from. I was a boss once - in my day I owned and self taught/created an entire social network much like FB was a few years ago, mine obviously didn't take off and now I'm a very capable bum. Maybe someday something I'm tinkering with will make me millions but prolly not, for many reasons, I could write books if I wanted ;)
At the end of the day, the facts are what they are - there is an optimal level of intelligence that is obviously higher than the bottom but is nowhere near the top tier, very likely near that 100 IQ baseline. What separates us all is our capabilities - mostly stuff we can directly control, like learning a trade.
A Master Plumber is a genius plumber by another name and that can and obviously is most often, learned genius. What you sus about yourself is truth - don't doubt that. No IQ test ever told me I lacked the tenacity of the C average student that would employ me someday - they can't actually measure the extent of our dedicated capacity.
I kno more than most people ever have before or rn presently - I don't know as much about plumbing as an apprentice with 2 years of a trade school dedicated to plumbing and a year or two of experience in the field, that's the reality of it. I could learn the trade - I could learn most every trade, but I won't. That's life. I can tell you how you the ancients plumbed bc that piqued my curiosity and I kno far more about Roman plumbing than I do how a modern city sewer system works. That's also life.
It isn't what we kno or how fast we can learn it - it's what we do that defines us.
Become more capable if you feel looked down on - this is the way bc even if what you hone your capabilities of can be replicated by others most won't even try.
That's my rant about this whole intelligence perception we currently have as a society. Having 100 IQ is nowhere near the barrier that having 150 IQ is.
Rant aside, to the article - how isn't this obvious? I mean feelings literally exist - not just the warm fuzzy ones, like the literal feeling of existence. Does a monkey's mind require words to interpret pain or pleasure for example. Do I need to know what "fire" or "hot" is in a verbal context to sufficiently understand "burn" - words exists to convey to to others what doesn't need to be conveyed to us. That's their function. Communication. To facilitate communication with our social brethren we adopt them fundamentally as our Lego blocks for understanding the world - we pretend that words comprising language are the ideas themselves. A banana is a - the word is the fruit, they are the same in our minds but if I erase the word banana and all it's meaning of the fruit and I randomly encounter a banana - I still can taste it. No words necessary.
Also, you can think without words, deliberately and consciously - even absentmindedly.
And LLMs can't reason ;)
Truthfully, the reality is that a 100 IQ normal human is far more capable than any AI I've been given access to - in almost every metric I attempted to asses I ultimately didn't even bother as it was so obvious that humans are functionally superior.
When AI can reason - you, and everyone else, will kno it. It will be self evident.
Anyways, tldr: ppl are smarter than given credit for, smarter and much more capable - IQ is real and matters but far less than we are led to believe. People are awesome - the epitome of biological life on Earth and we do a lot of amazing things and anyone can be amazing.
I hate it when the Hacker News collective belittles itself - don't do that. I rant here bc it's one of the most interesting places I've found and I care about what all of you think far more than I care about your IQ scores.
The abstract visualizations I could build in my mind where comparable to semi-transparent buildings that I could freely spin, navigate and bend to connect relations.
In my mid-twenties, someone introduced me to the concept of people using words for mental processes, which was completely foreign to me up to this point.
For some reason, this made my brain move more and more towards this language-based model and at the same time, I felt like I was losing the capacity for complex abstract thoughts.
Still to this day I (unsuccessfully) try to revive this and unlearn the language in my head, which feels like it imposes a huge barrier and limits my mental capacity to the capabilities of what the language my brain uses at the given time (mostly EN, partially DE) allows to express.
I think that I ultimately developed an obsessive need to cite all my ideas against the literature and formulate natural language arguments for my claims to avoid being bludgeoned over the head with wordcelry and being seen as inferior for my lesser verbal fluency despite having written software for years at that point, since early childhood, and even studied computer science.
Basically what to most people is so obvious that it becomes transparent ("air") isn't to us, which apparently is an incredible gift for becoming a language researcher. Or a programmer.
It seems more like a complement to it: the idea arises, and then I have this compulsion to verbalise it, which gets quite frustrating as it takes several iterations. Clearly words do matter to me as a way to structure and record my ideas but there is something that pre-empts verbalisation and to some extent resists it.
I cannot provide insight on how I arrive at ideas. Even when I did literary criticism, the best I can say is that I absorbed lots of text and then suddenly a pattern would spring out. But the same things would happen for me studying maths or the hard sciences.
Software engineering is actually a bit different for me because I am not naturally a good algorithmic problem solver. Really I am somebody very passionate about computing who has a near-compulsion to see and collect more and more technology. So for me it is as simple as saying "this resembles a reader monad" or "this puns on the active record pattern". Less impressive than my humanities intelligence but worth maybe 10x the amount in the labour market :-)
This begs a question though: Since programming is mostly done with language - admittedly primitive/pidgin ones - why isn't that a struggle? Not sure if you're a programmer yourself, but if so do you prefer certain programming languages for some sense of "less-verbalness" or does it even matter?
Just wondering, not attacking your claim per se.
Parent isn't saying they can't handle language (and we wouldn't have this discussion in the first place), just that they better handle complexity and structure in non verbal ways.
To get back to programming, I think this do apply to most of us. Most of us probably don't think in ruby or JS, we have a higher vision of what we want to build and "flatten" it into words that can be parsed and executed. It's of course more obvious for people writing in say basic or assembly, some conversion has to happen at some point.
> The dog's owner's house's roof's angle's similarity to an equilateral triangle is remarkable.
I very strongly suspect that you're overestimating yourself.
I spent the next few days trying to understand how that process worked. I would force myself to think in words and sentences. It was incredibly limiting! So slow and lacking in images, in abstract relationships between ideas and sensations.
It took me another few years to realise that many people actually depend on those structures in order to produce any thought and idea.
Also, many people simply repeat facts they were told. "We need words to think" is simply a phrase this person learned, a fact to recite in school settings. It doesn't mean they deeply reflected on this statement or compared it with their experience.
Try it now: Tap your hand on the desk randomly. Can you recall how many times you did it without "saying" a sequence in your head like "1, 2, 3" or "A, B, C" etc?
If yes, how far can you count? With a language it's effectively infinite. You could theoretically go up to "1 million 5 hundred 43 thousand, 2 hundred and 10" and effortlessly know what comes next.
For context I have both abstract "multimedia" thought processes and hypervisor-like internal narrative depending on the nature of the experience or task.
If I want to translate this knowledge into a number, I need to count the taps I am seeing in my head. At that point I do need to think of the word for the number.
I could even do computations on these items in my mind, imagine dividing them into two groups for instance, without ever having to link them to words until I am ready to do something with the result, such as write down the number of items in each group.
An example of this would be when I’m lifting weights with a friend and am lost in the set/focusing on mind-muscle connection, and as a result I forget to count my reps. I am usually quite accurate when I verify with my lifting partner the number of reps done/remaining.
As OP mentioned, many people have no internal speech, otherwise known as anendophasia, yet can still do everything anyone with an internal dialogue can do.
Similarly for me, I can do “mental object rotation” tasks even though I have aphantasia.
I would note though I have a really difficult time with arithmetic and mechanical tasks like counting. Mostly I just lose attention. Perhaps an inner voice would help if it became something that kept a continuity of thought.
This is a parallel stream, because if I count with imagined pictures, then I can speak and listen to someone talking without it disturbing the process. If I do it with subvocalization, then doing other speech/language related things would disturb the counting.
Other animals with at best very limited language, are still highly intelligent and capable of reasoning - apes, dogs, rats, crows, ...
They should start with what is their definition of language. To me it's any mean you can use to communicate some information to someone else and they generally get a correct inference of what kind of representations and responses are expected is the definition of a language. Whether it's uttered words, a series of gestures, subtle pheromones or a slap in your face, that's all languages.
For the same reason I find extremely odd that the hypothesis that animals don't have any form of language is even considered as a serious claim in introduction.
Anyone can prove anything and its contrary about language if the term is given whatever meaning is needed for premises to match with the conclusion.
Should we expect experts in cognitive science exposing their view in a scientific publication to stick to the narrowest median view of language though? All the more when in the same article you quote people like Russell who certainly didn't have a naïve definition of language when expressing a point of view on the matter.
And slapping in general can definitely communicate far more than a single thing depending on many parameters. See https://www.33rdsquare.com/is-a-slap-disrespectful-a-nuanced... for a text exploring some of nuances of the meaning it can encompasse. But even a kid can get that slap could perfectly have all the potential to create a fully doubly articulated language, as The Croods 2 creators funnily have put in scene. :D
Even tools present us a certain 'language', talking to us via beeps, blinks and buzzes, and are having increasingly interesting discussions amongst themselves (e.g. subreddit simulator, agent based modeling). Recent philosophers of technology as Mark Coeckelbergh present a comprehensive argument for why we need to move away from the tool/language barrier [0], and has been part in informing the EC Expert Group on AI [1].
[0]: https://www.taylorfrancis.com/books/mono/10.4324/97813155285...
[1]: https://philtech.univie.ac.at/news/news-about-publicatons-et...
> Do any forms of thought—our knowledge of the world and ability to reason over these knowledge representations—require language (that is, representations and computations that sup-port our ability to generate and interpret meaningfully structured word sequences)?
Emphasis on "word sequences," to the exclusion of, e.g. body language or sign language. They go on to discuss some of the brain structures involved in the production and interpretation of these word sequences:
> Language production and language understanding are sup-ported by an interconnected set of brain areas in the left hemisphere, often referred to as the ‘language network'.
It is these brain areas that form the basis of their testable claims regarding language.
> Anyone can prove anything and its contrary about language if the term is given whatever meaning is needed for premises to match with the conclusion.
This is why "coming to terms" on the definitions of words and what you mean by them should be the first step in any serious discussion if you aim to have any hope in hell of communicating precisely; it is also why you should be skeptical of political actors that insist on redefining the meanings of (especially well-known) terms in order to push an agenda. Confusing a term with its actual referent is exceedingly commonplace in modern day.
Think about it: almost every nontrivial conversation you’ve had or comment/blog/article/book you’ve read constituted an entirely new (to you) utterance which you understood and which enabled you to acquire new ideas and information you had previously lacked. No non-human animals have demonstrated this ability. At best they are able to perform single-symbol utterances to communicate previously-understood concepts (hungry, sad, scared, tired) but are unable to combine them to produce a novel utterance, the way a child could tell you about her day:
“Today the teacher asked me to multiply 3 times 7 and I got the answer right away! Then Bobby farted and the whole class was laughing. At lunch I bit my apple and my tooth felt funny. I think it’s starting to wiggle! Sally asked me if I could go to her house for a sleepover but I said I had to ask mom and dad first.”
We maybe disagree, in the sense that it seems to be mixing indefinitely bounded expressiveness with actual unlimited expression production that could potentially be in a bijective relationship with the an infinite set of expression.
We human are mortals and even at the whole humankind scale, we will produce a finite set of utterances.
The main thing bringing so much flexibility to languages, is our ability to reuse, fit and evolve them as we go through indefinitely many inedit experiences of the world. So something like context change tolerance. But if we want to be fair with crediting admirable unknowingly extensive creativeness, we should first consider the universe as a whole, with its permanent flow of novel context, which also include all interpretations of itself through mere mortals as ourself.
I guess I've always just assumed it refers to some feature that's uniquely human—notably, recursive grammars.
And recursion as the unique trait for human language differentiation is not necessarily completely consensual https://omseeth.github.io/blog/2024/recursive_language/
Also, let's recall that in its broader meaning, the scientific consensus is that humans are animals and they evolved through the same basic mechanism as all other life forms that is evolution. So even assuming that evolution made some unique language hability emerge in humans, it's most likely that they share most language traits with other species and that there is more things to learn from them that what would be possible if it's assumed they can't have a language and thoughts.
The claims here are exceptionally limited. You don't need spoken language to do well on cognitive tests, but that has never been a subject of debate. Obviously the deaf get on fine without spoken language. People suffering from aphasia, but still capable of communication via other mechanisms, still do well on cognitive tests. Brain scans show you can do sudoku without increasing bloodflow to language regions.
This kind of stuff has never really been in debate. You can teach plenty of animals to do fine on all sorts of cognitive tasks. There's never been a claim that language holds dominion over all forms of cognition in totality.
But if you want to discuss the themes present in Proust, you're going to be hard pressed to do so without something resembling language. This is self-evident. You cannot ask questions or give answers for subjects you lack the facilities to describe.
tl;dr: Language's purpose is thought, not all thoughts require language
Language's purpose - why it arose - is more likely communication, primarily external communication. The benefit of using language to communicate with yourself via "inner voice" - think in terms of words - seems a secondary benefit, especially considering that less than 50% of people report doing this.
But certainly language, especially when using a large vocabulary of abstract and specialist concepts, does boost cognitive abilities - maybe essentially through "chunking", using words as "thought macros", and boosting what we're able to do with our limited 7+/- item working memory.
Why the introduction of "spoken?" Sign languages are just as expressive as spoken language, and could easily be written. Writing is a sign.
> But if you want to discuss the themes present in Proust, you're going to be hard pressed to do so without something resembling language. This is self-evident.
And it's also a bad example. Of course you can't discuss the use of language without the use of language. You can't discuss the backstroke without any awareness of water or swimming, either. You can certainly do it without language though, just by waving your arms and jumping around.
> Language's purpose is thought
Is it, though? Did you make that case in the preceding paragraphs? I'm not going to go out on a limb here and alternatively suggest that language's purpose is communication, just like the purpose of laughing, crying, hugging, or smiling. This is why we normally do it loudly, or write it down where other people can see it.
We'd better hope that is true, because if we didn't have non-linguistic mastery of the cognitive processes underlying thought it's hard to see how we could even acquire language in the first place.
One must ask why this is such a common occurrence on this (and almost all other) social media, and conclude that it is because the structure of social media itself is rotten and imposes selective pressures that only allow certain kinds of content to thrive.
The actual paper itself is not readily accessible, and properly understanding its claims and conclusions would take substantial time and effort - by which point the article has already slid off the front page, and all the low-effort single-sentence karma grabbers who profit off of simplistic takes that appeal to majority groupthink have already occupied all the comment space "above the fold."
I think this may have been partially substantiated through experiments in decoding thoughts with machine sensors.
If this turns out to-not- to be true it would have huge implications for AI research.
Somewhat relatedly, I've started suspecting over the past few years that this is why I struggle to multitask or split my attention; while I can ruminate on several things at once, the "output" of my thinking is bottlenecked by a single stream that requires me to focus on exclusively to get a anything useful from it. Realizing this has actually helped me quite a bit in terms of being more productive because I can avoid setting myself up for failure by trying to get too much done at once and failing rather than tackling things one at a time.
IMO this rather reinforce Sapir-Whorf positions than refute, it means more than literal language/grammar influence thoughts. That's directly against UG theory that predetermined rigid grammar is all you need.
Serializing much higher dimensional freeform thoughts into language is a very lossy process, and this kinda ensures that mostly only the core bits get translated. Think of times when someone gets an idea you're trying to convey, but you realize they're missing some critical context you forgot to share. It takes some activation energy to add that bit of context, so if it seems like they mostly get what you're saying, you skip it. Over time, transferring ideas from one person to the next, they tend towards a very compressed form because language is expensive.
This process also works on your own thoughts. Thinking out loud performs a similar role, it compresses the hell out of the thought or else it remains inexpressible. Now imagine repeated stages of compressing through language, allowing ideas to form from that compressed form, and then compressing those ideas in turn. It's a bit of a recursive process and language is in the middle of it.
> this kinda ensures that mostly only the core bits get translated
The kinda is doing a lot here. Many times the very act of trying to communicate a thought colors/corrupts the main point and gives only one perspective or a snapshot of the overall thought. There's a reason why they say a picture is worth a thousand words. Except the mind can conjure much more than a static picture. The mind can also hold the idea and the exceptions to the idea in one coherent model. For me this can be especially apparent when taking psychedelics and finding that trying to communicate some thoughts with words requires constant babbling to keep refining the last few sentences, ad libidum. There are exceptions of course, like for simple ideas.
Yeah! Sometimes the thought isnt compressible and language doesnt help. But a lot of times it is, and it does
I could enter what we all here call the "Zone" quite often when i was young (once while doing math :D). I still can, but rarely on purpose, and rarely while coding. I have a lot of experience in this state, and i can clearly say that a marker of entering the zone is that your thoughts are not "limited" by language anymore and the impression of clarity and really fast thinking. This is why i never thought that language was required for thinking.
Now the question: would it be possible to scan the brain of people while they enter the zone? I know it isn't a state you can reach on command, but isn't it worth to try? understand the mechanism of this state? And maybe understand where our thought start?
That is, until the code refuses to work. Then the code is a bitch and I need a break.
“You cannot ask a question you that you have no words for”
- Judea Pearl
Language is a very poor substitute for freely flowing electrical information - it is evolved to compensate for the bottlenecks to external communication - bottlenecks that are lacking an internal analogue.
It's also a highly advanced feature - something as heavily optiimised as evolved life would not allow something as vital as cognition to be hampered by a lack of means for high fidelity external expression.
Also the title is editoralized for no reason. It makes searching, recognizing, citing etc waaay harder, and full of errors. I'll flag it.
No. But I'm going to stop there, because there are pages of comments saying the exact opposite (and of course some agreeing with you) above.
> Language serves not only to express thoughts, but to make possible thoughts which could not exist without it. It is sometimes maintained that there can be no thought without language, but to this view I cannot assent: I hold that there can be thought, and even true and false belief, without language. But however that may be, it cannot be denied that all fairly elaborate thoughts require words.
> Human Knowledge: Its Scope and Limits by Bertrand Russell, Section: Part II: Language, Chapter I: The Uses of Language Quote Page 60, Simon and Schuster, New York.
Of course, that would contravene the popular narrative that philosophers are pompous idiots incapable of subtlety.
Practically, I think the origins of fire-making abilities in humans tend to undermine that viewpoint. No other species is capable of reliably starting a fire with a few simple tools, yet the earliest archaeological evidence for fire (1 mya) could mean the ability predated complex linguistic capabilities. Observation and imitation could be enough for transmitting the skill from the first proto-human who successfully accomplished the task to others.
P.S. This is also why Homo sapiens should be renamed Homo ignis IMO.
It’s doubtless to me that thinking happens without intermediary symbols; but it’s also obvious that I can’t think deeply without the waypoints and context symbols provide. I think it is a common sense opinion.
Just a few days ago was "What do you visualize while programming?", and there's a few of us in the comments that, when programming, think symbolically without language: https://news.ycombinator.com/item?id=41869237
> In the stage of Cause and Effect, the relationships between mental and physical phenomena become very clear and sometimes ratchet-like. There is a cause, such as intention, and then an effect, such as movement. There is a cause, such as a sensation, and there is an effect, namely a mental impression.
Trying to increase the frequency at which you oscillate between physical sensations and mental sensations is a fascinating exercise.
[0] https://www.mctb.org/mctb2/table-of-contents/part-iv-insight...
https://www.cbc.ca/news/canada/saskatchewan/inner-monologue-...
Take riding a bike: I presume even people with an overactive inner monologue aren't constantly planning their actions (brakes, steering, turns) in words. Then just extend that out to most other stuff.
I want to remind everyone that your experiences are unique and do not necessarily translate to all other people.
There could be functional redundancies or alternative systems at play that we haven't identified, systems that allow thought to access linguistic capabilities even when the specialized language areas are offline or unnecessary. The question of what "language in thought" looks like remains open, particularly in tasks requiring comprehension. This underscores the need for further exploration into how thought operates and what role, if any, latent or alternative linguistic functionalities play when conventional language regions aren't active.
In short, we may have a good understanding of language in isolation, but not necessarily in its broader role within the cognitive architecture that governs thought, comprehension, and meaning-making.
The parent article is mostly about thinking without "words", not necessary without a "language".
Some thoughts might be completely different from sentences in a language, probably when they have a non-sequential nature, but other thoughts are exactly equivalent to a sentence in a language, except that they do not use the words.
I can look and see to things that I recognize, e.g. A and B, and I can see that one is bigger than the other and I can think "A is bigger than B" without thinking at the words used in the spoken language, but nonetheless associating some internal concepts of "A", "B" and "is greater than", exactly like when formulating a spoken sentence.
I do not believe that such a thought can be considered as an example of thinking without language, but just as an example that for a subset of the words used in a spoken language there is an internal representation that is independent of the sequence of sounds or letters that compose a spoken or written language.
All other things being equal, its is a reason to provisionally reject the hypothesis that those kinds of thought use language as introducing entities (the ties between those kinds of thought and language) into the model of reality being generated that are not needed to explain any observed phenomenon.
Then comes the need to transmit/transfer understanding.
From the fine article:
> various properties that human languages have—there are about 7,000 of them spoken and signed across the world—are optimized for efficiently transmitting information, making things easy to perceive, easy to understand, easy to produce and easy to learn for kids.
Another related tool is religion (for emotions instead of thoughts,) which funnily enough faces the same divergence language does.
Right now society that calls itself "secular" simply does not understand the role of religion, and its importance in society.
To be clear, I don't belong to any religion, I am saying one needs to be invented for people who are currently "secular."
In fact, you have the disorganized aspects of religion already. All one needs to spot these are to look at the aspects that attempt to systematize or control our feelings. Mass media, celebrities for example.
Instead of letting capitalistic forces create a pseudoreligion for society, it's better if people come together and organize something healthier, intentionally.
Thinking some type of materialism is even mostly correct, with the sum over all mostly materialist theories being close to 1, isn't a religion at all.
I think this is completely wrong-headed. It's like saying that until cars came about we just didn't have anything other than animals that could move around under its own power, therefore in order to understand how animals move around we should go and study cars. There is a great gulf of unsubstantiated assumptions between observing the behaviour of a technological artifact, like a car or a statistical language model, and thinking we can learn something useful from it about human or more generally animal faculties.
I am really taken aback that this is a serious suggestion: study large language models as in-silico models of human linguistic ability. Just putting it down in writing like that rings alarm bells all over the place.
It's hard for me to understand where my peers are coming from on the other side of this argument and respond without being dismissive, so I'll do my best to steelman the argument later.
Machine learning models are function approximators and by definition do not have an internal experience distinct from the training data any more than the plus operator does. I agree with the sentiment that even putting it in writing gives more weight to the position than it should, bordering on absurdity.
I suppose this is like the ELIZA phenomena on steroids, is the only thing I can think of for why such notions are being entertained.
However, to be generous, lets do some vigorous hand waving and say we could find a way to have an embodied learning agent gather sublinguistic perceptual data in an online reinforcement learning process, and furthermore that the (by definition) non-quantifiable subjective experience data could somehow be extracted, made into a training set, and fit to a nicely parametric loss function.
The idea then is that could find some architecture that would allow you to fit a model to the data.
And voila, machine consciousness, right? A perfect model for sentience.
Except for the fact that you would need to ignore that in the RL model gathering the data and the NN distilled from it, even with all of our vigorous hand waving, you are once again developing function approximators that have no subjective internal experience distinct from the training data.
Let's take it one step further. The absolute simplest form of learning comes in the form of habituation and sensitization to stimuli. Even microbes have the ability to do this.
LLMs and other static networks do not. You can attempt to attack this point by fiatting online reinforcement learning or dismissing it as unnecessary, but I should again point out that you would be attacking or dismissing the bare minimum requirement for learning, let alone a higher order subjective internal experience.
So then the argument, proceeding from false premises, would claim that the compressed experience in the NN could contain mechanical equivalents of higher order internal subjective experiences.
So even with all the might vigorous hand waving we have allowed, you have at best found a way to convert internal subjective processes to external mechanical processes fit to a dataset.
The argument would then follow, well, what's the difference? And I could point back to the microbe, but if the argument hasn't connected by this point, we will be chasing our tails forever.
A good book on the topic that examines this in much greater depth is "The Self Assembling Brain".
That being said, I am hella jealous of the VC money that the grifters will get for advancing the other side of this argument.
For enough money I'd probably change my tune too. I can't by a loaf of bread with a good argument lol
Much later, I did begin to think mostly in words, and (perhaps for unrelated reasons?) my thinking became much less efficient.
Also related, I experienced temporarily enhanced cognition while under the influence of entheogens. My thoughts, which normally fade within seconds, became stretched out, so that I could stack up to 7 layers of thought on top of each other and examine them simultaneously.
I remember feeling greatly diminished, mentally, once that ability went away.
What it seemed like subjectively though is that my thoughts themselves became "longer", imagine planks of wood. You can stack them (slightly offset, like a video timeline with layers), and the wider they are, the more ideas you can stack before it topples over.
I have unfortunately been unable to replicate the experience. There were after-effects for a few weeks where my senses and cognition were markedly enhanced, but this faded after a few weeks.
My main take-away here is "why are we trying to make machines smarter than humans, we should try to make humans smarter"! (I guess Neuralink kinda does that, but it doesn't actually make the human part smarter...)
Several factors contribute to the unfalsifiability of this claim:
Subjectivity of Thought: Thought processes are inherently internal and subjective. There is no direct method to observe or measure another being's thoughts without imposing interpretative frameworks influenced by social and material contexts.
Defining Language and Thought: Language is not merely a collection of spoken or written symbols; it is a system of signs embedded within social relations and power structures. If we broaden the definition of language to include any form of symbolic representation or communication—such as gestures, images, or neural patterns—then the notion of thought occurring without language becomes conceptually incoherent. Thought is mediated through these symbols, which are products of historical and material developments.
Animal Cognition and Symbolic Systems: Observations of animals like chimpanzees engaging in strategic gameplay or crows crafting tools demonstrate complex behaviors. Interpreting these actions as evidence of thought devoid of language overlooks the possibility that animals utilize their own symbolic systems. These behaviors reflect interactions with their environment mediated by innate or socially learned symbols—a rudimentary form of language shaped by their material conditions.
Limitations of Empirical Testing: To empirically verify that thought can occur without any form of language would require accessing cognitive processes entirely free from symbolic mediation. Given the current state of scientific methodologies—and considering that all cognitive processes are influenced by material and social factors—this is unattainable.
Because of these factors, Stix's claim cannot be empirically tested in a way that could potentially falsify it. It resides outside the parameters of verifiable inquiry, highlighting the importance of recognizing the interplay between language, thought, and material conditions.
Cognitive processes and language are deeply intertwined. Language arises from collective practice; it both shapes and is shaped by the material conditions of the environment. Thought is mediated through language, carrying the cognitive imprints of the material base. Even in non-human animals, the cognitive abilities we observe may be underpinned by forms of symbolic interaction with their environment—a reflection of their material engagement with the world.
Asserting that language is not essential for thought overlooks the fundamental role that social and material conditions play in shaping both language and cognition. It fails to account for how symbolic systems—integral to language—are embedded in and arise from material realities.
Certain forms of thought might appear to occur without human language, but this perspective neglects the intrinsic connection between cognition, language, and environmental conditiond. Reasoning itself can be viewed as a form of internalized language—a symbolic system rooted in social and material contexts. Recognizing this interdependence is crucial for a comprehensive understanding of the nature of thought and the pivotal role language plays within it.
Or vice versa?
Since it controls my limbs, I consider it to be the real me. My inner monologue is a bit frustrated that it can't control my limbs, and it can't really communicate with whoever controls my limbs.
Then there is my inner monologue, which does my thinking almost always, in an auditory way: imagine the sound of spoken words in an ~5 sec long duration, and let the answer appear. I consider it as an auditory deducing thingy, and also an intelligence on its own.
I am mostly fine with this, tho I am curious about my non-verbal me, and I wish I'd know more about it.
[0] https://archive.org/details/a-a-the-mystical-and-magical-sys...
I doubt that this is different for other people. I believe that those people who claim that they never think using language are never thinking about the abstract or remote things about which I think using language.
For instance, I can think about a model of CPU without naming it, if it has been included in some of the many computers that I have used during the years, by recalling an image of the computer, or of its motherboard, or of the CPU package, or recalling some experiences when running programs on that computer, how slow or how responsive that felt, and so on.
I cannot think about a CPU that I have never used, e.g. Intel 11900K, without naming it.
Similarly, I can think without language about the planet Jupiter, which I have seen directly many times, or even about the planet Neptune, which I have never seen with my eyes, but I have seen in photographs, but I cannot think otherwise than with words about some celestial bodies that I have never seen.
The same for verbs, some verbs name actions about which I can think by recalling images or sounds or smells or tactile feelings that correspond with typical results of those actions. Other verbs are too abstract, so I can think about the corresponding action only using the word that names it.
For some abstract concepts, one could imagine a sequence of images, sounds etc. that would suggest them, but that would be like a pantomime puzzle and it would be a too slow way of thinking.
I can look at a wood plank thrown over a precipice and I can conclude that it may be safe to walk on it without language, but if I were to design a bridge guaranteed to resist to the weight of some trucks passing on it, I could not do that design without thinking with language.
Therefore I believe that language is absolutely essential for complex abstract thinking, even if there are alternative ways of thinking that may be sufficient even most of the time for some people.
This makes me think of the Tao Te Ching, which opens with (translation dependent, of course)
The Tao that can be spoken is not the eternal Tao
The name that can be named is not the eternal nameWhy I mention this is that I see both language and reasoning as rooted in this more fundamental cognitive ability of "coherent sequencing". This sits behind all kinds of planning and puzzling tasks where you have to project forward a sequence of theoretical actions and abstractly evaluate the outcome.
Which is all to say, I don't think language and reasoning are the same, but I do think it is likely they stem from the same underlying fundamental mechanisms in our brain. And as a consequence, it's actually quite plausible that LLMs can reconstruct mechanisms of reasoning from language, in a regressive model kind of fashion. ie: just because their are other ways to reason doesn't exclude language as a path to it.
What if the things are part of a set, chosen for uniqueness and distinguishability. Meanings determined by tradition?
There's a lot of territory between the two.
His work explores the neuropsychology of emotions WAIT DON'T GO they are actually the substrate of consciousness, NOT the other way around.
We have 7 primary affective processes (measurable hardware level emotions) and they are not what you think[2]. They are considered primary because they are sublinguistic. For instance, witnessing the color red is a primary experience, you cannot explain in words the color red to someone who has not ever seen it before.
His work is a really fascinating read if you ever want to take a break from puters for a minute and learn how people work.
PS the reason this sort of research isn't more widely known is because the behaviorist school was so incredibly dominant since the 1970s they made it completely taboo to discuss subjective experience in the realm of scientific discourse. In fact the emotions we are usually taught are not based on emotional states but on muscle contractions in the face! Not being allowed to talk about emotions in psychological studies or the inner process of the mind is kinda crazy when you think about it. So only recently with neuroimaging has it suddenly become ok to acknowledge that things happen in the brain independent of externally observable behavior.
[2] - seeking - fear - anxiety and grief - rage - lust - play!!! - caring
[3] if this sounds familiar at all it's because Jordan Peterson cites Jaak Panksep all the time. Well 50% of the time, the other 50% is CG Jung and the final 50% is the book of Exodus for some reason.
If I had time and free use of an LLM, I'd like to investigate how well it understands constructional synonymy, like "the red car" and "the car that is red" and "John saw a car on the street yesterday. It was red." I guess models that can draw pictures can be used to test this sort of thing--surely someone has looked into this?
Base consciousness is surely not dependent on language, but I suspect base consciousness may be extremely different from what one might expect, so much that compared to what we perceive as consciousness, might seem something close to death.
And I'll hold to the notion that the complete absence of language (and its underlying structure) would resemble death if death can be resembled. Perhaps death is only the excoriation of thought, cognition and language, with something more fundamental persisting.
Since we all have language and opinions about it, the risk of genericness is high with a title like this. It's like this with threads about other universal topics too, such as food or health.
> You can ask whether people who have these severe language impairments can perform tasks that require thinking. You can ask them to solve some math problems or to perform a social reasoning test, and all of the instructions, of course, have to be nonverbal because they can’t understand linguistic information anymore.
Surely these "non-verbal instructions" are some kind of language. Maybe all human action can be considered language.
A contrarian example to this research might be feral children, i.e people who have been raised away from humans.[0] In most cases they are mentally impaired; as in not having human-like intelligence. I don't think there is a good explanation why this happens to humans. And why it doesn't happen to other animals, which develop normally in species-typical way whether they are in the wild or in human captivity. It seems that most human behavior (even high-level intelligence) is learned / copied from other humans, and maybe this copied behavior can be considered language.
If humans are "copy machines", there's also a risk of completely losing the "what's it like to be a human" behavior if children of the future are raised by AI and algorithmic feeds.
> DA was impaired in solving simple addition, subtraction, division or multiplication problems, but could correctly simplify abstract expressions such as (b×a)÷(a×b) or (a+b)+(b+a) and make correct judgements whether abstract algebraic equations like b − a = a − b or (d÷c)+a=(d+a)÷(c+a) were true or false.
> Sensitivity to the structural properties of numerical expressions was also evaluated with bracket problems, some requiring the computation of a set of expressions with embedded brackets: for example, 90 [(3 17) 3].
Discussions of whether or not these sorts of algebraic or numerical expressions constitute a "language of mathematics" aside (despite them not engaging the same brain regions and structures associated with the word "language"); it may be the case that these sorts of word sequences and symbols processed by structures in the brain's left hemisphere are not essential for thought, but can still serve as a useful psychotechnology or "bicycle of the mind" to accelerate and leverage its innate capabilities. In a similar fashion to how this sort of mathematical notation allows for more concise and precise expression of mathematical objects (contrast "the number that is thrice of three and seventeen less of ninety") and serves to amplify our mathematical capacities, language can perhaps be seen as a force multiplier; I have doubts whether those suffering from aphasia or an agrammatic condition would be able to rise to the heights of cognitive performance.
If you look up 'mentalese' you can find a bunch written about it. There's an in-depth article by Daniel Gregory and Peter Langland-Hassan, in the incredible Stanford Encyclopedia of Philosophy, on Inner Speech (admittedly, I'm taking a leap to think they mean precisely the same thing). [2]
[0] Steven Pinker, The Blank Slate: The Modern Denial of Human Nature (2002)
[1] Oxford English Dictionary
In my mind there should be some kind of parallel/hierarchical model that comes after language layers and then optionally can be converted back to a series of tokens. The middle layers are trained on world models such as from videos, intermediary layers on mapping, and other layers on text, including quite a lot of transcripts etc. to make sure the middle layers fully ground the outer layers.
I don't really understand transformers and diffusion transformers etc., but I am optimistic that as we increase the compute and memory capacity over the next few years it will allow more video data to be integrated with language data. That will result in fully grounded multimodal models that are even more robust and more general purpose.
I keep waiting to hear about some kind of manufacturing/design breakthroughs with memristors or some kind of memory-centric computing that gives another 100 X boost in model sizes and/or efficiency. Because it does seem that the major functionality gains have been unlocked through scaling hardware which allowed the development of models that took advantage of the new scale. For me large multimodal video datasets with transcripts and more efficient hardware to compress and host them are going to make AI more robust.
I do wish I understood transformers better though because it seems like somehow they are more general-purpose. Is there something about them that is not dependant on the serialization or tokenization that can be extracted to make other types of models more general? Maybe they are tokens that have scalars attached which are still fully contextualized but are computed as many parallel groups for each step.
But I thought in images and I still do in part. so I don’t think you need words to think.
I thought the people who did were overly computerized, maybe thinking in an over defined way.
We only consciously "know" something when we represent it with symbols. There are also unconscious processes that some would consider "thought", like driving a car safely without thinking about what you're doing, but I wouldn't consider those thoughts.
I find an interesting parallel to Chain of Thought techniques with LLMs. I personally don't (consciously) know what I think until I articulate it.
To me this is similar to giving an LLM space to print out intermediary thoughts, like a JSON array of strings. Language is our programming language, in a sense. Without representing something in a word/concept, it doesn't exist.
"Ich vermute, dass wir nur sehen, was wir kennen." - Nietzsche, where "know" refers to labeling something by projecting a concept/word onto it.
My take away is that language is secondary to thinking - aka intuitive pattern detection. Language is the Watson to Sherlock.
The corollary is that treating language as primary in decision making is (sometimes) not as effective as treating it as secondary. At this point in my life (I'm old) I seem to have spent much of my life attempting to understand why my pattern matching/intuition made a choice that turned out to be so superior to my verbal language process.
I guess this was the experiment the proved the point.
This I think is why so much popular psychology is so vacuous - the slogans are merely things that triggered some people to figure out how to improve their mental actions, but there's no strong linkage between the two.
The one thing I wonder is if it's mostly "code duplication": iow, would we be able to develop language by using a different region of the brain, or do we actually do cognitive processes in the language part too?
In other words, is this simply deciding to send language processing to the GPU even if we could do it with the CPU (to illustrate my point)?
How would one even devise an experiment to prove or disprove this?
To me it seems obvious that our language generation and processing regions really involve cognition as well, as languages are very much rule based (even of they came up in reverse: first language then rules): could we get both regions to light up in brain imaging when we get to tricky words that we aren't sure how to spell or adapt to context like declensions of foreign words
> But you can build these models that are trained on only particular kinds of linguistic input or are trained on speech inputs as opposed to textual inputs.
As someone from this side of the "fence" (mathematics and CS, though currently obly a practicing software engineer), I don't think LLMs provide this opportunity that is in any way comparable to human minds.
Comparing performance of small kids developing their language skills (I've only had two, but one is enough to prove by contradiction) to LLMs (in particular for Serbian), LLMs like ChatGPT had a much broader vocabulary, but kids were much better at figuring out complex language rules with very limited number of inputs (noticed by them making mistakes on exceptions by following a "rule" at 2 years of age or younger).
The amount of training input GenAI needs is multiple orders of magnitude larger compared to young kids.
Though it's not a fair comparison: kids learn language by listening, immitation, watching, smelling, hearing and in context (you'll talk about bread at breakfast).
So let's be careful in considering LLMs a model of a human language process.
I don't know why Russell is catching strays. Saying language exists to make possible thoughts which could not exist without it does not in any way imply that you can't think without language.
"Before my teacher came to me, I did not know that I am. I lived in a world that was a no-world. I cannot hope to describe adequately that unconscious, yet conscious time of nothingness. I did not know that I knew aught, or that I lived or acted or desired. I had neither will nor intellect. I was carried along to objects and acts by a certain blind natural impetus. I had a mind which caused me to feel anger, satisfaction, desire. These two facts led those about me to suppose that I willed and thought. I can remember all this, not because I knew that it was so, but because I have tactual memory. It enables me to remember that I never contracted my forehead in the act of thinking. I never viewed anything beforehand or chose it. I also recall tactually the fact that never in a start of the body or a heart-beat did I feel that I loved or cared for anything. My inner life, then, was a blank without past, present, or future, without hope or anticipation, without wonder or joy or faith.
It was not night—it was not day.
. . . . .
But vacancy absorbing space, And fixedness, without a place; There were no stars—no earth—no time— No check—no change—no good—no crime.
My dormant being had no idea of God or immortality, no fear of death.
I remember, also through touch, that I had a power of association. I felt tactual jars like the stamp of a foot, the opening of a window or its closing, the slam of a door. After repeatedly smelling rain and feeling the discomfort of wetness, I acted like those about me: I ran to shut the window. But that was not thought in any sense. It was the same kind of association that makes animals take shelter from the rain. From the same instinct of aping others, I folded the clothes that came from the laundry, and put mine away, fed the turkeys, sewed bead-eyes on my doll's face, and did many other things of which I have the tactual remembrance. When I wanted anything I liked,—ice-cream, for instance, of which I was very fond,—I had a delicious taste on my tongue (which, by the way, I never have now), and in my hand I felt the turning of the freezer. I made the sign, and my mother knew I wanted ice-cream. I "thought" and desired in my fingers. If I had made a man, I should certainly have put the brain and soul in his finger-tips. From reminiscences like these I conclude that it is the opening of the two faculties, freedom of will, or choice, and rationality, or the power of thinking from one thing to another, which makes it possible to come into being first as a child, afterwards as a man.
Since I had no power of thought, I did not compare one mental state with another. So I was not conscious of any change or process going on in my brain when my teacher began to instruct me. I merely felt keen delight in obtaining more easily what I wanted by means of the finger motions she taught me. I thought only of objects, and only objects I wanted. It was the turning of the freezer on a larger scale. When I learned the meaning of "I" and "me" and found that I was something, I began to think. Then consciousness first existed for me. Thus it was not the sense of touch that brought me knowledge. It was the awakening of my soul that first rendered my senses their value, their cognizance of objects, names, qualities, and properties. Thought made me conscious of love, joy, and all the emotions. I was eager to know, then to understand, afterward to reflect on what I knew and understood, and the blind impetus, which had before driven me hither and thither at the dictates of my sensations, vanished forever.
I cannot represent more clearly than any one else the gradual and subtle changes from first impressions to abstract ideas. But I know that my physical ideas, that is, ideas derived from material objects, appear to me first an idea similar to those of touch. Instantly they pass into intellectual meanings. Afterward the meaning finds expression in what is called "inner speech." When I was a child, my inner speech was inner spelling. Although I am even now frequently caught spelling to myself on my fingers, yet I talk to myself, too, with my lips, and it is true that when I first learned to speak, my mind discarded the finger-symbols and began to articulate. However, when I try to recall what some one has said to me, I am conscious of a hand spelling into mine.
It has often been asked what were my earliest impressions of the world in which I found myself. But one who thinks at all of his first impressions knows what a riddle this is. Our impressions grow and change unnoticed, so that what we suppose we thought as children may be quite different from what we actually experienced in our childhood. I only know that after my education began the world which came within my reach was all alive. I spelled to my blocks and my dogs. I sympathized with plants when the flowers were picked, because I thought it hurt them, and that they grieved for their lost blossoms. It was two years before I could be made to believe that my dogs did not understand what I said, and I always apologized to them when I ran into or stepped on them.
As my experiences broadened and deepened, the indeterminate, poetic feelings of childhood began to fix themselves in definite thoughts. Nature—the world I could touch—was folded and filled with myself. I am inclined to believe those philosophers who declare that we know nothing but our own feelings and ideas. With a little ingenious reasoning one may see in the material world simply a mirror, an image of permanent mental sensations. In either sphere self-knowledge is the condition and the limit of our consciousness. That is why, perhaps, many people know so little about what is beyond their short range of experience. They look within themselves—and find nothing! Therefore they conclude that there is nothing outside themselves, either.
However that may be, I came later to look for an image of my emotions and sensations in others. I had to learn the outward signs of inward feelings. The start of fear, the suppressed, controlled tensity of pain, the beat of happy muscles in others, had to be perceived and compared with my own experiences before I could trace them back to the intangible soul of another. Groping, uncertain, I at last found my identity, and after seeing my thoughts and feelings repeated in others, I gradually constructed my world of men and of God. As I read and study, I find that this is what the rest of the race has done. Man looks within himself and in time finds the measure and the meaning of the universe."
I think that using a LLM as the referred telepathy device to a wolfram-alpha/mathematica like general reasoning module is the way to AGI. The reasoning modules we have today are still much to narrow because of the very broad and deep search trees exploding in complexity. There is the need for a kind of pathfinder which could come from common knowledge already encoded in LLMs, like in o1. An system playing with real factual reasoning but exploring in directions coming from world knowledge.
What is still missing is the dialectic between possible and right, a physics engine, the motivation of analysed agents, the effects of emergent behavior and a lot of other -isms. But they may be encoded in the reasoning-explorer. And of course loops, more loops, refinement, working hypotheses and escaping cul-de-sacs.
There are people with great language skills and next to no reasoning skills. Some of them have general knowledge. If you ever talked to them, for a at least an hour freely meandering topics you will know. They seem intelligent for a couple of minutes but after a while you realise that they can refer fact, even interpret metaphors, but they will not find an elegant one, to navigate abstraction levels, even to differentiate root cause from effect or motivation and culture from cold logic. Some of them even ace IQ or can program but none did math so far. They hate, fear or despise rational results violation their learned rules. Sorry, chances are if you hate reading this, maybe you are one (or my English is annoyingly bad).
I love talking to people outside my bubble. They have an incredible broad diversity in abilities and experiences.
who cares right?
Most things we know, we are probably not aware of. And for most of us, direct experience of everything that surrounds us in the world certainly exceeds by several order of magnitude the best bandwidth we can ever dream to achieve through any human language.
Ok, there are no actual data to back this, but authors of the article don't have anything solid either to back such a bold statement, from what is presented in the article.
If most of what we know of the world would mostly be things we were told, it would obviously be mostly a large amount of phatic noises, lies and clueless random assertions that we would have no mean to distinguish from the few stable credible elements inferable by comparing with a far more larger corpus of self experiments with realty.