[HN Gopher] Here comes the Muybridge camera moment but for text
___________________________________________________________________
Here comes the Muybridge camera moment but for text
Author : RA2lover
Score : 189 points
Date : 2024-06-02 15:57 UTC (1 days ago)
(HTM) web link (interconnected.org)
(TXT) w3m dump (interconnected.org)
| 082349872349872 wrote:
| > _What would it mean to listen to a politician speak on TV, and
| in real-time see a rhetorical manoeuvre that masks a persuasive
| bait and switch?_
|
| Why do I suspect the offence will always be ahead of the defence
| in these areas?
|
| I'd earlier suggested that everyone, in elementary school, ought
| to watch Ancient Aliens and attempt to note the moment where each
| episode jumps the shark. I take it we could attempt this with
| LLMs, now?
| rablackburn wrote:
| > Why do I suspect the offence will always be ahead of the
| defence in these areas?
|
| because destroying is easier than creating/entropy increases
| over time?
|
| The only solution I can see is working on turning bad actors
| into good actors, or another way: positive reinforcement
| cycles.
|
| No idea what that would look like with regard to LLMs though.
| pixl97 wrote:
| At the end of the day there is no permanent solution.
|
| In nature we typically don't see something 'win' and that's
| the end of the story. I mean yes things do go extinct, but
| the winner always has something new to deal with. Could be a
| more advanced predator eating all it's food sources. Could be
| a bacteria that it's not resistant to. Simply put, when
| there's entropy on the table, something is going to evolve to
| take it with the least amount of work possible.
| dhosek wrote:
| For those perplexed by the headline, the Muybridge camera moment
| refers to Eadweard Muybridge who managed via camera photos taken
| in rapid succession to prove that when a horse runs it at times
| has all four legs above the ground.
|
| https://en.wikipedia.org/wiki/Eadweard_Muybridge
|
| (the article doesn't bother to mention any of this until near the
| end in the tl;dr section, which since it's tl and you dr, you
| never got to).
| stavros wrote:
| Not only that, but the tldr basically _only_ talks about that,
| so it 's not much of a summary at all. I read the tldr and I
| have no idea what the article is about.
| Animats wrote:
| (On an irrelevant note, the Stanford Barn, where those pictures
| were taken, has gradually been closed off to the world. It was
| open to the public until COVID. It's still there, and there's a
| Stanford equestrian team, but road access has been cut and all
| mentions of the barn removed from directional signs.)
| gausswho wrote:
| There are so many of these places I've encountered what used
| to be publicly available pre-COVID and are no longer. The
| reasons/excuses vary.
|
| Example: Sometimes it's a symptom of a small business already
| wanted a reason to pivot to a new venture, and they keep the
| old thing going to profit from some old whales while in
| transition.
| dhosek wrote:
| There was a lot of that post 9/11 too. It used to be that
| you could walk into nearly any office building in the world
| with little more than a smile and a confident wave. A lot
| of previously public areas got locked down on September
| 12th.
| PopAlongKid wrote:
| Office building security changed significantly much
| earlier than 2001. The mass shooting in 1993 at 101
| California Street in San Francisco was the beginning of
| many such changes.
|
| _The attack [...] also precipitated sweeping changes in
| downtown San Francisco. Before Ferri walked into the
| building that July day, almost no high-rises in the city
| had security measures. While many had a front desk, only
| a handful checked badges. The building at 101 California
| had two side entrances that were completely unguarded.
| The Examiner reported that at the time, the Chevron
| building and Charles Schwab's SF headquarters had the
| toughest security in town; electronic badges were
| required at Chevron, an anomaly in 1993.
|
| Today, security checks are standard at offices large and
| small, a fundamental shift that happened because of 101
| California._
|
| https://www.police1.com/active-
| shooter/articles/101-californ...
| seszett wrote:
| It's often public services that have reaffected resources
| while that place was closed, and found after Covid that
| they couldn't spare (of justify sparing) these resources
| again once they contemplated reopening the place.
|
| Ie, while that historic greenhouse in the city park was
| nice and appreciated by some people, now that the two
| gardeners who were working in it part-time have to take
| care of the newly planted trees along the streets, it's not
| possible to put them back to the less essential greenhouse
| and they don't have budget for hiring two new gardeners. So
| the greenhouse stays closed.
| qup wrote:
| https://archive.is/EcQfE
|
| Site is struggling
| anigbrowl wrote:
| _Zardoz_ predicted this ~50 years ago
| nickreese wrote:
| I thoroughly enjoyed reading this style of loose connected
| thoughts.
| kepano wrote:
| The repercussions of what the author summarizes as "could you
| colour-grade a book?" still feel wildly unknown to me, even after
| a couple years of thinking about it (see _Photoshop for text_
| [1][2]).
|
| Partially it's because we're still wrapping our heads around what
| kind of experience this might enable. The tools still feel ahead
| of the medium. I think we're closer to Niepce than Muybridge.
|
| In photography terms, we've just figured out how to capture
| photons on paper -- and artists haven't figured out how to use
| that to make something interesting.
|
| [1] https://news.ycombinator.com/item?id=33253606
|
| [2] https://stephango.com/photoshop-for-text
| throw46365 wrote:
| > The tools still feel ahead of the medium.
|
| Or maybe it's that we instinctively feel that writing should
| still be linear writing, if reading is still going to be linear
| reading.
|
| Personally I think the "photoshop for text" analogy shows just
| how misguided it is to expect people to tolerate words that
| were calculated, not crafted.
|
| Literacy is too important to mess with like this.
| kepano wrote:
| Genuine question -- do you think synthetic images pose less
| of a problem than synthetic text? If yes, why?
| throw46365 wrote:
| Images -- photos, paintings, designs -- are not primary
| human expression.
|
| Words are fundamental, dense, often objectively chosen, and
| the most primary way of communicating thoughts.
|
| Asking someone to read your thoughts that you didn't
| actually even _think_ , because you'd rather save the time
| writing them, is profoundly disrespectful to the reader,
| who has to invest the same amount of time reading generated
| words as real ones.
|
| Which is not to say that I think passing off generative
| images as one's own work is not disrespectful. Or that
| extensive, unreal body sculpting or skin retouching is not
| -- as a photographer I believe that to also often be not
| just unethical but immoral.
|
| But a judgement on a retouched image is less of a burden of
| time.
|
| I would likely judge someone who uses ChatGPT to
| communicate personally with me as harshly as I would judge
| them editing a photo to deliberately lie to me.
|
| (Which is not to say that I don't think GPTs have inherent
| grammatical advantages for cleaning up poorly-written text;
| I do think generating entirely new text is disrespectful to
| the reader, though)
| kepano wrote:
| When I think about Photoshop it is so tied in my mind to
| its history as an offshoot of ILM and the VFX industry ht
| tps://en.wikipedia.org/wiki/Adobe_Photoshop#Early_history
|
| ILM's famous t-rex scene from Jurassic Park contains very
| little text/dialog, but emotional, expressive, synthetic
| imagery: https://www.youtube.com/watch?v=Rc_i5TKdmhs
|
| In this case the scene is not made up of "generative"
| images in the current definition of the term, but
| synthetic images generated from polygons, virtual
| lighting, etc. It seems that there could be artistic
| utility to manipulating text in a similar way.
| throw46365 wrote:
| I don't think I mind it in explicitly artistic contexts
| so much, putting aside the fact that all the GPTs I have
| seen write in a banal, unimaginative, equivocating way
| that is exactly the opposite of what you want from
| creative dialogue.
|
| I can see narrow uses for it in that sort of way.
|
| But it's being marketed as a tool for businesses to use
| to talk lazy crap at people who would prefer to hear from
| humans: it's fundamentally a disrespectful thing in that
| context.
| 082349872349872 wrote:
| Artistically constructed images may not be primary human
| to human expression, but posture/silhouette is one of the
| most powerful human to other mammal expressions.
|
| You can't communicate much beyond imperatives, but you
| can communicate those fairly strongly, even in the
| absence of time working on the shared vocabulary needed
| for the precision of words.
| Der_Einzige wrote:
| I have proof from my commit history on the readme to CTGS[1]
| that my usage of the term "Photoshop for Creative Writing"
| (What I tried to market it as) predates all of this by... years
| now.
|
| https://github.com/Hellisotherpeople/Constrained-Text-Genera...
|
| I'm obsessed with this idea of a proper LLM desktop class
| prosumer front-end. Something feeling like it was made by Adobe
| in a world where they didn't go to shit in the early 2010s.
| Blender, but for LLMs. Oobabooga, but actually good and not
| janky. It would ideally implement all forms of "representation
| engineering" and hacking or playing with the embedding/latent
| spaces, along with every other LLM feature folks would love to
| have but often don't know exist (i.e. constrained generation)
|
| If you're a VC type reading this and believe in this idea, I
| really want to talk to you right about now.
|
| Also, if you are an expert in DearPyGUI or DearImGUI, I want to
| talk to you right now.
| Animats wrote:
| So embedding space itself is interesting. It's more than a step
| to an LLM. That's been known for a while, back to that early
| result where "King" - "Man" + "Woman" -> "Queen". This article,
| though, suggests more uses for embedding spaces. This could be
| interesting. It's a step beyond viewing them as a black box.
| 082349872349872 wrote:
| Is - m + f = specific to embeddings, or does it also work in
| https://en.wikipedia.org/wiki/Formal_concept_analysis#Exampl...
| ? (either as [?] f [?] m = or as [?] not(m) [?] f = ?)
|
| [alas, HN scrubs venus and mars symbols, and I shall spare you
| all the ancient egyptian hieroglyphs and O'Keeffean
| mathematical symbols, so `f` and `m` they are]
| szvsw wrote:
| One thing I always find interesting but not discussed _all that
| much_ at least in things I've read is - what happens in the
| spaces between the data? Obviously this is an incredibly high
| dimensional space which is only sparsely populated by the
| entirety of the English language; all tokens, etc. if the space
| is truly structured well enough, then there is a huge amount of
| interesting, implicit, almost platonic meaning occurring in the
| spaces between the data - synthetic? Dialectic? Idk. Anyways, I
| think those areas are a space that algorithmic intelligence will
| be able to develop its own notions of semantics and creativity in
| expression. Things that might typically be ineffable may find
| easy expression somewhere in embedding space. Heidegger's
| thisness might be easily located somewhere in a latent
| representation... this is probably some linguistics 101 stuff but
| it's still fascinating imo.
| Der_Einzige wrote:
| Ya I'm having my return to plato moment. It really feels like
| we are the demiurgos right now with AI systems. The nature of
| interpolation vs extrapolation and the exploration of latent
| spaces will answer a lot of philosophical questions that we
| didn't expect to be answered so quickly, and by computers of
| all things.
| skydhash wrote:
| I strongly believe there's nothing there other than gibberish.
| Piping /dev/random to a word selector will probably enumerates
| everything inside that set. There's a reason we can translate
| between every language on earth. That's because it's the same
| earth and reality. So there's a common sets of concepts that
| gives us the foundational rules of languages. Which is the data
| that you're speaking about.
| mortenjorck wrote:
| Now this is a fun idea. If you think of embeddings as a sort of
| quantization of latent space, what would happen if you "turned
| off" that quantization? It would obviously make no sense to us,
| as we can only understand the output of vectors that map to
| tokens in languages we speak, but you could imagine a language
| model writing something in a sort of platonic, infinitely
| precise language that another model with the same latent space
| could then interpret.
| Cacti wrote:
| The space is an uncountable set, at the limit. Mostly it's
| noise. See: curse of dimensionality.
| Kiro wrote:
| That reminds me of the crazy output you get when raising the
| temperature and letting the model deviate from regular
| language. E.g. https://news.ycombinator.com/item?id=38779818
| zharknado wrote:
| > Could you dynamically change the register or tone of text
| depending on audience, or the reading age, or dial up the
| formality or subjective examples or mentions of wildlife,
| depending on the psychological fingerprint of the reader or
| listener?
|
| This seems plausible, and amazing or terrible depending on the
| application.
|
| An amazing application would be textbooks that adapt to use
| examples, analogies, pacing, etc. that enhance the reader's
| engagement and understanding.
|
| An unfortunate application would be mapping which features are
| persuasive to individual users for hyper-targeted advertising and
| propaganda.
|
| A terrible application would be tracking latent political dissent
| to punish people for thought-crime.
| lsaferite wrote:
| I'm sure it comes up frequently, but the adapting textbook
| thought reminds me of the "Young Lady's Illustrated Primer"
| from Diamond Age.
| sebmellen wrote:
| Terence McKenna phrased this wonderfully, by saying "It seems to
| me that language is some kind of enterprise of human beings that
| is not finished."
|
| The full quote is more psychedelic, in the context of his
| experience with so-called 'jeweled self-dribbling basketballs' he
| would encounter on DMT trips, who he said were made of a kind of
| language, or 'syntax binding light':
|
| "You wonder what to make of it. I've thought about this for years
| and years and years, and I don't know why there should be an
| invisible syntactical intelligence giving language lessons in
| hyperspace. That certainly, consistently seems to be what is
| happening.
|
| I've thought a lot about language as a result of that. First of
| all, it is the most remarkable thing we do.
|
| Chomsky showed the deep structure of language is under genetic
| control, but that's like the assembly language level. Local
| expressions of language are epigenetic.
|
| It seems to me that language is some kind of enterprise of human
| beings that is not finished.
|
| We have now left the grunts and the digs of the elbow somewhat in
| the dust. But the most articulate, brilliantly pronounced and
| projected English or French or German or Chinese is still a poor
| carrier of our intent. A very limited bandwidth for the intense
| compression of data that we are trying to put across to each
| other. Intense compression.
|
| It occurs to me, the ratios of the senses, the ratio between the
| eye and the ear, and so forth, this also is not genetically
| fixed. There are ear cultures and there are eye cultures. Print
| cultures and electronic cultures. So, it may be that our
| perfection and our completion lies in the perfection and
| completion of the word.
|
| Again, this curious theme of the word and its effort to
| concretize itself. A language that you can see is far less
| ambiguous than a language that you hear. If I read the paragraph
| of Proust, then we could spend the rest of the afternoon
| discussing, what did he mean? But if we look at a piece of
| sculpture by Henry Moore, we can discuss, what did he mean, but
| at a certain level, there is a kind of shared bedrock that isn't
| in the Proust passage. We each stop at a different level with the
| textual passage. With the three-dimensional object, we all sort
| of start from the same place and then work out our
| interpretations. Is it a nude, is it an animal? Is it bronze, is
| it wood? Is it poignant, is it comical? So forth and so on."
|
| This post feels like the beginning of that concretization.
| eszed wrote:
| Fascinating comment, that articulates the point of TFA better
| than TFA did.
|
| I've always been highly articulate, and also frustrated by the
| limitations of spoken language. This is a common (maybe even
| the dominant?) theme in 20th century theatrical writing. People
| like Ibsen, Chekhov, Pinter, Genet, and Churchill all struggle
| with it in their own ways. People like Beckett and LePage and
| Sarah Kane ultimately kind of abandon language altogether.
|
| Or, though poetry's not as much my field as theatre, you could
| go back to TS Eliot:
|
| ... Words strain, Crack, and sometimes break, under the burden,
| Under the tension, slip, slide, perish, Decay with imprecision,
| will not stay in place, Will not stay still.
|
| My own speculation, along your lines, is that it's because
| sound is transient, hearing imperfect, and memory fallible.
| Even apart from ambiguity, two people will never quite agree on
| what was said. (Most of my arguments with my wife begin this
| way!) Even court transcripts, intended to eliminate this
| limitation, don't capture non-verbal cues.
|
| As someone who's been marinated in the written and spoken word
| for all my life, research like this is fascinating, and
| slightly creepy: will all of the ghosts in the machine be
| exorcised? If those are blown away, and the bare mechanism of
| language exposed, what comes next?
| pixl97 wrote:
| > "It seems to me that language is some kind of enterprise of
| human beings that is not finished."
|
| I would include this all the way up to higher intelligence
| itself, language is but the force carrier for intelligence.
| We've been developing muscles and balance for hundreds of
| millions of years, but our intelligence that communicates in
| advanced language is pretty much brand new.
| kaycebasques wrote:
| > Looking at this plot by @oca.computer, I feel like I'm peering
| into the world's first microscope and spying bacteria, or through
| a blurry, early telescope, and spotting invisible dots that turn
| out to be the previously unknown moons of Jupiter... There is
| something there! New information to be interpreted!
| 1024core wrote:
| Any tools to replicate @oca.computer's work?
|
| Once we have the 1000-dim vector embeddings I can make the rest
| work. Not sure how to go from 20-word span to a 1000-dim vector
| embedding.
| 10c8 wrote:
| Generating embeddings is relatively simple with a model and
| Python code. There's plenty of them on HuggingFace, along
| with code examples.
|
| all-MiniLM-L6-v2 is a really (if not the most) popular one
| (albeit not SotA), with 384 dimensions:
| https://huggingface.co/sentence-transformers/all-
| MiniLM-L6-v...
|
| Edit: A more modern and robust suite of models comes from
| Nomic, and can generate embeddings with 64 to 768 dimensions
| (https://huggingface.co/nomic-ai/nomic-embed-text-v1.5).
|
| When the author talks about thousands of dimensions, they're
| probably talking about the OpenAI embedding models.
| failrate wrote:
| For a game based on semantic vectors: https://semantle.com/
| nkurz wrote:
| > "Even in 1821, horses were wrongly depicted running like dogs."
|
| Great essay, but this small comment toward the end of the essay
| confused me. Is he saying that dogs never gallop?
|
| I'm still not sure about the answer breed-by-breed, but searching
| for it led me to this interesting page illustrating different dog
| gaits: https://vanat.ahc.umn.edu/gaits/index.html
|
| In particular, it seems to say that at least some dogs do the
| same "transverse gallop" that horses use:
| https://vanat.ahc.umn.edu/gaits/transGallop.html
|
| And that greyhounds at least also do a "rotary gallop":
| https://vanat.ahc.umn.edu/gaits/rotGallop.html
|
| I have a Vizsla (one of several breeds in the running for second
| fastest breed after greyhounds) and my guess is that she at times
| does both gallops. I can't find a reference to confirm this,
| though.
| mortenjorck wrote:
| Yes, yes, more explorations in this direction.
|
| For a couple of years now, I've had this half-articulated sense
| that the uncanny ability of sufficiently-advanced language models
| to back into convincing simulations of conscious thought entirely
| via predicting language tokens _means something profound about
| the nature of language itself._
|
| I'm sure there are much smarter people than I thinking about this
| (and probably quite a bit of background reading that would help;
| Chomsky, perhaps McLuhan?) but it feels like, in parallel to
| everything going on in the development of LLMs, there's also
| something big about _us_ waiting there under the surface.
| skydhash wrote:
| > convincing simulations of conscious thought entirely via
| predicting language tokens means something profound about the
| nature of language itself.
|
| > there's also something big about us waiting there under the
| surface.
|
| I don't believe so. In "The Origins of Knowledge and
| Imagination" by Jacob Brownoski, he argues that human language
| have four unique characteristics:
|
| - We can separate information (data of what being described)
| from emotional content (how we're supposed to react). There's
| no longer a bijection between communication and action.
|
| - We can extend the time reference of the communication
| content. We talk about the past, we plan for the future.
|
| - We can refer to ourselves. So we examine what we've done and
| iterate over it until we fix the errors. We can see ourselves
| doing the action without actually doing it.
|
| - We can rearrange units of languages to have different
| meanings. The same words can have different meanings based on
| their order. So meaning depends not only on the words, but
| their sequence. And that goes from words to phrases to sequence
| of dialogs.
|
| The fourth point is the most important. LLMs by predicting
| languages tokens can give use the most common order for a
| particular context. And because we don't have that many words,
| their orders can be extracted from books and other written
| content. But then they fail for the higher levels, mostly
| because that's when everything get unique.
|
| As for the third point, by observing ourselves, our
| communication is constantly being based on reality, which
| grounds it in truth. And because we can extend the reference
| it's based on, that leads us to observe changes and model laws.
| The first point allows us to separate what things are from what
| we should do or feel based on their existence and absence.
|
| Instead of the LLMs fooling us, it's more us fooling ourselves,
| because by recognizing meaning in sentences, we try to extract
| meanings for longer sequences of text where there aren't any.
| Why? Because there is no "I" that has done the job of
| extracting information and using language to transmit it (while
| still cognizant of the imperfection of natural languages). LLMs
| are lossy compressions of ideas. Only the smallest survives and
| then it generates much more false ones.
| justinjlynn wrote:
| Are you certain that you're not playing with words to arrive
| at a predetermined conclusion? What is this "I" to which
| you're referring and how can you demonstrate that "I" does
| not or cannot exist within systems such as these? Further, if
| you are to find something which qualifies as an "I"
| elsewhere, what makes that elsewhere fundamentally different
| and therefore capable of supporting and being an "I" and is
| that elsewhere such simply by definition or in and of itself?
| Further, if the language usage is indistinguishable from the
| language usage of an "I", is the difference of source
| meaningful? If so, why?
| skydhash wrote:
| The "I" is stemmed from the theory of the mind. We can only
| access our own mind and thus has no way to infer the
| thoughts of other. So we observe them and infer based on
| our own patterns. In a sense, we assume that others have
| the same mechanism that we possess, and thus we engage in
| interactions with them. So far, there is no demonstration
| of reasoning within systems such as these, it's all
| simulation of the communication channel themselves.
|
| > _Further, if the language usage is indistinguishable from
| the language usage of an "I", is the difference of source
| meaningful?_
|
| Is it indistinguishable? The first thing we look for in
| communication is consistency so that we can examine for
| intent. And this is after we determine the other party.
| Because we know the intent is not ours. But what I've seen
| of prompt engineering is that the communication intent
| always come from the person, not the models. Then it goes
| on to find the most likely continuation of this intent
| (based on the model training) and then it quickly become an
| echo chamber. It's search in lexical space and you can see
| the limits when it became a oscillating loop between the
| same set of reply. Because there's no "I don't know"
| damping.
| brianush1 wrote:
| Why does there need to be an "I" that uses language to
| transmit information? Language itself encodes information. I
| can read a piece of text and gain something from it. Where
| the text came from is irrelevant.
| skydhash wrote:
| > _Language itself encodes information._
|
| Which it does in a lossy manner. Information is independent
| from language. The more complex the information, the more
| language fails. Which is why there is so many mediums for
| communication. Language has three main components: the
| _symbols_ , the _grammar_ , and the _dictionary_. The first
| refers to the tokens of our vocabulary, the second to the
| rules to arrange these tokens, and the third describes the
| relation of the tokens to the things they represent.
|
| The relation between the three is interdependent. We name
| new things we encounter, creating entry in the dictionary,
| we figure the rules that governs these things, and the
| relation to other things encountered previously. And thus,
| we can issue statements. We can also name these statements
| and it continues recursively. But each of us possess its
| own copy of these stuff with its own variations. What you
| gain from what I said may be different from what I intended
| to transmit. And what I intended to transmit may be a poor
| description of the things itself. So flawed interpretation,
| flawed description, and flawed transmission result in
| flawed understanding. To correct it, you need to be in
| presence of the thing itself. Missing that, you strive to
| establish the tokens, the grammar, and the dictionary of
| the person that have written the text.
|
| In LLMs, the dictionary is missing. The token "snow" has no
| relation to the thing we call snow. But because it's often
| placed near other tokens like "ice", "freeze", etc,... Then
| a rule emerges (embedding?) that these things must be
| related to each other. In what way it does not know. But if
| we apply the data collected in a statistical manner, we can
| arrange these tokens and the result will _probably_ be
| correct. But there 's still a non-zero chance that the
| generated statement is meaningless as there's no foundation
| rule that drives it. So there's only tokens. And rules
| derived from analyzing texts (which lack the foundation
| rules that comes from being in the real world).
|
| All of these to say the act of learning is either observing
| the real world and figure how it works. Or read from
| someone that has done the observing and has written his
| interpretation, then go outside and confirm it. Barring
| that, we reconstruct the life of this person so that we can
| correct the imperfection of languages. With LLMs, there's
| no way to correct as the statement themselves are not
| truthful. they can just be accidentally be right.
| TeMPOraL wrote:
| I think the core insight OP may be looking for is that
| your dictionary is just an illusion - that concepts being
| related to other concepts to various degree is _all_ that
| there is. The meaning of a concept is defined entirely by
| other concepts that are close to it in something like a
| latent space of a language model.
|
| Of course humans get to also connect concepts with inputs
| from other senses, such as sight, touch, smell or sound.
| This provides some grounding. It is important for
| learning to communicate (and to have something to
| communicate about), and was important for humans when
| first developing languages - but they're not strictly
| necessary to learn the meanings. All this empirical
| grounding is already implicitly encoded in human
| communication, so it should be possible for an LLM to
| actually understand what e.g. "green" means, despite
| having never seen color. Case in point: blind people are
| able to do this, so the information is there.
| cymian wrote:
| Blind people are no more able to understand* (as qualia)
| "green" than a sighted human is able to understand* gamma
| rays. The confusion is between working with abstract
| concepts vs an actual experience _. A picture of bread
| provides no physical nourishment beyond the fiber in the
| paper it is printed on.
|
| In an abstract space (e.g. word vectors, poetry) green
| could have (many potential) meanings. But none of them
| are even in the same universe as the actual experience
| (qualia) of seeing something green. This would be a
| category mistake between qualia-space and concept-space
|
| _ understand in the experiential, qualia sense.
|
| https://en.wikipedia.org/wiki/Qualia
|
| https://en.wikipedia.org/wiki/Category_mistake
| furstenheim wrote:
| 100%, maybe intelligence is not as mysterious and extraordinary
| as we thought
| leobg wrote:
| Chomsky, of all people? Chomsky rose to fame by attacking BF
| Skinner's book "Verbal Behavior". Which is the book that made
| exactly the case you're making now, only some 60 years ago.
|
| Skinner would marvel at today's LLMs. They are the most elegant
| proof that intelligence is not just shaped by external
| contingencies, but that it is identical with those
| contingencies.
| ryandv wrote:
| To this list I would absolutely add Julian Jaynes' "The Origin
| of Consciousness in the Breakdown of the Bicameral Mind."
|
| > simulations of conscious thought entirely via prediction
| language tokens
|
| Jaynes goes so far as to assert that _language generates
| consciousness,_ which is characterized by (amongst other
| features) its narrative structure, as well as its production of
| a metaphor of our selves that can inhabit a spatiotemporal
| mental space that serves as an analog for the physical world;
| the mental space where we imagine potential actions, play with
| ideas, predict future outcomes, and analyze concepts prior to
| taking action in the "real, actual" world.
|
| The generation of metaphors is inextricably linked to the
| psychotechnology (to pull a word from vocabulary discussed by
| John Vervaeke in his "Awakening from the Meaning Crisis"
| series) of language, which is the means by which one object can
| be described and elaborated by its similarity to another. As an
| etymological example: the Sanskrit word "bhu" which means "to
| grow" forms the basis of the modern English verb "to be," but
| predates lofty abstract notions such as that of "being,"
| "ontology," or "existence." It's from the known and the
| familiar (plant or animal growth) that we can reach out into
| the unknown and the unfamiliar (the concept of being), using
| (psycho-)technologies such as language to extend our cognition
| in the same way a hammer or a bicycle extends our body.
|
| There is something here about language being the substrate of
| thought, and perhaps even consciousness in general as Jaynes
| would seem to assert in Book I of his 1976 work, where he
| spends a considerable amount of time discussing metaphor and
| language in connection to his definition of "consciousness."
|
| There are also questions of "intentionality" and whether or not
| computers and their internal representations can actually be
| "about" something in the way that our language and our ideas
| can be "about" something in the physical (or even ideal) world
| that we want to discuss. Searle and the "Chinese room" argument
| come to mind.
|
| Turing famously dodged this question in his paper "Computing
| Machinery and Intelligence" by substituting what is now called
| the "Turing test" in lieu of answering the question of whether
| or not "machines" can "think" (whatever those two words
| actually _mean_ ).
| lettergram wrote:
| Quite literally what my company does - https://ipcopilot.ai/
|
| We discover innovative ideas in companies and help them protect
| their IP.
| Terr_ wrote:
| > What if the difference between statements that are simply
| speculative and statement that mislead are as obvious as, I don't
| know, the difference between a photo and a hand-drawn sketch?
|
| Given how long these have been pored over by existing
| hyperconnected nanomachine networks (i.e. brains) it may be that
| we'll mostly unearth qualities humans can already detect, even if
| only subconsciously.
|
| When it comes to separating truth and lies, perhaps the real
| trick the computer will bring is _removing_ context, e.g. scoring
| text without confirmation bias towards its conclusion.
| TeMPOraL wrote:
| LLMs seem to do more of what brains do unconsciously, rather
| than consciously. Which means brains may be better at rating
| e.g. trustworthiness of some text, but they don't surface
| specific ratings to the conscious level. Meanwhile, language
| models seem to be able to expose those features as knobs,
| allowing you to boost or attenuate them. So you get to drag the
| e.g. "excited" slider down to minimum, and get a text that may
| be easier to process at a _conscious_ level. Having a slider to
| remove rhetoric from text would be really useful development.
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