[HN Gopher] Evidence of a predictive coding hierarchy in the hum...
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Evidence of a predictive coding hierarchy in the human brain
listening to speech
Author : bookofjoe
Score : 89 points
Date : 2023-03-10 18:34 UTC (4 hours ago)
(HTM) web link (www.nature.com)
(TXT) w3m dump (www.nature.com)
| nextaccountic wrote:
| > Yet, a gap persists between humans and these algorithms: in
| spite of considerable training data, current language models are
| challenged by long story generation, summarization and coherent
| dialogue and information retrieval13,14,15,16,17; they fail to
| capture several syntactic constructs and semantics
| properties18,19,20,21,22 and their linguistic understanding is
| superficial19,21,22,23,24. For instance, they tend to incorrectly
| assign the verb to the subject in nested phrases like 'the keys
| that the man holds ARE here'20. Similarly, when text generation
| is optimized on next-word prediction only, deep language models
| generate bland, incoherent sequences or get stuck in repetitive
| loops13.
|
| The paper is from 2023 but their info is totally out of date.
| ChatGPT doesn't suffer from those inconsistencies as much as
| previous models.
| mota7 wrote:
| The paper says "... optimized on next-word prediction only".
| Which is absolutely correct in 2023.
|
| ChatGPT (and indeed all recent LLMs) using much more complex
| training methods than simply 'next-word prediction'.
| nextaccountic wrote:
| This passage makes two claims
|
| * one, applicable to current language models (which ChatGPT
| is one of them), claim that they "they fail to capture
| several syntactic constructs and semantics properties" and
| "their linguistic understanding is superficial". It gives an
| example, "they tend to incorrectly assign the verb to the
| subject in nested phrases like 'the keys that the man holds
| ARE here", which is not the kind of mistake that ChatGPT
| makes.
|
| * Another claim, is that "when text generation is optimized
| on next-word prediction only" then "deep language models
| generate bland, incoherent sequences or get stuck in
| repetitive loops". Only this second claim is relative to
| next-word prediction.
| halfnormalform wrote:
| The interesting part to me (total outsider looking in) isn't a
| hierarchy as much as what they say is different at each level.
| Each "higher" level is "thinking" about a future of longer and
| longer length and with more meaning drawn from semantic content
| (vs. syntactic content) than the ones "below" it. The "lower"
| levels "think" on very short terms and focus on syntax.
| jcims wrote:
| I've tried simulating that with chatgpt to some effect. I was
| just tinkering by hand but used it to write a story and it
| really helped with consistency and conference.
| groestl wrote:
| ChatGPT itself does that, AFAIK, by increasingly summarizing
| past conversation and using it as context for the next
| prompt.
| kelseyfrog wrote:
| Impossible. If humans are just predicting the next word then this
| makes us no different from LLMs.
| LoganDark wrote:
| Ever wondered why some people always try to complete others'
| sentences (myself included)? It's because some people can't
| keep the possibilities to themselves. The problem isn't that
| they're predicting, it's that they echo their predictions
| before the other person is even done speaking.
|
| Everyone forms those predictions, it's how they come to an
| understanding of what was just said. You don't necessarily
| memorize just the words themselves. You derive conclusions from
| them, and therefore, while you are hearing them, you are
| deriving possible conclusions that will be confirmed or denied
| based on what you hear next.
|
| I have an audio processing disorder, where I can clearly hear
| and memorize words, but sometimes I just won't understand them
| and will say "what?". But sometimes, before the other person
| can repeat anything, I'll have used my _memory_ of those words
| to process them properly, and I 'll give a response anyway.
|
| A lot of people thought I just had a habit of saying "what?"
| for no reason. And this happens in tandem with tending to
| complete any sentences I _can_ process in time...
| permo-w wrote:
| there's more to humans than language processing
| whatshisface wrote:
| There are a lot of times when you're reading stuff that really
| does sound like the human equivalent of an LLM's output, but
| that is bad - you are not supposed to do it. A certain degree
| of that is necessary to write with good grammar but you are
| supposed to control your "tongue" (which is how previous
| generations would have phrased it) with the rest of your
| faculties.
| jalino23 wrote:
| word
| thewataccount wrote:
| Predicting words != LLM. There's different methods of doing it,
| current LLMs are not necessarily the most optimal method. The
| paper states this as well,
|
| > This computational organization is at odds with current
| language algorithms, which are mostly trained to make adjacent
| and word-level predictions (Fig. 1a)
|
| I feel like you're suggesting because humans != LLMs then
| humans cannot be doing next word prediction.
| petilon wrote:
| LLMs are no different from us, because we modeled it after our
| brains.
|
| These papers suggest we are just predicting the next word:
|
| https://www.psycholinguistics.com/gerry_altmann/research/pap...
|
| https://www.tandfonline.com/doi/pdf/10.1080/23273798.2020.18...
|
| https://onlinelibrary.wiley.com/doi/10.1111/j.1551-6709.2009...
|
| https://www.earth.com/news/our-brains-are-constantly-working...
| nuancebydefault wrote:
| There's one thing you forgot: we only have some model of how
| a brain might work. The model will only stand as long as we
| don't find a better model. That's how science works.
| taberiand wrote:
| At some point though, the difference between the model and
| reality fall within a negligible error margin -
| particularly within a practical everyday context. Like,
| Newton's theory of gravity isn't perfect, but for most
| things it's pretty much good enough.
|
| Similarly if LLMs can be used to model human intelligence,
| and predict and manipulate human behaviour, it'll be good
| enough for corporations to exploit.
| precompute wrote:
| I think brain == LLM is only approaching true in the
| clean, "rational" world of the academia. The internet now
| amplifies this. IMHO it is not possible to make something
| perfectly similar to our own image in a culture that has
| taken to feeding upon itself. This sort of culture makes
| extracting value from it much, much more difficult. I
| think we map the model of our understanding of how we
| understand things to these "AI" programs. Doesn't count
| for much. We have so much more than our five senses, and
| I fully believe that we were made by God. We might come
| close to something that fulfills a great number of
| conditions for "life" but it will never be truly alive.
| jonplackett wrote:
| I don't think that's the right conclusion - predicting the next
| word doesn't mean that's the only thing we're doing. But it
| would be a sensible and useful bit of information to have for
| more processing by other bits of brain.
|
| It makes complete sense you would have an idea of the next word
| in any sentence and some brain machinery to make that happen.
|
| It in no way means you're just a LLM
| FrustratedMonky wrote:
| I think this is moving the goal post. Every time there is an
| advance in AI/Machine Learning, the response is "well humans
| can still do X that a computer can't do, explain that!". And
| whenever there is a discovering in the brain, the response is
| "well, ok, that looks a lot like its running an algorithm,
| but we still have X that is totally un-explainable".
|
| "and some brain machinery to make that happen" - Getting
| close to not having a lot of "brain machinery" left that is
| still a mystery. Pretty soon we'll have to accept that we are
| just biological machines (albeit in the form of crap throwing
| monkeys), built on carbon instead of silicon, and we run a
| process that looks a lot like large scale neural nets, and we
| have same limitations, and how we respond to our environment
| is pre-determined.
| lloeki wrote:
| I find it funny that we expect AI-du-jour to qualify as
| equal to human brains when the first has been trained on a
| slice of content for a bunch of hours and is then getting
| compared to wetware that's been trained for at least a
| decade.
|
| Recently stuff like ChatGPT is challenged by people
| pointing out the nonsense it outputs, but it has no way of
| knowing whether either of its training input or its output
| is valid or not. I mean one could hack the prompt and make
| it spit out that fire is cold, but you and I know for a
| fact that it is nonsense, because at some point we
| challenged that knowledge by actually putting our hand over
| a flame. And that's actually what kids do!
|
| As a parent you can tell your kid not to do this or that
| and they will still do it. I can't recall where I read last
| week that the most terrible thing about parenting is the
| realisation that they can only learn through pain... which
| is probably one of the most efficient feedback loops.
|
| Copilot is no different, it can spit out broken or
| nonsensical code in response to a prompt but developers do
| that all the time, especially beginners because that's part
| of the learning process, but also experts as well. Yet we
| somehow expect Copilot to spit out perfect code, and then
| claim "this AI is lousy!", and while it has been trained
| with a huge body of work it has never been able to
| challenge it with a feedback loop.
|
| Similarly I'm quite convinced that if I were uploaded
| everything there is to know about kung fu, I would be
| utterly unable to actually perform kung fu, nor would I be
| able to know whether this or that bit that I now know about
| kung fu is actually correct without trying it.
|
| So, I'm not even sure moving goal posts is actually the
| real problem but only a symptom, because the whole thing
| seems to me as being debated over the wrong equivalence
| class.
| Jensson wrote:
| Setting short goals and them moving that goal once you hit
| it is a valid way to make progress, not sure why you think
| this is a bad thing. We hit a goal, now we are talking
| about future goals, why not?
| FrustratedMonky wrote:
| Sorry. Was responding to the overall gestalt of AI, where
| there are always things that "only a human can do", then
| they gets solved or duplicated by a computer, then the
| argument is "well, humans can still do X that a computer
| never will because of some mysterious component that is
| unique to humans, thus a computer can never ever replace
| humans or be conscious"
| Jensson wrote:
| To me it looked like you just repeated a meme, there
| isn't a large number of such people you talked about here
| on HN, so there is no need to repeat that meme
| everywhere.
|
| If someone says "Computers will never be smarter than
| humans", then sure go ahead, post it. But most of the
| time it is just repeated whenever someone says that
| ChatGPT could be made smarter, or there is some class of
| problem it struggles with.
| archon1410 wrote:
| Repeating a meme on cue sounds very LLM-like. More
| evidence in favour of the thesis.
| Jensson wrote:
| Make the thesis "some parts of human thinking works like
| an LLM" and you would see way less resistance. Making
| extreme statements like "humans are no different from
| LLM" will just hurt discussion since it is very clearly
| not true. Humans can drive cars, balance on a tight rope
| etc, so it is very clear that humans have systems that an
| LLM lacks.
|
| The objection people would come with then is something
| like "but we could add those other systems to an LLM, it
| is no different from a human!". But then the thesis would
| be "humans are no different from an LLM connected to a
| whole bunch of other systems", which is no different from
| saying "some parts of human thinking works like an LLM"
| as I suggested above.
| cscurmudgeon wrote:
| The "just" in your comment doesn't follow from the article.
| There is no evidence that there is nothing other than
| "predicting the next word" in the brain. It may be a part but
| not the only part.
| peteradio wrote:
| What is a word?
| FrustratedMonky wrote:
| Where are the jokes that most people aren't much more than
| copy/paste, or LLM. In most daily lives, a huge amount of what we
| do is habit, and just plain following a pattern. When someone
| says "Good Morning", nobody is stopping and thinking "HMMM, let
| me think about what word to say in response, what do I want to
| convey here, hmmmm, let me think".
| duskwuff wrote:
| Or imagine listening to someone speak very slowly. A lot of the
| time, you already know what words they're going to say, you're
| just waiting for them to say it. There's a considerable amount
| of redundancy in language.
| codetrotter wrote:
| > you already know what words they're going to say, you're
| just waiting for them to say it
|
| This is why I like to surprise my friends, family and
| coworkers with the occasional curveball
| ItsMattyG wrote:
| I also like to surprise my friends, family, and aardvarks
| with the occasional lamp post.
| codetrotter wrote:
| Lamp!
| cscurmudgeon wrote:
| There is a difference in processing between replying to "Good
| Morning" and typing out a comment on HN like this.
| FrustratedMonky wrote:
| Maybe it's just scale. Because my brain can write something
| longer that was 'thought out', doesn't mean it isn't
| responding like an LLM. Maybe articles on AI just trigger me
| and I spew the same arguments. I think a lot of people have
| just rote responses to many situations, and maybe if they
| have enough rote responses, with enough variety, they start
| to look human, or 'intelligent'. Yeah, its more complicated
| than a bunch of If/Then's. Doesn't make it not mecahnical.
| cscurmudgeon wrote:
| Maybe it's just scale and maybe it's not. We can't say it
| is scale from the evidence so far.
|
| > Maybe articles on AI just trigger me and I spew the same
| arguments. I
|
| But you are not representative of all humans.
|
| > Doesn't make it not mecahnical.
|
| There are mechanical things that are more than just
| prediction machines. Why did you make the "leap non-LLM" ==
| "not mechanical"?
| groestl wrote:
| > But you are not representative of all humans.
|
| I actually started to type almost the same reply as your
| parent earlier, but did not post it. I used "difference
| in quantity, not quality" instead of "scale", but I also
| included the self observation. So maybe that makes two of
| us.
| ben_w wrote:
| Something I've noticed a moment too late, as my automatic
| response used to be to repeat someone's greeting back at them.
|
| Fortunately I stopped only one syllable into "birthday".
| [deleted]
| testcase_delta wrote:
| Does anyone know how this fits with (or not) Chomsky's ideas of
| language processing?
| convolvatron wrote:
| the idea that some linguistic facilities are innate? or the
| government binding model of grammar or something else?
|
| for the first two, I think this orthogonal
| Kinrany wrote:
| Is there a good explanation of the mathematical model of
| predictive coding?
| adamnemecek wrote:
| I'm strongly convinced that the brain works like a Hopf algebra.
|
| https://en.wikipedia.org/wiki/Hopf_algebra
|
| It works by enforcing an invariant between the middle path
| (epsilon -> eta, corresponds to current understanding) and the
| top/bottom paths.
|
| The coalgebra (the delta symbol in the diagram) generates
| possible candidates (predictive coding) that are then passed
| through rest of the path and collapsed and combined in accordance
| with observed phenomena.
|
| Hopf algebra updates the middle path and the top/bottom paths in
| order to unify current understanding with observed phenomena.
|
| The middle path corresponds to the feedback in an electric
| circuit with feedback.
|
| It's the part that prevents the system from wild oscillations.
|
| I have a discord if you want to learn more
| https://discord.cofunctional.ai.
| c3534l wrote:
| That is inscrutably abstract and jargony.
| adamnemecek wrote:
| I don't know how to talk about this without some technical
| terms.
|
| Spend a little bit of time on it, it's a lot more
| understandable than you think.
|
| Peep this paper https://arxiv.org/abs/1206.3620.
|
| I have a discord channel if you want to learn more
| https://discord.cofunctional.ai.
| aatd86 wrote:
| Feynman would say... Oh well, nevermind.
| evolvingstuff wrote:
| You have been shamelessly self-promoting your Hopf algebra/deep
| learning research on a very large percentage of posts I have
| seen on HN lately, to the degree that I actually felt the need
| to log in so as to be able to comment on it. Please. Stop.
| adamnemecek wrote:
| People need to know. Also I'm not promoting my research in
| this port, I'm promoting Hopf algebra.
| ofirg wrote:
| one step closer to being able to "read minds", reading is
| automatic so cooperation is not required
| Jensson wrote:
| Pack animals cooperate that way, lions don't do a scrum meeting
| before they sneak up on a bunch of antelopes, they all just
| predict what the others will do and adapt to that. And it works
| since they all run basically the same algorithms on the same
| kind of hardware.
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