[HN Gopher] Evidence of a predictive coding hierarchy in the hum... ___________________________________________________________________ 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 | | The paper is from 2023 but their info is totally out of date.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. ___________________________________________________________________ (page generated 2023-03-10 23:00 UTC)