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XB, or eXtreme Bullshitting: a less misleading name for LLMs
- DonHopkins 3y agoLarge Lie Models
- usr1106 3y agoLying is intentional. LLMs have no intention, they are just clueless what is true or false
- DonHopkins 3y agoThey're certainly trained on intentional lies! That's kind of the point. Models of lies, not models that lie.
- Retr0id 3y agoThe purpose of a system is what it does
- tudorw 3y agowhich programmatically speaking is very interesting, and yet ultimately just another type of database, in my experience so far, with regards it obsoleti g humanity, as long as you can hold a basic train of thought through a few sentences and distractions without changing the subject or repeating verbatim things you literally just said, and don't consume the energy resources of a small planet then you are mostly fine. As a bit of a programmer it's fascinating to be able to write a yes, no, maybe loop where I hand off ambiguities to the llm for its best guess. human in the loop ftw.
- dymk 3y agoLying does not require intention
- maleldil 3y agoIf you say something untrue that you believe is true, are you lying?
- dijksterhuis 3y ago> A delusion is a false fixed belief that is not amenable to change in light of conflicting evidence. Another way to think of being delusional is “lying to yourself”… > If you say something untrue that you believe is true, are you lying? Personally I’d argue yes. I’m lying to myself and then by proxy to everyone around me. I could say “I don’t know” instead, but I didn’t. But that’s just this human’s opinion.
- deleted 3y ago[deleted]
- maleldil 3y agoI'm not talking about delusion. I mean the simplest case where you acquired some information, have no reason to believe that it is untrue, and convey that to someone else. There's no intention to deceive or any possibility for you to know that your information might be untrue.
- dymk 3y agoYes!
- hdjjhhvvhga 3y ago> Lying is intentional That's an interesting issue. When Gwyneth Paltrow is making strange statements about efficiency of certain procedures or aspects of human health, a lot of what she says is untrue. However, by your definition, she is not lying as she (most probably...) believes what she says. Many people are repeating lies in good faith. The fact they believe them doesn't magically make what they say true.
- usr1106 3y agoInteresting. Of course semantics of natural language is not formally defined. For me it sounds like lying and telling lies is not necessarily the same thing.
- honzabe 3y ago> by your definition I think that is commonly shared definition. We distinguish lying from just being wrong. Saying untrue things in good faith, as Gwyneth Paltrow in your example, is not lying.
- hdjjhhvvhga 3y agoI've just checked what Merriam-Webster says. It seems to accept both meanings but uses inanimate objects for the examples: > 2 > : to create a false or misleading impression > Statistics sometimes lie. > The mirror never lies.
- voidhorse 3y agoWell, yeah. There's a distinction between lying and being incorrect. I do think the parent is right in that when we accuse someone of lying, we're mostly accusing them of making assertions or statements they don't believe to be true (actually, this means that their lies could actually be factually correct—all that really matters is the the author of the utterance does not actually believe in the truth value of what they are saying)
- lamontcg 3y agoIf someone believes their own bullshit/lies or not, you're just as bad off if you believe them.
- pbnjeh 3y agoLazy Loaded Meaning Tempted to write that "Meaning".
- jasonvorhe 3y ago> XB, or eXtreme Bullshitting: a less misleading name for LLMs The author suggests that the term "LLM" (Last Minute Meeting) is misleading and proposes a new term, "XB" (eXtreme Bullshitting), to more accurately describe the pointless and time-wasting nature of these meetings. The tweet has sparked some controversy, with some arguing that not all LLMs are useless and that the new term is disrespectful to colleagues and the meeting process. However, others have praised the author for bringing attention to a common workplace issue. Kind of ironic that this is the ChatGPT summary of this post (I'm following a HN Telegram summary bot) and it hallucinated the meaning of LLM and thereby completely ruined the point the author was trying to make.
- fastball 3y agoSounds like a poorly made bot. I just fed the tweet to ChatGPT and it understood the meaning of "LLM" and responded to the meat of the post.
- gtirloni 3y agoTry this approach instead: https://chat.openai.com/share/9a430f2e-a124-4176-acf3-3211ec1fd062 https://chat.openai.com/share/9a430f2e-a124-4176-acf3-3211ec...
- dotancohen 3y agoThat is impressive. Is that GPT-3.5 or GPT-4?
- nuancebydefault 3y agoI think this proves that LLMs should not be labeled XB
- rgoulter 3y agohttps://en.wikipedia.org/wiki/Bullshit https://en.wikipedia.org/wiki/Bullshit I think "bullshit" is apt. -- As a term, it sometimes means "without caring about the truth". When LLMs output things which aren't true, they aren't trying to trick you.
- RjQoLCOSwiIKfpm 3y agoAnecdotally, I can say that their effect is already bullshitting indeed: When being in a random conversation on the "normal kind-of-average people Internet" (Twitch chat), discussing a subject where the host doesn't know a certain word, people already are pasting ChatGPT definitions of the word into the chat, believing it's some kind of dictionary or whatever. If you tell them it could be completely making things up they'll be like "yeah dunno but it can be a nice overview of the topic". So people will treat it like the new Google, with no idea (or no concern?) that all it does is mash words together because they're likely to occur next to each other in an arbitrarily defined reference dataset of text which was likely downloaded from random places all over the Internet.
- actionfromafar 3y agoNo concern for sure.
- jodrellblank 3y ago> "with no idea (or no concern?) that all it does is mash words together because they're likely to occur next to each other in an arbitrarily defined reference dataset of text" You propagate this meme with no idea (or no concern?) that it's incorrect. LLMs are not Markov chains.
- RjQoLCOSwiIKfpm 3y agoFeel free to prove me wrong with sources :)
- jodrellblank 3y agohttps://youtu.be/qbIk7-JPB2c https://youtu.be/qbIk7-JPB2c about 5 minutes in. > People say it doesn't have a world model but it's not as clean cut as that, it absolutely could build an internal representation of the world and act on it as it progresses through the sentence temporally. Beware of trillion-dimensional space and its surprises, it's very hard for humans to reason about. [...] We shouldn't think about those neural networks as learning simple concepts like 'Paris is the capital of France'; it's doing much more like operators, it's learning algorithms. Inside it, it's not just retrieving information, not at all, it's built internal representation that allows it to reproduce the data that it has seen succinctly. Really you shouldn't think about it as pattern matching and just trying to predict the next word, yes it was trained to predict the next word but what emerged out of this is a lot more than just a statistical pattern matching object. We need to think about it as learning algorithms. [..] it's something very different from what we are used to. - Sebastien Bubeck, Sr. Principal Research Manager in the Machine Learning Foundations group at Microsoft Research
- buro9 3y agoExtreme cargo culting is how I've been thinking about it. It mostly looks correct, but there's no real understanding going on so even if it looks viable you still need the wit to verify whether what you see is actually correct. In our field debugging is harder than writing code and is a distinctly different skill that is mostly gained from experience, this is true of other fields, so whilst a lot of jobs may be replaced by AI the skills needed to support "fewer people doing more" intuitively feels like a higher standard. I also think that appearing to do the right thing is actually "good enough" in most industries and jobs. That there's a lot of people who spend their working days in offices on social media who are going to have a rough decade.
- unyttigfjelltol 3y agoIt's really useful for the entertainment industry. Great copywriting, or rewriting, or perspective taking (tell me what is important about this from the perspective of [blank]). I also enjoy it as an interactive assistant. It's sort of ok with massive error correction for lots of other things, but what I find is prompt engineering is a serious skill to learn, not unlike learning a formal computer language. Maybe even higher effort. So, the barrier to know how to prompt ChatGPT is sort of high, and outside narrow fields the output is not especially useful, which makes it another niche automation tool.
- jacknews 3y agoI'm confused as to which is more BS, the models or this critic..
- juujian 3y agoNot a huge fanboy of LLMs, but is the name really all that misleading? It's a language model, a model designed to produce human language, and it is large, with billions of parameters. So it's quite descriptive.
- gmac 3y agoThe point of the linked tweet (admittedly not obvious from the title here) is that AI is the misleading term.
- moffkalast 3y agoBut it is artificial and intelligent? Also rather descriptive imo. One might also call it general.
- t-3 3y agoNot intelligent. It cannot reason anything, it can only regurgitate and synthesize words without any understanding.
- moffkalast 3y agoEven if that were true, baked-in reasoning is still reasoning. A simple state machine can be intelligent as well if you go by definition.
- deleted 3y ago[deleted]
- YeGoblynQueenne 3y agoThe term "language model" is ... well, let's be kind and not say misleading. Let's say it is over-ambitious given the current technological capabilities. What language models, model, is text, not language. More specifically, language models do not model the human language ability, i.e. the ability of humans to recognise and generate utterances in a natural language, like English. This difference is not some terminological quibble and it has very practical implications about what can be achieved by modelling text, rather than language. See, text is the product of language, but it isn't language. In technical terms, in the context of a corpus of text used to train a language model, language is a hidden, or latent variable that is not directly observable in the corpus and so cannot be modelled directly. That a hidden variable can "not be modelled directly" means that it must be inferred from observations of other variables, to which it is correlated. There are two problems with this, with respect to LLMs trained by Transformers. The first problem is that Transformers are not the right approach to model hidden variables. There are machine learning approaches that can be used to learn hidden variable models, for example various forms of Expectation-Maximisation, like the Viterbi algorithm; Hidden Markov Models; Latent Dirichlet Allocation; etc. But Transformers in particular are not a latent variable model. The second problem is that even latent variable models must be trained with examples of hidden variables in order to be able to predict the distribution of hidden variables in new data, not seen during training. What this means is that in order to train a latent variable model to predict language from text, one needs examples of language, not just text. And where are those examples of language? Remember that when I say "language" I'm talking about the human language ability, which is what, ultimately, produces all language generated by humans. Well, we do not have access to any examples of that human language ability. All we have is examples of its products, or maybe even byproducts. So we can't model that ability. tl;dr: We can't model language, only text, because we can observe no examples of language, only text.
- locallost 3y agoSuperficial Intelligence?
- mark_l_watson 3y agoPeople conflate the ChatGPT demo web app with proper use of Large Language Models. I think proper use is providing your own text and documents as context and then use LLMs for question answering, summarization, etc. It is unsurprising that chat with a LLM without providing lots of context can produce strange results.
- kajaktum 3y agoI think one of the biggest problem with this kind of tools is the inability to know that it doesn't know. It doesn't really know how to be humble besides things that it has been hardcoded to response as such (like giving financial or health advises). I think that every single response from an AI is a liability on the company's part. This is unlike an internet search where it is only displaying links but LLMs are basically synthesizing new contents. If they want to claim that what their AI produces is not merely a derivative of their inputs then I say let them have it (in order to not pay those that the AI gets its information from). Thus, if they do suggest submerging your kid under water for 5 minutes to cure their headache, then such recommendation necessarily comes from the company that provides them. And they should be liable for such posts; just like how every other company would if one of their employee ever suggests such a thing.
- steveBK123 3y agoOK I read the last paragraph and immediately though "I need to go ask ChatGPT something like this". "Does holding your breathe underwater for 5 minutes cure headaches?" Unsurprisingly of course while it said this is not a proven treatment, it did not have the reasoning skills to suggest that, hey that might be dangerous and is an unsafe thing to do, etc. It is funny how many responses it will fill with finger wagging and safety warning, but asking about holding your breath underwater for 5 minutes is not one of them. Makes it even more clear there are 1000s of manual overrides being programmed on top to meet OpenAIs specific world view of moral right & wrong.
- layer8 3y agoEven if ChatGPT had mentioned that it’s dangerous as an answer to your question, ChatGPT at the same time still might have suggested doing the submerging in an answer for a different prompt. The issue is that GPT doesn’t have a consistent model of the world and of its knowledge. That would arguably be a prerequisite before even trying to adjust or correct that model.
- steveBK123 3y ago
- steveBK123 3y agoTheres gonna be so many blackhat use cases for LLMs. For whitehat I think the use cases are narrower than people think. Low stakes things like - feed it your own data, and use its responses as a general direction pointer rather than anything authoritative. Like turning to your coworker who then sends you the correct doc/wiki link that you forgot, but AI. It just strikes me as being like a precocious 12 year old who is well read, overconfident, and occasionally lies. I find ChatGPT basically useless as they've put so many guard rails & programming around the LLM it basically "both sides" everything. It is really just data recall, summarization, and bullshit randomness layer on top.
- sakesun 3y agoAll human are XBers as well.
- gmac 3y agoBig claim. Support for that?
- born-jre 3y agoSplit brain patients, maybe? Edit: not agreeing or disagreeing, but that would be the most probable proof or sth
- ppaattrriicckk 3y agoTaking GP's point to less of an extreme: Are all humans always right in everything that they state?
- fjkccbkkj 3y ago[flagged]
- ppaattrriicckk 3y agoSure, or you know... Rather than ranting on twitter, one could look up "Large Language Model" (LLM), "Deep Learning", "Machine Learning" as well as "Artificial Intelligence" on Wikipedia, and realize that historically the following has been the norm in terminology for decades: Artificial Intelligence > Machine Learning > Deep Learning > LLMs I.e. LLMs are indeed a subset of what is classically considered Artificial Intelligence. Just as well as route planning in Google Maps or getting beat by a non-machine-learning chess algorithm. EDIT: Regarding "for decades" doesn't apply to LLMs, of course :-) and barely to deep learning. But for the time they've been around, this inequality holds
- gmac 3y agoHaving been the norm for decades in that research area doesn't make the term significantly less misleading for everyday usage, though, right?
- ppaattrriicckk 3y agoYeah, nah, I beg to differ: Just because the broader population might not (yet!) have an intuitive understanding of the field, and its shortcomings, I don't think we should rename decades of academic consensus. I have more faith in entire fields of research, at least. I can't make up a good counterexample, so here's a so-so one: Fusion vs. fission power. I've extremely rarely encountered the term "fission" outside of talks about fission power. Yet, I don't think we should call Fusion Power "Star-like energy generation" and Fission Power "never practically encountered power generation, but somewhat like star-like, except the opposite underlying mechanism"
- deleted 3y ago[deleted]
- deltaninenine 3y ago[dead]
- fjkccbkkj 3y ago[flagged]
- Zemtomo 3y ago[flagged]
- emmender 3y ago"GIGO at GBps" as someone put it. LLMs remix and sling BS in infinite ways to create more of the same. We are entering a golden-age of Bull