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"Hallucinating" AIs sound creative, but let's not celebrate being wrong
- glasss 3y agoI really didn't think anyone was applauding the "hallucinations" but maybe I just hang around people who aren't visionaries.
- ethanbond 3y agoI've seen more and more of it over the past few weeks. I work in clinical trials and just recently saw the claim that hallucinations can help researchers "expand the search space for molecules they didn't consider." I'm doubtful...
- 0xfae 3y agoInteresting. If the computer can simulate things that a human wouldn't have thought up, great, but if it's considering things that any sane person knows wouldn't work and passing them off as correct, framing it that way is laughable. That's not brilliant, it's just wrong. If your AI behaves in a way that makes me not trust what it tells me, that's a bug not a feature. But then again, many discoveries have been made because someone trying something that shouldn't work.
- mrbungie 3y agoJust a thought. Hypothesis making may be interpreted as interpolation/extrapolation in a hypothesis space plus some heuristics to reduce that search space based on previous knowledge/valid hypothesis, how much weight you give to said knowledge and evidence, and some soft and hard logic rules. That is in part what allows (some, not counting Dunning–Kruger here) humans how certain to be about what they're arguing/talking about. Maybe if the LLM is refeed with how likely (i.e. how many samples/tokens support it's response) is the output in its datasets, it may reevaluate its confidence and rephrase its answer. In the end, the real problem of hallucinations in LLMs is about its confidence in the correctness/plausability of its own output. But that is something 1) humans can also be guilty of; and 2) that is no purely negative, as it can be exploited to generate new knowledge when applying robust hypothesis validation and testing to said ideas. As you say in your last paragraph, people who've made discoveries in some areas have been treated as insane when tackling problems from a new perspective or when disregarding previous knowledge. If they weren't so strongheaded about their ideas, maybe we wouldn't even be posting in this forum right now. PS: Still, I agree LLMs commit laughable mistakes sometimes ;)
- nomel 3y ago> knows wouldn't work and passing them off as correct, framing it that way is laughable. I don't think this completely true. Considering something that wouldn't work often still leads to ideas, because it kicks your brain of a rut it may be in. This is why it can be incredibly useful to brainstorm with someone that doesn't have expertise in a topic. They'll say zany things that can be inspiring! Random word sequences are a pretty common way to get inspiration. Something more "on topic" can't be that bad.
- jrockway 3y agoI think people like the hallucinations because they seem like the right answer. Imagine I make an AI assistant. You ask it, "how do I catch the bus into town?" If it replies, "run around in your backyard in a circle, then clap 3 times", (i.e. just use a random number generator) you'll think that's junk and will hate the system. But if it says "go to the corner of Main and Pine at 6:53 AM", then you'll probably do that. No matter that there is no bus route on Main or Pine. It sounds right, so you'll want to follow up. I imagine the same applies to searching for novel molecules. "This looks kind of right, I never would have thought of that", so you get a grant to synthesize it, do some clinical trials, and find that it doesn't work at all. But hey, you had something to do for a couple years, and that outcome happened in the non-AI process all the time too. By the time there is enough data that points strongly at the AI suggestions being as good as random chance, the AI gold rush will be over and cashed out. Or, the hallucinations will turn out to be really good and we'll cure cancer or whatever. What matters is that whoever made the model makes a lot of money either way.
- jug 3y agoI mean, statistically it's maybe bound to happen but if it's drowned by bullshit it's probably not a very useful method anyway due to running costs.
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- Zigurd 3y ago"Hallucinating" is really a euphemism for fluent bullshitting. It also doesn't fit the normal understanding of a hallucination. It's just wrong information expressed confidently. Partly it's how the conversational UI works, and partly how the model works. Without the nice generated text that creates in our minds an impression of competence, it would just be an error.
- Grimblewald 3y agobullshitting implies internal knowledge of the deceit, if this were the case we could just train models to not bullshit and tell only the truth. A hallucination, when things are hallucinations, is when the model 'believes' what it is predicting to be equivalent to truth.
- deleted 3y ago[deleted]
- rdedev 3y agoIt's better to treat llms as more of a language encoders and decoders and have some for of intermediate representation where facts are verifiable. Or some form of a validation mechanism that isn't exactly checked against the generated texts. Pretty sure there are people working on integrating stuff like knowledge based but state of the art llms don't seem to have any kind of fact verification mechanism built in
- asow92 3y agoHave you met artists? They're always bullshitting and hallucinating on drugs.
- deleted 3y ago[deleted]
- renewiltord 3y agoFYI this is a fluff article that has zero value. Just skip it if you're curious about LLMs.
- happytiger 3y agoThe LLM AI technology generation is optimized to be fluently conversational and not to be factually correct all the time. 1) Hallucinations often appear because LLMs are designed to create fluent, coherent text. 2) LLMs have no understanding of the underlying reality that language describes. 3) LLMs use statistics to generate language that is grammatically and semantically correct within the context of the prompt. It sacrifices accuracy for being good at conversations as it is designed to do. All these criticisms of hallucinations are missing the point. Generative AI is generative and basically is a specialist at making things up. It’s going to take things like multiprompting, network AIs that fact check output, and a host of other technologies or even entirely new models of AI to solve these problems, but don’t make the mistake of thinking that the system is supposed to be working without hallucinations right now — that’s not what it’s optimized for.
- thfuran 3y agoDid you read the article?
- vinceguidry 3y agoskims article Nope, they summarized it without reading it. Useful enough for those who want to keep a finger to the pulse of AI without a huge time investment. God save me from having to read every article on HN.
- happytiger 3y agoI did. I’m aware. But I thought the comment worth writing anyways. I’m sorry it wasn’t enough of a response to the article for you, but that wasn’t my intention in writing it.
- teaearlgraycold 3y ago> LLMs have no understanding of the underlying reality Not true. They are slowly gaining an understanding of reality by reverse engineering the relationships built into human languages. The only reason LLMs are getting better is because they are better modeling the world. At some point the only way to improve token prediction is to gain an understanding of the world.
- Sohcahtoa82 3y agoI never liked that the term "hallucinating" ended up sticking. The AI doesn't know something so it just invents something. We usually call that "bullshitting", or in more polite crowds, "lying".
- farnsworth 3y agoThat's not a useful description. The AI doesn't "know" what it "knows". It's not even filling some gap in its knowledge. It's just putting words together that statistically can go together.
- famouswaffles 3y ago>The AI doesn't "know" what it "knows". Yes it does. https://news.ycombinator.com/item?id=37874556 https://news.ycombinator.com/item?id=37874556
- SirMaster 3y agoOK, how about we put it this way? Who cares if "it knows" if it's apparently impossible to get it to use that knowledge to stop hallucinating? To me, the end user there is no practical difference between not having the data and not being able to use the data it has. If it can't use it, or refuses to use it, it may as well not exist.
- famouswaffles 3y agoIf you'd bothered to look at the linked papers, you'd see it's not "impossible" to get much better calibration. Just difficult and something that could be further worked on.
- ta8645 3y ago> Who cares if "it knows" if it's apparently impossible to get it to use that knowledge to stop hallucinating? It sounds like you're describing the MSM. In any case, the same problem is true for a fair number of people. The difference is, silicon training has a much better chance of evolving beyond its current limitations much sooner than the typical human.
- swayvil 3y agoSo call it fiction. We like fiction. Truth is hard. Maybe too hard for a mere machine. But dramatic narrative and quirky dialogue might be quite doable. 3000 chapter litrpg fantasy generated overnight.
- duskwuff 3y agoThe problem with using LLMs for fiction is that they lack long-term internal consistency and direction. They can sometimes generate a decent vignette, but establishing (and sticking with!) settings, characters, and plot is still beyond them.
- swayvil 3y agoI imagine a componentized approach to fiction generation. The list of characters is one component. The narrative arc (in the abstract) is another. The world is another. Each dialog chunk, each action chunk, another. Each component AI generated. And each referring to the other components for its construction. For consistency. It could be horribly formulaic but cunning and tasty too.
- LeoPanthera 3y agoThis is an odd article. To me, it seems like the "creative" arts are an ideal arena for AI. After all, there's no such thing as "wrong" art. The article says "well, sometimes what it makes is bad". Well big deal. A lot of human-created art is awful too.
- mjr00 3y ago> This is an odd article. To me, it seems like the "creative" arts are an ideal arena for AI. After all, there's no such thing as "wrong" art. Yeah but who wants to consume art purely generated by AI (that is, not human-created with AI support)? Most art sites have had blanket bans, or at least required tagging, on ai-generated art because people hate it so much. Or to put it another way: why are you in the comment section of Hacker News, and not just asking ChatGPT to generate social media comments on the article?
- km3r 3y agoIf they hate it so much it shouldn't need tagging as it would be naturally lower ranked. Different forms of art (ai or human made) are good for different situations. Commenting on hacker news has a different set of needs and depth that ChatGPT cannot replicate. But I do switch over to chatGPT when trying to get background information about things. Different 'tools' for different needs.
- pixl97 3y ago>If they hate it so much it shouldn't need tagging as it would be naturally lower ranked. Eh, this is a two sided argument. For example, lots of people look at porn. This doesn't mean when I pull up an art/picture site I want to have porn displayed to me. In addition sites that allow porn are typically flooded with massive amounts of that kind of content. If you are a site that wants to show non-pornographic artistic content, in general you have to ban and heavily moderate it or it takes over the site. I can see where the same will be true for AI generated art. Where for human art, one work could take hours, maybe days or far longer to create. Nearly unlimited amounts of AI art could flood a site in days, so much so that even attempting to host content would not be feasible in any way.
- xwdv 3y agoIf an AI doesn’t hallucinate you run into another problem: you start to suspect that the output was copied whole cloth from some other source somewhere and is being passed off as novel.
- einpoklum 3y agoKey sentence for me: > It might be better to say that everything GPT does is a hallucination, since a state of non-hallucination, of checking the validity of something against some external perception, is absent from these models. I try to explain this to people who are obsessed with using ChatGPT to tell them things. So far I've been telling them something like: "it does not attempt to provide you valid information, it's optimizing for what would read like a reasonable continuation of the conversation, which is really not the same thing."
- TeMPOraL 3y ago> "it does not attempt to provide you valid information, it's optimizing for what would read like a reasonable continuation of the conversation, which is really not the same thing." No, but it's quite close - because "reasonable" is positively correlated with "valid, correct information".
- d0mine 3y agoThe same can be said about our brains too. What we think we see is quite different from what our eyes register (e.g., blind spot, hollow-face, colors on contrast backgrounds, etcchttps://m.youtube.com/watch?v=mf5otGNbkuc https://m.youtube.com/watch?v=mf5otGNbkuc
- pixl97 3y agoAlso one to add to your watch list. PBS: Perception Deception https://www.youtube.com/watch?v=HU6LfXNeQM4 https://www.youtube.com/watch?v=HU6LfXNeQM4
- IshKebab 3y agoYet another article that imagines we know of some secret sauce in the human brain that DNNs can't possibly have. One for the dustbin. > Unfortunately, this promotes a misunderstanding of how large language models (LLMs) work... It might be better to say that everything GPT does is a hallucination, since a state of non-hallucination, of checking the validity of something against some external perception, is absent from these models. Let me turn it around: > Unfortunately, this promotes a misunderstanding of how brains work... It might be better to say that every question a human answers without research is a hallucination, since a state of non-hallucination, of checking the validity of something against some external perception, is absent when simply answering a question. Obviously nonsense. If you're going to write an article about misconceptions you'd better make sure you are right! (Though it is silly to celebrate hallucinations; they're definitely not desirable.)
- fragmede 3y agoCuriously enough, I don't get the same result as the author on plain ChatGPT-4. https://chat.openai.com/share/e213e0bd-2838-45e2-9942-e529543be77d https://chat.openai.com/share/e213e0bd-2838-45e2-9942-e52954... https://chat.openai.com/share/64bc62d3-042c-40c4-8d50-8e28ce2af678 https://chat.openai.com/share/64bc62d3-042c-40c4-8d50-8e28ce... Hilariously, plugging the example in the article into Bing enhanced ChatGPT-4, ChatGPT-4 w/ Bing hallucinates because of that very article! https://chat.openai.com/share/4fe50933-8436-44ad-a778-6297cafaad02 https://chat.openai.com/share/4fe50933-8436-44ad-a778-6297ca... If you tell ChatGPT-4 w/ Bing to ignore thereader.mitpress.mit.edu where the article is hosted, it doesn't hallucinate the string "Evolution by Any Other Name?". https://chat.openai.com/share/b8a94a8e-723f-40b6-b7c5-698dcd7cd295 https://chat.openai.com/share/b8a94a8e-723f-40b6-b7c5-698dcd... source: https://chat.openai.com/share/4fe50933-8436-44ad-a778-6297cafaad02 https://chat.openai.com/share/4fe50933-8436-44ad-a778-6297ca...
- 7moritz7 3y ago> Hilariously, plugging the example in the article into Bing enhanced ChatGPT-4, ChatGPT-4 w/ Bing hallucinates because of that very article! Bing does not use the actual GPT 4 model. It's almost certainly a lower parameter model (like 180 billion vs > 1 trillion), or at the very least heavily quantized. That's why it makes more mistakes in your tests.
- wildrhythms 3y agoIsn't the whole point of these LLMs be that they are non-deterministic? And with OpenAI opaquely 'tweaking' the model, it's no surprise you don't get the same output.
- irrational 3y agoIsn't confabulation a better term than hallucination?
- invig 3y agoSo the argument is “Our brains can freewheel generative ideation without mistaking our imagination for fact”. When a human thinks it’s able to determine the difference between imagination and fact, but when a human reads words on a screen it isn’t? Drivel.
- gojomo 3y agoContra the headling, we should "celebrate being wrong" – when it's wrong in fast, interesting, & voluminous ways that can then be filtered or corrected. That's how lots of science, innovation, & learning work: generate many superficially-plausible candidates via a fast-and-loose process, then refine with a more rigorous evaluation. That AIs, in the form of LLMs, are now doing this so well was unexpected, and progress in checking 'hallucinations' is proceeding very fast. (Fortunately, the article is less dismissive than the headline, recognizing these model's potential & mainly urging an understanding of the limitations.)
- Retric 3y agoScience progresses because people are testing plausible ideas not random ideas. We don’t do human trials on random drugs, we do human trials on promising ones. Animal trials are more open but even then candidates are carefully considered as being viable. Things are even more open the earlier you are in drug discovery, but we aren’t testing molecules using Dubnium or most elements on the periodic table. Similarly Ecology isn’t studying what happens when you introduce each type of salt water fish into lakes because the general assumption is they would just die thus saving you from preforming millions of experiments. That basic check for plausibility is extraordinarily valuable across all sciences. There’s no sacred cows here. You do need to validate plausibility just like anything else, but you don’t need to do an exhaustive search across every possibility.
- gojomo 3y agoYes - but even bulk LLM 'hallucinations' are usually plausible, and far from 'random'.
- Retric 3y agoWhat seems plausible depends on your level of suspect matter expertise. Hallucinations are in general ridiculously incorrect and nowhere close to anything worth testing. Put another way what percentage of molecules are worth testing as a viable treatment for epilepsy? 1 in 100 trillion, less? Do you really expect hallucinations to generally pick both plausible and untested targets here?
- hirundo 3y agoThink of requiring a minimum amount of hallucination in AI output as a safety mechanism, like mixing the distinctive odor into a propane tank. The odor is a signal that there's a gas leak that must be dealt with. A high minimum amount of hallucinations is a signal that the source is untrustworthy and must be checked. Hallucinations may turn out to be a feature that protects against over reliance. And defers the need for a Butlerian jihad.
- BryanLegend 3y agoAll thoughts are hallucinations. https://en.wikipedia.org/wiki/Cogito,_ergo_sum https://en.wikipedia.org/wiki/Cogito,_ergo_sum
- delecti 3y ago"I think, therefore I am" means that one of the only things you can be sure of is that, as a thinking entity, you must exist. Thinking the thought "I am thinking", requires that you exist to do that thinking. So unless someone was arguing that LLMs didn't exist, that principle is pretty orthogonal to the discussion.
- Obscurity4340 3y ago*Confabulation
- jordanpg 3y agoWhat is the important distinction between a human dreaming about nonsense and an LLM sounding creative but being wrong?
- Barrin92 3y agoit's just a consequence of the annoying anthropomorphizing of tech. "Human's can't do X, the AI model can't do X, look it's just like me fr, fr". Of course nobody applies that logic to a forklift or a debugger. If gdb started to hallucinate variables into existence we don't call it a creative act, we call it a bug. Given that these AI systems just like any other machine operate at scale, automated, and fast, they must be precise and transparent, that is where the work should be.
- pixl97 3y agoI don't really think you understand the premise of generalization. A forklift is not a generalized machine. It is a specific machine for a very well defined set of tasks. A LLM can take a set of input information, choose a number of options, like using an external tool, and act upon that data.
- nomel 3y agoI'm trying to understand this type of perspective, which is somewhat at odds with mine, so the following questions are completely genuine: Which models have you used? What did you try with them? Have you used GPT-4? How frequently?
- Barrin92 3y agoI use Copilot pretty frequently when I program, find it very useful to explore an API i don't know or just help write bash or other stuff I suck at or just to save me some typing. Still often produces very unidiomatic and non-performant code though. But it's worth it for what it costs. I do have a separate GPT-4 subscription as well but I've used it less and less. Tried to use it for search and text summary but it makes too many mistakes. Invented authors, papers, wrong summaries are just too common for it to be useful. So effectively I found myself Googling every time i used it to make sure the information is correct, which made the entire thing redundant.
- hawski 3y agoWhen I hear the word "hallucination" in my mind appears an image of a crazy guy almost with foam on his mouth, probably on drugs or having severe mental problems. That is not a thing that I associate with being creative and certainly not trust worthy.
- daoboy 3y agoThe term "hallucinating" in this context is just another way we anthropomorphize machines. It is mostly harmless but I see the author's point that it can be misleading when trying to address specific issues. On the (rare) occasion I find it useful to avoid this very normal tendency I ask myself if it would make sense to apply the same framing to the output of an AI image generator.
- navjack27 3y agoLLMs aren't knowledge retrieval systems. Nor are they capable of creativity.
- Grimblewald 3y agosure they are, they're a searchable archive made using a lossy compression algorithm, which is capable of synthesizing creative output from known elements.
- nomel 3y agoCould you define "creativity" for us?
- GuB-42 3y agoAI hallucinations are the opposite of creativity. They give the most obvious wrong answer possible. For example, ask an AI about an unknown basketball player, it will probably describe it at fit and tall, because that's how we expect basketball players to be. That may be a good observation, but certainly not creativity. If instead it told the story of someone short and obese, with details on how he got to play basketball, that would be creative. Of course, you can ask an AI to tell the story of a short and obese basketball player, and it will tell you a likely story for such a player, but again that's not creativity, it is just the AI filling the blanks based on whatever similar stories it had in its training set.
- colanderman 3y agoThis is what the temperature parameter controls. Increase it for less probable (arguably more creative) output.
- ThrustVectoring 3y agoRandomness alone isn't creative. Creativity is the marriage of the improbable and the valuable. Without novel insight into the valuable outer reaches of concept-space, you're not going to generate creative outputs.
- kzrdude 3y agoCreating doesn't mean having to maxmize entropy either. Lots of good stories keep very close to the "obivous" or the well-known.
- chrisco255 3y agoRight, this is also why we don't see breakthroughs in science or literature from AI.
- ttoinou 3y agoHow do you recognize a breakthrough in literature ?
- jacurtis 3y agoHonestly AI's hallucinating isn't a whole lot different than real life. Only a small minority of humans fact check anything anymore before believing it. So "irl", we see people like Alex Jones that get up on their big platforms and start spewing nonsense, but if they sound confident enough and it confirms what you want out of the world, then people latch onto it as fact and don't bother to verify. You see this across the internet. Just today I saw a story on instagram that had been re-posted and the person that was talking about it was many degrees removed from the original, but believed it to be real. Looking through the comments, I had to scroll past 50+ comments to find someone who finally called it out as fake. Everyone else was just posting "no way", "wow, I never knew". You never knew because its completely made up. But when we hear someone speak with confidence and we don't care enough to fact-check, then people just believe it. This is no different than AI. AI models sound confident and reliable. We assume they are making proclamations based on fact but they aren't always (or "usually" in my experience). Many people blindly believe the AI models because they sound reliable and confident in the way they speak. They never say "i don't know". What AI is doing is problematic for sure. On one hand I want to take the pitchforks and revolt. But on the other hand I look around and realize, that even if we fixed it or vanquished this enemy, we still have a bunch of talking heads doing the same thing. Maybe AI hallucinations are actually the most human element of AI.
- pixl97 3y ago>anything anymore You can cut that part out of the statement. Humans in general are terrible at fact checking anything outside of walking outdoors and looking up at the sky. Leaving that in points to some glorious past where people were not idiots, that unfortunately never existed. >But when we hear someone speak with confidence and we don't care enough to fact-check, then people just believe it. When I was a teenager and was learning how people worked I came to the independent discovery of the Big Lie. Telling small lies with components that the listener may have understood didn't work well. But making up a nearly unbelievable fabrication with something the listener did not understand well at all, and saying it with conviction, works a scary percentage of the time.
- invig 3y agoYes! The AI is trained on human behaviour, it’s a mirror. We’re delusional if we think humans are any better at this. I think we’re also delusional if we think we can define what is true. At best we can give an approximation of what we think we know now.
- mritchie712 3y agowho is "celebrating" hallucinations? I've only heard of people trying to "solve" them.
- spandextwins 3y agoI remember when MIT used to do things. Same with RPI and Stanford. Now they just do papers.
- ryukoposting 3y agoSpot-on article, for the most part. I firmly believe that the use of an LLM as a fact-finding tool represents a misunderstanding of the technology's abilities and intent. If you're using an LLM like it's a search engine, then you should just use a search engine instead. LLMs are conversational devices. Search engines are an index of human knowledge. Right tool, right job. I'm fine with the term "hallucination," though. Hallucinations are, by definition, not real. The term emphasizes a detachment from reality that LLMs possess, and the general public is just beginning to grasp.
- pnpnp 3y agoI’m not sure I agree with this one. My Google results have gotten pretty awful lately. I’ll usually go to an LLM for a very specific search term, then Google to find a reference or validate.
- Nevermark 3y agoA few months ago, I didn't imagine I would have completely dumped Google for a huge quality improvement in knowledge acquisition and navigation. The Internet is shiny again!! :) I use GPT4 for questions, and Kagi (paid) for search. I would love to dump Amazon's search. Maybe someone can scrape Amazon (and other stores) and create a universal agnostic LLM product concierge. Please! Besides the conflicts of interest ads/trash-products, searching for a product based on highly specific specs has always been hard.
- pests 3y agoThe chat features are a fine tuning of the LLM tho. Not all LLMs are the conversational chat style.
- rollcat 3y agoHallucination... that's an anthropomorphism. LLMs are functions. They don't make things up, they just sometimes return non-factual data. Which makes complete sense; the model does not have the notion of a fact, otherwise we would be talking about something more like expert systems, or knowledge graphs, not LLMs.
- lxe 3y agoWhat a weird point and conclusions. Yes, we shouldn't treat LLMs as search engines. But who's to say what's creativity and what's not? Glitch art is "wrong" if we apply the author's judgement, but it's still creative.
- galaxyLogic 3y ago"Hallucinate" is the wrong word when applied to LLMs. Why? Because in common usage that means you are under the influence of some kind of external substance that has entered your blood-stream, or maybe you are under hypnosis, or shamanistic chanting. That is not the case when somebody says "LLM is hallucinating, again!", It is also sensationalist, implying we don't really know what's going on, why is this LLM hallucinating? It even sounds like an excuse: Hey my LLM did not come out with reasonable answer, but that is only because it was hallucinating, just like humans sometimes do, so it is even more human-like than we thought. See. Or may it was drunk! That explains it. No, it's just that LLMs are sometimes on the topic, sometimes not. When somebody says they are "hallucinating" it does not mean they are working in some kind of extra-ordinary mode of operation. They are working just as usual. What explains what some people (want to) call LLM "hallucinating" is that LLMs sometimes make sense, sometimes they don't.
- Nevermark 3y agoI couldn't agree more. Words matter and this is a complete mismatch between concepts. > HALLUCINATION: a sensory perception (such as a visual image or a sound) that occurs in the absence of an actual external stimulus and usually arises from neurological disturbance [...] [0] When we let a model run free, without input, or with random input, whatever the model imagined it was experiencing (i.e. its internal representation) would be an hallucination. > CONFABULATION: to fill in gaps in memory by fabrication This is exactly the right concept (and therefore word) for what is happening. [0] https://www.merriam-webster.com/dictionary/hallucination https://www.merriam-webster.com/dictionary/hallucination [1] https://www.merriam-webster.com/dictionary/confabulation https://www.merriam-webster.com/dictionary/confabulation
- galaxyLogic 3y agoGood point. "Hallucination" is about incorrectly perceived input, not incorrect output. When people hallucinate they don't usually react to it verbally at all, they just observe it. Not the case with LLMs. They just keep on saying something, because they are designed to produce answers.
- __rito__ 3y agoBoy, is the author out of loop! Hallucination is always and everywhere used as a negative term for LLMs. And it is seen as a problem/challenge that we should get rid of. Did not read the article after seeing such a wrong title.