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Storm: LLM system that researches a topic and generates full-length wiki article
- Logans_Run 2y agoOh dear lord .... sub heading states - Storm - Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models Good luck with this storm, wiki's the world over. Just a thought but ... maybe someone should ask an org like the Internet Archive to snap-shot Wikipedia asap and label it Pre-Storm and After-Storm
- tossandthrow 2y agothere is this sentiment of Ai induced deterioration and pollution. what if that is not the case? what if the quality of this type of content actually increases?
- CamperBob2 2y agoIt will for a while, I imagine. But the long-term is a concern. Where will new information come from, exactly?
- tossandthrow 2y agowhy not Ai? And even if we accept the premise (as flawed as it might be) that Ai is not able to create original knowledge, most of what's online is dessimination and dies not represent new information but just old information rewritten to be understandable by a certain segment. something LLMs excel at.
- poyu 2y ago> Ai is not able to create original knowledge The current state of LLMs do hallucinate though. It's just not a very trustworthy source of facts.
- tossandthrow 2y agojust like my first teachers said I should absolutely not use Wikipedia. LLMs was popularized less than 2 years ago. I think it is safe to assume that it will be as trustworthy as you see Wikipedia today, and probably even more as you can embed reasoning techniques into the LLMs to correct misunderstandings. Wikipedia cannot self correct.
- howenterprisey 2y agoWikipedia absolutely self-corrects, that's the whole point!
- tossandthrow 2y agoit does not. it's authors corrects it. unless you see Wikipedia as the organisation and not the encyklopedia? in that case: sigh, then everything self corrects
- howenterprisey 2y agoIt is incoherent to discuss Wikipedia as some text divorced from the community and process that made it, so I'm done here.
- pksebben 2y agoThere's an important difference between wikipedia and the LLMs that are actually useful today. Wikipedia is open, like completely open. GPT is not. Unless we manage to crack the distributed training / incremental improvement barriers, LLMs are a lot more likely to follow the Google path (that is, start awesome and gradually enshittify as capitalist concerns pollute the decision matrix) than they are the Wikipedia path (gradual improvement as more eyes and minds work to improve them).
- tossandthrow 2y agothis is super interesting! it also carves I to the question what constituted model openness? most people agree that just releasing weights are not enough. but I don't think it will ever be feasible to say that reproducing model training is feasible. especially when factoring in branching and merging of models. for me this is an open and super interesting question.
- prionassembly 2y agoI mean, putting a bullet to someone's head can extirpate a brain tumor they hadn't been alerted to before, while leaving a grateful person owing you kudos. What if?
- tossandthrow 2y agoyou can always find some radical regressionist argument that is completely out of contact with anything. congrats on that!
- pksebben 2y agoOn the one hand, a tool is as good or bad as the person wielding it. Smart folks with the right intentions will certainly be able to use this stuff to increase the rate and quality of their output (because they're smart, so they'll verify rather than trust. Hopefully.) On the other, moderation is an unsolved problem. The general mess of the internet is probably not quite ready to be handed a footgun of this caliber. As with many things tech, some of the outcome falls to us, the techies. We can build systems to help steer this.
- tossandthrow 2y ago> On the one hand, a tool is as good or bad as the person wielding it. I think the real reason is one line dogmas like this.
- pksebben 2y agoI'm not sure I follow you - reason for what? To be clear - I'm with you that these systems can absolutely be a force for vast good (at least, I think that was what you were getting at unless there was a missing '/s'). I use them daily to pretty astounding effect. I'll admit to being a little put off by being labeled dogmatic - it's not something I consider myself to be.
- tossandthrow 2y agoit was a half sentence, for that I apologize. and I don't remember entirely what I meant. However, I do see a lot of one-sentence "truthms" being thrown around. like "garbage in; garbage out" and the likest. these are not correct. we can just look at the current state of the art with LLMs that has vast amounts of garbage going in - it seems like the value is in the vastness of the data over the quality. > On the one hand, a tool is as good or bad as the person wielding it. I see this as being a dogme. smart people make good LLMs dumb people do not. but this is an open question. it seems like the biggest wallet will be the winner of the LLM game. please correct me if I misunderstood something.
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- jerf 2y agoThe concern is not just a vaguely cynical hand-wringing about how bad AI is. Feeding AIs their own output as training material is a bad thing for mathematical reasons, and feeding AIs the output of other very similar AIs is close enough for it to also be bad. The reasons are subtle and hard to describe in plain English, and I'm not enough of an expert to even try, so pardon if I don't. But given that it is hard to determine if output is from an AI, AI really does face a crisis of having a hard time coming across good training material in the future.
- tossandthrow 2y agocan you show me a mathematical reason that cannot philosophically be applied to people also? people only being fed other people output.
- jerf 2y agoI'd go with "no", because people just consuming the output of other people is a big ongoing problem. Input from the universe needs to be added in order to maintain alignment with the universe, for whichever "universe" you are considering. Without frequent reference to reality, people feeding too much on people will inevitably depart from reality. In another context, you may know this as an "echo chamber". Not quite exactly the same concept, but very, very similar. I do like to remind people that the AI of today and LLMs are not the whole of reality. Perhaps someday there will be AIs that are also capable of directly consulting the universe, through some sort of body they can use. But the current LLMs, which are trained on some sort of human output, need to exclude AI-generated input or they too will converge on some sort of degenerate attractor.
- tossandthrow 2y agoyep, then we are back a "vaguely cynical hand-wringing about how bad AI is." currently we have mostly LLMs in the mix. but there are no reason that the Ai mix will not contain embodied agents thst also publish stuff in the internet. (think search and rescue bots that automatically write a report). Now Ai is connected to reality without people in the mix.
- skywhopper 2y agoHow could it? LLMs hallucinate false information. Even if hallucinations are improved, the false information they've generated is now part of the body of text they will be trained on.
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- achrono 2y agoLLM mediocrity is just a reflection of human mediocrity, and my bet is on the average LLM to get way better much faster than the average human doing the same.
- _akhe 2y agoAgree with you, but on mediocrity: Mistral barely passes as usable, GPT-4 is barely better than Googling, and nothing else I've tried is even ready for production. So there's some element of the model's design, weights/embeddings, and training data that matters a lot. Only fine-tuned models are producing impressive work, because when we say something is impressive it by definition means not like the status quo - the model must be tuned toward some bias or other, whether it's aesthetic or otherwise, in order to stand out from the rest. And generic models like GPT or Stable Diffusion will always be generic, they won't have a bias toward certain truths - they'll be mostly unbiased which we want for general research or internet search. So it's interesting, in order to get incredible quality of work out of AI, you have to make it specific, but in order to that, you have to train it on the work of humans. I think for this reason AI will always be ultimately behind humans, though it of course will displace a lot of work we do, which is significant.
- singleshot_ 2y agoHumans are limited in the volume of garbage they can produce.
- LeoPanthera 2y agoI saved a full snapshot of Wikipedia (and Stack Overflow) in the weeks before ChatGPT launched, and every day I'm more glad that I did. They will become the Low Background Steel of text.
- jakderrida 2y agoThe thing is that the Wiki mods will need to be more diligent with uncited things. I also see 2 massive opportunities here. First is that they can have agents check the cited source and verify whether the source backs up what's said to a reasonable degree. Second opportunity is fitting in things only found in other language Wikis that either be incorporated into the english one or help introduce new articles. Believe it or not, LLMs can't generate english answers for things answered only in Russian (or any language) in the training data.
- groceryheist 2y ago> First is that they can have agents check the cited source and verify whether the source backs up what's said to a reasonable degree. This is a hard and tmk unsolved NLP/IR problem, and data access is an issue. > Second opportunity is fitting in things only found in other language Wikis that either be incorporated into the english one or help introduce new articles. This has been attempted via machine translation in the past, and it failed because you need native speakers to verify and correct the translations and this wasn't the sort of work that people were jumping to volunteer to do.
- lazyasciiart 2y agoI speak multiple languages. It'd be fun to be given a link saying "this article has content present that is not in the English version" and see if I can update either of the articles using what's in the other copy. But I'm not going to go read wikipedia articles in two languages to find them.
- WhitneyLand 2y ago>>LLMs can't generate english answers for things answered only in Russian in the training data. For multilingual LLM’s? Why do you think that? An LLM can translate inputs of arbitrary Russian text. If there were an English question about something only in the training data as Russian, I would expect an answer - with the quality being on par with its general translation capabilities.
- barbarr 2y agoI guess this is a good thing for increasing coverage of neglected areas. But given how cleverly LLMs can hide hallucinations, I feel like at least a few different auditor bots should also sign off on edits to ensure everything is correct.
- pksebben 2y agoThis method has actually been proven effective at increasing reliability / decreasing hallucinations [1] 1 - https://arxiv.org/abs/2402.05120 https://arxiv.org/abs/2402.05120
- whitehexagon 2y agoHmm something about this title containing the word 'research' disturbs me. I associate that word with rigorous scientific methods that leads to fact based knowledge or maybe some new hypothesis, not some LLM hallucinating sources, references, quotes and all the other garbage they spit out when challenged over a point of fact. Horrifying to think peeps might turn towards these tools for factual information.
- devmor 2y agoYes, I came to the comments to say the same thing. The LLM is not doing research - it is aggregating data associated with terms and reorganizing text based on what previous responses to a similar prompt would look like. At the most generous level of scrutiny, the only part that could be related to research would be the aggregation of sources - but that is only a precursor to research and likely is too generalized to be as accurate as a specialist preparing data for actual research.
- madeofpalk 2y agoThis anthropomorphism really bothers me. These tools are useful for what they’re good for, but I really dislike the agency people keep trying to give to them.
- Terr_ 2y agoI think there's always been fine line between anthropomorphism as a metaphorical way to indicate complexity versus a pitfall where people (especially outside of a field) start acting like it's a literal statement. Ex: "the gyroscope is trying to stay upright", or "the computer complains because the update is broken" or "evolution will give the birds longer beaks". That said, I agree that the problem is dramatically more-severe when it comes to "AI".
- _akhe 2y agoIt should also bother marketers in the AI industry because it confuses people on what the incredible value is. So many people think LLM means chatbot, even here on HN. So many people think agent means mentally humanoid. But we have others, like Stable Diffusion's Web UI and Leonardo.AI - these are just tools with interfaces and the text entry for prompting is not presented as though it's a conversation between 2 people. Someone shared an AI songmaker here recently... And there's a number of promising RAG tools for improving workflows for: Doctors, mechanics, researchers, lawyers. I agree with you and expect the "AI character" use case to narrow significantly.
- agilob 2y agoNucleo AI Alpha An AI assistant app that mixes AI features with traditional personal productivity. The AI can work in the background to answer multiple chats, handle tasks, and stream/feed entries. https://old.reddit.com/r/LocalLLaMA/comments/1b8uvpw/does_free_will_exist_let_your_llm_do_the_research/ https://old.reddit.com/r/LocalLLaMA/comments/1b8uvpw/does_fr...
- spxneo 2y agoI hope somebody took a snapshot of the entire internet before 2020, that is our only defence against knowledge laundry. Wreaking havoc on the digital Akashic records.
- manishsharan 2y agoAt what point will it be just LLM Bots arguing with Other LLM Bots on Wikepedia edits ?
- _akhe 2y agoAs long as the LLM Moderator deems it safe discourse let the best idea win! I'd love a debate between 2 highly-accurate and context-aware LLMs - if such a thing existed. Otherwise it would be like reading HN or Reddit debates where 2 egomaniacs who are both wrong continually straw man each other with statements peppered with lies and parroted disinfo, aint got time for that.
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- pstorm 2y agoI looked into this to see where it was getting new information, and as far as I can tell, it is searching wikipedia exclusively. Useful for sure, but not exactly what I was expecting based on the title.
- pksebben 2y agoThat gives me an idea. There are wikipedias in other languages - Maybe this framework could be adapted to translate the search terms, fetch mulitlingual sources, translate them back, and use those as comparisons. I've found a lot of stuff out through similar by-hand techniques that would be difficult to discover on english search. I'd be curious to see how much differential there is between accounts across language barriers.
- Lerc 2y agoAs a base for researching the idea, Wikipedia seems like a decent data source. For broader implementation you would want to develop the approach further. The idea of sampling other-language Wikipedia mentioned in a sibling comment seems to be a decent next step. Extending it to bringing in from wider sources would be another step. I doubt it would be infallible but it would be really interesting to see how it compares to humans performing the same task. Especially if there were a additional ability to verify written articles and make corrections.
- philipov 2y ago> As a base for researching the idea, Wikipedia seems like a decent data source. If your goal is to generate a wiki article, you can't assume one already exists. That's begging the question. If you could just search wikipedia for the answer, you wouldn't need to generate an article.
- Lerc 2y agoI don't think their goal is to generate a wikipedia article. Their goal is to figure out how one might generate a wikipedia article.
- lukev 2y agoI can see this being useful iif the content is generated on demand and then discarded. Publishing AI generated material is generally speaking a horrible idea and does nobody any good (at least until accuracy levels get much much better.) Even if they do it well and truthfully (which they don't) current LLMs can only summarize, digest, and restate. There is no non-transient value add. LLMs may have a place to help query, but there is no reason to publish LLM regurgitations alongside the ground truth used to generate them.
- tiptup300 2y agoare llms able to look at a list of categories, read content and then determine which of the categories apply?
- warkdarrior 2y agoThis is a very broad question, but in short, yes, they can do this. It depends on the granularity and overlap of those categories.
- msp26 2y agoAbsolutely
- OKRainbowKid 2y agoThis could be achieved by generating embeddings of suitable representations of the categories once, and then embedding the content at runtime, before using some distance metric to find matching categories for the content embedding.
- petercooper 2y agocurrent LLMs can only summarize, digest, and restate. There is no non-transient value add. Though, at a stretch, Wikipedia itself could be considered based around summarization, digesting, and restating/citing things said elsewhere, given its policy of verifiability: "Even if you are sure something is true, it must have been previously published in a reliable source before you can add it." Now, LLMs aren't well known for their citation skills, to be fair.. :-)
- cess11 2y agoKinda weird to promote automated reordering and rephrasing of information as research. What do the authors call what they're doing? Magic?
- brap 2y agoI don’t know how well this works (demo is broken on mobile), but I like the idea. Imagine an infinite wiki where articles are generated on the fly (from reputable sources - with links), including links to other articles (which are also generated) etc. I actually like this sort of interface more than chat.
- rrr_oh_man 2y agoCheck out https://github.com/MxDkl/AutoWiki https://github.com/MxDkl/AutoWiki (there are project with similar names doing stuff like this)
- jankovicsandras 2y agoThis looks cool! There's a small ironically funny typo in the first line: knolwedge
- jankovicsandras 2y agoOne
- _akhe 2y agoThis would be useful for RAG when a Wiki doesn't exist. findOrCreate
- samgriesemer 2y agoSmall thing, but the blurb on the README says > While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage. So it can't produce articles that require many edits? Meaning it can produce publication-ready articles that don't need lots of edits? Or it can't produce publication-ready articles, and the articles produced require lots of edits? I can't make sense of this statement.
- adr1an 2y agoIt gives you a draft that you should keep working on. For example, fact checking.
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- skywhopper 2y agoFrom my experiments, this thing is pretty bad. It mixes up things that have similar names, it pulls in entirely unrelated concepts, the articles it generates are mind-numbingly repetitive and verbose (although notably with slightly different "facts" each time things are restated), its citations are often completely unrelated to the topic at hand, and facts are cited by references that don't back them up. I mean, the spelling and syntax of the sentences is mostly correct, just like any LLM content. But there's ultimately still no coherence to the output.
- wwarner 2y agothis is important as it collects and reports its references. a) it’s the correct paradigm for using llms. b) through human interactions, it can learn from its mistakes.
- zingelshuher 2y agoExpect sh*t load of AI hallucinations. As if Wiki isn't bad enough with BS some intentionally posting.
- aaron695 2y ago[dead]
- ranyume 2y agoWhat's the point of a tool that helps you research a topic if said tool has to approve your topic first? It refused to research my topic because it was sensitive.