[HN Gopher] The LLama Effect: Leak Sparked a Series of Open Sour... ___________________________________________________________________ The LLama Effect: Leak Sparked a Series of Open Source Alternatives to ChatGPT Author : gardenfelder Score : 373 points Date : 2023-04-09 16:57 UTC (6 hours ago) (HTM) web link (thesequence.substack.com) (TXT) w3m dump (thesequence.substack.com) | hrpnk wrote: | What's amazing to see is the effort to attempt to run the models | on consumer-grade hardware, going as far as running 4-bit | quantized models on phones or raspberry pi. All the debacle about | mmap optimizations to llama.cpp [1] and the style these were | committed to the product is a great testimony of open source. | Both in the positive aspect (progress) and the negative ones | (visibility affecting human judgement and collaboration). The | sheer amount of experimentation is also providing a standard | interface for different models that can easily be integrated and | tried out. | | [1] https://github.com/ggerganov/llama.cpp | alfor wrote: | What kind of GPU is needed to run the 65B models, can a consumer | grade card do the job? Is it worth it? Or do you use cloud | instances? | AeiumNE wrote: | It's possible to run with a cpu and then use system memory. | superkuh wrote: | You can't fit a 65B even at 4bits (~50GB) on a consumer grade | GPU. With an average geek's home desktop computer running 65B | inference on a CPU with 64GB of system RAM you could expect | about 1 token every 2 seconds. | [deleted] | adeon wrote: | I'm a bit worried the LLaMA leak will make the labs much more | cautious about who they distribute models to for future projects, | closing down things even more. | | I've had tons of fun implementing LLaMA, learning and playing | around with variations like Vicuna. I learned a lot and probably | wouldn't have got so interested in this space if the leak didn't | happen. | echelon wrote: | If the copyright office determines model weights are | uncopyrightable (huge if), then one might imagine any | institutional leak would benefit everyone else in the space. | | You might see hackers, employees, or contractors leaking models | more frequently. | | And since models are distilled functionality (no microservices | and databases to deploy), they're much easier to run than a | constellation of cloud infrastructure. | pclmulqdq wrote: | Shouldn't that be the default position? The training methods | are certainly patentable, but the actual input to the | algorithm is usually public domain, and outputs of algorithms | are not generally copyrightable as new works (think of | to_lowercase(Harry Potter), which is not a copyrightable | work), so the model weights would be a derivative work of | public domain materials, and hence also forced into the | public domain from a copyright perspective. | | They are generally trade secrets now, which is what actually | protects them. Leaks of trade secrets are serious business | regardless of the IP status of the work otherwise. | vkou wrote: | I like your legal interpretation, but it's way too early to | tell if it is one that accurately represents the reality of | the situation. | | We won't know until this hits the courts. | pclmulqdq wrote: | For what it's worth, I've been working on a startup that | involves training some models, and this is likely how | we're going to be treating the legal stuff (and being | very careful about how customers can interact with the | models as a consequence). I assume people who have | different incentives will take a different view, though. | mattmcknight wrote: | Even if the weights are copyrighted, running one more epoch | of fine-tuning will result in different weights. At a certain | point, they'd have to copyright the shapes of the weight | vectors. | Szpadel wrote: | is uncertain, as with codding you need white room methods | to prove that new code is not contaminated with patented | implementation, as it might be here, so basing anything on | an existing model could be also copyrighted. | 0x0000000 wrote: | Clean room implementation is not a defense against | patents, it is a defense against copyright infringement. | amrb wrote: | Devil's Advocate: The EU comes down hard on any AI company that | doesn't work with researchers and institutions in future. | RhodesianHunter wrote: | Outright banning due to fear seems far more likely. | amrb wrote: | I mean it's a good power tool, cuts fast with little | effort. | | But what's it gonna do in the hands of your parents or | kids.. when it gets thing wrong, its could have way worst | impact if it's intergrated in government, health care, | finance etc.. | [deleted] | [deleted] | oliwarner wrote: | On the other side of the coin, they've distracted a huge amount | of attention from OpenAI and have open source optimisations | appearing for every platform they could ever consider running | it on, for no extra expense. | | If it was a deliberate leak, it was a good idea. | lagniappe wrote: | An alternative interpretation was the LLaMa leak was an effort | to shake or curtail the progress of ChatGPT's viral dominance | at the time. | seydor wrote: | "And as long as they're going to steal it, we want them to | steal ours. They'll get sort of addicted, and then we'll | somehow figure out how to collect sometime in the next | decade". | | That was ironically Bill Gates | | https://www.latimes.com/archives/la-xpm-2006-apr-09-fi- | micro... | rileyphone wrote: | It took him a while to come around | | https://en.wikipedia.org/wiki/An_Open_Letter_to_Hobbyists | elcomet wrote: | They clearly expected the leak, they distributed it very widely | to researchers. The important thing is the licence, not the | access: you are not allowed to use it for commercial purpose. | nkzd wrote: | How could Meta ever find out your private business is using | their model without a whistleblower? It's practically | impossible. | tel wrote: | Have reasonable suspicion, sue you, and then use discovery | to find any evidence at all that your models began with | LLaMA. Oh, you don't have substantial evidence for how you | went from 0 to a 65B-parameter LLM base model? How curious. | halotrope wrote: | You can just ask if there is no output filtering | guwop wrote: | The future is going to be hilarious. Just ask the model | who made it! | barbariangrunge wrote: | Does the model know, or will it just hallucinate an | answer? | PufPufPuf wrote: | Yes, that's how software piracy has always worked. | ben_w wrote: | I think you can make that argument for _all_ behind-the- | scenes commercial copyright infringement, surely? | isoprophlex wrote: | Is this a tactical leak, stemming from a "commoditize your | complement" strategy? Open source as a strategic weapon, without | having to explain board members/shareholders/whatever that you | threw around money on training an open sourced model? | nailer wrote: | It's not open source. Llama is proprietary, the license hasn't | changed. Just like the source code to windows leaking doesn't | make windows open source. | bugglebeetle wrote: | I would assume so. Meta's ML/AI team is very strong, but they | probably don't have a comparable product offering to ChatGPT | ready for public use. So instead, they bought themselves some | time by letting the open source community run wild with a | lesser model and eat into OpenAI's moat. | oezi wrote: | What would you think is holding back Meta and Google? Why | can't they just scale up the compute they throw at the | problem? | | What are they tinkering on? | bugglebeetle wrote: | I think Meta's problems are largely similar to Google's: | they have very bad leadership, specifically Zuckerberg, and | thus can't leverage their existing talent to | execute/compete. The whole Metaverse fiasco would seem to | demonstrate he's effectively a "mad king" at this point, | and probably surrounded by a sycophantic c-suite. Having | the best talent in the world (which they obviously do by | how fast LLama was spit out) isn't going to matter that | much if its all serving at the behest of someone who has | become deluded by their initial success and has no ability | to course correct. | BulgarianIdiot wrote: | They didn't leak it. Someone else did. | blameitonme wrote: | I dont think theyre saying Meta AI leaked it, but they | anticipated someone else will and still went ahead with it | as they wanted the consequences. | jjoonathan wrote: | It's extremely common for a "leak" to actually be fully | intentional, but the organization in question just wants | plausible deniability to mitigate legal/political/popular | blowback. | | In order to preserve plausible deniability, the leak will | look genuine in all aspects that are easy to simulate. | "Someone else did it" is easy to simulate. A better gauge | would be to see if anyone is caught and punished. If so, it | was probably a real leak. | ericpauley wrote: | I think the key here is that, given the way that Meta | distributed the model, a leak was inevitable. So while they | may not have directly orchestrated a leak it must have been | an intended result. | greyface- wrote: | They have tacitly endorsed the leak. https://github.com/fac | ebookresearch/llama/pull/73#issuecomme... | Mathnerd314 wrote: | That's a contributor to the repo, not someone with commit | access. | greyface- wrote: | A contributor who is also a Facebook employee and co- | author of the LLaMA paper, presumably speaking in | official capacity. | barbariangrunge wrote: | Why would you presume that by default? Need a quote to | conclude that | jagrsw wrote: | It's widely presumed within faang-type-of companies that | anything an employee says or does can be interpreted as | an official company statement, especially by the press. | As a result, many of these companies offer, often | mandatory, trainings that underscore the importance of | speaking carefully in public, since one's words can end | up on the front page of a popular newspaper. | | Although I don't know how FB rolls internally, it seems | more likely than not to me, that it was ack'd by someone | higher up in the organization than line engineers or | managers. Someone with a permission of speaking publicly | for a given area of a company - doesn't need to be CEO, | more like a VP/Director maybe. | [deleted] | yieldcrv wrote: | Only because publicly visible actions are worse for them | | People have gotten DMCA takedown requests from them over | Llama repositories | greyface- wrote: | If they were interested in limiting distribution, saying | essentially "go ahead and seed this torrent more" is | worse for them than doing nothing. | yieldcrv wrote: | I've actually beat the streisand effect before by not | responding. | | The crowd gets bored and my DMCA requests flurry out a | month later and all evidence disappears, individuals that | might notice dont have the crowd to amplify that they | noticed. | | You can call that "tacit consent" if you want. But | streisand removes all leverage. | whimsicalism wrote: | It appears there is this genre of articles pretending that LLAMA | or its RL-HF tuned variants are somehow even close to an | alternative to ChatGPT. | | Spending more than a few moments interacting even with the larger | instruct-tuned variants of these models quickly dispels that | idea. Why do these takes around open-source AI remain so popular? | What is the driving force? | tyfon wrote: | > Why do these takes around open-source AI remain so popular? | | I can only speak for myself, but I have a great desire to run | these things locally, without network and without anyone being | able to shut me out of it and without a running cost except the | energy needed for the computations. Putting powerful models | behind walls of "political correctness" and money is not | something that fits well with my personal beliefs. | | The 65B llama I run is actually usable for most of the tasks I | would ask chatgpt for (I have premium there but that will lapse | this month). The best part is that I never see the "As a large | language model I can't do shit" reply. | [deleted] | itake wrote: | I think it's hard to verify and those articles get clicks. | | Similar to vein of articles promising self driving cars in | 202x | kristianp wrote: | How do you run it locally? llama.cpp + 64GB RAM + 4bit | quantized? | tyfon wrote: | I have a 5950x with 64 gb ram and they are quantized to 4 | bit yes :) | | The weights are stored on a samsung 980 pro so the load | time is very fast too. I get about 2 tokens/second with | this setup. | | edit: forgot to confirm, it is llama.cpp | | edit2: I am going to try the FP16 version after easter as I | ordered 64 GB of additional ram. But I suspect the speed | will be abyssal with the 5950x having to calculate through | 120 gb of weights. Hopefully some smart person will come up | with a way to allow the GPU to run off system memory via | the amd infinity fabric or something. | barbariangrunge wrote: | I thought it needed 64gb of vram. 64gb of ram is easy to | obtain | apetresc wrote: | How have you managed to run the 65B model? Cloud resources, | or you have a very kitted-out homelab? | sp332 wrote: | If you're not running on GPU, you can upgrade your system | RAM instead of finding a card with lots of VRAM. 64GB of | DDR4 is only $120. | trifurcate wrote: | All you need is 2 3090s. | digitallyfree wrote: | Privacy and security is a big desire for the people running | these lower-quality local models. These assistants are becoming | more and more powerful and people want to use them for personal | tasks. For instance someone might want to chat about their | inner feelings or ask the AI to pen a confidential letter, | things that they wouldn't want to send to a cloud service. We | saw the same thing with Stable Diffusion and how people would | spend a lot of effort getting it to run on their machines so | they wouldn't have to rely on a public instance. | | I'm talking about individual people here as the fact that this | is a leak means that corps probably won't take the legal risk | of trying this out (maybe some are doing so in secret). In the | business world there definitely is a want for locally hosted | models for employees that can safely handle confidential inputs | and outputs. | | The Llama models are not as good as ChatGPT but there are new | variants like Alpaca and Vicuna with improved quality. People | are actively using them already to help with writing and as | chatbots. | micimize wrote: | I had the same reaction after seeing lots of "chatgpt on a | phone" etc hype around alpaca. Like I knew it wouldn't be | close, but was surprised at just how useless it was given the | noise around it. Nobody who was talking about it had used it | for even five minutes. | | This article is almost criminally imprecise around the "leak" | and "Open Source model" discussion as well. | matrix_overload wrote: | ChatGPT being an ultra-hot topic, so every article tangentially | related to it gets twice the views? | anonzzzies wrote: | It is vastly better than anything else so far though. The | rest will catch up but openai is not sleeping and they are | well funded. | jhbadger wrote: | I thought that was the case before trying Vicuna. I agree | that LLaMA and Alpaca are inferior to ChatGPT but I'm | really not sure Vicuna is. It even (unfortunately) copies | some of ChatGPT's quirks, like getting prudish when asking | it to write a love scene ("It would not be appropriate for | me to write...") | whimsicalism wrote: | I admittedly have not interacted with Vicuna yet. | sp332 wrote: | Have you tried koala? | seydor wrote: | is gpt4Xalpaca better? | nabakin wrote: | I've tried Vicuna but it still seems inferior to ChatGPT | imo. Maybe if it was applied to a version of LLaMA with a | number of parameters matching GPT-4 but I'm not sure of | that either | seydor wrote: | > Why do these takes around open-source AI remain so popular? | What is the driving force? | | people like to tinker with things until they break and fix | again. that's how we find their limits | | People constantly try to break chatGPT too (i d wager they | spend more time on that than real work). However talking to an | opaque authoritarian chatbot, no matter how smart, gets boring | after a while | throw778899 wrote: | quite funny that the weights leaked & the senior author then left | to build an llm startup | amrb wrote: | I love the human factor, llama was a thing only research would of | had access too, of course it leaked and everyone swarms to get it | a try and we get some first class support for apple hardware! | seydor wrote: | Someone needs to legally challenge openAI on using the output of | their models to train other commercial models. If web scraping is | legal, then this must be legal too , even if openAI tries to | curtail it. After all it was all trained on data they don't have | rights to. | api wrote: | ... and given that models may not be copyrightable unless | trained on data to which the trainer has full rights. | qwertox wrote: | Website content can be copyrightable, so web scraping for | commercial use being legal would be dubious. But even OpenAI | can't tell what ChatGPT will output, so I don't see how this | can be copyrightable. Should the outputted sentences really be | owned by OpenAI? | int_19h wrote: | They are not claiming copyright on the output, but instead | make it a part of their terms of use, so it's basically the | EULA debate all over again. | coding123 wrote: | what's weird to me though, is that we're all trained on both | open source and closed source source material. And our output | is totally 100% copyrightable by us. | | Why wouldn't we extend the same muster to computer generated | text. If there is a copy-written sentence, go after that? | | I don't work for openai, but I don't like 1 sided arguments | that are just looking for some bottom line. At the end of the | day we all have something to protect. When it benefits us to | protect something, we're all for it. When it benefits us to NOT | protect something, no one has a single argument for that. | cycomanic wrote: | We make distinction between humans and computers all the | time. They function distinctively different. For example I | can "turn off" a computer, but it would be illegal to do with | a person. | | More seriously and closely to the case at hand. I need a | licence to copy a program into memory on the computer, I | don't need that licence to do that for a human. So why should | there not be a difference for the material they output. | danShumway wrote: | Copyright is a practical right, not an inherent right. The | only reasons humans get copyright at all is because it's | useful for society to give it to them. | | The onus should be on OpenAI to prove that it will benefit | society overall if AIs are given copyright. We've already | decided that many non-human processes/entities don't get | copyright because there doesn't seem to be any reason to | grant those entities copyright. | | ---- | | The comparison to humans is interesting though, because | _teaching_ a human how to do something doesn 't grant you | copyright over their output. Asking a human to do something | doesn't automatically mean you own what they create. The | human actually doing the creation gets the copyright, and the | teacher has no intrinsic intellectual property claim in that | situation. | | So if we really want to be one-to-one, teaching an AI how to | do something wouldn't give you copyright over everything it | produces. The AI would get copyright, because it's the thing | doing the creation. And given that we don't currently grant | AIs personhood, they can't own that output and it goes into | the public domain. | | But in a full comparison to humans, OpenAI is the teacher. | OpenAI didn't create GPT's output, it only taught GPT how to | produce that output. | | ---- | | The followup here though is that OpenAI claims that it's OK | to train on copyrighted material. So even if GPT's output was | copyrightable, that still doesn't mean that they should be | able to deny people the ability to train on it. | | I mean, talk about one-sided arguments here: if we treat GPT | output the same as human output, then is OpenAI's position | that it can't train on human output? OpenAI has a TOS around | this basically banning people from using the output in | training, which... probably that shouldn't be enforceable | either, but people who haven't agreed to that TOS should | absolutely be able to train AI on any ChatGPT logs that they | can get a hold of. | | That is exactly what OpenAI did with copyrighted material to | train GPT. It's not one-sided to expect the same rules to | apply to them. | oceanplexian wrote: | > The comparison to humans is interesting though, because | teaching a human how to do something doesn't grant you | copyright over their output. | | Ehh, in rare cases in can though. If you have someone sign | an NDA, they can't go and publish technical details about | something confidential that they were trained on. For | example, this is fairly common in the tech industry when we | send engineers to train on proprietary hardware or | software. | vkou wrote: | > Ehh, in rare cases in can though. If you have someone | sign an NDA, they can't go and publish technical details | about something confidential that they were trained on. | For example, this is fairly common in the tech industry | when we send engineers to train on proprietary hardware | or software. | | And I think nearly everyone would agree that it would be | perfectly fine and reasonable for an AI trained on a | proprietary corpus of information to produce | copyrightable/secret material in response to questions. | | Just because I built an internal corporate search tool, | doesn't mean that _you_ get to view its output. | | The question at play here is when the AI is trained on | information that's in the public commons. The 'teacher' | analogy is, in this sense, a very good one. | danShumway wrote: | I would push back on that for a couple of reasons: | | First, what's happening in those scenarios where an | artist grants copyright to a teacher/commissioner is that | the artist gets the copyright, and then separately signs | an agreement about what they want to do with that | copyright. | | But an NDA/transfer-agreement doesn't change how that | copyright is generated. It's a separate agreement not to | use knowledge in a particular way or to transfer | copyright to someone else. | | More importantly, is the claim here that GPT is capable | of signing a contract? Because problems of personhood | aside, that immediately makes me wonder: | | - Is GPT mature enough to make an informed decision on | that contract in the eyes of the law? | | - Is that "contract" being made under duress given that | OpenAI literally owns GPT and controls its servers and is | involved in the training process for how GPT "thinks"? | | Can you call it informed consent when the party drawing | up the contract is doing reinforcement training to get | you to respond a certain way? | | ---- | | I mean, GPT does not qualify for personhood and it's not | alive, so it can't sign contracts period. But even if it | could, that "contract" would be pretty problematic | legally speaking. And NDAs/contracts don't change | anything about copyright. It's just that if you own | copyright, you have the right to transfer it to someone | else. | | Just to push the NDA comparison a little harder as well: | NDAs bind the people who sign them, not everyone else. If | you sign an NDA and break it and I learn about the | information, I'm not in trouble. So assuming that ChatGPT | has signed an NDA in specific -- that would not block me | from training on ChatGPT logs I found online. It would (I | guess) allow OpenAI to sue GPT for contract violation? | [deleted] | [deleted] | tdullien wrote: | We decided that animals can't create copyrightable works and | hence limited the ability to create copyrightable works to | _humans_. | | I am fine with granting AIs the ability to create | copyrightable works _provided_ we grant that right, and human | rights, to Orcas and other intelligent species. | kbrkbr wrote: | Animals seem ok with it. At least they did not indicate | otherwise so far. | crote wrote: | Let's say I were to create an algorithm which generated every | possible short story in the English language using Markov | chains. Should I be able to copyright all those generated | stories, thus legally preventing any other author from ever | writing a story again? | danShumway wrote: | IANAL but I really don't see how a case here would go in | OpenAI's favor in the long run, except maybe if someone | actually agreed to their EULA? | | And I really suspect that a lot of AI companies are putting out | a lot of bluster about this and are just kind of hoping that | nobody challenges them. _Maybe_ LLaMA weights are | copyrightable, but I would not take it as a given that they | are. | | I vaguely suspect (again IANAL) that companies like | Facebook/OpenAI might not be willing to even force the issue, | because they might be happier leaving it "unsettled" than going | into a legal process that they're very likely to lose. I would | love to see some challenges from organizations that have the | resources to issue them and defend themselves. | | Hiding behind the EULA is one thing, but there are a lot of | people that have never signed that EULA. | rmdashrfstar wrote: | > If web scraping is legal Source? That LinkedIn case did not | resolve how you think it did. | mountainriver wrote: | It's legal but if you don't consent to people doing it in | your robots.txt you can sue them civilly | bri3d wrote: | My understanding is that the current web scraping situation | is this: | | * Web scraping is not a CFAA violation. (EF Travel v. Zefer, | LinkedIn v. hiQ). | | * Scraping in spite of clickthrough / click-in ToS | "violation" on public websites does not constitute an | enforceable breach of contract, chattel trespass (ie - | incidental damage to a website due to access), or really mean | anything at all. This is not as clear once a user account or | log-in process is involved. (Intel v. Hamidi, Ticketmaster v. | Tickets.com) | | * Publishing or using scraped data may still violate | copyright, just as if the data had been acquired through any | means other than scraping. (AP v. Meltwater, Facebook v. | Power.com) | | So this boils down to two fundamental questions that will | need to get answered regardless of "scraping" being involved: | "is GPT output copyrightable" and "is training a model on | copyrighted data a copyright infringement." | visarga wrote: | Is training a model on second-hand data laundering | copyright? Second-hand data is data generated from a model | that has been trained on copyrighted content. | | Let's say I train a diffusion model on ten million images | generated by diffusion models that have seen copyrighted | data. I make sure to remove near duplicates from my | training set. My model will only learn the styles but not | the exact composition of the original dataset. So it won't | be able to replicate original work, because it has never | seen any original work. | | Is this a neat way of separating ideas from their | expression? Copyright should only cover expression. This | kind of information laundering follows the definition to | the letter and only takes the part that is ok to take - the | ideas, hiding the original expression. | sebzim4500 wrote: | The judgement of the LinkedIn case was that if the scraping | bots had 'clicked the button' to accept terms then they | should be held to those terms. | seydor wrote: | If openAI tries to legally claim against this, they will be | reminded that their model is trained on tons of unlicensed , | scraped without consent content. If their training is legal, | then this one is legal too | EGreg wrote: | I am shocked that it speaks the way it does when it was trained | on random stuff it doesn't have rights to. | | They say they trained it on databases they had bought access to | etc. And it seems that way. | | Because how does ChatGPT: | | 1. Do what you ask instead of continuing your instructions? | | 2. Use such nice and helpful language as opposed to just random | average of what people say? | | 3. And most of all -- how does it have a structure where it | helpfully restates things, summarizes things, warns you against | doing dangerous stuff... no way is it just continuing the most | probable random Internet text!! | jacquesm wrote: | There is a lot of massaging of inputs and outputs but at the | same time: that's done by tweaking the model reinforcing | those parts that are desirable and suppressing those parts | that are not, not by rewriting the output, though there may | be filters that check for 'forbidden fruits'. And it isn't | the 'random average' of what people say, that would give you | junk, the whole idea is that it tries to get to something | _better_ than a random average of what people say. | | And by curating your sources you are of course going to help | the model to achieve something a bit more sensible as well. | Finally: you are probably not looking at just one model, but | at a set of models. | WalterBright wrote: | I'd like the version without the "sanitized for my | protection" part. I cannot imagine being offended by what a | computer program generates. | rajansaini wrote: | Read the InstructGPT paper and see alpaca. You just need | instruction fine-tuning. | | Unlike what the other commenters are saying, RLHF, while | powerful, isn't the only way to get an LLM to follow | instructions. | seydor wrote: | It is steered by RLHF to give helpful, nice, structured | continuations. it was totally trained on random text they | never paid a dime for. | EGreg wrote: | Can you please elaborate and answer 1,2,3 directly -- I'd | love to find out more. Maybw links to the techniques | seydor wrote: | I am not an expert but as others have said, the | InstructGPT and Alpaca models do that | | https://arxiv.org/abs/2203.02155# | | https://crfm.stanford.edu/2023/03/13/alpaca.html | klyrs wrote: | Yeah, I'm particularly curious about that -- there's already | legal precedent in the US that an AI cannot author copyrighted | nor patented work. OpenAI can try to curtail it through a | clickwrap agreement, but those are notoriously weak. | egillie wrote: | And even if they do, if someone uses the api and makes a | publicly available website with no clickwrap, it would be | legal to scrape that right? | YetAnotherNick wrote: | It is just a copyright violation. My guess is that it would | be fine if you use already scraped data as you haven't | accepted TOS, but they have every right to block you or | access to your business if you violate this. | itake wrote: | I thought the copyright office said that ai generated | material isn't copyrighted? | YetAnotherNick wrote: | Sorry, can't edit my comment now. I meant it is "not a | copyright violation, but just a TOS violation." | aardvarkr wrote: | You're correct. US law states that intellectual property | can be copyrighted only if it was the product of human | creativity, and the USCO only acknowledges work authored | by humans at present. Machines and generative AI | algorithms, therefore, cannot be authors, and their | outputs are not copyrightable. | hanselot wrote: | Sorry for asking a stupid question. | | How much Theseus do I need to ship before I can copyright | it as my own? Is there some threshold for how much of an | AI generated work needs to be modified by "human | creativity" prior to it being copyrightable? | klyrs wrote: | As far as I can tell, you can claim credit for the output | of a tool which produces something at your direction. If | you write an algorithm to generate patents, and you | execute that algorithm and submit its output to USPTO | under your own name, no problem. If you gave credit to | the algorithm, their policy is to deny the claim. | JumpCrisscross wrote: | Can OpenAI claim copyright on GPT's outputs? | tintedfireglass wrote: | definetly. I don't think it's right when openai scraped data | without consent from other resources. I feel that if openai can | get data from the internet bard or someone else too can do it. | Now being that chatgpt is also a part of the internet it's a | fair game IMHO. | doubtfuluser wrote: | [Edited] Isn't the copyright question a red-Hering? We are | talking about models on the verge of generating output not | distinguishable from human output. How is then a copyright breach | - if it's only caused by AI, but not by human - enforced long | term? | | I'm not in favor of the 6 month moratorium- but seriously, we are | going to face tough questions very soon - and they will shake a | lot of assumptions we have. | | We should now really act as society to get standards in place, | standards that are enforceable. Otherwise the LeCun's et al. Will | have some pretty bad impact before we start doing something. | | We need to work on this globally and fast to not screw it up. I'm | nowadays more worried than ever about elections in the near | future. Maybe we will have something like real IDs attached to | content (First useful use case for crypto) or maybe we will all | stop getting information from people we don't know (yay filter | bubble). I hope people smarter than me will find something. | superkuh wrote: | I've spent an embarassing amount of time since the llamas leaked | playing with them, the tools to run them, and writing wrappers | for them. They are technically alternatives in the sense that | they're incomparably better chat bots than anything in the past. | But at least for the 30B and under versions (65B is too big for | me to run), no matter what fine tuning is done (alpaca, gpt4all, | vicuna, etc), the llamas themselves are incomparably worse at | doing useful tasks than openai's gpt3.5 models like text- | davinci-003, or even the gimped gpt3.5-turbo. | | I wish it wasn't so, but the llamas are toys. Amazing toys, but | toys. What openai is getting out of gpt3.5 (and presumbably 4, | though I have no access) are actually useful responses for | getting work done. | seydor wrote: | > (just a hobby, won't be big and professional like gnu) | | Llamas are creating the linux of AI and the ecosystem around | it. Even though openAI has a head start, this whole thing is | just starting. Llammas are showing the world that it doesn't | take monopoly-level hardware to run those things. And because | it's _fun_ , like, video-game-fun there is going to be a lot of | attention on them. Running a fully-owned, uncensored chat is | the kind of thing that gets people creative | danShumway wrote: | This is my hope as well. It would be disastrous if the future | of AI is one where only megacorps can run it and where they | control all access to it. In that sense, LLaMA is really | encouraging and I'm seriously rooting for it to improve. | | It's just not there yet. I tend to be kind of bearish on LLMs | in general, I think there's a lot more hype than is | warranted, and people are overlooking some pretty significant | downsides like prompt-injection that are going to end up | making them a lot harder to use in ubiquitous contexts in | practice, but... I mean, the big LLMs (even GPT-3.5) are | definitely still in a class above LLaMA. I understand why | they're hyped. | | I look at GPT and think, "I'm not sure this is worth the | trouble of using." But I look at LLaMA and I'm not sure | how/where to use it at all. It's a whole different level of | output. | | But that doesn't mean I'm not rooting for the "hobbyists" to | succeed. And it doesn't mean LLaMA _can 't_ succeed, it | doesn't necessarily need to be better than GPT-4, it just | needs to be good enough at a lot of the stuff GPT-4 does to | be usable, and to have the accessibility and access outweigh | everything else. It's just not there yet. | amrb wrote: | LoRa has been pretty popular and untill the llama leak was | not aware of it, maybe will see something cool out of the | open assistant project, we have a lot of English and | Spanish prompts and was crazy to see people doing an | massive open source project for ML. | syntheweave wrote: | I think there's a case to be made for the bottom of the | market being the important part. | | The aspects of LLMs that resemble AGI are pretty exciting, | but there's a huge playspace for using the model just as an | interface, a slightly smarter one that will understand the | specific computing tasks you're looking for and connect | them up with the appropriate syntax without requiring | direct encoding. | | A lot of what software projects come down to is in the | syntax, and a conversational interface that can go a little | bit beyond imperative command and a basic search box | creates possibilities for new types of development | environments. | inciampati wrote: | They can be modified to produce qualities of output that are | unique. This puts them back in the realm of individual | control. I will put the human in the artificial in a way that | is not true with the industrial models. | iamflimflam1 wrote: | GPT-4 is pretty mind blowing. It can follow very complex | prompts that 3.5 struggles with. | hrpnk wrote: | What this also shows is the degree of control that a single | company has over the market. At a time where GPT-4 is | integrated into products while others are on the waitlist, | competition can move far ahead of a company that's just trying | to gain access to the technology w/o clear insights on the | prioritization approach. As said, there just are no | alternatives at the moment, so to a degree competition is | skewed. | Al-Khwarizmi wrote: | In my particular tests (YMMV), even 13B vicuna beats Bard, | though... tough times for Google. | morrbo wrote: | massive YMMV moment for me. my particular usecase was | "extract the following attributes from a load of unstructured | text, format the results as JSON". ChatGPT was the best (but | only on 4 and Davinci), Vicuna just didn't perform at all | (nor other variants of llama 7/13/33). Bard smashed it, | relatively speaking, in terms of speed. I gave up pretty | quickly though because of no information on pricing and/or | API. It's funny how all-or-nothing these things seem to be | cubefox wrote: | Your conclusion seems not to be warranted since you haven't | tried out the 65B model. | superkuh wrote: | I agree, but I think my experience is representative. So far | most human people don't have the resources to be able to use | 65B. And most small companies / university groups don't have | the resources to fine-tune a 65B. | | I've talked to a couple dozen people in real time who've | played with up to 30B but no one I know has the resources to | run the 65B at all or fast enough to actually use and get an | opinion of. None of the open source llama projects out there | are using 65B in practice (despite support for it) so I think | my 30B and under conclusions are applicable to the topic the | article covers. I'd love to be wrong and I'm excited for this | to change in the future. | danShumway wrote: | This is a good point. Even if ordinary people did have the | resources to run the 65B well on their existing devices, | the speed would limit its usefulness quite a bit. In | practice, 30B is what most people are going to interact | with (if even, I've seen a lot of projects use 13B). | | My experience here is pretty similar. I'm heavily | (emotionally at least) invested in models running locally, | I refuse to build something around a remote AI that I can | only interact with through an API. But I'm not going to | pretend that LLaMA has been amazing locally. I really | couldn't figure out what to build with it that would be | useful. | | I'm vaguely hoping that compression actually gets better | and that targeted reinforcement/alignment training might | change that. GPT can handle a wide range of tasks, but for | a smaller AI it wouldn't be too much of a problem to have a | much more targeted domain, and at that point maybe the 30B | model is actually good enough if it's been refined around a | very specific problem domain. | | For that to happen, training needs to get more accessible | though. Or communities need to start getting together and | deciding to build very targeted models and then | distributing the weights as "plug-and-play" models you can | swap out for different tasks. | | And if there's a way to get 65B more accessible, that would | be great too. | matthewdgreen wrote: | Is it hard to spin up an appropriate EC2 instance with | 64GB+ of additional RAM? The m6a.8xlarge seems to have | 128GB and costs $1.38 per hour. Was going to try this | myself, but now I'm wondering if even that won't be worth | the trouble. (I know this is not "your own devices" but | would give a feel for what you're missing with the smaller | models.) | qeternity wrote: | I agree with your premise: I have used 65b variants and of | course they're not as good as OpenAI. GPT3 has 175b | parameters, and OpenAI has done more RLHF than anyone else. | Why would we expect to get comparable performance with | models a fraction of the size and a pittance of the fine | tuning? | | That said, it's clear that replicating GPT4+ performance is | within the resources of a number of large tech orgs. | | And the smaller models can definitely still be useful for | tasks. | lolinder wrote: | llama.cpp has great support for 65B, and I've been using it | on a Linux box (I upgraded my RAM for that purpose). 64GB | of RAM for a desktop is like $160 today, so it's not out of | reach for most people here if they cared to. | | Admittedly, it's quite slow and therefore not useful for | chatting or real-time applications, and it's unreliable | enough in its quality that I'd like to be able to iterate | faster. Definitely more of a toy at this point, at least | when run on CPU. | Scene_Cast2 wrote: | Could you quantify "quite slow"? | lolinder wrote: | A token per second-ish with a Ryzen 7 5800X. If I run it | for too long it gets slower as heat throttling kicks in, | I need a better cooling system if I'm going to run it | non-stop. | dandongus wrote: | For a bit of comparison, if you've tested, how fast are | 13B or 7B on the same setup? | lolinder wrote: | Really fast. I didn't bother timing, but they're faster | than ChatGPT by a long shot. I didn't spend very long | with them because the quality is so much worse than the | 65B. | | I should probably go back and try again to see if it's | worth it for the extra speed, now that I've played with | 65B for a while. | morrbo wrote: | i've had the same experience tbh, 7/13/30 on ryzen | (local) and intel (server) both on rhel/centos. It's a | shame really | muyuu wrote: | his conclusion is simultaneously not warranted and correct | | a like-for-like comparison would be GPT-4 against the larger | models like LLaMA 65B, but those cannot be run on consumer- | grade hardware | | so one ends up comparing the stuff one can run... against the | top stuff from OpenAI running on high-end GPU farms, and this | technology clearly benefits a lot still from much larger | scale than most people can afford | | the great revelation this year is how much does it get better | as it get much, much bigger without a clear horizon on where | will diminishing returns be hit | | but at the same time, some useful stuff can be done on | consumer hardware - just not the most impressive stuff | Szpadel wrote: | if "leaks" are true then even a 65B model is a toy when | GPT-4 is supposed to be 1000B I would really like to have | an open source model that could compete with even gpt3, but | basically all lammas I tried failed to create correct email | validation regex, where gpt3 is able to even refer to what | rfc it is | muyuu wrote: | 13B on my computer does produce useful output, it's | pretty hit and miss though | | GPT-3.5 OTOH is much better, but it's also much better at | producing convincing-sounding but completely incorrect | answers | jonplackett wrote: | The difference between 3.5 and 4 is gigantic even in my fairly | limited experience. | | I gave them both some common sense tests and this one stuck out | to me. | | Q: A glass door has 'push' written on it in mirror writing. | Should you push or pull it | | GPT-3.5: | | If the word "push" is written in mirror writing on a glass | door, you should push the door to open it | | GPT-4: | | Since the word "push" is written in mirror writing, it suggests | that the instruction is intended for people on the other side | of the door. Therefore, you should pull the door to open it. | FLT8 wrote: | This is what I get out of Vicuna-13b: | | Human: A glass door has 'push' written on it in mirror | writing. To open the door should you 'push' or 'pull' it? | | Assistant: _Since the word "push" is written in mirror | writing on the glass door, you should actually "pull" the | door open instead of "push" it. Mirror writing is a writing | method where the characters are reversed, so when you see the | word "push" written in mirror writing, it is actually "pull" | in the normal writing orientation._ | amrb wrote: | Would like to see a yearly benchmark's for models like this! | two_in_one wrote: | [dead] | PoignardAzur wrote: | Wait, how does GPT-4 even... | | Does it benefit from its visual attention, or is it a case of | "the question wasn't in GPT-3's training set but it was in | GPT-4's"? | hutzlibu wrote: | I would suspect, that this is one of the manual fine tuned | questions. | | Meaning in before versions people used this question to | show flaws and now this specific flaw is fixed. | | Otherwise it would be indeed reasoning in my understanding. | steveBK123 wrote: | The evolution of answers from version to version makes it | clear there are insane amounts of manual fine tunings | happening. I think this is largely overlooked by the "its | learning" crowd. | moritzwarhier wrote: | They have infinite amounts of training data, and probably | lots of interested users who also like to push the limits | of what the model is capable of and provide all kinds of | test cases and RLHF base data. | | They have millions of people training the AI for free | basicallly, and they have engineers who pick and rate | pieces of training data and use it together with other | sources and manual training. | tel wrote: | This is an interesting argument as it's easy to apply it | nearly universally to any example of learning. | | What sort of evidence would convince you that it is | learning? | Method-X wrote: | It has the ability to reason. It may not be conscious, but | it is intelligent. | PoignardAzur wrote: | That's not an answer. | | The given question is one which requires some spatial | reasoning to understand. By default, GPT can only | understand spatial questions as described by text tokens | which is a pretty noisy channel. So it's not obvious how | GPT-4 could answer a spatial reasoning question (aside | from memorizing it). | Method-X wrote: | This is a good explanation: | https://www.youtube.com/watch?v=qbIk7-JPB2c | tel wrote: | I think it's hard to deny that it's doing some level of | reasoning. It's quite clear that these models do not merely | echo elements of their training data and that they can | solve simple and novel puzzles. | | What that reasoning is, exactly, is hard to know. One can | suppose that ideas like "glass", "transparent", "mirror" | are all reasonable concepts that show up in the training | set and are demonstrated thoroughly | vharuck wrote: | The GPT models do not reason or hold models of any reality. | They complete text chunks by imitating the training corpus | of text chunks. They're amazingly good at it because they | show consistent relations between semantically and/or | syntactically similar words. | | My best guess about this result is mentions of "mirror" | often occur around opposites (syntax) in direction words | (semantics). Which does sound like a good trick question | for these models. | DangitBobby wrote: | Or they are capable of some level of reasoning. | Closi wrote: | I've got access to 4 and it's a huge leap up from 3.5 - much | more subtlety in the response, less hallucinations, less | hitting a brick wall, but all of it adding up to a giant leap. | WXLCKNO wrote: | It's funny how big the difference feels between 3.5 and 4 but | also feels subtle. Like it's just doing what I expect it to | versus seeing the limitations more clearly in 3.5. | nailer wrote: | > Llama was not initially open-sourced, but a week after its | release, the model was leaked on 4chan, sparking thousands of | downloads. | | The author very clearly does not know what Open source is. | Proprietary code that's been leaked isn't open source, and code | that is derived from proprietary code is still proprietary. | | Windows had it source code leaked, that doesn't make it open | source. | | So did the game Portal. Not open source either. | | Something being leaked does not change the license. | drcode wrote: | Meta before leak: we take safety very seriously and will only | give access to responsible researchers | | Meta after leak: lol lmfao | seydor wrote: | ... and thanks for the open source fast implementations that we | can now embed wherever we want or sell | imjonse wrote: | This makes is sound as if the Stanford and Berkeley teams also | benefited from the leak, whereas I doubt they didn't have | official access. So Alpaca/Vicuna/Koala projects would have | probably happened anyway. The leak helped with popularity and | demand and also somewhat positive PR for Meta, which makes me | think they do not mind the leak that much. | kmeisthax wrote: | Meta is actively trying to take down publicly available copies | of LLaMA: | https://github.com/github/dmca/blob/master/2023/03/2023-03-2... | techdragon wrote: | Haha good luck with that now... it's in the digital ether | available to all on IPFS... at worst you might have to ask | around for someone to help you, but its "distributed" widely | enough now I don't think even a billionaire can put this back | into the bottle. | jhbadger wrote: | Given that free alternatives like Vicuna (from the University | of California and CMU) are better than LLaMA, are freely and | legally available for download, and are compatible with code | like llama.cpp, even if every copy of LLaMA is taken down it | will have no effect on the development of chatbots. It might | even improve things as people who would otherwise go for the | better known LLaMA will move towards these newer, better, | models. | Tepix wrote: | They are all built on top of Llama... | jhbadger wrote: | Yes, but that doesn't matter mow. The University of | California has released Vicuna as open source. It doesn't | need the Llama model to be installed at this point. Nor | do you need any of Meta's code to run it either as you | can use llama.cpp (not created by Meta). That's the whole | point of the article. It's open source now. There's | nothing Meta can do. | sp332 wrote: | This is incorrect. According to the official | https://github.com/lm-sys/FastChat#vicuna-weights you | need the original Llama weights before applying the | Vicuna diff. | jhbadger wrote: | Seriously, you can download the Vicuna model and run it | locally with llama.cpp. I've done it! | Tepix wrote: | Right. Most of the fine-tuned models we've seen so far have | been by university teams. | | Meta is not being very selective here. I applied for the | download myself and got the links after two days (using a | university email address). | 0xDEF wrote: | The "leak" is being portrayed as something highly subversive done | by the darn 4chan hackers. | | Before the "leak" Meta was sending the model to pretty much | anyone who claimed to be a PhD student or researcher and had a | credible college email. | | Meta has probably been planning to release the model sooner than | later. Let's hope they release it under a true open source | license. | mtkd wrote: | A cynic might say FB are confident in the limitations of | current models and want to pour cold water on the ChatGPT | excitement (esp. with what appears to be a goldrush this month | to use it to generate numbers and insight into numbers) | pingwing wrote: | Doesn't surprise me that Meta wants everyone to install their | code onto their machines, lol. | whimsicalism wrote: | Feel like if they cared they would have at least watermarked | the weights in some way but maybe I'm an idiot. | drowsspa wrote: | It sounds like that king that wanted people to overcome their | aversion for potatoes. So he put armed guards around the potato | fields but instructed them to be very lax and allowed the | people to rob it | boppo1 wrote: | Tell me more. Real or anecdote? | grugagag wrote: | https://www.farmersalmanac.com/parmentier-made-potatoes- | popu... | DANmode wrote: | Seems unlikely at this point if they're machine-gun firing DMCA | Notices. | mrtweetyhack wrote: | [dead] | seydor wrote: | It's risky , they dont benefit. They will prefer to keep | plausible deniability | throwawayapples wrote: | "The training and serving code, along with an online demo, are | publicly available for _non-commercial_ use. " (from Vicuna's | home page.) | | In what universe is that "open source"?! | nailer wrote: | Nothing in the article is open source. A proprietary model got | leaked and there are other proprietary apps that are stupidly | building on the leaked model. | justinjlynn wrote: | It isn't. | sp332 wrote: | They also said they have no plans to release the dataset, so | it's not reproduceable either. | irrational wrote: | > OpenAI published a detailed blog post outlining some of the | principles used to ensure safety in their models. The post | emphasize in areas such as privacy, factual accuracy | | Am I the only one amused by the phrase "factual accuracy"? How | many stories have we read like the one where it tries to ghost | light the guy that this year is actually last year. "Oh, your | phone must be wrong too, because there is no way I could be | wrong." Though, maybe that is what factually accurate means. It | is convinced that it is always factually accurate, even though it | is not. | smoldesu wrote: | > It is convinced that it is always factually accurate, even | though it is not. | | I don't think that's true. ChatGPT (or any LLM) isn't convinced | much of anything. It might present something confidently (which | is what most people want) but that's a side-effect of it's | programming, not an indication of how good it feels on the | answer. If you reply to _anything_ ChatGPT says with "No, | you're wrong." it will try to write a new, confident and | satisfying answer that responds to your assertion. | | LLMs will always be "wrong" because they have no distinction | between fiction and fact. Everything it reads is mapped into | language, not concept space or an attitude or a worldview. | moonchrome wrote: | >Everything it reads is mapped into language, not concept | space | | Umm I'm pretty sure it's discovered concepts through | compressing text - it seems perfectly capable of generalizing | concepts | musha68k wrote: | Would be interesting to read some unbiased science on that. | | My hunch would be that any concept it might detect still | depends on 2nd order patterns acquired through training? | | The ultimate "book smart" at best, basically. | | I'm not a ML scientist though, again would be interesting | to read an unbiased evaluation of those aspects. | | Edit: downvoted, not sure why though. Isn't this a valid | question a lot of non-ML folks would ask themselves? | mdp2021 wrote: | > _it seems perfectly capable of generalizing concepts_ | | How would you support that perception? | firatsarlar wrote: | With hope and living? It is a dream come true for people. | An abstract perception of a knowledge, is like sniffing a | rose. It feels, yes, I get there. This 40.000 pages book, | woow, I'll make time to live it or sniff another daisy?! | mdp2021 wrote: | > _It is a dream come true for people_ | | For as long as they will be an active part of societies, | they'll better live in reality. We need to know what we | are dealing with factually, because water is not | exchangeable with iron in practice. | | The perception of a machine as being able <<to generalize | concepts>> may be an illusion, so it requires some | support: we want to avoid illusions for the contextual | purposes. | smoldesu wrote: | Text compression isn't a deterministic process, | unfortunately. It's "concept" of compression is clearly | derived from token sampling, in the same way it's concept | of "math" is based on guessing the number/token that comes | next. | | While I do agree that ChatGPT exhibits pattern-recognizing | qualities, that's basically what it was built to do. I'm | not arguing against emergent properties, just against | emergent intelligence or even the idea of "understanding" | in the first place. | groffee wrote: | [dead] | rcxdude wrote: | There's been quite a few different iterations of ChatGPT and | bing with different behaviours in this regard: it depends | somewhat on the base GPT version, the fine-tuning, and the | prompt. Bing very famously at one point was _extremely_ | passive aggressive when challenged on basically anything. | | And while there's nothing intrinsic to the structure and | training goals of LLMs which directs them towards more | structured reasoning, it does seem that in the process of | learning to predict language they pick up some degree of it, | however flawed it may be. | seba_dos1 wrote: | > Bing very famously at one point was extremely passive | aggressive when challenged on basically anything. | | It still wasn't an indication of how confident it "felt" | with its answers. It was just role-playing a more confident | and aggressive chat bot than ChatGPT does. | int_19h wrote: | Outside of the roleplay, there's no "it". The thing that | actually interacts with the user is the persona. But for | the same reason, it doesn't matter what the underlying | LLM "really thinks" - it'll be the persona that'll try to | con you, or write broken or malicious code. | rrauenza wrote: | I've been googling trying to figure out what "ghost light" is | in this context .. did you get an autocorrect for gas light? | gleenn wrote: | Looks like they meant "gaslight" but I did find it on Urban | Dictionary: | | ghost light | | Lighting in a video game that has no apparent source for the | light to come from. Its like going out on a bright day, but | not being able to find the sun in the sky even though the | surroundings are brightly lit. Dead Rising on XBOX is a good | example. | | http://ghost-light.urbanup.com/2450357 | harrylove wrote: | Agree on gaslight as the intended word. Ghost light also | has a theatrical origin, still in use today. | https://en.m.wikipedia.org/wiki/Ghost_light_(theatre) | isoprophlex wrote: | I find the thing incredibly smart and yet utterly useless at | times. | | I just spent 20 minutes getting the current iteration of | ChatGPT to agree with me that a certain sentence is | palindromic. Even when you make it print the unaccented | characters one by one, spaces excluded, backwards and forwards, | it still insists "Elu par cette crapule" isn't palindromic. | | I understand how tokenization makes this difficult but come | on... this doesn't feel like a difficult task for something | that supposedly passes the LSATs and whatnot. | | * _French for "Elected by this piece of shit"_ | ShannonLimiter wrote: | Just ask it to figure it out step-by-step and to remove | accents: | | GPT-4: | | Figure this out step by step and check your work: Remove the | accents and tell me if this a palindrome: Elu par cette | crapule | | GPT-3.5 (Needs to know that removing spaces and lowercasing | is okay): | | Figure this out step by step and check your work: Lowercase | it and remove the accents and spaces and tell me if this a | palindrome: Elu par cette crapule | [deleted] | im3w1l wrote: | That was Bing/Sydney. ChatGPT has a very different | "personality". | kolinko wrote: | Well, unless they designed it to have zero confidence in | itself, we are bound to have situations like this. | | When I was trying to troll it, by saying that IPCC just | released a report stating that climate change is not real, and | that they were completely wrong after all, it properly said | that it is not very likely and that I'm probably mistaken. It | admitted that it doesn't have internet access, but still | refused to believe the outrageous thing I was saying. | | I can also imagine GPT's super-low confidence leading to errors | in other places - e.g. when I mistakenly claim that it's wrong, | and it sheepishly takes my claim at a face value. | | Finally, considering that the whole world is using it, | including some people detached from reality, I really prefer it | to be overconfident, than to follow someone into some | conspiracy hole. | Guvante wrote: | For better or worse in the current age of the internet prose | is a good first pass filter for quality. | | Someone arguing incoherently is seen as less believable. | | Unfortunately the prose for these chat models doesn't change | based on how certain it is of the facts. So you can't tell | based on how it is talking whether it is true or not. | | Certainly people online speak well while lying either | intentionally or unintentionally but usually well intentioned | people will coach things they aren't as certain about helping | to paint a more accurate picture. | | I haven't taken a deep dive on the latest models but | historically most AI haven't worried about "facts" as much as | associating speech patterns. It knows how to talk about facts | because other people have done so in the past kind of thing. | | This means you need to patch in arbitrary rules to | reintroduce some semblance of truth to the outputs which | isn't an easy task. | | False training is a whole different area IMO. Especially when | there is a difference between responding to a particular user | and responding to everyone based on new information. | abstractbill wrote: | The models are a lot of fun to play with, but yeah, every time | I've tried to use them for something "serious" they nearly | always invent stuff (and are _so_ convincing in how they write | about it!). | | Most recently I've been interested in what's happened with the | 4-color theorem since the 1976 computer-assisted proof, and | decided to use GPTChat instead of google+wikipedia. GPTChat had | me convinced and excited that, apparently the computer-assisted | part of the proof has been getting steadily smaller and smaller | over the years and decades, and we're getting close to a proof | that might not need computer assistance at all. It wrote really | convincingly about it! And then I went and looked for the | papers it had talked about. They didn't exist, and their | authors either didn't exist, or worked in completely unrelated | fields. | riceart wrote: | Before the inevitable idiots come in to say hurr durr but | have you tried ChatGPT 4... yes I paid for it, and it is just | as prone to hallucinations of factual information. It loves | to make up new names for peoples initials. | vidarh wrote: | While it is still prone to hallucinations, with GPT4 I've | had it tell me "X is not a real project, but assuming it | exists and is designed to do Y [based on the name], I can | provide you with a general guide on how to use it." I never | had earlier version to do that. So it does appear to be | _better_ , though it's certainly still an issue. | [deleted] | dumbaccount123 wrote: | Also please refrain from calling other members idiots, next | time you wont be warned. | dumbaccount123 wrote: | I found the opposite to be true, i mean sure if youre | tricking it. Wait for GPT 5-6 in a year or two and see | haha. | senko wrote: | I hold a more charitable interpretation. | | We (the public) have found an important bug in the system, ie. | GPT can lie (or "hallucinate"), even if you try to convince it | not to lie. The bug is definitely lowering the usefulness of | their product, as well as the public option about it. But I'll | let the programmer who has never coded a bug cast the first | stone. | | I wouldn't be surprised if they're scrambling internally to | minimize the problem (in the product, not in public | perception). They have also recently added a note to ChatGPT: | "ChatGPT may produce inaccurate information about people, | places, or facts" which is an acknowledement that yes, watch | out (I compare it to "caution: contents hot" labels). | | On the topic of dealing with it, I like the stance that simonw | recently took: "We need to tell people ChatGPT will lie to | them, not debate linguistics" [0]. | | I don't attach intentions to a machine algorithm (to me, | "gaslight" definitely implies an evil intent), and I don't | think OpenAI people are evil, stupid, corrupted or something | else because they put out a product that has a bug. But since | the wide public can't handle nuances, I'd agree it's better to | say "chatgpt lies, use it for things where it either doesn't | matter or you can verify; don't use it for fact-finding" to get | the point across. | | [0] https://simonwillison.net/2023/Apr/7/chatgpt-lies/ | firatsarlar wrote: | Meet my darling https://gist.github.com/firatsarlar/5f25ebcc4 | c33ec484e6cd95b... We need to - pure - clear non commercial, | non owned AI first. It -hope lets say-, no, most of us still | guessing, sniffin, ... suspicions abut who own GPT -LLM we | need to abstract-, Who owns this - so called - open source | product? MS - with the power of NVIDA's - ? OpenAI people? | Why cant we talk our intentions, or whose product, or not to | generalize it As LLMs. Because, lets say public, - and our | ignore our delusions about the thing we made-, because, we're | in a delusion, what is this ? People could try to eat and sue | some, do we - purely - care for public. I need to skip my own | experience, but, yes, if you ready to be delusional , you | could easily make LLM your girlfriend, a liar, ... No, we - | software community - need to stop and see what we have. We | name it, public shape it, some abuse it for money that it | made me ... , and sue some ... What is the end product ? A | constant, machine - lets say system -, working to make this | happen. Justice, we - devs-, world, ... money, people, puclic | , we 're spendng time and resources a thing. Some claim its | mine, yes, we need a concencuss ? No. Open source is the only | thing if we - pure - lets say. I do not want to waste my time | to figure out poke FB's LLM, or -pleae Open - AI girl. Lets | learn to share, at least for us -devs- I'm really tired to | think commercial facts of this thing. I'm really tired to | this game we play. MS, say I have it, and make it yours. Boy | - sorry open AI- I do not know you, is it yours, MS's , FB, | they somehow managed to make a thing - inter-national, in | Paris - Skip gaslighting, delusions what you own ? | | Are we really there ? | [deleted] | dylan604 wrote: | >as well as the public option about it. | | assuming you mean the public opinion about it, and I would | have to agree that I do hold chatGPT in very low regard | because of this. people will argue that it is impressive that | they built this thing that can be this impressive, but yeah, | it might not be totally accurate. so my response is, what's | the point of it then? | | say someone was to invent a robot baseball player that can | throw the ball 200+mph, or hit about a literal mile but, it | can't hit a target with that 200+mph ball or hit the ball | without it going foul. yes, the tech would be impressive, but | what's the point? yeah yeah, language is hard, but it's just | an example of building something impressive that at best | almost does the job designed. unless we're saying it's | designed this way on purpose?? | vlovich123 wrote: | It's not a bug. It's an architectural defect / limitation in | our understanding of how to build AI. That makes it a | strictly harder problem that will take longer. And it's not | totally clear to me that you'll get there purely with LLMs. | LLMs accomplish a good chunk of what we classify as | intelligence for sure. But it's missing the cognition / | reasoning skills and the open question is whether you can | solve that by just bolting on more techniques into the LLM or | you need a totally different kind of model that you can marry | to an LLM. | vidarh wrote: | GPT 4 will admit to not knowing things in many cases where | 3.5turbo does not (tested the same prompt), and either will | stop there or go off on a "but if it did exist it might go | something like this" type continuation. It still | hallucinates a lot, but it's not at all clear that this | will be all that difficult an issue to solve given the | progress. | vlovich123 wrote: | We generally only hallucinate while dreaming / using our | imagination. And we can distinguish those two states. | Admitting lack of knowledge is of course good but, for | example, if you ask it to write some code that isn't | boilerplate API integrations, it'll do so happily even | when it's wildly wrong and it can't tell the difference | and that is also the case with GPT4 afaik. Moreover, you | can't solve it through prompt engineering because there's | clearly a lack of context it's unable to understand to | figure out what non trivial thing your asking it. | vidarh wrote: | The point is there's been progress in making it admit | when it doesn't know, and we simply don't know how fast | that will improve in future version. It may continue to | be an issue, or turn out to be easily solved. The | improvement with GPT4 does suggest it is at least | possible to make it recognise its limits. ___________________________________________________________________ (page generated 2023-04-09 23:00 UTC)