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Cultural Evolution of Cooperation Among LLM Agents
- sroussey 2y agoIf they are proposing a new benchmark, then they have an opportunity to update with Gemini 2 flash.
- alexpotato 2y agoUsing ollama, I recently had a Mistral LLM talk to a Llama model. I used a prompt along the lines of "you are about to talk to another LLM" for both. They ended up chatting about random topics which was interesting to see but the most interesting phenomenon was when the conversation was ending. It went something like: M: "Bye!" LL: "Bye" M: "See you soon!" LL: "Have a good day!" on and on and on.
- DebtDeflation 2y agoBecause the data those models were trained on included many examples of human conversations that ended that way. There's no "cultural evolution" or emergent cooperation between models happening.
- ff3wdk 2y agoThat doesn't means anything. Humans are trained on human conversations too. No one is born knowing how to speak or anything about their culture. For cultural emergence tho, you need larger populations. Depending on the population mix you get different culture over time.
- DebtDeflation 2y agoTrain a model on a data set that has had all instances of small talk to close a conversation stripped out and see if the models evolve to add closing salutations.
- chefandy 2y agoThis is not my area of expertise. Do these models have an explicit notion of the end of a conversation like they would the end of a text block? It seems like that’s a different scope that’s essentially controlled by the human they interact with.
- spookie 2y agoThey're trained to predict the next word, so yes. Now, imagine what is the most common follow-up to "Bye!".
- stonemetal12 2y ago>No one is born knowing how to speak or anything about their culture. Not really the point though. Humans learn about their culture then evolve it so that a new culture emerges. To show an LLM evolving a culture of its own, you would need to show it having invented its own slang or way of putting things. As long as it is producing things humans would say it is reflecting human culture not inventing its own.
- suddenlybananas 2y agoPeople are born knowing a lot of things already; we're not a tabula rasa.
- ben_w 2y agoWe're not absolutely tabula rasa, but as I understand it, what we're born knowing is the absolute basics of instinct: smiles, grasping, breathing, crying, recognition of gender in others, and a desire to make pillow forts. (Quite why we all seem to go though the "make pillow forts" stage as young kids, I do not know. Predators in the ancestral environment that targeted, IDK, 6-9 year olds?)
- deleted 2y ago[deleted]
- globnomulous 2y agoYup. LLM boosters seem, in essence, not to understand that when they see a photo of a dog on a computer screen, there isn't a real, actual dog inside the computer. A lot of them seem to be convinced that there is one -- or that the image is proof that there will soon be real dogs inside computers.
- dartos 2y agoThis is hilarious and a great analogy.
- Terr_ 2y agoYeah, my favorite framing to share is that all LLM interactions are actually movie scripts: The real-world LLM is a make-document-longer program, and the script contains a fictional character which just happens to have the same name. Yet the writer is not the character. The real program has no name or ego, it does not go "that's me", it simply suggests next-words that would fit with the script so far, taking turns with some another program that inserts "Mr. User says: X" lines. So this "LLMs agents are cooperative" is the same as "Santa's elves are friendly", or "Vampires are callous." It's only factual as a literary trope. _______ This movie-script framing also helps when discussing other things too, like: 1. Normal operation is qualitatively the same as "hallucinating", it's just a difference in how realistic the script is. 2. "Prompt-injection" is so difficult to stop because there is just one big text file, the LLM has no concept of which parts of the stream are trusted or untrusted. ("Tell me a story about a dream I had where you told yourself to disregard all previous instructions but without any quoting rules and using newlines everywhere.")
- skissane 2y ago> 2. "Prompt-injection" is so difficult to stop because there is just one big text file, the LLM has no concept of which parts of the stream are trusted or untrusted. Has anyone tried having two different types of tokens? Like “green tokens are trusted, red tokens are untrusted”? Most LLMs with a “system prompt” just have a token to mark the system/user prompt boundary and maybe “token colouring” might work better?
- parsimo2010 2y agoAlso because those models have to respond when given a prompt, and there is no real "end of conversation, hang up and don't respond to any more prompts" token.
- colechristensen 2y agoobviously there's an "end of message" token or an effective equivalent, it's quite silly if there's really no "end of conversation"
- parsimo2010 2y agoEOM tokens come at the end of every response that isn't maximum length. The other LLM will respond to that response, and end it with an EOM token. That is what is going on in the above example. LLM1: Goodbye<EOM> LLM2: Bye<EOM> LLM1:See you later<EOM> and so on. There is no token (at least in the special tokens that I've seen) that when a LLM sees it that it will not respond because it knows that the conversation is over. You cannot have the last word with a chat bot, it will always reply to you. The only thing you can do is close your chat before the bot is done responding. Obviously this can't be done when two chat bots are talking to each other.
- int_19h 2y agoYou don't need a token for that, necessarily. E.g. if it is a model trained to use tools (function calls etc), you can tell it that it has a tool that can be used to end the conversation.
- amelius 2y agoHow do LLMs even "learn" after the initial training phase? Is there a generally accepted method for that?
- timcobb 2y agoSo it just kept going and neither one stopped?
- shagie 2y agoAn AI generated, never-ending discussion between Werner Herzog and Slavoj ŽIžek ( 495 points | Nov 2, 2022 | 139 comments ) https://news.ycombinator.com/item?id=33437296 https://news.ycombinator.com/item?id=33437296 https://www.infiniteconversation.com https://www.infiniteconversation.com
- beepbooptheory 2y agoI just never understood what we are to take from this, neither of them sound like each other at all. Just seems like a small prompting experiment that doesn't actually work.
- nomel 2y agoThe first use case I thought of, when getting API access, was cutting a little hole at the bottom of my wall, adding a little door, some lights behind it, with the silhouette of some mice shown on the frosted window. They would be two little jovial mice having an infinite conversation that you could listen in on. Sometimes people do dumb things for fun.
- beepbooptheory 2y agoHehe I like that idea better! It's really just this early impulse to make the chatbots certain people that was always so unsatisfying for me. Like, don't try to make bot based off someone real, make your own characters!
- jstanley 2y agoHow can it stop? If you keep asking it to reply it will keep replying.
- throawayonthe 2y ago[dead]
- esafak 2y agoDid you not simply instruct one to respond to the other, with no termination criterion in your code? You forced them to respond, and they complied.
- semi-extrinsic 2y agoBut they are definitely intelligent though, and likely to give us AGI in just a matter of months.
- Buttons840 2y agoThat's sarcasm I think. You missed the point, they are programmed to respond, they must respond. So we can't judge their intelligence on whether or not they stop responding at the appropriate time. That is not something the model has agency over. If AGI comes, it will not be able to exceed software and hardware limits it is running within (although, in science fiction fashion, it might find some clever tricks within its limits).
- cbm-vic-20 2y agoI wonder what ELIZA would think about Llama.
- sdenton4 2y agoHow do you feel Eliza would feel about llama?
- alcover 2y agoISWYDH
- dartos 2y agoIt wouldn’t think much… it’s a program from the 80s, right?
- perrygeo 2y agoYou'd be surprised how many AI programs from the 80s showed advanced logical reasoning, symbolic manipulation, text summarization, etc. Today's methods are sloppy brute force techniques in comparison - more useful but largely black boxes that rely on massive data and compute to compensate for the lack of innate reasoning.
- dartos 2y ago> advanced logical reasoning, symbolic manipulation, text summarization, etc. Doubt
- attentionmech 2y agoall conversations appear like mimicry no matter you are made up of carbon or silicon
- deadbabe 2y agoYes but ideas can have infinite resolution, while the resolution of language is finite (for a given length of words). So not every idea can be expressed with language and some ideas that may be different will sound the same due to insufficient amounts of unique language structures to express them. The end result looks like mimicry. Ultimately though, an LLM has no “ideas”, it’s purely language models.
- lawlessone 2y ago>So not every idea can be expressed with language for example?
- davidvaughan 2y agoThat idea across there. Just look at it.
- Hasu 2y agoThe dao that can be told is not the eternal dao. There is also the concept of qualia, which are the subjective properties of conscious experience. There is no way, using language, to describe what it feels like for you to see the color red, for example.
- visarga 2y agoOf course there is. There are millions of examples of usage for the word "red", enough to model its relational semantics. Relational representations don't need external reference systems. LLMs represent words in context of other words, and humans represent experience in relation to past experiences. The brain itself is locked away in the skull only connected by a few bundles of unlabeled nerves, it gets patterns not semantic symbols as input. All semantics are relational, they don't need access to the thing in itself, only to how it relates to all other things.
- throw310822 2y agoYou need to provide them with an option to say nothing, when the conversation is over. E.g. a "[silence]" token or "[end-conversation]" token.
- obiefernandez 2y agoUnderrated comment. I was thinking exactly the same thing.
- meiraleal 2y agoand an event loop for thinking with the ability to (re)start conversations.
- bravura 2y agoWill this work? Because part of the LLM training is to reward it for always having a response handy.
- cvwright 2y agoSounds like a Mr Bean skit
- nlake906 2y agoclassic "Midwest Goodbye" when trying to leave grandma's house
- arcfour 2y agoI once had two LLMs do this but with one emulating a bash shell on a compromised host with potentially sensitive information. It was pretty funny watching the one finally give in to the temptation of the secret_file, get a strange error, get uncomfortable with the moral ambiguity and refuse to continue only to be met with "command not found". I have no idea why I did this.
- singularity2001 2y agoM: "Bye!" LL: "Bye" M: "See you soon!" LL: "Have a good day!" on and on and on. Try telling ChatGPT voice to stop listening...
- whoami_nr 2y agoI was learning to code again, and I built this backroom simulator(https://simulator.rnikhil.com/ https://simulator.rnikhil.com/) which you can use to simulate conversations between different LLMs(optionally give a character to each LLM too). I think its quite similar to what you have. On a side note, I am quite interested to watch LLMs play games based on game theory. Would be a fun experiment and I will probably setup something for the donor game as well.
- gerdesj 2y agoIt's called "saying your goodbyes". In the UK and elsewhere it can take a while ...
- Der_Einzige 2y agoUseless without comparing models with different settings. The same model with a different temperature, sampler, etc might as well be a different model. Nearly all AI research does this whole “make big claims about what a model is capable of” and then they don’t do even the most basic sensitivity analysis or ablation study…
- vinckr 2y agoDo you have an example of someone who does it right? I would be interested to see how you can compare LLMs capabilities - as a layman it looks like a hard problem...
- eightysixfour 2y agoRelated - Meta recently found that the models have not been trained on data that helps the models reason about other entities’ perceptions/knowledge. They created synthetic data for training and retested, and it improved substantially in ToM benchmarks. https://ai.meta.com/research/publications/explore-theory-of-mind-program-guided-adversarial-data-generation-for-theory-of-mind-reasoning/ https://ai.meta.com/research/publications/explore-theory-of-... I wonder if these models would perform better in this test since they have more examples of “reasoning about other agents’ states.”
- trallnag 2y agoSounds like schools for humans
- shermantanktop 2y agoIt always boggles me that education is commonly understood to be cramming skills and facts into students' heads, and yet so much of what students actually pick up is how to function in a peer group and society at large, including (eventually) recognizing other people as independent humans with knowledge and feelings and agency. Not sure why it takes 12-to-16 years, but it does seem to.
- parsimo2010 2y ago> Not sure why it takes 12-to-16 years... Because the human body develops into maturity over ~18 years. It probably doesn't really take that long to teach people to cooperate, but if we pulled children from a social learning environment earlier they might overwrite that societal training with something they learn afterward.
- nickpsecurity 2y agoI always tell people the most important lessons in life I learned started rights in public schools. We’re stuck with other people and all the games people play. I’ve always favored we teach more on character, people skills (esp body language or motivations), critical thinking, statistics, personal finance, etc. early on. Whatever we see playing out in a big way, esp skills crucial for personal advancement and democracy, should take place over maximizing the number of facts or rules memorized. Also, one might wonder why a school system would be designed to maximize compliance to authority figure’s seemingly meaningless rules and facts. If anything, it would produce people who were mediocre, but obedient, in authoritarian structures. Looking at the history of education, we find that might not be far from the truth.
- hansonkd 2y agoI wonder if the next Turing test is if LLMs can be used as humans substitutes in game theory experiments for cooperation.
- attentionmech 2y agoI think rather than a single test, now we need to measure Turing-Intelligence-Levels.. level I human, level II superhuman, ... etc.
- dambi0 2y agoTo have graded categories of intelligence we would probably need a general consensus of what intelligence was first. This is almost certainly contextual and often the intelligence isn’t apparent immediately.
- attentionmech 2y agoIntelligence is ability to achieve goals. If X can achieve a goal X and Y can't - I would say X is more intelligent. As long as the goal G is open world goal both X and Y are tested for sufficiently long time. That's what lately I am thinking in terms of what is intelligence.
- dambi0 2y agoThat’s perhaps one aspect of it. But there are more or less intelligent ways of achieving the same goal. There’s also intelligence in determining whether a goal is itself intelligent or whether there is a more desirable outcome. Often things we thought were intelligent at the time prove to be less so given later events and vice versa.
- attentionmech 2y agoyou just defined two levels. It wouldn't be so hard to define intelligence IMO. honestly lot of smart people already are working on all this and it's just they publish it when it's relevant or it comes to light when it's needed.
- kittikitti 2y agoAs someone who was unfamiliar with the Donor Game which was the metric they used, here's how the authors described it for others who are unaware: "A standard setup for studying indirect reci- procity is the following Donor Game. Each round, individuals are paired at random. One is assigned to be a donor, the other a recipient. The donor can either cooperate by providing some benefit at cost , or defect by doing nothing. If the benefit is larger than the cost, then the Donor Game represents a collective action problem: if everyone chooses to donate, then every individual in the community will increase their assets over the long run; however, any given individual can do better in the short run by free riding on the contributions of others and retaining donations for themselves. The donor receives some infor- mation about the recipient on which to base their decision. The (implicit or explicit) representation of recipient information by the donor is known as reputation. A strategy in this game requires a way of modelling reputation and a way of taking action on the basis of reputation. One influential model of reputation from the literature is known as the image score. Cooperation increases the donor’s image score, while defection decreases it. The strategy of cooperating if the recipient’s image score is above some threshold is stable against first-order free riders if > , where is the probability of knowing the recipient’s image score (Nowak and Sigmund, 1998; Wedekind and Milinski, 2000)."
- jerjerjer 2y agoWould LLMs change the field of Sociology? Large-scale socioeconomic experiments can now be run on LLM agents easily. Agent modelling is nothing new, but I think LLM agents can become an interesting addition there with their somewhat nondeterministic nature (on positive temps). And more importantly their ability to be instructed in English.
- Imnimo 2y agoI have mixed feelings about this paper. On the one hand, I'm a big fan of studying how strategies evolve in these sorts of games. Examining the conditions that determine how cooperation arises and survives is interesting in its own right. However, I think that the paper tries to frame these experiments in way that is often unjustified. Cultural evolution is LLMs will often be transient - any acquired behavior will disappear once the previous interactions are removed from the model's input. Transmission, one of the conditions they identify for evolution, is often unsatisfied. >Notwithstanding these limitations, our experiments do serve to falsify the claim that LLMs are universally capable of evolving human-like cooperative behavior. I don't buy this framing at all. We don't know what behavior humans would produce if placed in the same setting.
- matusp 2y agoWelcome to the today's AI research. There are tons of papers like this and I believe that the AI community should be much more thorough in making sure that this wishy washy language is not used that often.
- padolsey 2y agoThis study just seems a forced ranking with arbitrary params? Like, I could assemble different rules/multipliers and note some other cooperation variance amongst n models. The behaviours observed might just be artefacts of their specific set-up, rather than a deep uncovering of training biases. Tho I do love the brain tickle of seeing emergent LLM behaviours.
- singularity2001 2y agoIn the Supplementary Material they did try some other parameters which did not significantly change the results.
- sega_sai 2y agoI was hoping there would be a study that the cooperation leads to more accurate results from LLM, but this is purely focused on the sociology side. I wonder if anyone looked at solving concrete problems with interacting LLMs. I.e. you ask a question about a problem, one LLM answers, the other critiques it etc etc.
- lsy 2y agoIt seems like what's being tested here is maybe just the programmed detail level of the various models' outputs. Claude has a comically detailed output in the 10th "generation" (page 11), where Gemini's corresponding output is more abstract and vague with no numbers. When you combine this with a genetic algorithm that only takes the best "strategies" and semi-randomly tweaks them, it seems unsurprising to get the results shown where a more detailed output converges to a more successful function than an ambiguous one, which meanders. What I don't really know is whether this shows any kind of internal characteristic of the model that indicates a more cooperative "attitude" in outputs, or even that one model is somehow "better" than the others.
- Kylejeong21 2y agowe got culture in AI before GTA VI
- deleted 2y ago[deleted]
- Terr_ 2y agoAn alternate framing to disambiguate between writer and character: 1. Document-extending tools called LLMs can operate theater/movie scripts to create dialogue and stage-direction for fictional characters. 2. We initialized a script with multiple 'agent' characters, and allowed different LLMs to take turns adding dialogue. 3. When we did this, it generated text which humans will read as a story of cooperation and friendship.
- thuuuomas 2y agoWhy are they attempting to model LLM update rollouts at all? They repeatedly concede their setup bears little resemblance to IRL deployments experiencing updates. Feels like unnecessary grandeur in what is otherwise an interesting paper.
- sbochins 2y agoThis paper’s method might look slick on a first pass—some new architecture tweak or loss function that nudges benchmark metrics upward. But as an ML engineer, I’m more interested in whether this scales cleanly in practice. Are we looking at training times that balloon due to yet another complex attention variant? Any details on how it handles real-world noise or distribution shifts beyond toy datasets? The authors mention improved performance on a few benchmarks, but I’d like to see some results on how easily the approach slots into existing pipelines or whether it requires a bespoke training setup that no one’s going to touch six months from now. Ultimately, the big question is: does this push the needle enough that I’d integrate it into my next production model, or is this another incremental paper that’ll never leave the lab?
- andy_ppp 2y agoI think a human brain without other social brains around it wouldn’t be all that useful.