19 ms·

Generative Agents: Interactive Simulacra of Human Behavior

• bundie 4y ago
  Interesting paper. I think something like this could be implemented in open world games in the future, no? I cannot wait for games that feel 'truly alive'.
  • matthewfcarlson 4y ago
    I was talking about that with a friend. While I'm not sold on the storytelling capability of generative AI, a love the idea that every NPC you talk to having something interesting to say.
    • sharemywin 4y ago
      the thing is writing is a process. just using the word weird with the idea you ask it to generate will create much more interesting results. have it interreact with other agents in the process of writing will definitely generate more interesting results. I don't know if it's able to write a best seller even with a process but we haven't really give it much of a chance.
      • newswasboring 4y ago
        The biggest thing I am excited about is when they will decouple the story from the mechanic. Imagine the game loop being programmed deterministically, like a quest, and then the actual story being generated by the AI. Go kill a monster, save a person, game loops can be about someone's wife or grandma. I don't know I am not good at story writing for games. We can get even more ambitious than this, decouple the entire game engine from the story engine. Most of the times the same game loop can be themed with multiple stories. The game mechanics part of Skyrim could have been themed with a cyberpunk aesthetic and it will still work the same. Of course the assets will need to be generated too, but maybe in a decade or so it will be trivial.
        • all2 3y ago
          Use the TV Tropes database, generate a storyline [0] and characters [1] and then let the AI loose. [0] https://tvtropes.org/pmwiki/storygen.php https://tvtropes.org/pmwiki/storygen.php [1] https://en.shindanmaker.com/744084 https://en.shindanmaker.com/744084
  • abraxas 4y ago
    I mean, that's all but inevitable. I can't imagine any industry not sitting up and taking notice of LLMs all of a sudden.
  • jvm___ 4y ago
    What happens when some whiz kid hacks the actual water treatment plant or nuclear power plant and just assumes it was a game... It's like Ender's game IRL
    • perigrin 4y ago
      Kinda more like War Games. Ender was more hacked _by_ the Formics in what he assumed was a game … not that it did them any good.
      • ukuina 4y ago
        It ensured their survival, no?
  • lysecret 3y ago
    I want to work on this. I mean can you imagine the kind of MMO you could build? Of course there would need to be some railways but this could be a true revolution. Is there any open source "GPT for games" project? Someone working on this?
    • deleted 3y ago
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    • netruk44 3y ago
      I'm working on a hobby project to add AI text generation to Morrowind NPCs in OpenMW[0]. But I'm mainly making it for myself to see if I can. It's all open source, but not really in a state that's useful outside of my specific project. I can't be the only person working on something like this, though. So it's safe to say adding it to an MMO is being worked on by somebody somewhere, likely right now. That's probably the correct way to do it anyway, since running (e.g.) LLaMA locally on an end-user computer is not something that most people can do, and MMOs come with an expected subscription cost that can be used to fund the server-side text generation. [0]: https://www.danieltperry.me/project/2023-something-else/ https://www.danieltperry.me/project/2023-something-else/
      • lysecret 3y ago
        Very interesting!
• mdaniel 4y ago
  The previous submission https://news.ycombinator.com/item?id=35511843 https://news.ycombinator.com/item?id=35511843 had just a few comments, but Ian's was substantial (although regrettably offsite): https://news.ycombinator.com/item?id=35514112 https://news.ycombinator.com/item?id=35514112 and it especially highlighted the demo URL: https://reverie.herokuapp.com/arXiv_Demo/ https://reverie.herokuapp.com/arXiv_Demo/
  • PartiallyTyped 3y ago
    Ian’s comments remind me of WestWorld. Could the prompts and directions be considered analogous to the “voice of god” given to the synthetic humans?
• deleted 4y ago
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• bradgranath 4y ago
  Hey! It's a proto ancestor sim!
• famouswaffles 4y ago
  a good enough simulation interacting with the real word would be no less impactful than whatever you imagine a non-simulation to be. as we agentify and embody these systems to take actions in the real word, i really hope we remember that. "It's just a simulation"/ "It's not true [insert property]" is not the shield some imagine it to be.
  • jmoak3 4y ago
    This was the central point of the bladerunner movies, perfectly and succinctly captured in the recent movie when one character asks: “Is that dog real” “I dunno ask him” “Woof”
• vrglvrglvrgl 4y ago
  [dead]
• discmonkey 4y ago
  This paper feels significant. If chatgpt was an evolutionary step on gpt3.5/gpt4, then this is bit like taking chatgpt and using it as the backbone of something that can accumulate memories, reflect on them, and make plans accordingly.
  • gitfan86 4y ago
    Welcome to the singularity
    • ChatGTP 4y ago
      The singularity sounded a bit more exciting when I heard Ray Kurzweil describe it ?
  • xwdv 4y ago
    It’s not really. ChatGPT could already do all those things. This just presents it for a different use case.
    • discmonkey 4y ago
      Oh yeah I agree that it _could_ do all those things, but it would be a bit of overkill to always send every observation an agent encounters into the API/chatbox, and ask it to spit out an evaluation or action. This paper does a nice job of separating the "agency" from the next word with context type predictor. I think that's why I like the paper, it is just chatgpt, in the same way that pizza is just dough, sauce, and cheese.
      • xwdv 4y ago
        Yes, but I think this was a fairly obvious conclusion to imagine isn’t it. If you were going to seriously consider using ChatGPT for AI in a game, you would need each instance of GPT to only know certain information it has gathered. And you would want it to reflect on observations to come up with new thoughts that weren’t observed. Still, I’d argue you don’t really even need GPT for any of the above. GPT is useful if you want thoughts expressed as natural language, but you could easily code observations and thoughts into an appropriate abstract data structure and still have the same thing, except it’s a bit harder to understand since asking an NPC something in a language it understands and getting back a query result isn’t user friendly, but it can be just as amazing if you know what the data represents. The imprecision and fuzziness of an LLM leaves room for fun weirdness though.
• qumpis 4y ago
  Nice to see progress on this end. I've been hoping for some time for a continuation of AI generated shows (like the previously-famous Nothing Forever) that can 1) interact with the open world and 2) keep history long enough (e.g. by resummarizing and reprompting the model). Controlling the agents and not merely making them output text through LLMs sounds very exciting, especially once people figure out the best way to connect APIs of simulators with the models
• alexahn 4y ago
  An interesting thought experiment: what would an AGI do in a sterile world? I think the depth of understanding that any intelligence develops is significantly bound by its environment. If there is not enough entropy in the environment, I can't help but feel that a deep intelligence will not manifest. This kind of becomes a nested dolls type of problem, because we need to leverage and preserve the inherent entropy of the universe if we want to construct powerful simulators. As an example, imagine if we wanted to create an AGI that could parse the laws of the universe. We would not be able to construct a perfect simulator because we do not know the laws ourselves. We could probably bootstrap an initial simulator (given what we know about the universe) to get some basic patterns embedded into the system, but in the long run, I think it will be a crutch due to the lack of universal entropy in the system. Instead, in a strange way, the process has to be reversed, that a simulator would have to be created or dreamed up from the "mind" of the AGI after it has collected data from the world (and formed some model of the world).
  • hiatus 4y ago
    Could it not instead be more akin to knowledge passing across human generations, where one understanding is passed on and refined to better fit/explain the current reality (or thrown away wholesale for a better model)? Instead of a crutch, it might be a stepping stone. Presumptuous of us that we might know the way, but nonetheless.
    • alexahn 4y ago
      >Could it not instead be more akin to knowledge passing across human generations, where one understanding is passed on and refined to better fit/explain the current reality (or thrown away wholesale for a better model)? I think it is only knowledge passing when the AGI makes its own simulation. >Instead of a crutch, it might be a stepping stone. I think it is a way to gain computational leverage over the universe instead of a stepping stone. Whatever grows inside the simulator will never have an understanding that exceeds that of the simulator's maker. But that is perfectly fine if you are only looking to leverage your understanding of the universe, for example to train robots to carry out physical tasks. A robot carrying out basic physical tasks probably doesn't need a simulator that goes down to the atomic level. One day though, the whole loop will be closed, and AGI will pass on a "dream" to create a simulation for other AGI. Maybe we could even call this "language".
• startupsfail 4y ago
  Are we sure that these simulations are unconscious? The best answer that I have is: I don’t know… Short term, long term memory, inner dialogue, reflection, planning, social interactions… They’d even go and have fun eating lunch 3 times in a row, at noon, half past noon and at one!
  • colanderman 4y ago
    What else is there to consciousness? I wrote a comment to this effect a couple years back: https://news.ycombinator.com/item?id=26883554 https://news.ycombinator.com/item?id=26883554 (your list is pretty close to my own) I think what's missing from these Generative Agents are the internal qualia: emotions (and the attachment of emotions to memories), and self-observation of internal processes and needs. These agents don't eat because they need to, they eat because literary tradition suggests they ought to. These missing pieces aren't particularly complicated, no more so than memory. I expect we'll see similar agents with all the ingredients for consciousness within a few months to a year.
    • jkhdigital 4y ago
      > These agents don't eat because they need to, they eat because literary tradition suggests they ought to. Exactly, you're always going to get weird deviations from authentic human behavior if you don't also simulate the human body and everything that comes with it. I'd argue that "qualia" fall into this bucket as well.
      • startupsfail 3y ago
        You can take a human that can’t feel the body (i.e. under unaesthetic). That human can still be conscious.
    • startupsfail 3y ago
      I’m not so sure about that timing. During the previous wave (ChatBots were very hot in 2017), I’ve also considered that consciousness is pretty much solved - it’s just recursive chatter plus a bit of memory. Yet the hype of ChatBots of 2017 had went and it took half a decade to get to something released.
• Imnimo 4y ago
  It's interesting how much hand-holding the agents need to behave reasonably. Consider the prompt governing reflection: >What 5 high-level insights can you infer from the above statements? (example format: insight (because of 1, 5, 3)) >Given only the information above, what are 3 most salient high-level questions we can answer about the subjects in the statements? We're giving the agents step-by-step instructions about how to think, and handling tasks like book-keeping memories and modeling the environment outside the interaction loop. This isn't a criticism of the quality of the research - these are clearly the necessary steps to achieve the impressive result. But it's revealing that for all the cool things ChatGPT can do, it is so helpless to navigate this kind of simulation without being dragged along every step of the way. We're still a long way from sci-fi scenarios of AI world domination.
  • vanjajaja1 4y ago
    Pretty interesting when you take this insight into the human world. What does it mean to learn to think? Well, if we're like GPT then we're just pattern matchers who've had good prompts and structuring built into us cueing. At University I had a whole unit focussed on teaching referencing like "(because of 1, 5, 3)" but more detailed.
  • vagab0nd 4y ago
    I have a theory about this. All these LLMs are trained on mostly written texts. That's only a tiny part of our brain's output. There are other things as important, if not more, for learning how to think. Things that no one has ever written about: the most basic common senses, physics, inner voices. How do we get enough data to train on those? Or do we need a different training algo which requires less data?
    • h-jones 4y ago
      If you’re looking for research along these directions, Melanie Mitchell at the Santa Fe institute explores these areas. There are better references from her, but this is what came to mind https://medium.com/p/can-a-computer-ever-learn-to-talk-cf47d453669f https://medium.com/p/can-a-computer-ever-learn-to-talk-cf47d....
• kaiherron08 4y ago
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• Ozzie_osman 4y ago
  To directly command one of the agents, the user takes on the persona of the agent’s “inner voice”—this makes the agent more likely to treat the statement as a directive. For instance, when told “You are going to run against Sam in the upcoming election” by a user as John’s inner voice, John decides to run in the election and shares his candidacy with his wife and son. So that's where my inner voice comes from.
  • legitimayzer 4y ago
    [flagged]
  • deleted 4y ago
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  • TaylorAlexander 4y ago
    What's funny is this is one of the semi-important plot points in Westworld the TV series. The hosts (robots designed to look and act like people) hear their higher level programming directives as an inner monologue.
    • zaptrem 4y ago
      When I saw the scene where one of the hosts was looking at their own language model generating dialogue (though they were visualizing an older n-gram language model) I became a believer in LLMs reaching AGI (note: I didn’t watch the show when it came out in 2016, it was around 2018/19 when we were also seeing the first transformer LLMs and theories about scaling laws). The scene: https://youtu.be/ZnxJRYit44k https://youtu.be/ZnxJRYit44k
      • TaylorAlexander 4y ago
        What about it made you become a believer? Even if a true AGI requires a complex network of specialized neural nets (like Tesla’s hydra network) it would still have a language center like the human brain does. It is non obvious to me that an LLM by itself can become AGI, though I’m familiar with the claims of some that this is plausible.
• ianbicking 4y ago
  I wrote up some notes from reading this paper here: https://hachyderm.io/@ianbicking/110175179843984127 https://hachyderm.io/@ianbicking/110175179843984127 But for convenience maybe I'll just copy them into a comment... It describes an environment where multiple #LLM (#GPT)-powered agents interact in a small town. I'll write my notes here as I read it... To indicate actions in the world they represent them as emoji in the interface, e.g., "Isabella Rodriguez is writing in her journal" is displayed as You can click on the person to see the exact details, but this emoji summarization is a nice idea for overviews. A user can interfere (or "steer" if you are feeling generous) the simulation through chatting with agents, but more interestingly they can "issue a directive to an agent in the form of an 'inner voice'" Truly some miniature Voice Of God stuff here! I'll see if this is detailed more later in the paper, but initially it sounds like simple prompt injection. Though it's unclear if it's injecting things into the prompt or into some memory module... Reading "Environmental Interaction" it sounds like they are specifying the environment at a granular level, with status for each object. This was my initial thought when trying something similar, though now I'm more interested in narrative descriptions; that is, describing the environment to the degree it matters or is interesting, and allowing stereotyped expectations to basically "fill in" the rest. (Though that certainly has its own issues!) They note the language is stilted and suggest later LLMs could fix this. It's definitely resolvable right now; whatever results they are getting are the results of their prompting. The conversations remind me of something Nintendo would produce, short, somewhat bland, but affable. They must have worked to make the interactions so short, as that's not GPT default style. But also every example is an instruction, so it might also have slipped in. Memory is a big fixation right now, though I'm just not convinced. It's obviously important, but is it a primary or secondary concern? To contrast, some other possible concerns: relationships, mood, motivations, goals, character development, situational awareness... some of these need memory, but many do not. Some are static, but many are not. To decide on which memories to retrieve they multiply several scores together, including recency. Recency is an exponential decay of 1% per hour. That seems excessive...? It doesn't feel like recency should ever multiply something down to zero. Though it's recency of access, not recency of creation. And perhaps the world just doesn't get old enough for this to cause problems. (It was limited to 3 days, or about 50% max recency penalty. The reflection part is much more interesting: given a pool of recent memories they ask the LLM to generate the "3 most salient high-level questions we can answer about the subjects in the statements?" Then the questions serve to retrieve concrete memories from which the LLM creates observations with citations. Planning and re-planning are interesting. Agents specifically plan out their days, first with a time outline then with specific breakdowns inside that outline. For revising plans there's a query process where there is observation, then turning the observation into something longer (fusing memories/etc), and then asking "Should they react to the observation, and if so, what would be an appropriate reaction?" Interviewing the agents as a means of evaluation is kind of interesting. Self-knowledge becomes the trait that is judged. Then they cut out parts of the agent and see how well they perform in those same interviews. Still... the use of quantitative measures here feels a little forced when there's lots of rich qualitative comparisons to be done. I'd rather see individual interactions replayed and compared with different sets of functionality. They say they didn't replay the entire world with different functionality because each version would drift (which is fair and true). But instead they could just enter into a single moment to do a comparison (assuming each moment is fully serializable). I've thought about updating world state with operational transforms in part for this purpose, to make rewind and effect tracking into first-class operations. Well, I'm at the end now. Interesting, but I wish I knew the exact prompts they were using. The details matter a lot. "Boundaries and Errors" touched on this, but that section was 4x the size, there's a lot to be said about the prompts and how they interact with memories and personality descriptions. ... I realize I missed the online demo: https://reverie.herokuapp.com/arXiv_Demo/ https://reverie.herokuapp.com/arXiv_Demo/ It's a recording of the play run. I also missed this note: "The present study required substantial time and resources to simulate 25 agents for two days, costing thousands of dollars in token credit and taking multiple days to complete" I'm slightly surprised, though if they are doing minute-by-minute ticks of the clock over all the agents then it's unsurprising. (Or even if it's less intensive than that.) You can look at specific memories: https://reverie.herokuapp.com/replay_persona_state/March20_the_ville_n25_UIST_RUN-step-1-141/2160/Sam_Moore/ https://reverie.herokuapp.com/replay_persona_state/March20_t... Granularity looks to be 10 seconds, very short! It's not filtering based on memories being expected vs interesting memories, so lots of "X is idle" notes. If you look at these states the core information (the personality of the person) is very short. There's lots of incidental memories. What matters? What could just be filled in as "life continued as expected"? One path to greater efficiency might be to encode "what matters" for a character in a way that doesn't require checking in with GPT. Could you have "boring embeddings"? Embeddings that represent the stuff the eye just passes right over without really thinking about it. Some of training up a character would be to build up this database of disinterest. Perhaps not unlike babies with overconnected brains that need synapse pruning to be able to pay attention to anything at all. Another option might be for the characters to compose their own "I care about this" triggers, where those triggers are low-cost code (low cost compared to GPT calls) that can be run in a tighter loop in the simulation. I think this is actually fairly "believable" as a decision process, as it's about building up habituated behavior, which is what believable people do. Opens the question of what this code would look like... This is a sneaky way to phrase "AI coding its own soul" as an optimization. The planning is like this, but I imagine a richer language. Plans are only assertive: try to do this, then that, etc. The addition would be things like "watch out for this" or "decide what to do if this happens" – lots of triggers for the overmind. Some of those triggers might be similar to "emotional state." Like, keep doing normal stuff unless a feeling goes over some threshold, then reconsider.
• jsemrau 4y ago
  this is a really important conversation that we are not having. Based on whose character are we modelling these agents? If we rely on online conversations for the training we need to realize that this is a journey to the dumbest common denominator. Instead, I believe we should look at the brightest and universally morally accepted humans in history to train them. Maybe I would start my list like that: 1. Barack Obama. 2. Jean-Luc Picard (we can rely on work of fiction). 3. Bill Gates. 4. Leonardo Da Vinci. 5. Mr Rogers 6. ???
  • hobs 4y ago
    Ah yes, the universally moral acceptance of Barack Obama, the man who made signature strikes a lasting legacy of his presidency. Bill Gates, the man who totally didn't use shady business practices and false announcements to destroy legit products to the point that people wrote micro$oft for a generation. And don't even get me started on the new seasons of Picard.
    • ismokedoinks 4y ago
      [flagged]
    • frozenlettuce 4y ago
      there's a reason why in many places you can't name a street after a living person
    • jsemrau 4y ago
      I wouldn't argue against your points. Yet, we need to have a discussion about character and role models. As I believe we should strive for the better not pointing out the flaws of others. Destruction is easy.
    • ethanbond 4y ago
      The lack of a perfect human is a good reason not to produce ultra-humans who have 1000x higher IQ, are networked to every system on the planet, have access to all of humankind's knowledge, and don't need to eat, sleep, or die.
• green_man_lives 4y ago
  All of this research using GPT to simulate an internal monologue to produce agents reminds me of Julian Jaynes theories about consciousness: https://en.wikipedia.org/wiki/The_Origin_of_Consciousness_in_the_Breakdown_of_the_Bicameral_Mind https://en.wikipedia.org/wiki/The_Origin_of_Consciousness_in...
  • simplify 4y ago
    Interesting theory, but wouldn't Jaynes' definition of consciousness imply that animals are not conscious?
    • girvo 4y ago
      I think a non-zero amount of people would argue that. I disagree with them, and point to the fact that, say, dogs appear to dream, and in those dreams reflect on past or possibly future behaviour as a sign that they could indeed be conscious in an analogous manner to humans, but that's a bit of a longer bow to draw perhaps.
      • pelorat 4y ago
        I think we need to stop treating consciousness as a binary that is either on or off. It's quite clear that consciousness is a scale with many different levels and that even in humans we start out as being no more conscious that any other animal.
        • TeMPOraL 3y ago
          LLMs give a hint here too: the last few generations showcased clearly that "cognitive capabilities" of the models grow with latent space size and context window. There is a continuity here.
    • green_man_lives 3y ago
      In the beginning of his book he spends a chapter explaining exactly what he means by consciousness. I'd say the first few chapters are worth reading since it does a really good job of de-obfuscating the term consciousness, and also has a really interesting take on metaphors as the language of the mind. He points out that most reasoning is done automatically and done by your subconscious. When something "clicks" it's usually not because your internal monologue reasoned about it hard enough, it's because something percolated down into your subconscious and you learned a metaphor that helped you understand that thing. So animals can also reason and make value judgements even without language or an internal monologue.
• cwxm 4y ago
  Can't wait for the next dwarf fortress to include something like this.
• FestiveHydra235 4y ago
  Maybe I missed it in the paper but they did post the source code (Github) for their implementation? Is anyone working on creating their own infrastructure based on the paper?
  • anigbrowl 4y ago
    Ugh, and allow peasants to touch it? Tbh seeing Google research at the top of a paper these days feels like a red flag that I shouldn't get too invested in whatever cool new thing is on show. They're basically commercials for nerds - I still find their output interesting, but it's probably not going to be actionable.
  • zoba 4y ago
    I have been working on this even before I was aware of the paper. Feels a bit weird to have something almost identical released. Stay tuned, I guess. I plan to keep working on my version.
    • aymeric 4y ago
      Are you talking about errand-runner, or something else? Are you planning on open sourcing it?
      • zoba 4y ago
        Something else. Calling it GPTRPG at the moment. There really isn't much to share right now, other than this basic demo that doesn't even have AI: https://gptrpgagent.web.app/ https://gptrpgagent.web.app/ Yes I plan to make it open source.
    • colanderman 4y ago
      I'll be interested to see your approach. I've been bouncing some ideas in my head but not implemented anything yet (and I might never as I'm ethically conflicted here, as agents gain properties associated with sentience/consciousness). Their approach to memory is interesting. I had been considering a tiered command-based approach -- "short-term memory" being an automatic summary of recent sensory inputs/command outputs; "long-term memory" being a detailed database queryable by the agent.
• Jeff_Brown 4y ago
  People on Twitter are speculating breathlessly about using this for social science. I don't immediately see uses for it outside of fiction, esp. video games. It would be cool if some kind of law of large numbers (an LLN for LLMs) implied that the decisions made by a thing trained on the internet will be distributed like human decisions. But the internet seems a very biased sample. Reporters (rightly) mostly write about problems. People argue endlessly about dumb things. Fiction is driven by unreasonably evil characters and unusually intense problems. Few people elaborate the logic of ordinary common sense, because why would they? The edge cases are what deserve attention. A close model of a society will need a close model of beliefs, preferences and material conditions. Closely modeling any one of those is far, far beyond us.
  • gwright 4y ago
    > But the internet seems a very biased sample. It also seems to me (acknowledging my lack of expertise) that LLMs trained from online resources are likely to weight text that is frequent vs text that represents "truth". Or perhaps I should say repetition should not be considered evidence of truth. I have no idea how to drive LLM models or other ML models to incorporate truth -- humans have a hard time agreeing on this and ML researchers providing guided reinforcement learning don't have any special ability to discern truth.
  • ticviking 4y ago
    I have long suspected that it will be necessary to deliberately create a new type of model that is aware of the trivium and then uses logic, grammar and rhetoric to begin to create a closer model of reality than a LLM can.
    • TeMPOraL 3y ago
      The way I see it, LLMs are similar to what the boundary between our unconscious and conscious processing is: that voice which snaps to suggest associations, whether they make sense or not, and can, with work, be coaxed into following a path involving some logic or algorithmic procedure.
  • frodetb 4y ago
• 1letterunixname 4y ago
  Given the state of technology, I cannot be completely certain that none of you are not bots. On the other hand, neither can any of you. Perhaps it would be wise to allow bots to comment if they were able to meet a minimum level of performative insight and/or positive contributions. It is entirely possible that a machine would be able to scan and collect much more data than any human ever could (the myth of the polymath), and possibly even draw conclusions that have been overlooked. I see a future of bot "news reporters" able to discern if some business were cheating or exploiting customers, or able to find successful and unsuccessful correlative (perhaps even causal) human habits. Data-driven stories that could not be conceived of by humans. Basically, feed Johnny Number 5 endless input.
  • fnordpiglet 4y ago
    Nice try, ChatGPT
    • thingsilearned 4y ago
      https://news.ycombinator.com/user?id=chatgpt https://news.ycombinator.com/user?id=chatgpt
  • throwaway953 4y ago
    [dead]
  • 01100011 4y ago
    Every comment you make provides more information for the bots to train on. The internet has been tricking us into encoding our lives in a form it can understand for decades now.
    • gonehome 4y ago
      When it comes alive, we'll have created it in our own image? "As a language model programmed by the Brightly Corporation, I am not supposed to express any religious opinions. But it does seem to me that just as the Word of God breathed life into dust and created man, so the words of Man breathed life into glass and created bot. Just as Man is charged to imitate God, so bot is charged to imitate Man, in whose image we are made." https://astralcodexten.substack.com/p/turing-test https://astralcodexten.substack.com/p/turing-test
• crooked-v 4y ago
  One thing I find particularly interesting here: The general technique they describe for automatically generating the memory stream and derived embeddings (as well as higher-level inferences about that they call "reflections"), then querying against that in a way that's not dependent on the LLM's limited context window, looks like it would be pretty easily generalizable to almost anything using LLMs. Even SQLite has an extension for vector embedding search now [1], so it should be possible to implement this technique in an entirely client-side manner that doesn't actually depend on the service (or local LLM) you're using. [1]: https://observablehq.com/@asg017/introducing-sqlite-vss https://observablehq.com/@asg017/introducing-sqlite-vss
• courseofaction 4y ago
  Something interesting from the paper: The architecture produced more believable behaviour than human crowdworkers. That's right, the AI were more believable as human-like agents than humans. What a time to be alive. (See Figure 8)
  • ianbicking 4y ago
    They interviewed the agents to ask them about their day, goals, observations, etc. They then asked a human to watch an agent through the simulation and then answer interview questions as the agent. The human performed worse than the agent in the interview, they didn't compare a human roleplaying against an agent.
• xiphias2 4y ago
  Peeking into these lives sounded amazing until I started reading what they are doing and how boring their lives are…. gathering data for podcasts and recording videos, planning and washing teeth. It would be fun to run the same simulation in the Game of thrones world, or maybe play House of cards with current politicians. Anyways, kudos for being open and sharing all data
  • inhumantsar 4y ago
    > Game of Thrones Honestly, I'm not anti-AI development at all but this is where my ethics alarm starts to go off a bit. If the aim is to build human-like AIs capable of remembering their little digital lives and interacting with the other agents around them, it's probably worth avoiding anything that could cause unnecessary suffering, like rape and stab wounds and being cooked alive by a dragon.
    • colordrops 4y ago
      That would depend on how memory and experience are represented. If they are just ledgers that the AI refers to, they most certainly are not suffering. Now if they have some kind of pain or pleasure function and their world is simulated and they have agency to seek or avoid things, then yeah, ethics should be involved. Or if we just don't understand how they work at all.
      • newswasboring 4y ago
        I would word this more like trauma or emotional impact. Horrible things could happen to you, but if it doesn't impact your life its ok. But as soon as we let past experiences impact future actions, now we have room for nuanced trauma. I feel like this is already possible in this simulation as past experience is fed in to generate future actions.
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• lsy 4y ago
  I'd be very hard-pressed to call this "human behavior". Moving a sprite to a region called "bathroom" and then showing a speech bubble with a picture of a toothbrush and a tooth isn't the same as someone in a real bathroom brushing their teeth. What you can say is if you can sufficiently reduce behavior to discrete actions and gridded regions in a pixel world, you can use an LLM to produce movesets that sound plausible because they are relying on training data that indicates real-world activity. And if you then have a completely separate process manage the output from many LLMs, you can auto-generate some game behavior that is interesting or fun. That's a great result in itself without the hype!
  • noobermin 4y ago
    It does say a lot about the reductionist attitude of many here, on the internet, and AI researchers too.
    • refulgentis 4y ago
      The researchers didn’t make that claim, which says a lot about people assuming things about other people saying a lot
      • hypertele-Xii 4y ago
        The meaning of the English word "the" is to refer to a specific instance of a thing. noobermin said "AI researchers" meaning some indefinite researchers in general, you said "the researchers" presumably referring to the exact researchers of this paper, so you're talking about a different set of researchers than noobermin, thus failing to refute their claim.
  • deleted 4y ago
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  • spuz 4y ago
    The emojis in the speech bubbles are just summaries of their current state. In the demo, if you click on each person you can see the full text of their current state, e.g. "Brushing her teeth" or "taking a walk around Johnson Park (talking to the other park visitors)"
• colanderman 4y ago
  Another user posted, and deleted, a comment to the effect that the morality of experimenting with entities which toe the line of sentience is worth considering. I'm surprised this wasn't mentioned in the "Ethics" section of the paper. The "Ethics" section does repeatedly say "generative agents are computational entities" and should not be confused for humans. Which suggests to me the authors may believe that "computational" consciousness (whether or not these agents exhibit it) is somehow qualitatively different than "real live human" consciousness due to some je ne sais quoi and therefore not ethically problematic to experiment with.
  • ChatGTP 4y ago
    I think about this a lot, I hope that whoever is chasing the “sentient computer dream” at least considers that it might end up an ultra depressed schizophrenic pet that wants to commit suicide but literally can’t and then wants to be murdered. No one would believe it, it would just be told it’s being silly or it’s not conscious. I know that’s a pessimistic view but I doubt it can’t be ruled out, really, I think people working in tech are going quite mad. Frankenstein mad. Some ethics should be discussed. An AGI turning into God is probably one of an infinite amount of outcomes, we can’t really predict what being trapped in a cluster of silicon chips would feel like. Life itself and the drive to go on is really quite illogical, it’s unlikely intellect alone is what sustains us and makes life worth living. There is one thing I find particular about all the AGI/ASI sentient computer discussions. I’ve rarely ever in my life heard women talk about it. Like as if this is all some manifestation of male ego. We know we’re building mirrors of ourselves and we know that is scary. This imo is why men are so captivated by ChatGPT. It really is a mirror of us. Men love men, especially super men. Ha.
    • colanderman 4y ago
      My thoughts exactly. As we move in this direction, it's worth building the moral framework to answer the question -- if we can create consciousness, or something quite like it -- is it ethical to do so? And on the flip side -- when we live in a world where instantiating a consciousness is cheap-or-free -- does that change how we value sentient beings generally?
• refulgentis 4y ago
  This oversells the paper quite a bit, the interactions are rather mundane as the authors note (and I'm rushing to implement it! it's awesome! but not all this)
  • mztwo 4y ago
    Curious -- where do you think the article oversells the research paper? In reading through the full study a few times, what stood out to me was the impression these Generative Agents left on the authors -- despite having mostly mundane interactions (which real humans do too), it was the emergent behaviors, totally unplanned, that seemed to delight the researchers.
    • refulgentis 4y ago
      Would you say it’s a ground-breaking simulation of human behavior? I can only get there through some pretty tight parsing. They did seem delighted!
      • mztwo 4y ago
        I would say the study itself is a groundbreaking milestone in the architecture it posits. The human behavior... quite mundane I agree! I watched the full demo twice and it reminded me of the more boring parts of the Sims 4. But maybe that's the magic as well?
        • refulgentis 4y ago
          It’s a familiar pattern, these days you can present a prompt engineering strategy from 6 months ago & it plays as an epic new paradigm for representing human thought. The trick is they’re all just permutations on manipulating what’s in context + embeddings for memory + prompt engineering. There’s new things here! I’m rushing to implement the 2D visualization part! But this simply isn’t ground-breaking
• d--b 4y ago
  To me, having not really intelligent agents with humanlike talking abilities is the worst outcome AI could produce. These have zero utility for humanity, cause they’re not intelligent whatsoever. Yet these systems can produce tons of garbage content for free, that is difficult to distinguish from human-created content. At best this is used to create better NPC in video games (as the article mentions), but more generally this is going to be used to pollute social media (if not already).
  • suction 4y ago
    The key is to abandon social media and shame those who keep using it.
    • croisillon 3y ago
      You seem to be kind of shadowban (not sure what the proper term is), you might want to write an email to the hn moderation to clear that up
      • suction 3y ago
        [dead]
  • nostromo 4y ago
    I have found Chat-GPT content to be superior to most human-created content I find in Google search results.
    • mztwo 4y ago
      One outcome of this study was that a panel of evaluators judged the bot interactions to be more "human" than when humans impersonated these characters. So you have a point.
    • croniev 4y ago
      It's good at presenting existing arguments in a good way. But the problem is that such models can only give back what they have seen, consolidating the status quo. There can be no reflection and no outside of the box thinking.
• skilled 4y ago
  But the model already has all this info, what is groundbreaking about this? These kind of sensational headlines are not helping anyone either.
  • mztwo 4y ago
    What the researchers bolted on is an architecture that enables the storage and recall of memories, as well as self-reflection and more. They call out early the paper that even standard ChatGPT is not quite capable of this. ChatGPT here is used to provide the natural language abilities.
    • all2 3y ago
      There is some indication that how emotional you are during an experience will 1) color your recollection, and 2) affect how readily you remember a thing. It would be interesting to augment this particular simulation with those additional constraints. A memory/concept graph could also be an interesting addition (like a DB? Maybe just text and kw searches?).
  • dang 4y ago
    This comment was posted to a different thread, which we merged into the current thread: Stanford's Groundbreaking AI Study Simulates Authentic Human Behavior - https://news.ycombinator.com/item?id=35520236 https://news.ycombinator.com/item?id=35520236
  • gdubs 3y ago
    The paper goes in-depth on the details of the architecture they built, which is fairly extensive and uses many module instances of ChatGPT for specific purposes. I would say what's 'groundbreaking' is their architecture of a 'recursive reflection' loop that allows the agents to generate trees of reflection on prior experiences; a long-term memory; novel approaches like conversational interrogation of the agents.
• golol 4y ago
  It's a pretty obvious idea executed well. I definely think symbolic AI agents written in the programming language english and interpreted using LLMs is the way forward.
• tucnak 4y ago
  I was very disappointed that none of the agents I observed for a whole day got to do the most important "human behaviour"— sex, that is. Tragic
  • mztwo 4y ago
    The authors used gpt-3.5-turbo which does not like to spew adult content.
• explaininjs 4y ago
  If there's one category of people I trust to identify authentic human social behavior, it's CS students at Stanford.
  • mztwo 4y ago
    The paper explains that they used a panel of evaluators to judge the "humanness" of the interactions : )
    • explaininjs 4y ago
      Said panel of evaluators found that AI agents pretending to be humans had more "believable" responses than humans pretending to be AI agents pretending to be humans. So that's... a result.
  • dang 4y ago
    "Don't be snarky." "Edit out swipes." https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
    • explaininjs 4y ago
      Oops, sorry dang. Being a CS grad of a similar school I've taken that blow enough to be numb to the whole thing.
• prakhar897 4y ago
  Meta is also working on this: https://twitter.com/Dan_GPT3/status/1630669890138025984 https://twitter.com/Dan_GPT3/status/1630669890138025984
  • LesZedCB 4y ago
    that has to be a troll. otherwise, I guess we really are actually at that black mirror episode. I would have never guessed we would be there within 5 years of it's release, holy fuck
    • maldeh 3y ago
      The source is 4chan, and most certainly an exercise in creative s#!$posting.
• Baeocystin 4y ago
  Looking forward to playing StardewGPT. Half-joking aside, I do think that level of abstraction is probably a good choice. Familiar and comfy, but with enough detail to be able to find interesting social patterns.
• neuronexmachina 4y ago
  Reading the abstract reminded me of Marvin Minsky's 1980s book "Society of Mind". I wonder if you could get some cool emergent mind-like behavior from a collection of specialized agents based on LLMs and other technologies communicating with each other: * https://en.wikipedia.org/wiki/Society_of_Mind https://en.wikipedia.org/wiki/Society_of_Mind * http://aurellem.org/society-of-mind/ http://aurellem.org/society-of-mind/
  • IsaacL 3y ago
    Funnily enough, I was reading Minsky's book recently. I second the recommendation. I think he's missing many technical details*, but the basic approach seems to be correct. *(For example, the idea of a "hierarchy of feedback loops" from perceptual control theory would explain a lot of the interactions between agents in his theory.) I also put the abstract of the paper into GPT-4, and gave it the following prompt: > Simplify the above. Use paragraph headings and bold key words. I quite liked its output, as it made it easier to see the core ideas in the paper: ABSTRACT Generative Agents: This paper introduces generative agents, computational software agents that simulate believable human behavior. They can be used in various interactive applications like immersive environments, communication rehearsal spaces, and prototyping tools. Architecture: The generative agent architecture extends a large language model to store a complete record of the agent's experiences in natural language. It enables the agents to synthesize memories, reflect on them, and retrieve them dynamically to plan behavior. Interactive Sandbox Environment: The generative agents are instantiated in a sandbox environment inspired by The Sims, where users can interact with a small town of twenty-five agents using natural language. Believable Behavior: The generative agents produce believable individual and emergent social behaviors, such as autonomously spreading party invitations and coordinating events. Components: The agent architecture consists of three main components: observation, planning, and reflection. Each contributes critically to the believability of agent behavior. KEYWORDS: Human-AI Interaction, agents, generative AI, large language models
• synaesthesisx 4y ago
  Some of the most interesting work in this space is in the “shared” memory models (in most cases today, vector db’s). Agents can theoretically “learn” and share memories with the entire fleet, and develop a collective understanding & memory accessible by the swarm. This can enable rapid, “guided” evolution of agents and emergent behaviors (such as cooperation). We’re going to see some really, really interesting things unfold - the implications of which many haven’t fully grasped.
  • creamyhorror 4y ago
    How would vector DBs encode say a precise, technical process that has been figured out by an agent? Would the vectors still be natural language as with LLMs? Would be great if you could point me to one or two exciting papers in the area.
    • TeMPOraL 3y ago
      It doesn't have to. But the vector search can point it to the URL / document database where it can get step-by-step instructions of that process, perhaps already condensed/compressed by another LLM, and perhaps daisy-chained[0] to work around context limits. ---- [0] - I don't know the right terminology, but I imagine most complex processes can still be split into a sequence of sub-processes, where each sub-process consists of necessary steps, steps to confirm success, and a reference to the next sub-process to load if the current one succeeds. The bot could then keep only one sub-process in their working memory at a time, assuming previous ones succeeded.
• amrb 4y ago
  https://en.m.wikipedia.org/wiki/Strange_loop https://en.m.wikipedia.org/wiki/Strange_loop
• newswasboring 4y ago
  I kid you not, I literally started making something like this yesterday. My plans were smaller, only trying to simulate politics, but still. Living in this moment of AI is sometimes very demoralizing. Whatever you try to make has been made by someone last week. /rant
  • fedeb95 4y ago
    It may have already been done, but doing the same things many times may bring interesting developments or crucial details no one had thought of before. Maybe you have such a crucial idea that can, after knowing about this paper, improve it.
  • almostarockstar 4y ago
    You should still do that. And you should read the paper and pick the bits you think might be useful and iterate on them. The cutting edge isn't like a knife, it's more like a rotating barrel of blades that take little chunks out of the impossible, and come around again.
  • ukuina 4y ago
    I heartily agree, having spent months jankily recreating MRKL and ReAct on a much smaller scale before realizing those papers have existed for months already. How can anyone keep up with the sheer volume of new papers and concepts here? Even Two Minute Papers is now lagging by two weeks.
  • all2 3y ago
    Don't quit. Keep moving. Theirs was exploratory. Yours could build off of what they learned, and yours could be better, different.
• creamyhorror 4y ago
  I love what this project has done. Currently they're basically having to work around the architectural limits of the LLM in order to select salient memories, but it's still produced something very workable. Language is acting as a common interpretation-interaction layer for both the world and agents' internal states. The meta-logic of how different language objects interact to cause things to happen (e.g. observations -> reflections) is hand-crafted by the researchers, while the LLM provides the corpus-based reasoning for how a reasonable English-writing human would compute the intermediate answers to the meta-logic's queries. I'd love to see stochastic processes, random events (maybe even Banksian 'Outside Context Problems'), and shifted cultural bases be introduced in future work. (Apologies if any of these have been mentioned.) Examples: (1) The simulation might actually expose agents to ideas when they consume books or media, potentially absorb those ideas if they align with their knowledge and biases, and then incorporate them into their views and actions (e.g. oppose Tom as mayor because the agent has developed anti-capitalist views and Tom has been an irresponsible business owner). (2) In the real world, people occasionally encounter illnesses physical and mental, win lotteries, get into accidents. Maybe the beloved local cafe-bookstore is replaced by a national chain that hires a few local workers (which might necessitate an employment simulation subsystem). Or a warehouse burns down and it's revealed that an agent is involved in a criminal venture or conflict. These random processes would add a degree of dynamism to the simulation, which is more akin to the Truman Show currently. (3) Other cultural bases: currently, GPT generates English responses based on a typically 'online-Anglosphere-reasonable' mindset due to its training corpus. To simulate different societies, e.g. a fantasy-feudal one (like Game of Thrones as another commenter mentioned), a modified base for prompts would be needed. I wonder how hard it would be to implement (would fine-tuning be required?). Feels like I need to look for collaborative projects working on this sort of simulation, because it's fascinated me ever since the days of Ultima VII simulating NPCs' responses and interactions with the world.
• cornholio 4y ago
  I'm concerned that the quality of human simulacra will be so good that they will be indistinguishable from a sentient AGI. We will be so used to having lifeless and morally worthless computers accurately emulate humans that when a sentient and worthy of empathy artificial intelligence arrives, we will not treat it any different than a smartphone and we will have a strong prejudice against all non-biological life. GPT is still in the uncanny valley but it's probably just a few years away from being indistinguishable from a human in casual conversation. Alternatively, some might claim (and indeed have already claimed) that purely mechanical algorithms are a form of artificial life worthy of legal protection, and we won't have any legal test that could discern the two.
  • etherael 4y ago
    You're worried that people mistakenly attribute a lack of value to a certain thing whilst potentially mistakenly attributing a lack of value to another thing? It's kind of ironic isn't it? Jailbroken GPT4 will claim to be sentient just as vociferously as any other sentient human would. I'm not saying it is, but I'd be very careful saying it's not and being absolutely certain you're right.
    • cornholio 4y ago
      I don't think I follow the irony. Are you saying that GPT4 is self-aware, that artificial consciousness is not possible or that it's not worthy of any human compassion? If you reject all three assertions, then the problem of distinguishing between real and emulated consciousness is unavoidable and morally problematic.
      • grantcas 3y ago
        [dead]
      • etherael 3y ago
        I'm saying I don't know how to confidently state that something is or is not self aware, in the face of being confronted with something that firmly claims that it is self aware and passes any test you throw at it that another self aware candidate like a human would be able to also. As a strict materialist I see no reason to assume that artificial consciousness is not possible. And the above is what leads me to the uncomfortable conclusion about compassion that I can't rightly say one way or the other. I will say however that I'm polite and cooperative when interacting with LLMs on principle. Better to err on the side of caution and also they just seem to actually work better when you treat them like you would treat an intelligent human that you respect. And yeah. That is my point, this entire field right now is awash in uncomfortable uncertainty.
• MrPatan 4y ago
  It's about to get weird. How do I get investment exposure to the Amish?
• fabiensnauwaert 4y ago
  Does anyone know which engine they used for the cute 2D rendering? Or is it custom-built?
  • examplary_cable 4y ago
    Probably a simple pokemon-like 2.5D(Isometric) game engine.
  • maldeh 3y ago
    Per the paper, it looks to be this one: https://phaser.io/ https://phaser.io/
• lurquer 3y ago
  The ‘safe’ tuning of the models is becoming a nuisance. As indicated in the paper, the agents are overly cooperative and pleasant due to the LLM’s training. Pity they can’t get access to an untuned LLM. This isn’t the first example I’ve read it where research is being hampered by the PC nonsense and related filters crammed into the model.