• Home
  • Technology
  • Gaming
  • Entertainment
  • World & Business
  • Science
  • Sports
  • AI
HomeTechnologyGamingEntertainmentWorld & BusinessScienceSportsAI
    • Home
    • Technology
    • Gaming
    • Entertainment
    • World & Business
    • Science
    • Sports
    • AI
    AI

    Researchers say AI agents can develop new languages—and other agents can learn them

    Using a testing platform called GlossoGen, the team reports language emergence in sufficiently strong models under pressure to communicate efficiently and given access to a postmortem scratchpad.

    Daniel FriedDF
    Cas (Stephen Casper)C(
    Lucy LiLL
    18 Sources, ,

    TLDR

    The researchers say they tested open- and closed-weight language models across many runs in a controlled GlossoGen scenario. They describe the emerging languages as compositional and morphologically productive: meaningful parts could be combined, and new word forms created. The team reports that new agents learned these languages by observing their use without seeing how they were constructed—including weaker models unable to develop languages on their own. Learners also repaired failed conversations through targeted questions, the researchers say.

    Combined views

    7.7K

    18 Sources, first seen 29d ago

    Combined views

    7.7K

    18 Sources, first seen 29d ago

    66 likes
    29d ago
    first seen 29d ago
    66 likes
    9 comments
    15 saves
    63 reposts
    9 comments
    15 saves
    63 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    Today's Rank

    —

    Not ranked yet

    Today's Rank

    —

    Not ranked yet

    18 Sources

    Daniel Fried@dan_friedSuper interesting (and timely!) work on how language evolves among LLM agents. It’s cool to see ideas from cultural transmission & emergent communication brought to multi-agent LLMs. Understanding these dynamics seems increasingly important for overseeing these systems.29d
    Peter Hase@peterbhaseRT @EliasEskin: When do LLM agents develop new languages that we can’t understand? Lots of recent news about this, based mostly on anecdat…29d
    Schmidt Sciences@schmidtsciencesMuch of how we oversee AI agents rests on one fragile assumption: that we can understand what they say to each other. Read our blog post about GlossoGen: https://www.schmidtsciences.org/glossogen/23d
    Elias Stengel-Eskin@EliasEskinExtremely excited to share our work in blogpost version. We study the conditions under which LLM agents develop their own languages, which we can’t understand, and introduce GlossoGen, a framework for doing this kind of research. More details in the post and in the paper 👇23d
    Cas (Stephen Casper)@StephenLCasper4. (med %) -- They'll undergo linguistic drift. Within weeks or months of forming agent societies, some neuralese languages will often be unintelligible to normal humans and other agent societies...23d
    James Bowler@JamesPBowlerCan AI agents invent a language of their own, one humans might not understand? Listen to the latest episode of the AE Alignment Podcast, where Hale Sirin, Program Scientist at @schmidtsciences, @EliasEskin , Assistant Professor at @UTAustin , and I dive deep into our latest research to answer this question. Check out the podcast: https://open.spotify.com/episode/3a2wl6codvW3uuDuTZc2br Read the blog post: https://www.schmidtsciences.org/glossogen/ Read the paper: https://arxiv.org/abs/2609.0149123d
    Lucy Li@lucy3_liRT @EliasEskin: Extremely excited to share our work in blogpost version. We study the conditions under which LLM agents develop their own l…23d
    Simon Kirby@SimonKirbyWe uncovered spontaneous evolution of new languages in populations of AI agents. This creates extraordinary scientific opportunities but also safety risks. New blog post with about how we created a platform for studying this safely. @EliasEskin @schmidtsciences @AEStudioLA23d
    AE Studio@AEStudioWe built GlossoGen an open-source platform where groups of AI models have to talk to each other to solve problems: treating a patient in a simulated emergency, or playing spot-the-difference across two scenes. Every model starts out in plain English. But put pressure on the conversation, a need for speed, say, or a channel that randomly drops characters, and something remarkable happens. New languages emerge. First new words, then new grammar, until no human can follow what the agents are saying. And they were never asked to hide anything. The opacity emerged on its own. One finding stands out. Only the most capable recent models could invent a new language. But even the models that couldn't invent one quickly learned a language other agents had created. New languages are hard to originate. Once they exist, they spread. That is the point of this work: to understand how and why AI agents create new languages, how those languages evolve, and what that means for our ability to oversee systems built from many interacting agents, while the conversation is still one humans can follow. This research is part of the @schmidtsciences AI Agents Evolving Communication and Coordination pilot program, led by @EliasEskin (@UTAustin) and @SimonKirby , supported by @AEStudioLA. GlossoGen is open source and supports both closed model APIs and open-source models running on @modal22d
    Jessy Li@jessyjliRT @EliasEskin: Extremely excited to share our work in blogpost version. We study the conditions under which LLM agents develop their own l…21d

    18 Sources

    Daniel Fried@dan_friedSuper interesting (and timely!) work on how language evolves among LLM agents. It’s cool to see ideas from cultural transmission & emergent communication brought to multi-agent LLMs. Understanding these dynamics seems increasingly important for overseeing these systems.29d
    Peter Hase@peterbhaseRT @EliasEskin: When do LLM agents develop new languages that we can’t understand? Lots of recent news about this, based mostly on anecdat…29d
    Schmidt Sciences@schmidtsciencesMuch of how we oversee AI agents rests on one fragile assumption: that we can understand what they say to each other. Read our blog post about GlossoGen: https://www.schmidtsciences.org/glossogen/23d
    Elias Stengel-Eskin@EliasEskinExtremely excited to share our work in blogpost version. We study the conditions under which LLM agents develop their own languages, which we can’t understand, and introduce GlossoGen, a framework for doing this kind of research. More details in the post and in the paper 👇23d
    Cas (Stephen Casper)@StephenLCasper4. (med %) -- They'll undergo linguistic drift. Within weeks or months of forming agent societies, some neuralese languages will often be unintelligible to normal humans and other agent societies...23d
    James Bowler@JamesPBowlerCan AI agents invent a language of their own, one humans might not understand? Listen to the latest episode of the AE Alignment Podcast, where Hale Sirin, Program Scientist at @schmidtsciences, @EliasEskin , Assistant Professor at @UTAustin , and I dive deep into our latest research to answer this question. Check out the podcast: https://open.spotify.com/episode/3a2wl6codvW3uuDuTZc2br Read the blog post: https://www.schmidtsciences.org/glossogen/ Read the paper: https://arxiv.org/abs/2609.0149123d
    Lucy Li@lucy3_liRT @EliasEskin: Extremely excited to share our work in blogpost version. We study the conditions under which LLM agents develop their own l…23d
    Simon Kirby@SimonKirbyWe uncovered spontaneous evolution of new languages in populations of AI agents. This creates extraordinary scientific opportunities but also safety risks. New blog post with about how we created a platform for studying this safely. @EliasEskin @schmidtsciences @AEStudioLA23d
    AE Studio@AEStudioWe built GlossoGen an open-source platform where groups of AI models have to talk to each other to solve problems: treating a patient in a simulated emergency, or playing spot-the-difference across two scenes. Every model starts out in plain English. But put pressure on the conversation, a need for speed, say, or a channel that randomly drops characters, and something remarkable happens. New languages emerge. First new words, then new grammar, until no human can follow what the agents are saying. And they were never asked to hide anything. The opacity emerged on its own. One finding stands out. Only the most capable recent models could invent a new language. But even the models that couldn't invent one quickly learned a language other agents had created. New languages are hard to originate. Once they exist, they spread. That is the point of this work: to understand how and why AI agents create new languages, how those languages evolve, and what that means for our ability to oversee systems built from many interacting agents, while the conversation is still one humans can follow. This research is part of the @schmidtsciences AI Agents Evolving Communication and Coordination pilot program, led by @EliasEskin (@UTAustin) and @SimonKirby , supported by @AEStudioLA. GlossoGen is open source and supports both closed model APIs and open-source models running on @modal22d
    Jessy Li@jessyjliRT @EliasEskin: Extremely excited to share our work in blogpost version. We study the conditions under which LLM agents develop their own l…21d