LLMs are stateless and they do not remember the past (as in they don't have a database), making the training data a non-issue here. Therefore, the claims made here in this paper are not possible because the simulation would require each agent to have a memory context larger than any available LLM's context window. The claims made here by the original poster are patently false.
The ideas here are not supported by any kind of validated understanding of the limitations of language models. I want to be clear -- the kind of AI that is being purported to be used in the paper is something that has been in video games for over 2 decades, which is akin to Starcraft or Diablo's NPCs.
The key issue is that this is a intentional false claim that can certainly damage mainstream understanding of LLM safety and what is possible at the current state of the art.
Agentic systems are not well-suited to achieve any of the things that are proposed in the paper, and Generative AI does not enable these kinds of advancements.
The ideas here are not supported by any kind of validated understanding of the limitations of language models. I want to be clear -- the kind of AI that is being purported to be used in the paper is something that has been in video games for over 2 decades, which is akin to Starcraft or Diablo's NPCs.
The key issue is that this is a intentional false claim that can certainly damage mainstream understanding of LLM safety and what is possible at the current state of the art.
Agentic systems are not well-suited to achieve any of the things that are proposed in the paper, and Generative AI does not enable these kinds of advancements.