Mindstorms in Natural Language-Based Societies of Mind

Inspired by Minsky's Society of Mind, Schmidhuber's Learning to Think, and other more recent works, this paper proposes and advocates for the concept of natural language-based societies of mind (NLSOMs). We imagine these societies as consisting of a collection of multimodal neural networks, including large language models, which engage in a “mindstorm” to solve problems using a shared natural language interface. Here, we work to identify and discuss key questions about the social structure, governance, and economic principles for NLSOMs, emphasizing their impact on the future of AI. Our demonstrations with NLSOMs-which feature up to 129 agents-show their effectiveness in various tasks, including visual question answering, image captioning, and prompt generation for text-to-image synthesis.