With a mission "To encourage the Spirit of Learning" and to enhance learning opportunities for children in need, Esquel Group joined hands with Lego Group, and Semia Limited and
Inspired by Minsky’s Society of Mind,Schmidhuber’s Learning to Think,and other more 9-16 recent works,this paper proposes and advocates for the concept of natural language-based societies of mind(NLSOMs).We imagine ...Inspired by Minsky’s Society of Mind,Schmidhuber’s Learning to Think,and other more 9-16 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.展开更多
文摘With a mission "To encourage the Spirit of Learning" and to enhance learning opportunities for children in need, Esquel Group joined hands with Lego Group, and Semia Limited and
基金supported by the European Research Council(ERC,Advanced Grant Number 742870the Swiss National Science Foundation(SNF,Grant Numbers 200021 and 192356)the National Natural Science Foundation of China(Grant Number 62476143).
文摘Inspired by Minsky’s Society of Mind,Schmidhuber’s Learning to Think,and other more 9-16 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.
