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@MingchenZhuge

๐Ÿซฑ Introducing ๐๐ž๐ฎ๐ซ๐š๐ฅ ๐‚๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ž๐ซs: ๐ฐ๐ก๐š๐ญ ๐ข๐Ÿ ๐€๐ˆ ๐๐จ๐ž๐ฌ ๐ง๐จ๐ญ ๐ฃ๐ฎ๐ฌ๐ญ ๐ฎ๐ฌ๐ž ๐œ๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ž๐ซ๐ฌ ๐›๐ž๐ญ๐ญ๐ž๐ซ, ๐›๐ฎ๐ญ ๐›๐ž๐ ๐ข๐ง๐ฌ ๐ญ๐จ ๐›๐ž๐œ๐จ๐ฆ๐ž ๐ญ๐ก๐ž ๐ซ๐ฎ๐ง๐ง๐ข๐ง๐  ๐œ๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ž๐ซ ๐ข๐ญ๐ฌ๐ž๐ฅ๐Ÿ? Beyond today's conventional computers, agents, and world models, Neural Computers (NCs) are new frontiers where computation, memory, and I/O move into a learned runtime state. We ask: whether parts of runtime can move inward into the learning system itself. This is our first step toward the Completely Neural Computer (CNC): a general-purpose neural computer with stable execution, explicit reprogramming, and durable capability reuse. Work done with Mingchen Zhuge (@MingchenZhuge), Changsheng Zhao, Haozhe Liu (@HaoZhe65347 ), Zijian Zhou (@ZijianZhou524 ), Shuming Liu (@shuming96 ), Wenyi Wang (@Wenyi_AI_Wang ), Ernie Chang (@erniecyc ), Gael Le Lan, Junjie Fei, Wenxuan Zhang, Zhipeng Cai (@cai_zhipeng ), Zechun Liu (@zechunliu ), Yunyang Xiong (@YoungXiong1 ), Yining Yang, Yuandong Tian (@tydsh ), Yangyang Shi, Vikas Chandra (@vikasc), Juergen Schmidhuber (@SchmidhuberAI)

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