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A Preliminary Study on the Capability Boundary of LLM and a New Implementation Approach for AGI 作者： Yongcong Chen 1 Ting Zeng 2 Xiaoyi Qia 3 作者单位： 1. New Millennium Future Technology Co.,Ltd 2. Library of Tsinghua University 3. Galaxyeye Technology Co.,Ltd 通讯作者： Yongcong Chen Email:[email protected] Ting Zeng Email:[email protected] 提交时间： 2023-05-06 摘要: With a preliminary exploration of the capability boundaries of LLM(Language Large Model),we believe that the current mainstream artificial intelligence generally adopts the technical of attention mechanism + deep learning + reinforcement learning, which cannot be applied to those fields that are difficult to a lot of trial and error. So, to achieve AGI (Artificial General Intelligence) that works in any field, its better to change the way we do it. Therefore, we propose a set of machine learning solution different from deep learning + reinforcement learning. It adopts small samples and cumulative learning, and also realizes the attention mechanism similar to transformer, and also creates a fully connected knowledge network. In addition, it can realize interactive decision making with the environment without using lots of trial and error style learning. In addition, humans can preset different innate needs to it to achieve multi-objective balance, thus achieving far higher security than the current artificial intelligence. In this paper, we propose a set of new machine learning techniques which maybe guide humans realizes AGI LLM ChatGPT GPT-4 AGI 来自： 曾婷 分类： 计算机科学 >> 计算机科学技术其他学科 投稿状态： 未投稿 引用： ChinaXiv:202305.00046 (或此版本 ChinaXiv:202305.00046V1 ) DOI:10.12074/202305.00046V1 CSTR:32003.36.ChinaXiv.202305.00046.V1 推荐引用方式： Yongcong Chen,Ting Zeng, Xiaoyi Qia.(2023).A Preliminary Study on the Capability Boundary of LLM and a New Implementation Approach for AGI.中国科学院科技论文预发布平台.doi:10.12074/202305.00046V1 版本历史 [V1] 2023-05-06 11:26:44 ChinaXiv:202305.00046V1 下载全文