A Preliminary Study On The Capability Boundary Of LLM And A New Implementation Approach For AGI - Info and Reading Options
By Yongcong Chen and Ting Zeng, Xiaoyi Qia
“A Preliminary Study On The Capability Boundary Of LLM And A New Implementation Approach For AGI” Metadata:
- Title: ➤ A Preliminary Study On The Capability Boundary Of LLM And A New Implementation Approach For AGI
- Authors: Yongcong ChenTing Zeng, Xiaoyi Qia
“A Preliminary Study On The Capability Boundary Of LLM And A New Implementation Approach For AGI” Subjects and Themes:
- Subjects: ➤ ChinaXiv - 中国科学院科技论文预发布平台 - 计算机科学 - 计算机科学技术其他学科 - LLM - ChatGPT - GPT-4 - AGI
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- Internet Archive ID: ChinaXiv-202305.00046V1
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The Internet Archive:
<div class="hd"> <h1> A Preliminary Study on the Capability Boundary of LLM and a New Implementation Approach for AGI </h1> <div class="flex" style="border:0px;padding-bottom:0px;"> </div> <div class="bd" style="border-bottom:1px solid #ced6e0;"> <ul style="margin-top:0px;"> <li> <b> 作者: </b> <a href="https://chinaxiv.org/user/search.htm?field=author&value=Yongcong%20Chen" style="color:#3060cc;" rel="nofollow"> Yongcong Chen </a> <sup style="margin-left:0px;"> 1 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&value=Ting%20Zeng" style="color:#3060cc;" rel="nofollow"> Ting Zeng </a> <sup style="margin-left:0px;"> 2 </sup> <a href="https://chinaxiv.org/user/search.htm?field=author&value=%20Xiaoyi%20Qia" style="color:#3060cc;" rel="nofollow"> Xiaoyi Qia </a> <sup style="margin-left:0px;"> 3 </sup> </li> <li> <b> 作者单位: </b> <div style="margin-left:70px;margin-top:-26px;"> <div> 1. <a href="https://chinaxiv.org/user/search.htm?field=affication&value=%20New%20Millennium%20Future%20Technology%20Co.,Ltd" style="color:#3060cc;" rel="nofollow"> New Millennium Future Technology Co.,Ltd </a> </div> <div> 2. <a href="https://chinaxiv.org/user/search.htm?field=affication&value=%20Library%20of%20Tsinghua%20University" style="color:#3060cc;" rel="nofollow"> Library of Tsinghua University </a> </div> <div> 3. <a href="https://chinaxiv.org/user/search.htm?field=affication&value=%20Galaxyeye%20Technology%20Co.,Ltd" style="color:#3060cc;" rel="nofollow"> Galaxyeye Technology Co.,Ltd </a> </div> </div> </li> <li> <b> 通讯作者: </b> <a href="https://chinaxiv.org/user/search.htm?field=author&value=Yongcong%20Chen" style="color:#bb3536;" rel="nofollow"> Yongcong Chen </a> Email:[email protected] <a href="https://chinaxiv.org/user/search.htm?field=author&value=Ting%20Zeng" style="color:#bb3536;" rel="nofollow"> Ting Zeng </a> Email:[email protected] </li> <li> <b> 提交时间: </b> 2023-05-06 </li> </ul> </div> <div class="bd" style="margin-top:15px;"> <p style="color:#333;"> <b> 摘要: </b> 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 </p> <div class="brdge"> <span class="spankwd"> <a href="https://chinaxiv.org/user/search.htm?field=keywords&value=%20LLM" rel="nofollow"> LLM </a> </span> <span class="spankwd"> <a href="https://chinaxiv.org/user/search.htm?field=keywords&value=ChatGPT" rel="nofollow"> ChatGPT </a> </span> <span class="spankwd"> <a href="https://chinaxiv.org/user/search.htm?field=keywords&value=GPT-4" rel="nofollow"> GPT-4 </a> </span> <span class="spankwd"> <a href="https://chinaxiv.org/user/search.htm?field=keywords&value=AGI" rel="nofollow"> AGI </a> </span> </div> <ul> <li> <b> 来自: </b> 曾婷 </li> <li> <b> 分类: </b> <a href="https://chinaxiv.org/user/search.htm?field=domain&value=243" rel="nofollow"> 计算机科学 </a> >> <a href="https://chinaxiv.org/user/search.htm?field=subject&value=768" rel="nofollow"> 计算机科学技术其他学科 </a> </li> <li> <b> 投稿状态: </b> <a rel="nofollow"> 未投稿 </a> </li> <li> <b> 引用: </b> <a href="https://chinaxiv.org/abs/202305.00046" rel="nofollow"> <font color="#0000FF"> ChinaXiv:202305.00046 </font> </a> (或此版本 <a href="https://chinaxiv.org/abs/202305.00046v1" rel="nofollow"> <font color="#0000FF"> ChinaXiv:202305.00046V1 </font> </a> ) <br /> <a href="http://dx.doi.org/10.12074/202305.00046V1" style="color:#0000FF;margin-left:45px;" rel="nofollow"> <font color="#0000FF"> DOI:10.12074/202305.00046V1 </font> </a> <br /> <a href="https://www.cstr.cn/CSTR:32003.36.ChinaXiv.202305.00046.V1" style="margin-left:45px;" rel="nofollow"> <font color="#0000FF"> CSTR:32003.36.ChinaXiv.202305.00046.V1 </font> </a> </li> <li> <b> 推荐引用方式: </b> <span> 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 </span> </li> </ul> </div> <div class="ft"> <h4> <span> 版本历史 </span> </h4> <table style="font-size:14px;"> <tr> <td> <b> [V1] </b> </td> <td> 2023-05-06 11:26:44 </td> <td> ChinaXiv:202305.00046V1 </td> <td> <a class="btn" href="https://chinaxiv.org/user/download.htm?id=52781" rel="nofollow"> 下载全文 </a> </td> </tr> </table> </div> </div>
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