人工智能业界在2月共计发生 662 篇新闻,197 个事件， 基本与上月持平，热度总体趋势如下图所示。本月，业界学术顶会陆续召开或公布论文 录取结果，多位计算机领域华人学者荣获得重要奖项或当选院士或 Fellow，引发了较 多关注；尤其，教育部本月公布新增了 95 所高校获批人工智能专业，反映出我国在人 工智能领域加大了高层次人才的培养力度。

进入 2022 年，人工智能技术将进一步朝着前沿和实用两个方向发展，监管日益严 格。新年伊始，我国就出台了 AI 重磅监管《互联网信息服务算法推荐管理规定》，引 发了业内较多关注和热议。数据显示，1 月份人工智能共计发生 658 篇新闻,212 个事 件，具体信息如下图所示。从事件涉及主题来看，本月未发现人工智能领域有重大顶会 召开，领域研究报告、重大榜单奖项发布等事件数量较多。

目前人工智能商业化在算力、算法和技术方面基本达到阶段性成熟，想要更加落地，解决行业具体痛点， 需要大量经过标注处理的相关数据做算法训练支撑 ，可以说数据决定了 AI 的落地程度。

Deep learning is expected to drive training for neural networks requiring massive datasets for AI algorithm development • This in turn leads to a shift in the pe廿ormance focus of computing from general application to neural nets, increasing demand for high pe廿o「mance computing

Businesses are increasingly adopting AI to create new applications, driving the development of AI-optimized chips

Previously in Part I，we reviewed the ADAC loop and key factors driving innovation for Al­optimized chipsets. In Part II， we review the shift in performance focus computing from general application neu『al nets and how this is driving demand for high performance computing. To this end, some startups are adopting alternative, novel approaches and this is expected to pave the way for other Al-optimized chipsets