近年来AI、大数据无论是在科技圈，还是在商界或日常生活中， 都成为备受关注的热词。随着信息化 、互联网技术的发展、AI、大数据进了飞驰的快车道， 深刻地参与着、影响着全球的社会经济，乃至政治文化的发展进程。 AI 被世界不少国家都纳入了国家层面的战略发展规划而大数据则被公认为国家基础性战略资源，是21世纪的“钻石矿”。 ​

Artificial intelligence is currently attracting considerable interest and attention from industry, researchers, governments as well as investors, who are pouring record amounts of money into the development of new machine learning technologies and applications.

2019年，智能家居行业，在技术、市场和行业的变革中迎接新的挑战和机遇。 一方面，AI、IoT、边缘计算全面赋能智能家居；另一方面，中国的房地产行业正在从上半场的“增量 开发”，切换到下半场的“存量经营”、“楼盘精装化”政策在更多中国城市落地。

AI芯片即为面向人工智能应用的芯片。人工智能与芯片的发展需紧密合作，但过去碍于跨学科合作困难，加上人工智能算法并未成熟，世界各国对于人工智能的多项投入最后都以失败告终。

金融资讯整体阅读量金融用户占全网用户占比达1 1 % ，金融兴趣用户阅读时间分布为早午晚时间段为阅读高峰期。

2019中国AI产业生态图谱。

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

近年来，随着相关技术的飞速发展，人工智能在医疗领域中的应用也在快速的推广，包括医学影像、临床决策支持、病例分析、语言识别、药物挖掘、健康管理、病理学等众多场景。随着医学数据集的扩增，硬件设备的提升，AI算法的不断优化改进，AI在医疗场景中的技术积累愈发成熟，越来越多的AI研究开始落地于医疗领域。 ​