一个完整的AI系统不仅仅包括处理数据的计算部分，还包括保存数据的存储部分和传输数据的网络部分。只有各部分互相协调一致、消除了系统的短板，整个系统才能发挥最大的效能。英特尔®公司推出了各种各样的硬件产品，这些产品共同构建用于不同场景的高效能AI系统。

An AI system includes not only computing part for data processing, also storage for data saving and network for data transferring. The AI system cannot achieve maximum efficiency unless each part works coordinately to eliminate bottleneck. Intel® has various products that can construct high efficiency AI systems for different usage modes.

AI技术的发展离不开软件层面的优化，该系列课程介绍英特尔®在基础加速库，编程语言和特定深度学习开源框架所做的优化工作。通过软件层面的优化，将底层硬件的加速性能完全发挥出来，为客户提供更加强大的计算力。

Software optimization is very crucial to AI technology development. This session includes optimization on MKL&MKL-DNN, programming language and specific deep learning framework. It will fully unleash hardware accelerate feature and provide more powerful compute to customers.

深度学习与机器学习是一个实践性非常强的领域。本分会面向开发者分享英特尔®在深度学习与机器学习领域的实战经验，包括如何在人工智能软件框架中实现高性能的应用开发，如何构建大规模的人工智能训练集群，同时也将介绍英特尔®架构数据中心平台在具体应用案例中的应用效果及技巧

Deep Learning and Machine Learning are practical. This track is to share Intel's experience in deep learning and machine learning practices on Intel ® Architecture, including how to develop high-performance AI application with frameworks;  how to build large-scale Deep Learning training clusters, as well as the best known methods from AI case studies.