一個完整的AI系統不僅僅包括處理數據的計算部分，還包括保存數據的存儲部分和傳輸數據的網絡部分。只有各部分互相協調一致、消除了系統的短板，整個系統才能發揮最大的效能。英特爾?公司推出了各種各樣的硬件產品，這些產品共同構建用于不同場景的高效能AI系統。

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技術的發展離不開軟件層面的優化，該系列課程介紹英特爾?在基礎加速庫，編程語言和特定深度學習開源框架所做的優化工作。通過軟件層面的優化，將底層硬件的加速性能完全發揮出來，為客戶提供更加強大的計算力。

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.

深度學習與機器學習是一個實踐性非常強的領域。本分會面向開發者分享英特爾?在深度學習與機器學習領域的實戰經驗，包括如何在人工智能軟件框架中實現高性能的應用開發，如何構建大規模的人工智能訓練集群，同時也將介紹英特爾?架構數據中心平臺在具體應用案例中的應用效果及技巧

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.