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Da Vinci — A scalable architecture for neural network computing

27/3/2020

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In this presentation, I give an introduction into microprocessor trends, describe two distinct eras of computing usage in training AI systems and show the wide variety of computing architectures in computer science. I also describe our advanced computing and artificial intelligence product portfolio, which focuses on innovation, continuous dedication and backward compatibility. The central part of this talk is insights into our Da Vinci architecture, descriptions of all building block, the core architecture and its micro-architectural configurations. Last, I show the process of how we execute artificial intelligence projects and the challenges which are still ahead of us.
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New flagship smartphones, an elegant speaker, smart watches and eyewear

26/3/2020

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​Today we announced terrific new products. Our new flagship smartphone delivers an outstanding photography experience by using the worlds first multi-reflection super periscope telephoto, 10x long-range optical zoom, 100x max and an ultra vision Leica Penta camera system. We also incorporate "Hey Celia", a new virtual private assistant that supports you in your daily life.

The HUAWEI Sound X speaker, with its refined and elegant design, delivers a visible stunning shaking bass and 360 degrees surround sound with six of full-range speakers.

The HUAWEI Watch GT2 products appear in new designs and editions.

Finally, our HUAWEI Eyewear combines leading technology with fashion.

Step into new products and rewatch our live stream.
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Prediction of protein subcellular localization

3/3/2020

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  • Use deep learning tools to accurately identify the organelles where proteins are located in human protein fluorescence micrographs
  • The trained model was executed on the Atlas 200 DK developer kit, and use Atlas 200 DK
  • The model analyses unlabelled protein fluorescence and predicts the location of sub-cells with pictures
  • Protein subcellular localisation prediction targets the microscopic fluorescence images of proteins in cancer tissues and other tissues to identify the localisation of proteins; to find location markers related to cancer
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Retinal blood vessel segmentation in the eyeground

3/3/2020

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  • The fundus retinal blood vessel segmentation application was developed for the Atlas 200 DK inference system, in partnership with the Nankai University, led by Professor Li Tao of Intelligent Computing System Research Office .
  • This project makes full use of the neural network computing power of the Atlas 200 DK system to segment the fundus vessels in real-time.
  • The total inference time of 20 pictures is 761.8 milliseconds, and the average inference time of one image is 38 milliseconds.
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