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        F眺望2018系列|眺望2018前瞻議題觀測: AIoT的美麗與哀愁
        AIoT’s Beauty and Sorrow
        • 2017/11/06
        • 17893
        • 1105

        簡報大綱

        【簡報大綱】

        • Promising AI !?
        • The Beauty and the Sorrow of AI
        • Closing Remarks

        簡報內容

        AIoT’s Beauty and Sorrow
        NO.1
        Unlike humans, machines are not (yet!)...
        NO.2
        Outline
        NO.3
        These companies have invested in 80 AI startups and acquired 50 in the last 5 years
        NO.4
        Promising AI ! Beauty?
        NO.5
        Promising AI ? Sorrow?
        NO.6
        Five key platforms of digital business- Analytics platform advancement with AI injection -
        NO.7
        AI technology''s impact on B2B sales organizations
        NO.8
        A bi-directional AIoT systemIoT and AI co-create a virtuous cycle for digital innovation
        NO.9
        DeepMind reinforcement learning reduces Google data center cooling bill by 40%
        NO.10
        AI promising applications in organizations
        NO.11
        MACHINE INTELLIGENCE 3.0
        NO.12
        Outline
        NO.13
        Beauty or Sorrow: In 2020, AI creates 2.3 million jobs while eliminating 1.8 million jobs
        NO.14
        AI will put 10M US jobs at high risk, Sorrow?
        NO.15
        Google is teaching its AI how humans hug, cook, and fight
        NO.16
        Human-augmentation with task-replacement by AI to react faster and more accurately, Beauty?
        NO.17
        Strategic Planning Assumptions on Deep Learning
        NO.18
        Thanks to the processor evolution for Deep Learning
        NO.19
        Broad range of problems potentially solved by Deep Learning, Beauty?
        NO.20
        The Secret to AI Success: Talent
        NO.21
        Various optimization algorithms to train DNN
        NO.22
        Identify use cases then AI prototyping by leveraging open-source platforms, Beauty?
        NO.23
        Inner workings of DNN is not transparent, Sorrow?
        NO.24
        Opening up the black box - DARPA Explainable Artificial Intelligence Initiative, Beauty?
        NO.25
        Organizations working to address the transparency / interpretability problem in DL
        NO.26
        Can DNNs deal with “Trolley problem”?
        NO.27
        Outline
        NO.28
        A Berkeley View of Systems Challenges for AI
        NO.29
        Mapping from AI trends to challenges- Research Opportunities -
        NO.30
        AI success requires elements similar to those in successful digital transformations
        NO.31
        Closing Remark
        NO.32
        Thank You
        NO.33

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