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首页> 外文会议>IEEE International System-on-Chip Conference >Meeting the Hyper Growth Challenge of AI Applications
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Meeting the Hyper Growth Challenge of AI Applications

机译：满足AI应用的超增长挑战

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Organizations today looking to accelerate their AI and deep learning applications must make significant compromises in performance, price and ease of use due to the limited capabilities of traditional hardware solutions, which only address a narrow set of requirements for very specific needs. For example, they have to use multiple solutions for a single AI application, or they need to use different implementations for different types of data sets. This has created “silos” of different hardware architectures, making the extraction of intelligence from data difficult to manage, provision and scale to meet the hyper growth of AI applications. In this presentation, Wave Computing VP of Marketing Fadi Azhari will explain how the lack of a common AI platform, from the datacenter to the edge, is slowing AI market growth and reducing the productivity of data scientists in a wide range of fields. He will also explain how Wave Computing is addressing this challenge, and enabling data scientists to experiment, develop, test and deploy neural networks on a common platform spanning to the Edge of Cloud - and enabling enterprise-class companies better leverage AI as a fundamental part of their digital strategies.
机译：今天希望加速其AI和深度学习应用程序必须由传统的硬件解决方案的能力有限，这只能解决一个狭窄的一系列要求非常具体的需求对性能，价格和易用性显著妥协的组织。例如，它们必须使用多个解为单个AI应用程序，或者它们需要使用不同的实现对于不同类型的数据集。这就造成了不同硬件架构的“孤岛”，使得智能难以从数据管理，提供和规模提取满足AI应用的超速发展。在此演示文稿，营销法迪·爱资哈里的浪潮计算副总裁将解释如何缺乏一个共同的AI平台，从数据中心到边缘，正在放缓AI的市场增长和减少数据科学家们的生产力在广泛的领域。他还将解释波计算是如何应对这一挑战，并实现数据科学家的实验，开发，测试和部署的神经网络在一个共同的平台跨越到云的边缘 - 而实现企业级的企业更好地利用AI作为一个基本组成部分他们的数字化战略。

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