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The Conversation 06/05/2020 01:32
Algorithmic decision-making has enormous potential to do good. From identifying priority areas for first response after an earthquake hits, to identifying those at risk of COVID-19 within minutes, their application has proven hugely beneficial. But things can go drastically wrong when decisions are trusted to algorithms without ensuring they adhere to established ethical norms. Two recent examples illustrate how government agencies are failing to automate fairness. 1. The algorithm doesn’t match reality. This problem arises when a one-size-fits-all rule is implemented in a complex environment. The most recent devastating example was Australia’s . In that case, welfare payments made on the basis of self-reported fortnightly income were cross-
Recently, researchers from DeepMind, UC Berkeley and the University of Oxford introduced a knowledge distillation strategy for injecting syntactic biases into BERT pre-training in order to benchmark natural language understanding. Bidirectional Encoder Representation from Transformers or BERT is one of the most popular neural network-based techniques for natural language processing (NLP) while pre-training. At the…. .
Business Wire 06/05/2020 01:29
加州桑尼维尔--(BUSINESS WIRE)--(美国商业资讯)--云数据服务的领导者NetApp® (NASDAQ: NTAP)今天宣布,该公司已签署最终协议,将收购公共云计算管理和成本优化的领导者Spot,以在应用程序驱动的基础架构(Application Driven Infrastructure)领域建立领导者地位。 数字化转型计划正加速发展,并且依然是企业的首要任务,尤其是在当今环境下。由于公司找到了新的工作、互动和经营方式,公共云可提供适应这种新常态所需的速度和灵活性。但未经优化的云可能成本高昂,并拖慢业务转型。为了应对这一挑战,应用程序驱动的基础架构可以转换应用程序的工作负载模式,并为存储和计算提供最佳的性能和成本水平,同时保持约定的服务级别协议(SLA)和服务级别目标(SLO)。NetApp和Spot用于持续优化的应用程序驱动基础架构将共同帮助客户节省高达90%的计算和存储云费用(这些费用通常占云总支出的70%),并有助于加速公共云的采用。 NetApp公共云服务高级副总裁兼总经理Anthony Lye表示:"对于当今的公共云,速度成为新的尺度。但是,因为资源闲置和.

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