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Digital Transformation from Leveraging Blockchain Technology, Artificial Intelligence, Machine Learning and Deep Learning

机译:从利用区块链技术,人工智能,机器学习和深度学习的数字转换

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These are exciting times as new software development paradigms are fast emerging to cope up with the shift in focus from "mobile first" to "AI first" approach being adapted by Google, Facebook, Amazon and others. This can mainly be attributed to the stability of the cloud computing platform and the developments in search capabilities which have extended from traditional text and web pages to achieving voice and vision recognitions relating to images and videos. Continued research focus has brought the error rate in image recognition by machine to converge sharply with that of the human. Apart from developments in big data analytics, artificial intelligence, machine learning and deep learning, break throughs in peer to peer distributed ledgers with a blockchain technology platform, which incorporates multiple levels of strong encryptions, have created massive developmental interests. Most of the "popular apps" that we use today, are being built using AI algorithms. To achieve this, changes are being incorporated to computational architecture to make them compatible with "AI first" data centers equipped with AI driven features. Tensor Processing Unit (TPU), which powered Google's developments in ML and AI, has now become part of cloud computing service. Anticipating cost related issues, new hardware developments are focusing on moving from the cloud to the edge with the new "Edge TPU". Digital transformation is further augmented by the fact that block chain platforms, which are built on de-centralized tools and technology, are exhibiting greater maturity by the day. The paper highlights several blockchain applications to deliver on several of the promises. The paper also discusses the fundamentals of Neural network to demonstrate how well these concepts that are incorporated in deep learning have decreased error rates by tenfold compared to previous technologies.
机译:这些是令人兴奋的时代,因为新的软件开发范式很快,以应对焦点的转变,从“移动第一”到“AI第一”方法由谷歌,Facebook,亚马逊和其他人改编。这主要归因于云计算平台的稳定性以及从传统文本和网页扩展到从传统文本和网页扩展到的搜索功能的开发,以实现与图像和视频有关的语音和视觉识别。持续的研究重点将机器带来了图像识别的错误率,以利用人类急剧收敛。除了大数据分析的发展,人工智能,机器学习和深度学习外,突破对等分布式分区的路障技术平台,包括多个级别的强加密,创造了大规模的发育兴趣。我们今天使用的大多数“流行应用程序”正在使用AI算法建造。为实现这一目标,更改被纳入计算架构,以使其与配备有AI驱动特征的“AI第一”数据中心兼容。 Tensor处理单元(TPU),它提供了Google在ML和AI中的发展,现在已成为云计算服务的一部分。预期成本相关的问题,新的硬件开发集中在与新的“Edge TPU”从云移动到边缘。通过基于去集中工具和技术构建的块链平台,进一步增强了数字转换,这是一天的成熟度。本文突出了几个区块链申请来提供几个承诺。本文还讨论了神经网络的基础知识,以展示在深度学习中纳入的这些概念如何减少了与以前的技术相比减少了十倍的错误率。

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