As we are fast approaching the beginning of a paradigm shift in the field of science, Data driven science (the so called fourth science paradigm) is going to be the driving force in research and innovation. From medicine to biodiversity and astronomy to geology, all these terms are somehow going to be affected by this paradigm shift. The huge amount of data to be processed under this new paradigm will be a major concern in the future and one will strongly require cloud based services in all the aspects of these computations (from storage to compute and other services). Another aspect will be energy consumption and performance of prediction jobs and tasks within such a scientific paradigm which will change the way one sees computation. Data science has heavily impacted or rather triggered the emergence of Machine Learning, Signal/Image/Video processing related algorithms, Artificial intelligence, Robotics, health informatics, geoinformatics, and many more such areas of interest. Hence, we envisage an era where Data science can deliver its promises with the help of the existing cloud based platforms and services with the addition of new services. In this article, we discuss about data driven science and Machine learning and how they are going to be linked through cloud based services in the future. It also discusses the rise of paradigms like approximate computing, quantum computing and many more in recent times and their applicability in big data processing, data science, analytics, prediction and machine learning in the cloud environments.
翻译:随着我们迅速接近科学领域范式转变的开端,数据驱动科学(即所谓的第四科学范式)将成为研究和创新的动力。从医学到生物多样性和天文学到地质,所有这些术语都将在某种程度上受到范式转变的影响。在这个新范式转变下处理的大量数据将成为未来的一个主要关切,并且将强烈要求在这些计算的各个方面(从储存到计算和其他服务)提供云服务。另一个方面将是能源消耗和预测工作及任务在这种科学范式中的绩效,这将改变人们看待计算的方式。数据科学已经或者会引发机器学习、信号/图像/视频处理相关算法、人工智能、机器人学、健康信息学、地质学和许多其他感兴趣的领域。因此,我们设想了一个时代,数据科学可以在现有的云基平台和服务的帮助下,在新的服务中兑现其承诺。在文章中,我们讨论了数据驱动科学和机器学习方式的严重影响或者相反地触发了机器学习、信号/图像处理相关算法、人工智能学、健康信息学、地质学、以及数字学中的许多数字学时代是如何通过云层学和数字学在将来的学习中进行。