مشخصات مقاله | |
ترجمه عنوان مقاله | مسائل خاص “هوش مصنوعی در رایانش ابری” |
عنوان انگلیسی مقاله | Special issue on ‘‘artificial intelligence in cloud computing’’ |
انتشار | مقاله سال 2021 |
تعداد صفحات مقاله انگلیسی | 5 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه اسپرینگر |
نوع نگارش مقاله |
سرمقاله (Editorial) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
2.688 در سال 2020 |
شاخص H_index | 60 در سال 2021 |
شاخص SJR | 0.409 در سال 2020 |
شناسه ISSN | 1436-5057 |
شاخص Quartile (چارک) | Q2 در سال 2020 |
فرضیه | ندارد |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مهندسی کامپیوتر |
گرایش های مرتبط | رایانش ابری، هوش مصنوعی |
نوع ارائه مقاله |
ژورنال |
مجله | رایانش – Computing |
دانشگاه | Lakehead University, Thunder Bay, Canada |
شناسه دیجیتال – doi |
https://doi.org/10.1007/s00607-021-00985-z |
کد محصول | E15804 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
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In this special issue Reference Author information Additional information Rights and permissions About this article |
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Cloud computing equips artificial intelligence (AI) with tremendous power and considered to be one of the most important catalyst for developing innovative smart applications. With its potential to change the way data used to get stored and processed across various geographies,the scope and impact of AI have reached larger market. With all the cloud models, AI developers and consumers started to create an ecosystem that improve the lives of millions. Now digital assistants like Siri, Google Home, and Amazon’s Alexa blend AI and cloud computing in our lives every day. AI practitioners based on the Infrastructure as a Service cloud model (IaaS) can use advanced infrastructure facilities—CPU, GPU, memory, disk, network, and O/S without waiting for an infrastructure team to prepare it. Moreover with Platform as a Service cloud model (PaaS), AI practionars can use variety of AI algorithms and data science services including jupyter notebooks, data catalog services to develop new generation smart applications. Additionally, consumers based on the Software as a Service cloud model (SaaS) can to employ and embed AI services within their application (e.g. Smart Building). Before the SaaS, software and data were only “on premise.” SaaS moved everything to the cloud, collaboration and efficiency as well as sharing telents. With AI, the next step is to have “smart SaaS” as services can begin to use wider AI/machine learning to create higher consumer experience. Cloud computer, however, is adding more capabilities that can fuel the use of higher AI applications. Capabilities like containerization, developers can isolate applications to fit different computing environments and platforms. With Kubernetes the automating deployment, scaling, and management of containerized applications can be achieved where applications running on containers can run on different cloud providers without worrying about compute environment. On this large scale of research and development, AI capabilities are working in the cloud computing environment to make organizations more efficient, strategic, and insight-driven. Cloud computing offers businesses more flexibility, agility, and cost savings by hosting data and applications in the cloud. Artificial intelligence capabilities are now layering with cloud computing and helping companies manage their data, look for patterns and insights in information, deliver customer experiences, and optimize workflows [1]. |