{"id":5538,"date":"2024-07-22T15:36:23","date_gmt":"2024-07-22T13:36:23","guid":{"rendered":"https:\/\/bdva.eu\/docs\/bdva-strategic-agenda-2024\/iv-making-data-and-ai-innovations-fit-for-emerging-infrastructures-and-platforms\/"},"modified":"2024-08-05T09:46:16","modified_gmt":"2024-08-05T07:46:16","slug":"iv-making-data-and-ai-innovations-fit-for-emerging-infrastructures-and-platforms","status":"publish","type":"docs","link":"https:\/\/bdva.eu\/docs\/bdva-strategic-agenda-2024\/iv-making-data-and-ai-innovations-fit-for-emerging-infrastructures-and-platforms\/","title":{"rendered":"IV. Making data and AI innovations fit for emerging infrastructures and platforms"},"content":{"rendered":"<p><em>(V1.0 August 2024)<\/em><\/p>\n<p>This theme addresses the seamless integration and deployment of new AI workflows and data pipelines across diverse technological infrastructures.<\/p>\n<p>This involves harmonising various stages in the data lifecycle (capture, storage, computation, analysis, and transmission) within an ecosystem that includes IoT devices, edge computing, cloud environments, HPC, quantum computing, and 5G networks. It implies smooth interoperability between the different technologies and ensures that data flows seamlessly across these platforms.<\/p>\n<p>But equally important is adapting AI workflows and data pipelines to operate effectively within this computing continuum. This will ensure that AI processes are flexible and compatible with different computing environments, from edge to cloud to HPC and beyond, leading to optimised deployment and execution of AI tasks.<\/p>\n<p>Finally, this theme also pursues the achievement of real and practical use cases that show this convergence between AI\/Data and edge\/cloud\/HPC and the application in real-world computing environments (including quantum computing).<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"featured_media":0,"parent":5504,"menu_order":3,"comment_status":"open","ping_status":"closed","template":"","doc_tag":[],"class_list":["post-5538","docs","type-docs","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>IV. Making data and AI innovations fit for emerging infrastructures and platforms - BDV Big Data Value Association<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/bdva.eu\/docs\/bdva-strategic-agenda-2024\/iv-making-data-and-ai-innovations-fit-for-emerging-infrastructures-and-platforms\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"IV. Making data and AI innovations fit for emerging infrastructures and platforms - BDV Big Data Value Association\" \/>\n<meta property=\"og:description\" content=\"(V1.0 August 2024) This theme addresses the seamless integration and deployment of new AI workflows and data pipelines across diverse technological infrastructures. 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Sustainable data and AI: enhancing efficiency and resilience while reducing resource demands","link":"https:\/\/bdva.eu\/docs\/bdva-strategic-agenda-2024\/v-4-sustainable-data-and-ai-enhancing-efficiency-and-resilience-while-reducing-resource-demands\/","href":"https:\/\/bdva.eu\/wp-json\/wp\/v2\/docs\/5546"}],"prev":[{"title":"III. Expanding data-driven ecosystems across sectors and (global) value chains","link":"https:\/\/bdva.eu\/docs\/bdva-strategic-agenda-2024\/iii-2-expanding-data-driven-ecosystems-across-sectors-and-global-value-chains\/","href":"https:\/\/bdva.eu\/wp-json\/wp\/v2\/docs\/5529"}],"wp:attachment":[{"href":"https:\/\/bdva.eu\/wp-json\/wp\/v2\/media?parent=5538"}],"wp:term":[{"taxonomy":"doc_tag","embeddable":true,"href":"https:\/\/bdva.eu\/wp-json\/wp\/v2\/doc_tag?post=5538"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}