{"id":1165,"date":"2023-09-22T15:41:37","date_gmt":"2023-09-22T22:41:37","guid":{"rendered":"https:\/\/ambienttrends.com\/?p=1165"},"modified":"2023-09-23T07:14:27","modified_gmt":"2023-09-23T14:14:27","slug":"imprecise-computing","status":"publish","type":"post","link":"https:\/\/ambienttrends.com\/?p=1165","title":{"rendered":"Imprecise Computing"},"content":{"rendered":"\n<p>The rise of artificial intelligence, machine learning, and the exponential growth in quantity and scale of data and sensor inputs redefines storage and processing criticality. Optimal task prioritization is morphing from linear-stacked to dynamic-flat. For edge and embedded systems where architecture and power are limited, traditional mixed-criticality systems (and storage) introduce a new dimension: accuracy. This dimension provides the greatest value in systems where the availability of data and sensor inputs exceeds the hardware&#8217;s capability to compute all potentially beneficial elements, and a processing-level imprecise calculation enables inputs to, in turn, inform accuracy needs. The key to achieving this at the hardware layer can be found in analog computing. For AI\/ML systems, imprecise and analog processing approaches hold the potential to dramatically increase overall accuracy for a growing range of applications. An added benefit of analog computing is its resiliency to a variety of external interference &#8211; especially critical for lightweight space applications. <\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The rise of artificial intelligence, machine learning, and the exponential growth in quantity and scale of data and sensor inputs redefines storage and processing criticality. Optimal task prioritization is morphing from linear-stacked to dynamic-flat. For edge and embedded systems where architecture and power are limited, traditional mixed-criticality systems (and storage) introduce a new dimension: accuracy. [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":1212,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[7,4,52],"tags":[],"class_list":{"0":"post-1165","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","6":"hentry","7":"category-communications","8":"category-security-automation","9":"category-technology","11":"post-with-thumbnail","12":"post-with-thumbnail-large"},"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 4.9.9 - aioseo.com -->\n\t<meta name=\"description\" content=\"The rise of artificial intelligence, machine learning, and the exponential growth in quantity and scale of data and sensor inputs redefines storage and processing criticality. Optimal task prioritization is morphing from linear-stacked to dynamic-flat. For edge and embedded systems where architecture and power are limited, traditional mixed-criticality systems (and storage) introduce a new dimension: accuracy.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"atsite\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/ambienttrends.com\/?p=1165\" \/>\n\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 4.9.9\" \/>\n\t\t<meta property=\"og:locale\" content=\"en_US\" \/>\n\t\t<meta property=\"og:site_name\" content=\"Ambient Trends - Ideas for the Future, Products and Technologies for Today\" \/>\n\t\t<meta property=\"og:type\" content=\"article\" \/>\n\t\t<meta property=\"og:title\" content=\"Imprecise Computing - Ambient Trends\" \/>\n\t\t<meta property=\"og:description\" content=\"The rise of artificial intelligence, machine learning, and the exponential growth in quantity and scale of data and sensor inputs redefines storage and processing criticality. Optimal task prioritization is morphing from linear-stacked to dynamic-flat. For edge and embedded systems where architecture and power are limited, traditional mixed-criticality systems (and storage) introduce a new dimension: accuracy.\" \/>\n\t\t<meta property=\"og:url\" content=\"https:\/\/ambienttrends.com\/?p=1165\" \/>\n\t\t<meta property=\"article:published_time\" content=\"2023-09-22T22:41:37+00:00\" \/>\n\t\t<meta property=\"article:modified_time\" content=\"2023-09-23T14:14:27+00:00\" \/>\n\t\t<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n\t\t<meta name=\"twitter:title\" content=\"Imprecise Computing - Ambient Trends\" \/>\n\t\t<meta name=\"twitter:description\" content=\"The rise of artificial intelligence, machine learning, and the exponential growth in quantity and scale of data and sensor inputs redefines storage and processing criticality. Optimal task prioritization is morphing from linear-stacked to dynamic-flat. 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