{"id":65239,"date":"2025-10-07T16:24:08","date_gmt":"2025-10-07T16:24:08","guid":{"rendered":"https:\/\/www.newsbeep.com\/ie\/65239\/"},"modified":"2025-10-07T16:24:08","modified_gmt":"2025-10-07T16:24:08","slug":"multidimensional-computing-fuels-next-generation-ai-factories","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ie\/65239\/","title":{"rendered":"Multidimensional computing fuels next-generation AI factories"},"content":{"rendered":"

Unlike traditional linear computing<\/a>, multidimensional computing operates across many dimensions simultaneously, unlocking native parallelism and far richer, more expressive data representations needed in artificial intelligence workloads.\u00a0<\/p>\n

Multidimensional computing is transforming AI factories, enabling them to tackle complex tasks with speed and efficiency. By surpassing traditional computing limits, it drives real-time adaptability, accelerates innovation and powers smarter AI solutions across industries, according to Bill Tai<\/a> (pictured), chairman of the board of Hut8 Corp.<\/p>\n

\"Bill<\/p>\n

Hut8\u2019s Bill Tai talks about how multidimensional computing underpins AI factories.<\/p>\n

\u201cWhat\u2019s happening is that we\u2019ve moved from a world where computing used to be kind of linear to computing is now multidimensional,\u201d Tai said. \u201cOne of the reasons Nvidia is the center of the universe now is they got a very big head start processing what\u2019s called matrix math \u2026 that is in effect what a GPU does. Now you\u2019re going to have basically gigantic computation AI factories placed throughout this nation and the world where those connection points of telco lines connect and interconnect those brain elements into a giant pattern.\u201d<\/p>\n

Tai spoke with theCUBE\u2019s John Furrier<\/a> at\u00a0theCUBE + NYSE Wired: AI Factories \u2013 Data Centers of the Future<\/a> event, during an exclusive broadcast on theCUBE, SiliconANGLE Media\u2019s livestreaming studio. They discussed how multidimensional computing underpins AI factories, enabling them to handle complex workloads and scale intelligence effectively.<\/p>\n

How multidimensional computing is enhancing AI factories<\/p>\n

AI factories<\/a> transform multidimensional computing from theory into a scalable reality. This is attained through model parallelism, automated tuning and hardware optimization to accelerate innovation and redefine complex computation, according to Tai.\u00a0<\/p>\n

\u201cThese brains are getting larger and larger as people are able to now connect tens of thousands \u2026 of GPUs into one big cluster that then really does resemble something like a brain,\u201d he said. \u201cI think it\u2019s leading to structural change in computing, structural change in the software and applications that can run on them and also insane amounts of power required to run all of this stuff. These AI factories are redefining computing.\u201d<\/p>\n

An AI factory is the convergence of massive data, computing power and advanced software, functioning like a synthetic brain. It processes streams of input \u2014 images, text, speech, sensors \u2014 much like human senses, enabling perception, reasoning, adaptation and creativity at industrial scale, Tai pointed out.<\/p>\n

\u201cIt\u2019s the integration of all of those things into something that looks like a gigantic neural fabric of computation elements with some very dense areas that might resemble parts of your brain that do certain things and other parts that are the interconnect between those dense parts and other dense parts that do other functions,\u201d he said. \u201cIn the end, it\u2019s going to resemble a little bit of what the internet backbone looks like. We\u2019re going to see something that is just a vibrant fabric. We\u2019re moving from a kind of a world of connected information to connected abstracted intelligence.\u201d<\/p>\n

Graphics processing units are essential to multidimensional computing, built for massive parallelism that powers high-dimensional data processing and complex model training. Unlike central processing units with a few sequential cores, GPUs pack thousands of smaller cores to run computations simultaneously \u2014 making them indispensable for AI and advanced data analysis, Tai emphasized.<\/p>\n

\u201cGPU, it\u2019s a quick transformation of, relatively speaking, huge amounts of data,\u201d he added. \u201cI think because the architecture allowed multiple little points to be calculated all at once against many multiple other points, it became a much better architecture to kind of resemble the neural patterns of a brain where you have many neurons connected, interconnected by many synapses. GPUs, they\u2019re performing incredible amounts of calculation at rates that are just thousands and thousands of times faster than a CPU could do.\u201d<\/p>\n

Here\u2019s the complete video interview, part of SiliconANGLE\u2019s and theCUBE\u2019s coverage of theCUBE + NYSE Wired: AI Factories \u2013 Data Centers of the Future<\/a> event:\u00a0<\/p>\n

Photo: SiliconANGLE<\/p>\n

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About SiliconANGLE Media<\/p>\n

SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-time audience engagement. As the parent company of SiliconANGLE<\/a>, theCUBE Network<\/a>, theCUBE Research<\/a>, CUBE365<\/a>, theCUBE AI<\/a> and theCUBE SuperStudios \u2014 with flagship locations in Silicon Valley and the New York Stock Exchange \u2014 SiliconANGLE Media operates at the intersection of media, technology and AI.<\/p>\n

Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digital media brands that reach 15+ million elite tech professionals. Our new proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.<\/p>\n","protected":false},"excerpt":{"rendered":"Unlike traditional linear computing, multidimensional computing operates across many dimensions simultaneously, unlocking native parallelism and far richer, more…\n","protected":false},"author":2,"featured_media":65240,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[44549,44548,241,61,60,13065,80],"class_list":{"0":"post-65239","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-computing","8":"tag-beyond-linear-limits-multidimensional-computing-reshaping-ai-factory-design","9":"tag-brian-njuguna","10":"tag-computing","11":"tag-ie","12":"tag-ireland","13":"tag-siliconangle","14":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/65239","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/comments?post=65239"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/65239\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media\/65240"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media?parent=65239"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/categories?post=65239"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/tags?post=65239"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}