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While the world scrambles to adapt to the explosive demand for generative AI, Google Cloud CEO Thomas Kurian says his company isn\u2019t reacting to a trend, but rather executing a strategy set in motion 10 years ago. In a recent panel for Fortune Brainstorm AI, Kurian detailed how Google anticipated the two biggest bottlenecks facing the industry today: the need for specialized silicon, and the looming scarcity of power.<\/p>\n
According to Kurian, Google\u2019s preparation began well before the current hype cycle. \u201cWe\u2019ve worked on TPUs since 2014 \u2026 a long time before AI was fashionable,\u201d Kurian said, referring to Google\u2019s custom Tensor Processing Units. The decision to invest early was driven by a fundamental belief that chip architecture could be radically redesigned to accelerate machine learning.<\/p>\n
Perhaps more critical than the silicon itself was Google\u2019s foresight regarding the physical constraints of computing. While much of the industry focused on speed, Google was calculating the electrical cost of that speed.<\/p>\n
\u201cWe also knew that the most problematic thing that was going to happen was going to be energy because energy and data centers were going to become a bottleneck alongside chips,\u201d Kurian said.<\/p>\n
This prediction influenced the design of their infrastructure. Kurian said Google designed its machines \u201cto be super efficient in delivering the maximum number of flops per unit of energy.\u201d This efficiency is now a critical competitive advantage as AI adoption surges, placing unprecedented strain on global power grids.<\/p>\n
Kurian said the energy challenge is more complex than simply finding more power, noting that not all energy sources are compatible with the specific demands of AI training. \u201cIf you\u2019re running a cluster for training \u2026 the spike that you have with that computation draws so much energy that you can\u2019t handle that from some forms of energy production,\u201d he said.<\/p>\n
To combat this, Google is pursuing a three-pronged strategy: diversifying energy sources, utilizing AI to manage thermodynamic exchanges within data centers, and developing fundamental technologies to create new forms of energy. In a moment of recursive innovation, Kurian said \u201cthe control systems that monitor the thermodynamics in our data centers are all governed by our AI platform.\u201d<\/p>\n
Despite Google\u2019s decade-long investment in its own silicon, Kurian pushed back against the narrative that the rise of custom chips threatens industry giants like Nvidia. He argues that the press often frames the chip market as a \u201czero sum game,\u201d a view he considers incorrect.<\/p>\n
\u201cFor those of us who have been working on AI infrastructure, there\u2019s many different kinds of chips and systems that are optimized for many different kinds of models,\u201d Kurian said.<\/p>\n
He characterized the relationship with Nvidia as a partnership rather than a rivalry, noting that Google optimizes its Gemini models for Nvidia GPUs and recently collaborated to allow Gemini to run on Nvidia clusters while protecting Google\u2019s intellectual property. \u201cAs the market grows,\u201d he said, \u201cwe\u2019re creating opportunity for everybody.\u201d<\/p>\n
Kurian attributed Google Cloud\u2019s status as the \u201cfastest growing\u201d major cloud provider to its ability to offer a complete \u201cstack\u201d of technology. In his view, doing AI well requires owning every layer: \u201cenergy, chips or systems infrastructure, models, tools, and applications,\u201d noting that Google is the only player that offers all of the above. <\/p>\n
However, he said this vertical integration does not equate to a \u201cclosed\u201d system. He argued that enterprises demand choice, citing how 95% of large companies use cloud technology from multiple providers. Consequently, Google\u2019s strategy allows customers to mix and match\u2014using Google\u2019s TPUs or Nvidia\u2019s GPUs, and Google\u2019s Gemini models alongside those from other providers.<\/p>\n
Despite the advanced infrastructure, Kurian offered a reality check for businesses rushing into AI. He identified three primary reasons why enterprise AI projects fail to launch: poor architectural design, \u201cdirty\u201d data, and a lack of testing regarding security and model compromise. Furthermore, many organizations fail simply because \u201cthey didn\u2019t think about how to measure the return on investment on it.\u201d<\/p>\n
For this story,\u00a0<\/em>Fortune\u00a0journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing<\/em>.<\/p>\n<\/div>\n #Google #Cloud #chief #reveals #long #game #decade #silicon #energy #battle #boom<\/p>\n","protected":false},"excerpt":{"rendered":" While the world scrambles to a… <\/p>\n","protected":false},"author":1,"featured_media":6241,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[2],"tags":[1918,850,1088,1429,104,815,714,715,2855,307,717,4314],"_links":{"self":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts\/6240"}],"collection":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=6240"}],"version-history":[{"count":0,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/posts\/6240\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=\/wp\/v2\/media\/6241"}],"wp:attachment":[{"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6240"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6240"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/microvibenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6240"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}