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On set with theCUBE at Google Cloud Next.<\/p>\n
\u201cThe big thing was they have a whole vision around the stack of AI. It\u2019s basically AI everywhere and all the apps, everywhere all at once kind of thing,\u201d Furrier said. \u201cAll their apps are going to be infused with AI. I think last year we said that, AI infused everywhere. That was one thing that was clear.\u201d<\/p>\n
Furrier spoke with fellow analysts\u00a0Paul Nashawaty<\/a> (second from left), Savannah Peterson<\/a> (second from right) and Dave Vellante<\/a> (right) as a part of the day one keynote analysis at Google Cloud Next<\/a>, during an exclusive broadcast on theCUBE, SiliconANGLE Media\u2019s livestreaming studio. They discussed how AI is driving innovation in cloud infrastructure, with an emphasis on hybrid and multicloud solutions. (* Disclosure below.)<\/p>\n Quantum computing\u2019s impact on AI and cloud infrastructure<\/p>\n Significant attention is currently placed on Google\u2019s extensive infrastructure investments, notably highlighted by the introduction of Ironwood TPU technology<\/a>. This innovation marks Google\u2019s seventh-generation tensor processing unit, promising enterprises substantial operational cost savings alongside improved computational capabilities. These infrastructure moves are strategically essential, supporting expansive, AI-intensive operations increasingly demanded by global enterprises, according to Furrier.<\/p>\n \u201cThe Ironwood TPU announcement was the big thing that jumped,\u201d he said. \u201cMassive investments in CapEx. This year \u2026 they quoted to have 45 billion, seventh generation TPU at Ironwood, next-gen networking opening up their global distributed network, that\u2019s Google-only to enterprises. That\u2019s going to be a big deal.\u201d<\/p>\n The technology industry also continues to observe remarkable momentum in quantum computing, which has re-emerged as a critical area of research and development. Quantum computing promises exponential processing capabilities that will revolutionize data-intensive computations, reshaping competitive advantages across various industries, Peterson explained.<\/p>\n \u201cWe sort of had AI coming up here, then both things and if we look at supercomputing and looking at the real high-performance computing going on around the world. Now, it\u2019s coming back,\u201d she said, \u201cThere\u2019s a lot of progress. Don\u2019t sleep on quantum is all I\u2019m saying.\u201d<\/p>\n AI and multicloud strategies reshaping enterprise IT operations<\/p>\n Moreover, the integration of AI with traditional cloud services is proving essential for enterprises needing increased flexibility in their IT operations. Companies are leveraging AI to bridge existing skill gaps<\/a> and streamline complex tasks, significantly impacting development efficiency and application portability.<\/p>\n \u201cWhen you look at what Google announced with Firebase Studios and the ability to have that development effort eased across these different platforms, using AI in the platform, that\u2019s going to be a differentiator,\u201d Nashawaty said. \u201cBecause that\u2019s going to accelerate development and allow for that ease of use.\u201d<\/p>\n The multicloud and hybrid cloud strategy is becoming central to future industry growth. Enterprises increasingly require strong multicloud strategies to maintain flexibility, reduce dependency on single providers and ensure application portability. The movement toward this type of infrastructure highlights the need for interoperability and consistent user experience across platforms, Nashawaty explained.<\/p>\n \u201cI think the big area of growth for Google right now is we\u2019re seeing it in our own research that 94% of organizations are using two or more clouds, 65% are using four or more clouds,\u201d he added. \u201cThey have to adopt the multicloud hybrid cloud approach. GKE is a way to do this, to harmonize this across the platforms, make sure that it\u2019s working.\u201d<\/p>\n Additionally, the industry\u2019s trajectory indicates a substantial investment in bringing AI directly to data, both in cloud and on-premises solutions. This strategy is a response to challenges such as data gravity and the complexities involved in migrating large-scale data sets, ensuring companies can efficiently utilize their existing data repositories, according to Vellante.<\/p>\n \u201cThey really aggressively recognized that not all AI is going to be done in the cloud,\u201d he said. \u201cThey talked about sovereign AI and bringing the cloud, the AI to the data on-prem, which I think recognizes that there is data gravity, there\u2019s a lot of data that\u2019s not going to go into the cloud. That\u2019s a potential vector of opportunity.\u201d<\/p>\n Here\u2019s the complete video interview, part of SiliconANGLE\u2019s and theCUBE\u2019s coverage of Google Cloud Next<\/a>:<\/p>\n<\/p>\n (* Disclosure: TheCUBE is a paid media partner for Google Cloud Next. Neither Google Cloud, the primary sponsor of theCUBE\u2019s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)<\/p>\n Photo: SiliconANGLE<\/p>\n