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The intersection of artificial intelligence, data management and cloud computing stand as the epicenter of transformative change in the current age of technological innovation.

In a look at AIs transformative potential, theCUBE explores how the technology is poised to reshape industries and drive innovation in the years to come. During this journey into the AI-driven future, collaboration, innovation and a holistic approach will be the guiding principles propelling the enterprise toward unprecedented technological advancements.

In the industry, were very concerned and excited about what the computing power, the chip level can do, said Matt Hull (pictured, right), vice president of global AI platform solutions at Nvidia Corp. We obviously look at the output at the chip level the full data center level and how you bring all the components together and harmonize to produce very quick and accurate results.

Hull was joined by Baris Gultekin (center), VP of AI products at Snowflake Inc., as they spoke with AI/data executive and theCUBE panel host Howie Xu (left), at the Supercloud 6: AI Innovators event, during an exclusive broadcast on theCUBE, SiliconANGLE Medias livestreaming studio. They discussed navigating the complex terrain of AI, data and cloud computing, which is unveiling the dawn of a new era of innovation.

Both Hull and Gultekin have traversed unique paths into the AI landscape, reflecting the diverse avenues through which individuals find themselves at the forefront of innovation.

Hulls journey through IT infrastructure led him to Nvidia, where he witnessed the explosive growth of AI firsthand. Gultekin, with roots at Google and a startup background, now spearheads AI and machine learning product teams at Snowflake, at the heart of enterprise AI endeavors. Their stories underscore the multifaceted nature of AI adoption and the pivotal role of diverse expertise in driving progress.

CPUs are still very necessary in the great realm of things, Hull said. All of our accelerated computing has some sort of CPU in it, but the CPU innovation just isnt there. At Nvidia were very concerned and excited about what the computing power, the chip level can do.

The panel also assessed the seismic shift expected in 2024, marking a transition from AI experimentation to enterprise-scale deployment.

The pivotal role played by recent breakthroughs, such as ChatGPT, are catalyzing enterprises to embrace AIs transformative potential, according to Hull. However, the journey from experimentation to production isnt devoid of challenges, as exemplified by the need for organizational culture shifts and shared learnings to facilitate seamless integration.

I think this year is going be a massive sea change, Hull said. The biggest explosion was [that] ChatGPT really woke up everyone, every enterprise, every individual, every researcher out there as to what was possible with AI. Over the past year and a half we have seen a lot of experimentation. It was a lot of experimentation at the beginning. They have to figure out how theyre going to implement AI.

Vast opportunities await innovative ventures, from foundational AI models to domain-specific applications, according to Gultekin. Startups, leveraging partnerships with industry leaders such as Nvidia and Snowflake, are poised to revolutionize diverse sectors, empowered by access to cutting-edge technology and supportive ecosystems.

I think there is still a lot of innovation waiting to be unlocked in that foundation model layer, Gultekin said. It is very resource intensive, and therefore a lot of investment is going there. Beyond that, were starting to see [an] application layer develop, and then theres a lot of tooling thats necessary.

The conversation culminated in a reflection on the evolving AI cloud landscape, challenging conventional perceptions of cloud computing.There is a need for a holistic approach, transcending traditional cloud paradigms to accommodate AIs unique requirements, according to Gultekin. With Snowflakes focus on data governance and Nvidias commitment to empowering AI factories, the stage is set for a collaborative ecosystem where data, compute and software converge seamlessly, fueling innovation at scale.

What we want to enable is we want to bring compute to where the data is, Gultekin said. For Snowflake what this means is having large language models running inside this parameter. We break all these data silos that are otherwise going to be created when you take the data to one vendor for one thing, another vendor for another thing. We like to consolidate all the data in one place and bring all of the LLM functionality to there.

Heres the complete video interview, part of SiliconANGLEs and theCUBE Researchs coverage of the Supercloud 6: AI Innovators event:

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Innovation unveiled: Snowflake and Nvidia on AI, data and cloud - SiliconANGLE News