“The era of enterprise AI is here,” said Snowflake CEO Sridhar Ramaswamy. The crowd of over 20,000 attendees at the Snowflake Summit 2024, hosted in San Francisco, went wild and cheered.
In seconds, the keynote session’s blue strobe lights softened, and NVIDIA CEO Jensen Huang appeared on a screen next to Ramaswamy.
“We’re at the beginning of a new era in computing,” Huang said on a video call from Taiwan in his signature black leather jacket. “The computing infrastructure of the world is really built here. And so, I'm here to unite an ecosystem of companies, technology companies, so they can work on that AI infrastructure.”
In this new era, according to Huang and Ramaswamy, businesses can build customized AI applications in the Snowflake data cloud, powered by NVIDIA AI. This essentially brings “computing to the data,” not the other way around, Jensen said.
This major announcement, shared on June 3, brings the global partnership between NVIDIA and Snowflake to a new level of influence and makes it easier for enterprises to unlock the power of AI so they can literally chat with their data, Huang explained. Here’s what IT leaders need to know:
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Snowflake and NVIDIA Announce New AI Data Application Tools
With this latest collaboration, Snowflake has adopted NVIDIA AI Enterprise software to integrate NVIDIA’s NeMo Retriever microservices into Snowflake Cortex AI, Snowflake’s fully managed large language model and vector search service. This enables organizations to seamlessly connect custom models to diverse business data and deliver highly accurate responses.
In addition, Snowflake Arctic, the most open, enterprise-grade LLM, is now fully supported by NVIDIA TensorRT-LLM software, providing users with highly optimized performance. Arctic is also now available as an NVIDIA NIM inference microservice, allowing more developers to access Arctic’s efficient intelligence.
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“Pairing NVIDIA’s full-stack accelerated computing and software with Snowflake’s state-of-the-art AI capabilities in Cortex AI is game-changing,” said Ramaswamy. “Together, we are unlocking a new era of AI, where customers from every industry and every skill level can build custom AI applications on their enterprise data with ease, efficiency and trust.”
Transforming Data Sets Ahead of Generative AI Implementation
Snowflake’s unified platform specializes in “offering people the car and not the parts,” said Titiaan Palazzi, head of power and utilities go-to-market strategy at Snowflake. It’s “a ready-to-go platform, not just different tools that require a lot of ownership.”
But even with that built-in simplicity that Snowflake Cortex AI, Snowflake ML, Snowflake Iceberg Tables and Snowflake Horizon offer, IT leaders still need to understand exactly how their data is being transformed ahead of AI implementation.
Joining the stage at the keynote’s conclusion, industry experts — including Anu Jain, head of data technology at JPMorgan Chase; Shahran Haider, deputy chief data officer at NYC Health + Hospitals; and Thomas Davey, chief data officer at Booking.com — emphasized that IT leaders must still verify that their enterprise data passes three rounds of assessment, even with automation procedures in place.
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These assessments include data integrity (as in trustworthiness, governance and accuracy), data visualization (the degree to which the data tells a story and is represented clearly) and data value to stakeholders (this involves operational efficiencies, dozens of use cases across the business and the degree to which LLMs can be operationalized to scale).
“It's about being really methodical,” said Phil Andriyevsky, principal, wealth and access management, data and analytics, at EY. And, making sure companies “refactor your data the right way, in order for it to be labeled consumable and digestible by the right business stakeholders,” he added.
What Defines This New Era of Enterprise AI?
The era of enterprise AI is defined by a data-centric mindset. AI will be leveraged at every level of the organization and accessible to all employees, whether entry level or executive.
It’s also an era of immense collaboration — between legacy on-premises systems and the cloud, new schools of thought and old, and an ecosystem of technology partners driving complementary solutions.
“Snowflake has a powerful and unique partner ecosystem — part of our success is that we have many partners that amplify the power of our platform,” Ramaswamy said, naming Microsoft, Google and CDW as just a few.
But above all, this era is defined by “breakneck speed,” Huang said. “The technology is moving so fast.” Time-to-market is everything, he added, signaling the ricochet effect that enterprise AI will have on the way we work today.
“The size and scale of this is similar to a late 90s sort of moment, with the wide adoption of the internet,” Andriyevsky added. “Industries will just transform because of the advancement of technology and AI. And I fundamentally think it's gonna be better for industry. It's gonna be better for the world.”
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