Every Company’s Data Is Their ‘Gold Mine,’ NVIDIA CEO Says at Databricks Data + AI Summit

Databricks to leverage NVIDIA’s full stack to accelerate generative AI, enhancing data processing efficiency. 
by Anne Hecht

Accelerated computing is transforming data processing and analytics for enterprises, declared NVIDIA founder and CEO Jensen Huang Wednesday during an on-stage chat with Databricks cofounder and CEO Ali Ghodsi at the Databricks Data + AI Summit 2024.

“Every company’s business data is their gold mine,” Huang said, explaining that every company has enormous amounts of data, but extracting insights and distilling intelligence from it has been challenging.

Databricks Leverages NVIDIA’s Full Stack to Accelerate Generative AI Applications

To unlock all that intelligence, Huang and Ghodsi announced the integration of NVIDIA’s accelerated computing with Databricks Photon, Databricks’ engine for fast data processing, designed to power Databricks SQL with top-tier performance and cost efficiency.

“This is a big announcement,” Huang said, adding that accelerated computing and generative AI are the two most important technological trends today. “NVIDIA and Databricks are going to partner to combine our skills in these areas and bring them to all of you.”

Huang shared that it’s taken NVIDIA five years to build a set of libraries that make it possible to accelerate Photon, allowing users to “wrangle data faster, more cost-effectively and consume a lot less energy.”

“We are super-excited to partner with you to use GPU acceleration on the Photon engine to enhance core data processing and get them to also run on NVIDIA GPUs,” Ghodsi said.

Creating Generative AI Factories With NVIDIA NIM

NVIDIA and Databricks also announced that Databricks’ open-source model DBRX is now available as an NVIDIA NIM microservice hosted on the NVIDIA API catalog.

NVIDIA NIM inference microservices provide models as fully optimized, pre-built containers for deployment anywhere.

“Creating these endpoints is complicated,” Huang explained. “We optimized everything into a microservice, which runs on every cloud and on premises.”

Microservices dramatically increase enterprise developer productivity by providing a simple, standardized way to add generative AI models to applications.

Launched in March, DBRX was built entirely on top of Databricks, leveraging all the tools and techniques available to Databricks customers and partners, and was trained with NVIDIA DGX Cloud, a scalable end-to-end AI platform for developers.

Organizations can customize DBRX with enterprise data to create high-quality, organization-specific models or use it to build a custom DBRX-style mixture of expert models as a reference architecture.

Huang said that accelerating data processing is a huge opportunity, encouraging everyone to put accelerated computing and generative AI to work.

“Whatever you do, just start — you have to engage in this incredibly fast-moving train,” Huang said. “Remember, generative AI is growing exponentially — you don’t want to wait and observe an exponential trend, because in a couple of years, you’ll be so far behind.”

Joining the Conversation

Attendees at the summit are encouraged to participate in sessions and engage with NVIDIA experts to learn more about how NVIDIA and Databricks are driving the future of AI and data intelligence.

Key sessions, taking place June 13, include:

  • “Development and Deployment of Generative AI with NVIDIA” at 12:30 p.m. PT
  • “Architecture Analysis for ETL Processing: CPU vs. GPU” at 4:30 p.m. PT;
  • “Spark RAPIDS ML: GPU Accelerated Distributed ML in Spark Clusters” at 1:30 p.m. PT