NVIDIA and Google Cloud are creating a bridge linking the tools of data science to the muscle of the cloud with one click.
Most data scientists work in Jupyter Notebooks, open-source development environments that can run code, show visualizations and display text notes, too.
But it can take many complex steps to move this rich development environment to the cloud. And they’re steps more familiar to an IT specialist than a data scientist.
For instance, notebook deployment in the cloud requires:
- Knowing software requirements of the cloud service
- Installing and optimally configuring a myriad of AI software and libraries
- Configuring and launching a Jupyter instance in the cloud
In collaboration with Google Cloud, we’re simplifying that to a single click through NVIDIA’s NGC catalog, the one-stop shop for AI software, so data scientists can get started or scale their work quickly.
Leveraging the Power of Two
NGC will allow you to deploy content directly to Google’s Vertex AI Workbench, a new managed Jupyter Notebook service on top of Vertex AI, Google’s service for machine-learning operations (MLOps).
Vertex AI Workbench is a data science environment that accelerates data engineering by deeply integrating with all of the services necessary to rapidly build and deploy models in production,” said Craig Wiley, director of product management for cloud AI at Google Cloud.
“The notebooks from NVIDIA’s NGC Catalog will let data scientists start their model development on Google Cloud with a single click, speeding the path to building and deploying state of the art AI,” he added.
One Stop for AI Software
Meanwhile, we’re expanding the rich trove of NVIDIA AI software in NGC to ensure we have everything a data scientist needs to get started.
In addition to the frameworks, industry-specific SDKs and pre-trained models already in NGC, we’re going to host Jupyter Notebooks tailored for the most popular AI jobs. It’s a grab-and-go selection to fuel data scientists on their AI journey.
All of the AI models in NGC come with credentials. They’re like resumes that show the model’s skills, the dataset that trained it, how to use the model and how it’s expected to perform.
These model credentials provide transparency which gives you the confidence you’re picking the right model for your use case.
In addition, NGC now offers detailed security reports for our AI software packaged as containers. These specifics let users make informed decisions about the software they choose.
Various Roads to Enterprise AI
Sign up to find out when the one-click capability is launched early next year. It’s one of many routes NVIDIA is paving to enterprise AI.
We’re also announcing expanded availability of NVIDIA LaunchPad at GTC this week. It helps speed and manage deployment of AI jobs running at any of nine co-location facilities including Equinix.
So whatever route you take to AI, we’ll help you find the fastest vehicle.
See NGC in Action
To see an early preview of one-click deployment of Jupyter notebooks and other new features in NGC, attend our session on accelerating AI workflows at NVIDIA GTC taking place online through Nov. 11.
And watch NVIDIA CEO Jensen Huang’s GTC keynote address below.