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 Notebook, an open-source development environment 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.
Leveraging the Power of Two
Today, we’re announcing the general availability of the One Click Deploy feature on NVIDIA NGC, the one-stop shop for AI software.
In collaboration with Google Cloud, we’re simplifying the complex steps of deploying Jupyter Notebooks to a single click through the NGC catalog.
This allows data scientists to deploy frameworks, software development kits and models 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.
“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 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.
The one-click deploy feature automatically sets up the Vertex AI instance with an optimal configuration, preloads the dependencies, runs the software from NGC, and allows data scientists to focus on development rather than setup.
One Stop for AI Software
We’re expanding the rich trove of NVIDIA AI software in NGC to ensure AI practitioners have everything they need to get started — from frameworks to models. Recent additions include model credentials and detailed security scan reports.
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 developers the confidence in picking the right model for their use case.
- Computer Vision – A collection of models for detecting human actions, gestures and more.
- Automatic Speech Recognition – An end-to-end workflow for text-to-speech training.
- Recommendation – A collection of example notebooks to help build end-to-end recommendation services.
Furthermore, 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.
Accelerate AI Developments
Join NVIDIA today at the Google Cloud Data Cloud Summit.
Explore hundreds of Jupyter notebook examples for speech, computer vision and recommenders and, if you’re just getting started with AI, browse our collection of Jupyter notebook examples and run it using One-Click Deploy.