We’re pleased to announce that Plotly and NVIDIA are partnering to bring GPU-accelerated Artificial Intelligence (AI) & Machine Learning (ML) to a vastly wider audience of business users. By integrating the Plotly Dash frontend with the NVIDIA RAPIDS backend, we are offering one of the highest performance AI & ML stacks available in Python today. This is all open-source and accessible in a few lines of Python code.

On the Enterprise side, Dash Enterprise Kubernetes (DEK)now ships with out-of-the-box support for horizontally scalable GPU acceleration through RAPIDS and Dask. Once you’ve created a Dash + RAPIDS app on your desktop, get it into the hands of business users by uploading it to DEK. No IT or devops team required 🙅‍♀️.

NVIDIA’s CEO Jensen Huang mentioned some of the early fruits of this partnership in the first minute of his GTC 2020 Kitchen Keynote last week, and today we’re more formally announcing our partnership.

A typical business intelligence (BI) dashboard or analytical application combines graphs, maps, and controls to provide interactive access to queries and AI models running on large, complex datasets. Any organization delivering goods or services at scale will have millions of records to analyze, spread out in time and space and across various more-abstract dimensions. Building a performant application on top of such a dataset usually requires a multi-team, multi-week effort and results in a complex, multi-tiered architecture. New technologies like Dash and RAPIDS are changing this landscape, empowering individual Python developers to easily and quickly build analytical applications that are more performant than their complex counterparts.

#machine-learning #business-intelligence #artificial-intelligence #gpu #data-visualization #deep learning