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Nvidia and IBM Partner for Open Source Machine Learning

AI Machine Larning Coming to Data Science

IBM has announced a new partnership with Chip maker Nvidia for an open source AI Machine Learning platform. The company brings Nvidia Rapids open source data science toolkit into its own data science platform for hybrid, and multi-cloud environments.

Nvidia and IBM are taking Rapids and adding GPU acceleration capabilities to IBM’s platform. In doing so, taking advantage of IBM’s Anaconda, a web-based big data platform. Other platforms include BlazingDB, Graphistry, NERSC, PyData, INRIA, and Ursa Labs.

With IBM’s vast portfolio of machine learning solutions, its partnership with Nvidia will generate lucrative results.

According to an estimate by IBM, by 2020 the world’s volume of digital data would exceed 44 zettabytes. IBM worked hard to create the industry’s most complete data science platform.

IBM has worked to build the industry’s most complete data science platform. Integrated with NVIDIA GPUs and software designed specifically for AI and the most data-intensive workloads, IBM has infused AI into offerings that clients can access regardless of their deployment model.

Today, we take the next step in that journey in announcing the next evolution of our collaboration with NVIDIA. We plan to leverage their new data science toolkit, RAPIDS, across our portfolio so that our clients can enhance the performance of machine learning and data analytics.

Over the years IBM’s close collaboration has helped enterprises and organizations deal with some of the world’s largest problems, Nvidia claims. Thanks to IBM’s partnership with Nvidia for RAPIDS open source, GPU machine accelerated machine learning is coming to data science.

Machine learning is a type of AI that is capable of learning from data rather than vigorous programming. In the past decade, we have seen retail, finance, and telecommunications benefit from AI machine learning. IBM and Nvidia are expanding the field.


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